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For peer review only Maternal and perinatal risk factors for childhood cancer Journal: BMJ Open Manuscript ID: bmjopen-2013-003656 Article Type: Research Date Submitted by the Author: 25-Jul-2013 Complete List of Authors: Bhattacharya, Sohinee; University of Aberdeen, Public Health Beasley, Marcus; University of Aberdeen, Epidemiology Group Pang, Dong; University of Bedfordshire, Institute of Health Research Macfarlane, Gary; University of Aberdeen, Epidemiology Group <b>Primary Subject Heading</b>: Epidemiology Secondary Subject Heading: Obstetrics and gynaecology, Oncology Keywords: EPIDEMIOLOGY, Fetal medicine < OBSTETRICS, Paediatric oncology < ONCOLOGY For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml BMJ Open on March 3, 2021 by guest. Protected by copyright. http://bmjopen.bmj.com/ BMJ Open: first published as 10.1136/bmjopen-2013-003656 on 6 January 2014. Downloaded from

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Page 1: bmjopen.bmj.com€¦ · For peer review only 1 Maternal and Perinatal Risk Factors for Childhood Cancer Sohinee Bhattacharya1* Marcus Beasley1 Dong Pang2 Gary J Macfarlane1 1Epidemiology

For peer review only

Maternal and perinatal risk factors for childhood cancer

Journal: BMJ Open

Manuscript ID: bmjopen-2013-003656

Article Type: Research

Date Submitted by the Author: 25-Jul-2013

Complete List of Authors: Bhattacharya, Sohinee; University of Aberdeen, Public Health

Beasley, Marcus; University of Aberdeen, Epidemiology Group Pang, Dong; University of Bedfordshire, Institute of Health Research Macfarlane, Gary; University of Aberdeen, Epidemiology Group

<b>Primary Subject Heading</b>:

Epidemiology

Secondary Subject Heading: Obstetrics and gynaecology, Oncology

Keywords: EPIDEMIOLOGY, Fetal medicine < OBSTETRICS, Paediatric oncology < ONCOLOGY

For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml

BMJ Open on M

arch 3, 2021 by guest. Protected by copyright.

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Maternal and Perinatal Risk Factors for Childhood Cancer

Sohinee Bhattacharya1* Marcus Beasley1 Dong Pang2 Gary J Macfarlane1

1Epidemiology Group, Division of Applied Health Sciences, University of Aberdeen 2 Institute of Health Research, University of Bedfordshire, Luton *Corresponding author: Sohinee Bhattacharya Dugald Baird Centre for Research on Women’s Health Aberdeen Maternity Hospital Aberdeen AB25 2ZL Tel: +44 1224 438441 e-mail: [email protected] Running title: Risk factors for childhood cancer

Conflict of Interest: All authors have completed the Unified Competing Interest form at http://www.icmje.org/coi_disclosure.pdf and declare: NHS Grampian Endowment funded the study; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, a worldwide licence to the Publishers and its licensees in perpetuity, in all forms, formats and media (whether known now or created in the future), to (i) publish, reproduce, distribute, display and store the Contribution, (ii) translate the Contribution into other languages, create adaptations, reprints, include within collections and create summaries, extracts and/or, abstracts of the Contribution, (iii) create any other derivative work(s) based on the Contribution, (iv) to exploit all subsidiary rights in the Contribution, (v) the inclusion of electronic links from the Contribution to third party material where-ever it may be located; and, (vi) licence any third party to do any or all of the above. Contributorship: SB was responsible for designing the study, facilitating data extraction, supervising data analysis and writing of the first draft of the paper; MB analysed the data; SB, GJM and DP conceived of the research idea and GJM was responsible for overall supervision. All authors contributed to the writing of the final draft of the paper. SB is the guarantor of this paper. Ethics: This research proposal was approved by the Privacy Advisory Committee of the Information and Services Division NHS Scotland and the steering group of the Aberdeen Maternity and Neonatal Databank. Formal ethical approval was not considered necessary by North of Scotland Research Ethics Service as only anonymised data were analysed in this study. Funding: This research was funded by the NHS Grampian Endowment Fund (Project no. 10/15) Role of sponsors: The University of Aberdeen acted as sponsors for this research project, but the findings and their interpretation in this study are the authors’ own. Independence of authors from funders: All authors were employed by the University of Aberdeen at the time of conducting this research and are independent from the funders. Article Summary: Article Focus –

• What are the maternal characteristics associated with childhood cancer?

• What factors during pregnancy and at the time of birth are associated with

childhood cancer?

Key Messages –

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• Extremes of maternal age at delivery, parental smoking, preterm birth and low

birthweight have all been reported to be risk factors for childhood cancer.

• The large effect of delivery by caesarean section on the increased risk of childhood

cancer is a novel finding in this study.

Strengths and limitations –

• Detailed and contemporaneous recording of data in the databases eliminated recall

and reporting bias.

• The large number of social and demographic variables recorded in the AMND

enabled incorporation of most potential covariates in the analysis.

• Inadequate power to detect some weak associations reported previously in the

literature.

• The number of cases according to site specific cancer diagnosis was too small in our

sample to allow any subgroup analysis.

Abstract Objective: To investigate maternal and perinatal risk factors for childhood cancer.

Study Design: Case control analysis of linked records from the Aberdeen Maternity and

Neonatal Databank with the Scottish Cancer Registry and the General Registry of Births and

Deaths in Scotland was carried out.

Setting: Aberdeen, Scotland

Participants: Cases (n=176) comprised children diagnosed with cancer under 15 years or

recorded as having died of cancer. Four controls per case were matched by age and gender.

Risk factors tested: Maternal age, BMI, social class, marital status and smoking as well as

preeclampsia, antepartum haemorrhage and previous miscarriage, gestational age,

birthweight, and Apgar scores were compared between groups to test for association with

cancer. Odds ratios with 95% Confidence Intervals were calculated using conditional logistic

regression in both univariable and multivariable models.

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Results: Of the maternal characteristics tested, mother’s age at delivery {cases mean

28.9(S.D.5.6) years versus controls mean 30.2(S.D4.6), p = 0.002} and smoking status

(38.6% smokers among cases, 29.7% among controls, p=0.034) were found to be different

between groups. Of the perinatal factors tested, low Apgar score at 5 minutes (AOR 4.59,

95% CI 1.52, 13.87) and delivery by caesarean section (AOR 1.95, 95% CI 1.30, 2.92)

showed statistically significant associations with childhood cancer in the multivariable model.

Conclusions: Younger maternal age, maternal smoking, delivery by caesarean section and

low Apgar score at 5 minutes were independently associated with increased risk of

childhood cancer. The association with caesarean delivery may be mediated through

epigenetic mechanism and warrants further investigation.

Key words: childhood cancer, perinatal risk factors, smoking, caesarean delivery

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Introduction:

Childhood cancer has been increasing in Scotland. A published report estimates that its

incidence has risen from 108.3 per million child-years in 1976 to 160.6 per million child-years

in 20071. The reason for this increasing trend remains unexplained as the etiopathogenesis

of childhood cancer is poorly understood. As most present in the first few years of life,

epidemiologists hypothesize that prenatal and perinatal exposures may have a part to play in

its pathogenesis. The evidence surrounding this is however, conflicting. While some

researchers have found associations of younger maternal age at delivery2 maternal

anaemia3,4, previous history of miscarriage2,5,6 maternal overweight7, and smoking8, with

some childhood cancers, others have found no such associations9-11. Fetal growth is

perhaps the most investigated perinatal risk factor for childhood cancer7,12,13 ; and yet the

authors report conflicting results. While specific central nervous system tumours have been

found to be associated with intrauterine growth restriction, the overall risk was small12.

Therefore, apart from the associations with Down’s syndrome and in utero exposure to

radiation, research into the maternal and perinatal risk factors has remained inconsistent, the

results limited by small sample sizes and recall or reporting bias.

Our objective was therefore to investigate maternal and perinatal risk factors for childhood

cancer, specifically to examine the effects of intrauterine growth restriction, preterm birth and

birth asphyxia on the development of childhood cancer in the offspring, taking advantage of

the opportunities offered by record linkage of a cancer registry with a local birth register.

Methods:

Data Sources:

The Aberdeen Maternity and Neonatal Databank (AMND) holds data for all Aberdeen City

births from 1950 to the present, and includes all reproductive events to women resident in a

defined geographical area with a relatively stable population. The exposure variables in

terms of potential maternal and perinatal risk factors were derived from the AMND. The

Scottish Cancer Registry has been in existence since 1951 and was complete up to 2010, at

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the time of the present analysis. The cases of childhood cancer were identified from this

register.

Data Linkage:

All children born between 1993 and 2006 were identified from the AMND. Their records were

linked to the Cancer Registry in Scotland (SMR 06) and the General Registry of Births and

Deaths in Scotland (GRO-S), using deterministic matching. The linkage was carried out by

data analysts from the Information and Services Division of NHS Scotland using Community

Health Index (CHI) numbers. The CHI number is a number unique to all individuals

registered with a general practice in Scotland and recorded in both databases used in this

study. In a small proportion of cases where CHI number was not available, probabilistic

matching using surname, date of birth and postcode was used. After data linkage, all

identifying information, including CHI numbers were removed and an anonymised dataset

was provided for analysis.

Study design:

A case control study design was employed. Cases comprised all children identified as above

from the AMND who were diagnosed with cancer under 15 years of age in Scotland as

recorded in the Scottish Cancer Registry or recorded as having died of cancer. Controls

were selected from the pool of children not diagnosed as having cancer, matched by age

and gender using four controls per case.

Twins and multiple births were excluded as were stillbirths and early neonatal deaths. As

Down’s syndrome is known to be associated with a higher risk of Acute Lymphoblastic

Leukaemia (ALL), all cases of diagnosed Down’s syndrome were excluded. Moreover, those

children who had died of non-cancer causes prior to their 15th birthday, as identified from

GRO-S were also excluded.

Exposure and outcome variables used in the analysis:

Maternal sociodemographic factors such as age at delivery, body mass index (BMI),

Registrar General’s occupation-based social class, marital status, previous history of

miscarriage and smoking habits were extracted from the AMND. Any complications recorded

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during the index pregnancy such as preeclampsia, gestational hypertension, and antepartum

haemorrhage as well as mode of delivery, gestational age at delivery, birthweight,

Standardised Birthweight Score14, and Apgar score at 1 and 5 minutes were also extracted.

Data extractors were blind to the case-control status of the individual children.

The outcome variables obtained from the Cancer Registry in Scotland were in the form of a

binary variable (yes/no) indicating whether or not a cancer record was present and if

present, the site of cancer given as International Classification of Diseases (ICD) codes.

Similarly, death records with up to 10 different causes of death given by ICD codes were

obtained from linking with GRO-S.

Statistical Analysis:

All analyses were conducted using STATA version 11 (STATA Corp, Texas, USA).

Maternal baseline characteristics were compared between children diagnosed with cancer

and controls using independent two-sample t-tests and chi-square tests. Maternal

complications such as gestational hypertension, pre-eclampsia, antepartum haemorrhage

and previous history of miscarriage were compared between the cases and controls using

univariate conditional regression to calculate odds ratios (OR) with 95% confidence intervals

(CI). Similarly, perinatal factors like gestation at birth, birth weight, intrauterine growth

restriction measured by standardised birthweight score, Apgar score at 1 and 5 minutes

were also tested in univariate models for any association with childhood cancer. Then a

multivariable conditional logistic regression model was fitted that included as independent

variables all risk factors tested on univariate analysis. The possibility of cancer subgroup

analysis was considered according to the International Classification of Childhood Cancer,

but the number of cases in each subgroup was too small to warrant this.

Missing data:

Apart from the variables describing maternal baseline characteristics, the other risk factors

did not have any missing values. There were 18 controls and 1 case with missing smoking

data. The multivariable model was repeated including and excluding the individuals with

missing information. We used two methodological approaches to handle this - listwise

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deletion – ie, not including any group where one person in that group has missing data, and

imputation by creation of a missing value (999) so that all cases and controls were included

in the analyses. The odds ratios obtained by both methods are presented.

Ethical considerations:

Approval to carry out the study was obtained from the AMND steering committee and the

Privacy Advisory Committee for the Information Services Division of National Health

Services, Scotland. As the study involved the analysis of routinely collected anonymised

data, formal ethical approval was not required as declared by the North of Scotland

Research Ethics Service.

Results:

There were 62375 deliveries between 1993 and 2006 as identified from the AMND. After

excluding Down’s syndrome cases, twins and multiple births, stillbirths and early neonatal

deaths, there were 60117 children eligible for linkage with the Cancer Registry. It was

possible to link 43591 of these children to the cancer and GRO-S databases. Amongst the

children with linked data, 106 had died of non-cancer causes before they reached the age of

15 and were therefore excluded from the analysis. Of the remainder, 176 were found to have

a record in the Cancer Registry, giving a cumulative incidence rate of childhood cancer up to

15 years of 4.05 per 1000 deliveries. They constituted the cases for the analysis and were

matched in 1:4 ratio by year of birth and sex from the pool of remaining children without any

records of cancer to obtain 704 controls.

Maternal baseline characteristics were compared between cases and matched controls in

Table 1. Of the maternal characteristics tested, mother’s age at delivery (cases mean 28.9

years, s.d. 5.6; controls mean 30.2, s.d. 4.6; p = 0.002) and smoking status (38.6% current

or ex-smokers among cases, 29.7% among controls, p=0.022) were found to be significantly

different between the two groups.

Table 2 presents the unadjusted odds ratios with 95% confidence intervals for all the

perinatal potential risk factors for childhood cancer. Of the factors tested, preterm birth {OR

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2.23(1.31 – 3.79)}; low birth weight {OR 1.87(1.03 – 3.39)}, low Apgar score at 5 minutes

{OR 5.01(1.73 – 14.54)} and delivery by caesarean section {OR 1.77(1.23 – 2.56)} were

found to be statistically significant. Subsequently, these factors were adjusted for maternal

age at delivery and smoking. As the maternal smoking variable had some missing data, we

handled this using two approaches – listwise deletion and imputation of a missing value.

After these adjustments, low birthweight no longer remained significant, but the other

associations were strengthened.

After conducting the univariate analyses multivariable models were fitted including maternal

age, smoking status, preeclampsia, placenta praevia, preterm birth, low birthweight, low

Apgar at 5 minutes and delivery by caesarean as independent variables (results in Table 3).

Similar to the previous analyses, we used two methods of listwise deletion and imputation of

the missing value to adjust for smoking status. Of the perinatal factors tested, Apgar score

below 7 at 5 minutes {AOR 3.91, 95% CI 1.13 – 13.61(listwise deletion); AOR 4.59, 95% CI

1.52, 13.87 (imputation)} and delivery by caesarean section {AOR 2.11, 95% CI 1.38, 3.23

(listwise deletion); AOR 1.95, 95% CI 1.30, 2.92 (imputation)} showed statistically significant

associations with childhood cancer in both multivariable models adjusted for maternal age,

smoking and other factors simultaneously included in the models. Preterm birth (delivery

before 37 completed weeks of gestation) and low birth weight defined as a birth weight

below 2500g, showed a significant association in the univariate analysis, but these

associations were no longer significant in the multivariable model. The associations were not

statistically significant on univariate or multivariable analysis between the risk of childhood

cancer and hypertensive disorders, antepartum haemorrhage, previous history of

miscarriage or IUGR. Unlike the Apgar score at 5 minutes, the score at 1 minute did not

show any association with childhood cancer.

We further investigated the types of preterm delivery (spontaneous or induced) and

caesarean section (elective or emergency) as risk factors for childhood cancer and found

that both spontaneous and induced preterm delivery were significantly associated in the

adjusted model but only delivery by emergency caesarean section remained significant on

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subgroup analysis (AOR 1.43, 95% CI 1.20, 2.18). Further, we found that the commonest

indication for caesarean delivery in the babies who were subsequently diagnosed with

cancer was fetal distress (data not shown).

Table 4 shows the distribution of cancer sites in the 176 cases. As this table shows, the

commonest sites were the brain and haemopoietic organs, especially leukaemia, but the

numbers in the subgroups were too small to allow any meaningful analysis.

Discussion:

We aimed to study the maternal and perinatal risk factors at the time of birth associated with

the diagnosis of childhood cancer using record linkage between two high quality registers in

Scotland. We found a positive association between younger maternal age at delivery and

maternal smoking with childhood cancer. In addition, preterm birth before 37 weeks of

gestation, Apgar score below 7 at 5 minutes and delivery by emergency caesarean section

showed statistically significant associations with childhood cancer the last two of which

remained significant in the adjusted models.

Childhood cancer is a rare condition. Case control studies are therefore the most efficient

epidemiological study design to study several risk factors at the time of birth. Cancer

registries across the world have been utilised to identify cases, but finding appropriate

controls remains problematic. Moreover, data collections regarding exposures by means of

interviews or questionnaires are subject to recall and reporting bias. More recently, linkage

of birth registers with cancer registries has been utilised to design large scale cohort studies.

However, the routine data collection is liable to lack sufficiently detailed data regarding

exposure and potential confounding factors. We have tried to minimise these problems by

linking two high quality registers in Scotland. Previous validation projects have shown these

databases to be 100% complete and over 97% accurate15. Detailed and contemporaneous

recording of obstetric data in the AMND eliminated recall and reporting bias. The large

number of social and demographic variables recorded in the AMND enabled incorporation of

most potential covariates in the analysis. Despite these strengths to our study design, we

were limited by the small number of cases and it is possible that we did not have sufficient

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power to detect some weak associations reported previously in the literature. Maternal and

perinatal risk factors for childhood cancer appear to differ by the site of cancer in the

published literature. The number of cases according to site specific cancer diagnosis was

too small in our sample to allow any subgroup analysis. Further, morphology codes were not

available for us to carry out more appropriate groupings of childhood cancers. This, coupled

with the fact that we had to conduct our analyses on all cancers would have made it less

likely for us to find associations that exist with site specific cancers. This could be a major

limitation of the current analysis.

The association of parental age with the diagnosis of cancer in general as well as in specific

sites has been studied before. Johnson et al16 in a pooled analysis of register linkage data

from several US states, found that the risk of childhood cancer increased with increasing

maternal age, while paternal age appeared to have no effect on the risk. On the other hand

several other studies, similar to the current analysis have shown that younger maternal age

was associated with increased childhood cancer risk2,17. There could be several

explanations for the disparate findings. In a register linkage study carried out in Sweden18,19,

researchers found that advancing maternal age was positively associated with childhood

cancer risk but only in a historical cohort. This association disappeared in a more recent

cohort of women although the reasons for this are unknown. Moreover, Schutz20 suggests

that the association of lower maternal age at the time of delivery with leukaemia in the

offspring could be explained by non-response bias, although this is not applicable to the

present study.

The relationship between maternal smoking and childhood cancer in the offspring is complex

and controversial. While Sorahan et al21 - 23 and Edraki24 found an increased overall risk of

childhood cancer with paternal cigarette smoking, there did not appear to be an association

with maternal smoking after adjusting for birthweight. Further, Pang et al9 did not find

evidence of smoking as a risk factor for childhood cancer after adjusting for parental age.

Similar associations were reported by Chang et al25 with regard to Acute Lymphoblastic

Leukaemia (ALL). The evidence appears to indicate that neonatal passive smoking plays a

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more important role than in utero transfer of maternal smoke related toxins, although we

cannot rule out the possibility of an association between maternal smoking and site-specific

cancers26,27. For the current analysis, we did not have access to data on paternal smoking

habits and the association seen with maternal smoking could be due to this variable acting

as proxy for paternal smoking.

Other associations noted in this study have been reported before – preterm birth28, and low

Apgar score2,28. Birthweight has received a lot of attention as a risk factor for childhood

cancer. While brain tumours and retinoblastoma appear to be associated with high

birthweight29 - 31 others have found hepatoblastomas7,32 and gliomas33 to be associated with

very low birthweight infants. Schmidt28 et al observed a U-shaped relationship between

birthweight and cancer risk, while Podvin34 found birthweight adjusted for gestational age to

be a better predictor than birthweight alone for the diagnosis of ALL, lending support to our

findings. It is however, important to note, that we did not find an association with intrauterine

growth restriction as measured by the z-score or standardized birthweight score.

Few studies have assessed mode of delivery, specifically caesarean delivery, as a possible

risk factor for the development of childhood cancer. Those that have done, have found a

weak to moderate association7,35,36 between caesarean delivery and subsequent risk of

developing ALL. Several hypotheses can be developed regarding the biological mechanism

underpinning this association. First, caesarean delivery is likely to be a marker of adverse

pregnancy and delivery events – indeed, our finding of increased emergency caesarean

rates indicated by fetal distress seems to support this hypothesis. However, the association

remained and actually became stronger, after adjusting for most other possible pregnancy

complications. It was customary to use 100% oxygen to resuscitate babies born by

caesarean section in the past. It is possible that this could have played a role in the

subsequent development of cancer. The last explanation involves epigenetic modulations at

birth. Schlinzig et al37 have demonstrated altered DNA-methylation in cord white blood cells

after caesarean delivery and suggested that this may be the basis of increased risk of

asthma, diabetes and ALL seen in infants born by caesarean section.

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The association of caesarean delivery with childhood cancer seen in this analysis, is likely to

have far reaching consequences for obstetric practice. The recent NICE guidelines38

recommends caesarean delivery on maternal request, further evidence to support a link

between caesarean section and subsequent cancer in the offspring would seriously question

the ethics of such practice. Although, we have to remember that the majority of the

caesarean deliveries seen in the cases of childhood cancer in the current analysis were

emergency procedures with strong indications such as fetal distress. Our finding of the

strong association of childhood cancer with caesarean delivery certainly warrants further

research using record linkage of larger cohorts or prospective follow up of birth cohorts.

From the point of view of Public Health interventions, the only other modifiable risk factor

appears to be parental smoking. Several population based lifestyle interventions are already

underway to reduce the prevalence of smoking in pregnancy.

Conclusion: We found a positive association between younger maternal age at delivery and

maternal smoking with childhood cancer. In addition, preterm birth, low Apgar score at 5

minutes and delivery by caesarean section showed associations with childhood cancer,

which remained significant even after controlling for various covariates. While maternal age

and smoking, preterm birth and low Apgar Score have all been previously shown to be

associated with childhood cancer, delivery by caesarean section is a novel finding and

warrants further investigation in larger cohorts. We also propose a mechanistic study

exploring epigenetic changes associated with caesarean delivery as the underlying

mechanism linking the two conditions.

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What is already known on this topic

Extremes of maternal age at delivery, parental smoking, preterm birth and low birthweight

have all been reported to be risk factors for childhood cancer.

What this study adds

The large effect of delivery by caesarean section on the increased risk of childhood cancer is

a novel finding in this study.

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23. Sorahan T, Prior P, Lancashire RJ, et al. Childhood cancer and parental use of

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34. Podvin D, Kuehn CM, Mueller BA, et al. Maternal and birth characteristics in relation

to childhood leukaemia. Paediatr Perinat Epidemiol 2006;20:312-22.

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35. Cnattingius S, Zack M, Ekbom A et al. Prenatal and neonatal risk factors for

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36. Kaye SA, Robinson LL, Anthony Smithson W et al. Maternal reproductive history and

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DNA methylation in white blood cells after caesarean section. Acta Paediatrica. 2009;

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38. National Institute for Health and Clinical Excellence. CG132 Caesarean Section.

Available at: http://guidance.nice.org.uk/CG132 [accessed March 2012].

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Table 1. Comparison of maternal baseline characteristics between case children and control children

Characteristics Cases Controls p-

value

Age at delivery (mean, s.d.) 28.9 (5.6) 30.2 (4.6) 0.002

Maternal social class

Manual 26 (14.8%) 79 (11.2%)

0.187 Non-Manual 62 (35.2%) 295 (41.9%)

Single/widowed 87 (49.4%) 325 (46.2%)

Missing 1 (0.6%) 5 (0.7%)

Paternal social class

Manual 71 (40.3%) 329 (46.7%)

0.193 Non-manual 47 (26.7%) 183 (26.0%)

Single/widowed 57 (32.4%) 184 (26.1%)

Missing 1 (0.6%) 8 (1.1%)

Marital status

Single/Widowed/Divorced/Separated/Cohabiting 62 (35.2%) 222 (31.5%) 0.324

Married 113 (64.2%) 482 (68.4%)

Missing 1 (0.6%) 0 (0%)

BMI (mean, s.d.) (Missing cases = 12, Missing controls = 39) 25.2 (5.1) 25.5 (5.1) 0.407

Smoking

Non-smoker 107 (60.8%) 477 (67.8%) 0.034

Smoker/ex-smoker 68 (38.6%) 209 (29.7%)

Missing 1 (0.6%) 18 (2.6%)

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Table 2. Comparison of perinatal factors between cases and controls with statistically significant odds ratios shown in bold

Perinatal factors Cases N=176 Controls N=704 Unadjusted odds ratio

(95% CI)

Age and smoking adjusted

odds ratio (95% CI) – listwise

deletion

Age and smoking adjusted

odds ratio (95% CI) –

imputation of missing value

Preeclampsia 11 (6.3%) 23 (3.3%) 1.98 (0.94-4.18) 1.94 (0.88-4.28) 1.92 (0.91-4.09)

Gestational hypertension 19 (10.8%) 71 (10.1%) 1.09 (0.62-1.89) 1.21 (0.67-2.17) 1.13 (0.64-2.01)

Placenta praevia 3 (1.7%) 4 (0.6%) 3.00 (0.67-13.40) 3.46 (0.76-15.65) 3.45 (0.76-15.62)

Abruption 1 (0.6%) 4 (0.6%) 1.00 (0.11-8.95) 1.31 (0.14-12.66) 1.04 (0.12-9.41)

Other APH 19 (10.8%) 77 (10.9%) 0.99 (0.58-1.68) 0.98 (0.56-1.72) 0.96 (0.56-1.65)

Previous miscarriage 18 (10.2%) 103 (14.6%) 0.67 (0.39-1.13) 0.83 (0.48-1.43) 0.70 (0.41-1.19)

Preterm birth 24 (13.6%) 47 (6.7%) 2.23 (1.31-3.79) 2.09 (1.16-3.76) 2.23 (1.29-3.85)

Low birthweight 17 (9.7%) 38 (5.4%) 1.87 (1.03-3.39) 1.81 (0.94-3.45) 1.78 (0.97-3.28)

Low apgar at 1 minute 30 (17.1%) 107 (15.4%) 1.14 (0.73-1.78) 1.14 (0.71-1.84) 1.15 (0.73-1.81)

Low apgar at 5 minutes 8 (4.6%) 7 (1.0%) 5.01 (1.73-14.54) 4.91 (1.46-16.51) 5.70 (1.93-16.78)

Delivery by caesarean 55 (31.3%) 143 (20.4%) 1.77 (1.23-2.56) 2.25 (1.50-3.36) 2.07 (1.41-3.05)

Instrumental delivery 26 (14.8%) 144 (20.5%) 0.66 (0.41-1.04) 0.68 (0.41-1.13) 0.67 (0.42-1.08)

Intrauterine Growth

Restriction 23 (13.4%) 71 (10.3%) 1.41 (0.85-2.36) 1.20 (0.68-2.12) 1.35 (0.80-2.23)

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Table 3. Odds ratios from multivariable model

*All variables adjusted for maternal age and smoking and for other variables in the model

Statistically significant odds ratios are shown in bold.

Perinatal factors OR (95%CI) from multivariable model – listwise deletion* OR (95% CI) from multivariable model – imputation of missing

value*

Preeclampsia 1.56 (0.68-3.59) 1.55 (0.70-3.44)

Placenta praevia 1.64 (0.32-8.34) 1.65 (0.32-8.43)

Preterm birth 1.60 (0.76-3.37) 1.85 (0.92-3.72)

Low birthweight 1.00 (0.44-2.28) 0.90 (0.41-1.97)

Low apgar at 5 minutes 3.91 (1.13-13.61) 4.59 (1.52-13.87)

Delivery by caesarean 2.11 (1.38-3.23) 1.95 (1.30-2.92)

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Table 4. Distribution of sites of cancer

Cancer site No. %

C22 – Liver and intrahepatic bile ducts 2 1.14

C34 – Bronchus and lung 2 1.14

C41 – Bone and articular cartilage of other and unspecified sites 10

5.68

C49 – Other connective and soft tissue 7

3.98

C52 – Vagina 5 2.84

C56 – Ovary 3 1.70

C62 – Testis 12 6.82

C64 – Kidney except renal pelvis 7 3.98

C69 – Eye and adnexa 6 3.41

C71 – Brain 27

15.34

C72 – Spinal cord, cranial nerves, other CNS 3 1.70

C74 – Adrenal gland 6

3.41

C75 – Other endocrine glands and related structures 4

2.27

C76 – Other and ill-defined sites 2 1.14

C83 – Diffuse non-Hodgkin’s lymphoma 3 1.70

C85 – Other and unspec. non-Hodgkin’s 2 1.14

C91 – Lymphoid Leukaemia 37 21.02

C92 – Myeloid leukaemia 10 5.68

C94 – Other leukaemias of specified cell type 2 1.14

D32 - Meninges 3 1.70

D40 – Uncertain/uknown bhvr male genital 2 1.14

D43 – Uncertain/unknown bhvr. brain and CNS 2 1.14

D44 – Uncertain/unknown bhvr. endocrine 1 0.57

D47 – Uncertain/uknown bhvr. of lymphoid, haematopoietic and related tissue 9

5.11

D48 – Uncertain/unknown bhvr. unknown sites 9 5.11

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Maternal and Perinatal Risk Factors for Childhood Cancer

Sohinee Bhattacharya1* Marcus Beasley1 Dong Pang2 Gary J Macfarlane1

1Epidemiology Group, Division of Applied Health Sciences, University of Aberdeen 2 Institute of Health Research, University of Bedfordshire, Luton

*Corresponding author: Sohinee Bhattacharya Dugald Baird Centre for Research on Women’s Health Aberdeen Maternity Hospital Aberdeen AB25 2ZL Tel: +44 1224 438441 e-mail: [email protected] Running title: Risk factors for childhood cancer

Conflict of Interest: All authors have completed the Unified Competing Interest form at http://www.icmje.org/coi_disclosure.pdf and declare: NHS Grampian Endowment funded the study; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, a worldwide licence to the Publishers and its licensees in perpetuity, in all forms, formats and media (whether known now or created in the future), to (i) publish, reproduce, distribute, display and store the Contribution, (ii) translate the Contribution into other languages, create adaptations, reprints, include within collections and create summaries, extracts and/or, abstracts of the Contribution, (iii) create any other derivative work(s) based on the Contribution, (iv) to exploit all subsidiary rights in the Contribution, (v) the inclusion of electronic links from the Contribution to third party material where-ever it may be located; and, (vi) licence any third party to do any or all of the above. Contributorship: SB was responsible for designing the study, facilitating data extraction, supervising data analysis and writing of the first draft of the paper; MB analysed the data; SB, GJM and DP conceived of the research idea and GJM was responsible for overall supervision. All authors contributed to the writing of the final draft of the paper. SB is the guarantor of this paper. Ethics: This research proposal was approved by the Privacy Advisory Committee of the Information and Services Division NHS Scotland and the steering group of the Aberdeen Maternity and Neonatal Databank. Formal ethical approval was not considered necessary by North of Scotland Research Ethics Service as only anonymised data were analysed in this study. Funding: This research was funded by the NHS Grampian Endowment Fund (Project no. 10/15) Role of sponsors: The University of Aberdeen acted as sponsors for this research project, but the findings and their interpretation in this study are the authors’ own. Independence of authors from funders: All authors were employed by the University of Aberdeen at the time of conducting this research and are independent from the funders. Data sharing: There is no additional data available for sharing

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Abstract Objective: To investigate maternal and perinatal risk factors for childhood cancer.

Study Design: Case control analysis of linked records from the Aberdeen Maternity and

Neonatal Databank with the Scottish Cancer Registry and the General Registry of Births and

Deaths in Scotland was carried out.

Setting: Aberdeen, Scotland

Participants: Cases (n=176) comprised children diagnosed with cancer under 15 years or

recorded as having died of cancer. Four controls per case were matched by age and gender.

Risk factors tested: Maternal age, BMI, social class, marital status and smoking as well as

preeclampsia, antepartum haemorrhage and previous miscarriage, gestational age,

birthweight, and Apgar scores were compared between groups to test for association with

cancer. Odds ratios with 95% Confidence Intervals were calculated using conditional logistic

regression in both univariable and multivariable models.

Results: Of the maternal characteristics tested, mother’s age at delivery {cases mean

28.9(S.D.5.6) years versus controls mean 30.2(S.D4.6), p = 0.002} and smoking status

(38.6% smokers among cases, 29.7% among controls, p=0.034) were found to be different

between groups. Of the perinatal factors tested, low Apgar score at 5 minutes (AOR 4.59,

95% CI 1.52, 13.87) and delivery by caesarean section (AOR 1.95, 95% CI 1.30, 2.92)

showed statistically significant associations with childhood cancer in the multivariable model.

Conclusions: Younger maternal age, maternal smoking, delivery by caesarean section and

low Apgar score at 5 minutes were independently associated with increased risk of

childhood cancer. The association with caesarean delivery may be mediated through

epigenetic mechanism and warrants further investigation.

Key words: childhood cancer, perinatal risk factors, smoking, caesarean delivery

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Introduction:

Childhood cancer has been increasing in Scotland. A published report estimates that its

incidence has risen from 108.3 per million child-years in 1976 to 160.6 per million child-years

in 20071. The reason for this increasing trend remains unexplained as the etiopathogenesis

of childhood cancer is poorly understood. As most present in the first few years of life,

epidemiologists hypothesize that prenatal and perinatal exposures may have a part to play in

its pathogenesis. The evidence surrounding this is however, conflicting. While some

researchers have found associations of younger maternal age at delivery2 maternal

anaemia3,4, previous history of miscarriage2,5,6 maternal overweight7, and smoking8, with

some childhood cancers, others have found no such associations9-11. Fetal growth is

perhaps the most investigated perinatal risk factor for childhood cancer7,12,13 ; and yet the

authors report conflicting results. While specific central nervous system tumours have been

found to be associated with intrauterine growth restriction, the overall risk was small12.

Therefore, apart from the associations with Down’s syndrome and in utero exposure to

radiation, research into the maternal and perinatal risk factors has remained inconsistent, the

results limited by small sample sizes and recall or reporting bias.

Our objective was therefore to investigate maternal and perinatal risk factors for childhood

cancer, specifically to examine the effects of intrauterine growth restriction, preterm birth and

birth asphyxia on the development of childhood cancer in the offspring, taking advantage of

the opportunities offered by record linkage of a cancer registry with a local birth register.

Methods:

Data Sources:

The Aberdeen Maternity and Neonatal Databank (AMND) holds data for all Aberdeen City

births from 1950 to the present, and includes all reproductive events to women resident in a

defined geographical area with a relatively stable population. The exposure variables in

terms of potential maternal and perinatal risk factors were derived from the AMND. The

Scottish Cancer Registry has been in existence since 1951 and was complete up to 2010, at

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the time of the present analysis. The cases of childhood cancer were identified from this

register.

Data Linkage:

All children born between 1993 and 2006 were identified from the AMND. Their records were

linked to the Cancer Registry in Scotland (SMR 06) and the General Registry of Births and

Deaths in Scotland (GRO-S), using deterministic matching. The linkage was carried out by

data analysts from the Information and Services Division of NHS Scotland using Community

Health Index (CHI) numbers. The CHI number is a number unique to all individuals

registered with a general practice in Scotland and recorded in both databases used in this

study. In a small proportion of cases where CHI number was not available, probabilistic

matching using surname, date of birth and postcode was used. After data linkage, all

identifying information, including CHI numbers were removed and an anonymised dataset

was provided for analysis.

Study design:

A case control study design was employed. Cases comprised all children identified as above

from the AMND who were diagnosed with cancer under 15 years of age in Scotland as

recorded in the Scottish Cancer Registry or recorded as having died of cancer. Controls

were selected from the pool of children not diagnosed as having cancer, matched by age

and gender using four controls per case.

Twins and multiple births were excluded as were stillbirths and early neonatal deaths. As

Down’s syndrome is known to be associated with a higher risk of Acute Lymphoblastic

Leukaemia (ALL), all cases of diagnosed Down’s syndrome were excluded. Moreover, those

children who had died of non-cancer causes prior to their 15th birthday, as identified from

GRO-S were also excluded.

Exposure and outcome variables used in the analysis:

Maternal sociodemographic factors such as age at delivery, body mass index (BMI),

Registrar General’s occupation-based social class, marital status, previous history of

miscarriage and smoking habits were extracted from the AMND. Any complications recorded

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during the index pregnancy such as preeclampsia, gestational hypertension, and antepartum

haemorrhage as well as mode of delivery, gestational age at delivery, birthweight,

Standardised Birthweight Score14, and Apgar score at 1 and 5 minutes were also extracted.

Data extractors were blind to the case-control status of the individual children.

The outcome variables obtained from the Cancer Registry in Scotland were in the form of a

binary variable (yes/no) indicating whether or not a cancer record was present and if

present, the site of cancer given as International Classification of Diseases (ICD) codes.

Similarly, death records with up to 10 different causes of death given by ICD codes were

obtained from linking with GRO-S.

Statistical Analysis:

All analyses were conducted using STATA version 11 (STATA Corp, Texas, USA).

Maternal baseline characteristics were compared between children diagnosed with cancer

and controls using independent two-sample t-tests and chi-square tests. Maternal

complications such as gestational hypertension, pre-eclampsia, antepartum haemorrhage

and previous history of miscarriage were compared between the cases and controls using

univariate conditional regression to calculate odds ratios (OR) with 95% confidence intervals

(CI). Similarly, perinatal factors like gestation at birth, birth weight, intrauterine growth

restriction measured by standardised birthweight score, Apgar score at 1 and 5 minutes

were also tested in univariate models for any association with childhood cancer. Then a

multivariable conditional logistic regression model was fitted that included as independent

variables all risk factors tested on univariate analysis. The possibility of cancer subgroup

analysis was considered according to the International Classification of Childhood Cancer,

but the number of cases in each subgroup was too small to warrant this.

Missing data:

Apart from the variables describing maternal baseline characteristics, the other risk factors

did not have any missing values. There were 18 controls and 1 case with missing smoking

data. The multivariable model was repeated including and excluding the individuals with

missing information. We used two methodological approaches to handle this - listwise

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deletion – ie, not including any group where one person in that group has missing data, and

imputation by attaching a value to the missing data so that all cases and controls were

included in the analysis. The odds ratios obtained by both methods are presented.

Ethical considerations:

Approval to carry out the study was obtained from the AMND steering committee and the

Privacy Advisory Committee for the Information Services Division of National Health

Services, Scotland. As the study involved the analysis of routinely collected anonymised

data, formal ethical approval was not required as declared by the North of Scotland

Research Ethics Service.

Results:

There were 62375 deliveries between 1993 and 2006 as identified from the AMND. After

excluding Down’s syndrome cases, twins and multiple births, stillbirths and early neonatal

deaths, there were 60117 children eligible for linkage with the Cancer Registry. It was

possible to link 43591 of these children to the cancer and GRO-S databases. Amongst the

children with linked data, 106 had died of non-cancer causes before they reached the age of

15 and were therefore excluded from the analysis. Of the remainder, 176 were found to have

a record in the Cancer Registry, giving a cumulative incidence rate of childhood cancer up to

15 years of 4.05 per 1000 deliveries. They constituted the cases for the analysis and were

matched in 1:4 ratio by year of birth and sex from the pool of remaining children without any

records of cancer to obtain 704 controls.

Maternal baseline characteristics were compared between cases and matched controls in

Table 1. Of the maternal characteristics tested, mother’s age at delivery (cases mean 28.9

years, s.d. 5.6; controls mean 30.2, s.d. 4.6; p = 0.002) and smoking status (38.6% current

or ex-smokers among cases, 29.7% among controls, p=0.022) were found to be significantly

different between the two groups.

Table 2 presents the unadjusted odds ratios with 95% confidence intervals for all the

perinatal potential risk factors for childhood cancer. Of the factors tested, preterm birth {OR

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2.23(1.31 – 3.79)}; low birth weight {OR 1.87(1.03 – 3.39)}, low Apgar score at 5 minutes

{OR 5.01(1.73 – 14.54)} and delivery by caesarean section {OR 1.77(1.23 – 2.56)} were

found to be statistically significant. Subsequently, these factors were adjusted for maternal

age at delivery and smoking. As the maternal smoking variable had some missing data, we

handled this using two approaches – listwise deletion and imputation of missing value. After

these adjustments, low birthweight no longer remained significant, but the other associations

were strengthened.

After conducting the univariate analyses multivariable models were fitted including maternal

age, smoking status, preeclampsia, placenta praevia, preterm birth, low birthweight, low

Apgar at 5 minutes and delivery by caesarean as independent variables (results in Table 3).

Similar to the previous analyses, we used two methods of listwise deletion and imputation of

missing value to adjust for smoking status. Of the perinatal factors tested, Apgar score below

7 at 5 minutes {AOR 3.91, 95% CI 1.13 – 13.61(listwise deletion); AOR 4.59, 95% CI 1.52,

13.87 (imputation)} and delivery by caesarean section {AOR 2.11, 95% CI 1.38, 3.23

(listwise deletion); AOR 1.95, 95% CI 1.30, 2.92 (imputation)} showed statistically significant

associations with childhood cancer in both multivariable models adjusted for maternal age,

smoking and other factors simultaneously included in the models. Preterm birth (delivery

before 37 completed weeks of gestation) and low birth weight defined as a birth weight

below 2500g, showed a significant association in the univariate analysis, but these

associations were no longer significant in the multivariable model. The associations were not

statistically significant on univariate or multivariable analysis between the risk of childhood

cancer and hypertensive disorders, antepartum haemorrhage, previous history of

miscarriage or IUGR. Unlike the Apgar score at 5 minutes, the score at 1 minute did not

show any association with childhood cancer.

We further investigated the types of preterm delivery (spontaneous or induced) and

caesarean section (elective or emergency) as risk factors for childhood cancer and found

that both spontaneous and induced preterm delivery were significantly associated in the

adjusted model but only delivery by emergency caesarean section remained significant on

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subgroup analysis (AOR 1.43, 95% CI 1.20, 2.18). Further, we found that the commonest

indication for caesarean delivery in the babies who were subsequently diagnosed with

cancer was fetal distress (data not shown).

Table 4 shows the distribution of cancer sites in the 176 cases. As this table shows, the

commonest sites were the brain and haemopoietic organs, especially leukaemia, but the

numbers in the subgroups were too small to allow any meaningful analysis.

Discussion:

We aimed to study the maternal and perinatal risk factors at the time of birth associated with

the diagnosis of childhood cancer using record linkage between two high quality registers in

Scotland. We found a positive association between younger maternal age at delivery and

maternal smoking with childhood cancer. In addition, preterm birth before 37 weeks of

gestation, Apgar score below 7 at 5 minutes and delivery by emergency caesarean section

showed statistically significant associations with childhood cancer the last two of which

remained significant in the adjusted models.

Childhood cancer is a rare condition. Case control studies are therefore the most efficient

epidemiological study design to study several risk factors at the time of birth. Cancer

registries across the world have been utilised to identify cases, but finding appropriate

controls remains problematic. Moreover, data collections regarding exposures by means of

interviews or questionnaires are subject to recall and reporting bias. More recently, linkage

of birth registers with cancer registries has been utilised to design large scale cohort studies.

However, the routine data collection is liable to lack sufficiently detailed data regarding

exposure and potential confounding factors. We have tried to minimise these problems by

linking two high quality registers in Scotland. Previous validation projects have shown these

databases to be 100% complete and over 97% accurate15. Detailed and contemporaneous

recording of obstetric data in the AMND eliminated recall and reporting bias. The large

number of social and demographic variables recorded in the AMND enabled incorporation of

most potential covariates in the analysis. Despite these strengths to our study design, we

were limited by the small number of cases and it is possible that we did not have sufficient

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power to detect some weak associations reported previously in the literature. Maternal and

perinatal risk factors for childhood cancer appear to differ by the site of cancer in the

published literature. The number of cases according to site specific cancer diagnosis was

too small in our sample to allow any subgroup analysis. Further, morphology codes were not

available for us to carry out more appropriate groupings of childhood cancers. This, coupled

with the fact that we had to conduct our analyses on all cancers would have made it less

likely for us to find associations that exist with site specific cancers. This could be a major

limitation of the current analysis.

The association of parental age with the diagnosis of cancer in general as well as in specific

sites has been studied before. Johnson et al16 in a pooled analysis of register linkage data

from several US states, found that the risk of childhood cancer increased with increasing

maternal age, while paternal age appeared to have no effect on the risk. On the other hand

several other studies, similar to the current analysis have shown that younger maternal age

was associated with increased childhood cancer risk2,17. There could be several

explanations for the disparate findings. In a register linkage study carried out in Sweden18,19,

researchers found that advancing maternal age was positively associated with childhood

cancer risk but only in a historical cohort. This association disappeared in a more recent

cohort of women although the reasons for this are unknown. Moreover, Schutz20 suggests

that the association of lower maternal age at the time of delivery with leukaemia in the

offspring could be explained by non-response bias, although this is not applicable to the

present study.

The relationship between maternal smoking and childhood cancer in the offspring is complex

and controversial. While Sorahan et al21 - 23 and Edraki24 found an increased overall risk of

childhood cancer with paternal cigarette smoking, there did not appear to be an association

with maternal smoking after adjusting for birthweight. Further, Pang et al9 did not find

evidence of smoking as a risk factor for childhood cancer after adjusting for parental age.

Similar associations were reported by Chang et al25 with regard to Acute Lymphoblastic

Leukaemia (ALL). The evidence appears to indicate that neonatal passive smoking plays a

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more important role than in utero transfer of maternal smoke related toxins, although we

cannot rule out the possibility of an association between maternal smoking and site-specific

cancers26,27. For the current analysis, we did not have access to data on paternal smoking

habits and the association seen with maternal smoking could be due to this variable acting

as proxy for paternal smoking.

Other associations noted in this study have been reported before – preterm birth28, and low

Apgar score2,28. Birthweight has received a lot of attention as a risk factor for childhood

cancer. While brain tumours and retinoblastoma appear to be associated with high

birthweight29 - 31 others have found hepatoblastomas7,32 and gliomas33 to be associated with

very low birthweight infants. Schmidt28 et al observed a U-shaped relationship between

birthweight and cancer risk, while Podvin34 found birthweight adjusted for gestational age to

be a better predictor than birthweight alone for the diagnosis of ALL, lending support to our

findings. It is however, important to note, that we did not find an association with intrauterine

growth restriction as measured by the z-score or standardized birthweight score.

Few studies have assessed mode of delivery, specifically caesarean delivery, as a possible

risk factor for the development of childhood cancer. Those that have done, have found a

weak to moderate association7,35,36 between caesarean delivery and subsequent risk of

developing ALL. Several hypotheses can be developed regarding the biological mechanism

underpinning this association. First, caesarean delivery is likely to be a marker of adverse

pregnancy and delivery events – indeed, our finding of increased emergency caesarean

rates indicated by fetal distress seems to support this hypothesis. However, the association

remained and actually became stronger, after adjusting for most other possible pregnancy

complications. It was customary to use 100% oxygen to resuscitate babies born by

caesarean section in the past. It is possible that this could have played a role in the

subsequent development of cancer. The last explanation involves epigenetic modulations at

birth. Schlinzig et al37 have demonstrated altered DNA-methylation in cord white blood cells

after caesarean delivery and suggested that this may be the basis of increased risk of

asthma, diabetes and ALL seen in infants born by caesarean section.

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The association of caesarean delivery with childhood cancer seen in this analysis, is likely to

have far reaching consequences for obstetric practice. The recent NICE guidelines38

recommends caesarean delivery on maternal request, further evidence to support a link

between caesarean section and subsequent cancer in the offspring would seriously question

the ethics of such practice. Although, we have to remember that the majority of the

caesarean deliveries seen in the cases of childhood cancer in the current analysis were

emergency procedures with strong indications such as fetal distress. Our finding of the

strong association of childhood cancer with caesarean delivery certainly warrants further

research using record linkage of larger cohorts or prospective follow up of birth cohorts.

From the point of view of Public Health interventions, the only other modifiable risk factor

appears to be parental smoking. Several population based lifestyle interventions are already

underway to reduce the prevalence of smoking in pregnancy.

Conclusion: We found a positive association between younger maternal age at delivery and

maternal smoking with childhood cancer. In addition, preterm birth, low Apgar score at 5

minutes and delivery by caesarean section showed associations with childhood cancer,

which remained significant even after controlling for various covariates. While maternal age

and smoking, preterm birth and low Apgar Score have all been previously shown to be

associated with childhood cancer, delivery by caesarean section is a novel finding and

warrants further investigation in larger cohorts. We also propose a mechanistic study

exploring epigenetic changes associated with caesarean delivery as the underlying

mechanism linking the two conditions.

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What is already known on this topic

Extremes of maternal age at delivery, parental smoking, preterm birth and low birthweight

have all been reported to be risk factors for childhood cancer.

What this study adds

The large effect of delivery by caesarean section on the increased risk of childhood cancer is

a novel finding in this study.

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16. Johnson KJ, Carozza SE, Chow EJ, et al. Parental age and risk of childhood cancer:

A pooled analysis. Epidemiology 2009; 20: 475-483.

17. Schüz J, Kaatsch P, Kaletsch U, et al. Association of childhood cancer with factors

related to pregnancy and birth. Int J Epidemiol 1999; 28:631-9.

18. Maule MM, Merletti F, Pastore G et al. Effects of maternal age and cohort of birth on

incidence time trends of childhood acute lymphoblastic leukemia. Can Epi Bio Prev

2007;16:347-51.

19. 22. Maule MM, Vizzini L, Czene K, et al. How the effect of maternal age on the risk of

childhood leukemia changed over time in Sweden, 1960-2004. Environ Health

Perspect 2009;117:299-302.

20. Schüz J. Non-response bias as a likely cause of the association between young

maternal age at the time of delivery and the risk of cancer in the offspring. Paediatr

Perinat Epidemiol 2003;17:106-12.

21. Sorahan T, Lancashire RJ, Hultén MA, et al. Childhood cancer and parental use of

tobacco: Deaths from 1953 to 1955. Br J Cancer 1997;75:134-8.

22. Sorahan T, McKinney PA, Mann JR, et al. Childhood cancer and parental use of

tobacco: Findings from the inter-regional epidemiological study of childhood cancer

(IRESCC). Br J Cancer 2001;84:141-6.

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23. Sorahan T, Prior P, Lancashire RJ, et al. Childhood cancer and parental use of

tobacco: Deaths from 1971 to 1976. Br J Cancer 1997;76:1525-31.

24. Edraki M, Rambod M. Parental smoking and risk of childhood cancer: Hospital-based

case-control study in Shiraz. Eastern Mediterranean Health Journal 2011;17:303-8.

25. Chang JS, Selvin S, Metayer C, et al. Parental smoking and the risk of childhood

leukemia. Am J Epidemiol 2006;163:1091-100.

26. Mucci LA, Granath F, Cnattingius S. Maternal smoking and childhood leukemia and

lymphoma risk among 1,440,542 Swedish children. Can Epi Bio Prev. 2004;13:1528-

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27. Stavrou EP, Baker DF, Bishop JF. Maternal smoking during pregnancy and

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28. Schmidt LS, Schüz J, Lähteenmäki P, et al. Fetal Growth, Preterm Birth, Neonatal

Stress and Risk for CNS Tumors in Children: A Nordic Population- and Register-

Based Case-Control Study. Can Epi Bio Prev. 2010; 19: 1042-1052.

29. Harder T, Plagemann A, Harder A. Birth weight and risk of neuroblastoma: a meta-

analysis. Int J Epidemiol 2010; 39: 746-756

30. Daling JR, Starzyk P, Olshan AF, et al. Birth weight and the incidence of childhood

cancer. J Natl Cancer Inst 1984;72:1039-41.

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low birth weights. Pediatrics 2009;124:96-104.

34. Podvin D, Kuehn CM, Mueller BA, et al. Maternal and birth characteristics in relation

to childhood leukaemia. Paediatr Perinat Epidemiol 2006;20:312-22.

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35. Cnattingius S, Zack M, Ekbom A et al. Prenatal and neonatal risk factors for

childhood myeloid leukaemia. Cancer Epidemiol Biomarkers and Prev 1995; 4:441 -

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36. Kaye SA, Robinson LL, Anthony Smithson W et al. Maternal reproductive history and

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DNA methylation in white blood cells after caesarean section. Acta Paediatrica. 2009;

98:1096 – 1099.

38. National Institute for Health and Clinical Excellence. CG132 Caesarean Section.

Available at: http://guidance.nice.org.uk/CG132 [accessed March 2012].

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Table 1. Comparison of maternal baseline characteristics between case children and control children

Characteristics Cases Controls p-

value

Age at delivery (mean, s.d.) 28.9 (5.6) 30.2 (4.6) 0.002

Maternal social class

Manual 26 (14.8%) 79 (11.2%)

0.187 Non-Manual 62 (35.2%) 295 (41.9%)

Single/widowed 87 (49.4%) 325 (46.2%)

Missing 1 (0.6%) 5 (0.7%)

Paternal social class

Manual 71 (40.3%) 329 (46.7%)

0.193 Non-manual 47 (26.7%) 183 (26.0%)

Single/widowed 57 (32.4%) 184 (26.1%)

Missing 1 (0.6%) 8 (1.1%)

Marital status

Single/Widowed/Divorced/Separated/Cohabiting 62 (35.2%) 222 (31.5%) 0.324

Married 113 (64.2%) 482 (68.4%)

Missing 1 (0.6%) 0 (0%)

BMI (mean, s.d.) (Missing cases = 12, Missing controls = 39) 25.2 (5.1) 25.5 (5.1) 0.407

Smoking

Non-smoker 107 (60.8%) 477 (67.8%) 0.034

Smoker/ex-smoker 68 (38.6%) 209 (29.7%)

Missing 1 (0.6%) 18 (2.6%)

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Table 2. Comparison of perinatal factors between cases and controls with statistically significant odds ratios shown in bold

Perinatal factors Cases N=176 Controls N=704 Unadjusted odds ratio

(95% CI)

Age and smoking adjusted

odds ratio (95% CI) – listwise

deletion

Age and smoking adjusted

odds ratio (95% CI) –

imputation of missing value

Preeclampsia 11 (6.3%) 23 (3.3%) 1.98 (0.94-4.18) 1.94 (0.88-4.28) 1.92 (0.91-4.09)

Gestational hypertension 19 (10.8%) 71 (10.1%) 1.09 (0.62-1.89) 1.21 (0.67-2.17) 1.13 (0.64-2.01)

Placenta praevia 3 (1.7%) 4 (0.6%) 3.00 (0.67-13.40) 3.46 (0.76-15.65) 3.45 (0.76-15.62)

Abruption 1 (0.6%) 4 (0.6%) 1.00 (0.11-8.95) 1.31 (0.14-12.66) 1.04 (0.12-9.41)

Other APH 19 (10.8%) 77 (10.9%) 0.99 (0.58-1.68) 0.98 (0.56-1.72) 0.96 (0.56-1.65)

Previous miscarriage 18 (10.2%) 103 (14.6%) 0.67 (0.39-1.13) 0.83 (0.48-1.43) 0.70 (0.41-1.19)

Preterm birth 24 (13.6%) 47 (6.7%) 2.23 (1.31-3.79) 2.09 (1.16-3.76) 2.23 (1.29-3.85)

Low birthweight 17 (9.7%) 38 (5.4%) 1.87 (1.03-3.39) 1.81 (0.94-3.45) 1.78 (0.97-3.28)

Low apgar at 1 minute 30 (17.1%) 107 (15.4%) 1.14 (0.73-1.78) 1.14 (0.71-1.84) 1.15 (0.73-1.81)

Low apgar at 5 minutes 8 (4.6%) 7 (1.0%) 5.01 (1.73-14.54) 4.91 (1.46-16.51) 5.70 (1.93-16.78)

Delivery by caesarean 55 (31.3%) 143 (20.4%) 1.77 (1.23-2.56) 2.25 (1.50-3.36) 2.07 (1.41-3.05)

Instrumental delivery 26 (14.8%) 144 (20.5%) 0.66 (0.41-1.04) 0.68 (0.41-1.13) 0.67 (0.42-1.08)

Intrauterine Growth

Restriction 23 (13.4%) 71 (10.3%) 1.41 (0.85-2.36) 1.20 (0.68-2.12) 1.35 (0.80-2.23)

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Table 3. Odds ratios from multivariable model

*All variables adjusted for maternal age and smoking and for other variables in the model

Statistically significant odds ratios are shown in bold.

Perinatal factors OR (95%CI) from multivariable model – listwise deletion* OR (95% CI) from multivariable model – imputation by missing

value*

Preeclampsia 1.56 (0.68-3.59) 1.55 (0.70-3.44)

Placenta praevia 1.64 (0.32-8.34) 1.65 (0.32-8.43)

Preterm birth 1.60 (0.76-3.37) 1.85 (0.92-3.72)

Low birthweight 1.00 (0.44-2.28) 0.90 (0.41-1.97)

Low apgar at 5 minutes 3.91 (1.13-13.61) 4.59 (1.52-13.87)

Delivery by caesarean 2.11 (1.38-3.23) 1.95 (1.30-2.92)

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Table 4. Distribution of sites of cancer

Cancer site No. %

C22 – Liver and intrahepatic bile ducts 2 1.14

C34 – Bronchus and lung 2 1.14

C41 – Bone and articular cartilage of other and unspecified sites 10

5.68

C49 – Other connective and soft tissue 7

3.98

C52 – Vagina 5 2.84

C56 – Ovary 3 1.70

C62 – Testis 12 6.82

C64 – Kidney except renal pelvis 7 3.98

C69 – Eye and adnexa 6 3.41

C71 – Brain 27

15.34

C72 – Spinal cord, cranial nerves, other CNS 3 1.70

C74 – Adrenal gland 6

3.41

C75 – Other endocrine glands and related structures 4

2.27

C76 – Other and ill-defined sites 2 1.14

C83 – Diffuse non-Hodgkin’s lymphoma 3 1.70

C85 – Other and unspec. non-Hodgkin’s 2 1.14

C91 – Lymphoid Leukaemia 37 21.02

C92 – Myeloid leukaemia 10 5.68

C94 – Other leukaemias of specified cell type 2 1.14

D32 - Meninges 3 1.70

D40 – Uncertain/uknown bhvr male genital 2 1.14

D43 – Uncertain/unknown bhvr. brain and CNS 2 1.14

D44 – Uncertain/unknown bhvr. endocrine 1 0.57

D47 – Uncertain/uknown bhvr. of lymphoid, haematopoietic and related tissue 9

5.11

D48 – Uncertain/unknown bhvr. unknown sites 9 5.11

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Maternal and perinatal risk factors for childhood cancer

Supplemental file: STROBE Statement

Checklist of items that should be included in reports of case control studies

Item No Recommendation

Location within manuscript

Title and

abstract

1 (a) Indicate the study’s design with a

commonly used term in the title or the

abstract

Abstract: Methods

(b) Provide in the abstract an

informative and balanced summary of

what was done and what was found

Abstract: Methods and

Results

Introduction

Background/

rationale

2 Explain the scientific background and

rationale for the investigation being

reported

Introduction: Lines 2 -

17

Objectives 3 State specific objectives, including

any prespecified hypotheses

Introduction: Lines 18 -

22

Methods

Study design 4 Present key elements of study design

early in the paper

Methods: Lines 41-51

Setting 5 Describe the setting, locations, and

relevant dates, including periods of

recruitment, exposure, follow-up, and

data collection

Methods, Lines 24 - 64

Participants 6 (a) Give the eligibility criteria, and the

sources and methods of selection of

participants. Describe methods of

follow-up

Methods, Lines 47 - 51

(b) For matched studies, give

matching criteria and number of

exposed and unexposed

Methods, Lines 41 - 47

Variables 7 Clearly define all outcomes,

exposures, predictors, potential

confounders, and effect modifiers.

Give diagnostic criteria, if applicable

Methods, Lines 52 - 64

Data

sources/

measuremen

t

8* For each variable of interest, give

sources of data and details of

methods of assessment

(measurement). Describe

comparability of assessment methods

if there is more than one group

Methods: Lines 24 - 40

Bias 9 Describe any efforts to address

potential sources of bias

Lines 141 - 161

Study size 10 Explain how the study size was

arrived at

Results Lines 90 - 99

Quantitative

variables

11 Explain how quantitative variables

were handled in the analyses. If

applicable, describe which groupings

were chosen and why

Methods: Lines 65 - 81

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Statistical

methods

12 (a) Describe all statistical methods,

including those used to control for

confounding

Lines 65 - 81

(b) Describe any methods used to

examine subgroups and interactions

Not specified

(c) Explain how missing data were

addressed

Methods lines 81 - 84

(d) If applicable, explain how loss to

follow-up was addressed

Not applicable.

(e) Describe any sensitivity analyses Not conducted

Results

Participants 13* (a) Report numbers of individuals at

each stage of study—eg numbers

potentially eligible, examined for

eligibility, confirmed eligible, included

in the study, completing follow-up,

and analysed

Results: Lines 90 - 99

(b) Give reasons for non-participation

at each stage

Not applicable

Descriptive

data

14* (a) Give characteristics of study

participants (eg demographic, clinical,

social) and information on exposures

and potential confounders

Table 1 and Results:

Lines 104 - 114

Outcome

data

15* Report numbers of outcome events or

summary measures over time

Tables 2, Results: 115

- 131

Main results 16 (a) Give unadjusted estimates and, if

applicable, confounder-adjusted

estimates and their precision (eg,

95% confidence interval). Make clear

which confounders were adjusted for

and why they were included

Table 2

(b) Report category boundaries when

continuous variables were

categorized

Not applicable

Other

analyses

17 Report other analyses done—eg

analyses of subgroups and

interactions, and sensitivity analyses

Lines 125 - 134

Discussion

Key results 18 Summarise key results with reference

to study objectives

Discussion: Lines 136 -

143

Limitations 19 Discuss limitations of the study, taking

into account sources of potential bias

or imprecision. Discuss both direction

and magnitude of any potential bias

Discussion: Lines 144 -

164

Interpretation 20 Give a cautious overall interpretation

of results considering objectives,

limitations, multiplicity of analyses,

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relevant evidence

Discussion: Lines 213 -

224

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Generalis-

ability

21 Discuss the generalisability (external

validity) of the study results

Discussion: Lines 156 -

164

Other information

Funding 22 Give the source of funding and the role of the funders

for the present study and, if applicable, for the

original study on which the present article is based

Title page

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Journal: BMJ Open

Manuscript ID: bmjopen-2013-003656.R1

Article Type: Research

Date Submitted by the Author: 18-Oct-2013

Complete List of Authors: Bhattacharya, Sohinee; University of Aberdeen, Public Health

Beasley, Marcus; University of Aberdeen, Epidemiology Group Pang, Dong; University of Bedfordshire, Institute of Health Research Macfarlane, Gary; University of Aberdeen, Epidemiology Group

<b>Primary Subject Heading</b>:

Epidemiology

Secondary Subject Heading: Obstetrics and gynaecology, Oncology

Keywords: EPIDEMIOLOGY, Fetal medicine < OBSTETRICS, Paediatric oncology < ONCOLOGY

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Maternal and Perinatal Risk Factors for Childhood Cancer

Sohinee Bhattacharya1* Marcus Beasley1 Dong Pang2 Gary J Macfarlane1

1Epidemiology Group, Division of Applied Health Sciences, University of Aberdeen 2 Institute of Health Research, University of Bedfordshire, Luton *Corresponding author: Sohinee Bhattacharya Dugald Baird Centre for Research on Women’s Health Aberdeen Maternity Hospital Aberdeen AB25 2ZL Tel: +44 1224 438441 e-mail: [email protected]

Running title: Risk factors for childhood cancer

Key words: childhood cancer, perinatal risk factors, smoking, caesarean delivery

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Abstract Objective: To investigate maternal and perinatal risk factors for childhood cancer.

Study Design: Case control analysis of linked records from the Aberdeen Maternity and

Neonatal Databank with the Scottish Cancer Registry and the General Registry of Births and

Deaths in Scotland was carried out.

Setting: Aberdeen, Scotland

Participants: Cases (n=176) comprised children diagnosed with cancer under 15 years or

recorded as having died of cancer. Four controls per case were matched by age and gender.

Risk factors tested: Maternal age, BMI, social class, marital status and smoking as well as

preeclampsia, antepartum haemorrhage and previous miscarriage, gestational age,

birthweight, and Apgar scores were compared between groups to test for association with

cancer. Odds ratios with 95% Confidence Intervals were calculated using conditional logistic

regression in both univariable and multivariable models.

Results: Of the maternal characteristics tested, mother’s age at delivery {cases mean

28.9(S.D.5.6) years versus controls mean 30.2(S.D4.6), p = 0.002} and smoking status

(38.6% smokers among cases, 29.7% among controls, p=0.034) were found to be different

between groups. Of the perinatal factors tested, low Apgar score at 5 minutes (AOR 4.59,

95% CI 1.52, 13.87) and delivery by caesarean section (AOR 1.95, 95% CI 1.30, 2.92)

showed statistically significant associations with childhood cancer in the multivariable model.

Conclusions: Younger maternal age, maternal smoking, delivery by caesarean section and

low Apgar score at 5 minutes were independently associated with increased risk of

childhood cancer. The association with caesarean delivery may be mediated through

epigenetic mechanism and warrants further investigation.

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Article Summary: Article Focus –

• What are the maternal characteristics associated with childhood cancer?

• What factors during pregnancy and at the time of birth are associated with

childhood cancer?

Key Messages –

• Extremes of maternal age at delivery, parental smoking, preterm birth and low

birthweight have all been reported to be risk factors for childhood cancer.

• The large effect of delivery by caesarean section on the increased risk of childhood

cancer is a novel finding in this study.

Strengths and limitations –

• Detailed and contemporaneous recording of data in the databases eliminated recall

and reporting bias.

• The large number of social and demographic variables recorded in the AMND

enabled incorporation of most potential covariates in the analysis.

• Inadequate power to detect some weak associations reported previously in the

literature.

• The number of cases according to site specific cancer diagnosis was too small in our

sample to allow any subgroup analysis.

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Introduction:

Childhood cancer has been increasing in Scotland. A published report estimates that its

incidence has risen from 108.3 per million child-years in 1976 to 160.6 per million child-years

in 20071. The reason for this increasing trend remains unexplained as the etiopathogenesis

of childhood cancer is poorly understood. As most present in the first few years of life,

epidemiologists hypothesize that prenatal and perinatal exposures may have a part to play in

its pathogenesis. The evidence surrounding this is however, conflicting. While some

researchers have found associations of younger maternal age at delivery2 maternal

anaemia3,4, previous history of miscarriage2,5,6 maternal overweight7, and smoking8, with

some childhood cancers, others have found no such associations9-11. Fetal growth is

perhaps the most investigated perinatal risk factor for childhood cancer7,12,13 ; and yet the

authors report conflicting results. While specific central nervous system tumours have been

found to be associated with intrauterine growth restriction, the overall risk was small12.

Therefore, apart from the associations with Down’s syndrome and in utero exposure to

radiation, research into the maternal and perinatal risk factors has remained inconsistent, the

results limited by small sample sizes and recall or reporting bias.

Our objective was therefore to investigate maternal and perinatal risk factors for childhood

cancer, specifically to examine the effects of intrauterine growth restriction, preterm birth and

birth asphyxia on the development of childhood cancer in the offspring, taking advantage of

the opportunities offered by record linkage of a cancer registry with a local birth register.

Methods:

Data Sources:

The Aberdeen Maternity and Neonatal Databank (AMND) holds data for all Aberdeen City

births from 1950 to the present, and includes all reproductive events to women resident in a

defined geographical area with a relatively stable population. The exposure variables in

terms of potential maternal and perinatal risk factors were derived from the AMND. The

Scottish Cancer Registry has been in existence since 1951 and was complete up to 2010, at

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the time of the present analysis. The cases of childhood cancer were identified from this

register.

Data Linkage:

All children born between 1993 and 2006 were identified from the AMND. Their records were

linked to the Cancer Registry in Scotland (SMR 06) and the General Registry of Births and

Deaths in Scotland (GRO-S), using deterministic matching. The linkage was carried out by

data analysts from the Information and Services Division of NHS Scotland using Community

Health Index (CHI) numbers. The CHI number is a number unique to all individuals

registered with a general practice in Scotland and recorded in both databases used in this

study. In a small proportion of cases where CHI number was not available, probabilistic

matching using surname, date of birth and postcode was used. After data linkage, all

identifying information, including CHI numbers were removed and an anonymised dataset

was provided for analysis.

Study design:

A case control study design was employed. Cases comprised all children identified as above

from the AMND who were diagnosed with cancer under 15 years of age in Scotland as

recorded in the Scottish Cancer Registry or recorded as having died of cancer. Controls

were selected from the pool of children not diagnosed as having cancer, matched by age

and gender using four controls per case.

Twins and multiple births were excluded as were stillbirths and early neonatal deaths. As

Down’s syndrome is known to be associated with a higher risk of Acute Lymphoblastic

Leukaemia (ALL), all cases of diagnosed Down’s syndrome were excluded. Moreover, those

children who had died of non-cancer causes prior to their 15th birthday, as identified from

GRO-S were also excluded.

Exposure and outcome variables used in the analysis:

Maternal sociodemographic factors such as age at delivery, body mass index (BMI),

Registrar General’s occupation-based social class, marital status, previous history of

miscarriage and smoking habits were extracted from the AMND. Any complications recorded

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during the index pregnancy such as preeclampsia, gestational hypertension, and antepartum

haemorrhage as well as mode of delivery, gestational age at delivery, birthweight,

Standardised Birthweight Score14, and Apgar score at 1 and 5 minutes were also extracted.

Data extractors were blind to the case-control status of the individual children.

The outcome variables obtained from the Cancer Registry in Scotland were in the form of a

binary variable (yes/no) indicating whether or not a cancer record was present and if

present, the site of cancer given as International Classification of Diseases (ICD) codes.

Similarly, death records with up to 10 different causes of death given by ICD codes were

obtained from linking with GRO-S.

Statistical Analysis:

All analyses were conducted using STATA version 11 (STATA Corp, Texas, USA).

Maternal baseline characteristics were compared between children diagnosed with cancer

and controls using independent two-sample t-tests and chi-square tests. Maternal

complications such as gestational hypertension, pre-eclampsia, antepartum haemorrhage

and previous history of miscarriage were compared between the cases and controls using

univariate conditional regression to calculate odds ratios (OR) with 95% confidence intervals

(CI). Similarly, perinatal factors like gestation at birth, birth weight, intrauterine growth

restriction measured by standardised birthweight score, Apgar score at 1 and 5 minutes

were also tested in univariate models for any association with childhood cancer. Then a

multivariable conditional logistic regression model was fitted that included as independent

variables all risk factors tested on univariate analysis. The possibility of cancer subgroup

analysis was considered according to the International Classification of Childhood Cancer,

but the number of cases in each subgroup was too small to warrant this.

Missing data:

Apart from the variables describing maternal baseline characteristics, the other risk factors

did not have any missing values. There were 18 controls and 1 case with missing smoking

data. The multivariable model was repeated including and excluding the individuals with

missing information. We used two methodological approaches to handle this - listwise

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deletion – ie, not including any group where one person in that group has missing data, and

imputation by creation of a missing value (999) so that all cases and controls were included

in the analyses. The odds ratios obtained by both methods are presented.

Ethical considerations:

Approval to carry out the study was obtained from the AMND steering committee and the

Privacy Advisory Committee for the Information Services Division of National Health

Services, Scotland. As the study involved the analysis of routinely collected anonymised

data, formal ethical approval was not required as declared by the North of Scotland

Research Ethics Service.

Results:

There were 62375 deliveries between 1993 and 2006 as identified from the AMND. After

excluding Down’s syndrome cases, twins and multiple births, stillbirths and early neonatal

deaths, there were 60117 children eligible for linkage with the Cancer Registry. It was

possible to link 43591 of these children to the cancer and GRO-S databases. Amongst the

children with linked data, 106 had died of non-cancer causes before they reached the age of

15 and were therefore excluded from the analysis. Of the remainder, 176 were found to have

a record in the Cancer Registry, giving a cumulative incidence rate of childhood cancer up to

15 years of 4.05 per 1000 deliveries. They constituted the cases for the analysis and were

matched in 1:4 ratio by year of birth and sex from the pool of remaining children without any

records of cancer to obtain 704 controls.

Maternal baseline characteristics were compared between cases and matched controls in

Table 1. Of the maternal characteristics tested, mother’s age at delivery (cases mean 28.9

years, s.d. 5.6; controls mean 30.2, s.d. 4.6; p = 0.002) and smoking status (38.6% current

or ex-smokers among cases, 29.7% among controls, p=0.022) were found to be significantly

different between the two groups.

Table 2 presents the unadjusted odds ratios with 95% confidence intervals for all the

perinatal potential risk factors for childhood cancer. Of the factors tested, preterm birth {OR

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2.23(1.31 – 3.79)}; low birth weight {OR 1.87(1.03 – 3.39)}, low Apgar score at 5 minutes

{OR 5.01(1.73 – 14.54)} and delivery by caesarean section {OR 1.77(1.23 – 2.56)} were

found to be statistically significant. Subsequently, these factors were adjusted for maternal

age at delivery and smoking. As the maternal smoking variable had some missing data, we

handled this using two approaches – listwise deletion and imputation of a missing value.

After these adjustments, low birthweight no longer remained significant, but the other

associations were strengthened.

After conducting the univariate analyses multivariable models were fitted including maternal

age, smoking status, preeclampsia, placenta praevia, preterm birth, low birthweight, low

Apgar at 5 minutes and delivery by caesarean as independent variables (results in Table 3).

Similar to the previous analyses, we used two methods of listwise deletion and imputation of

the missing value to adjust for smoking status. Of the perinatal factors tested, Apgar score

below 7 at 5 minutes {AOR 3.91, 95% CI 1.13 – 13.61(listwise deletion); AOR 4.59, 95% CI

1.52, 13.87 (imputation)} and delivery by caesarean section {AOR 2.11, 95% CI 1.38, 3.23

(listwise deletion); AOR 1.95, 95% CI 1.30, 2.92 (imputation)} showed statistically significant

associations with childhood cancer in both multivariable models adjusted for maternal age,

smoking and other factors simultaneously included in the models. Preterm birth (delivery

before 37 completed weeks of gestation) and low birth weight defined as a birth weight

below 2500g, showed a significant association in the univariate analysis, but these

associations were no longer significant in the multivariable model. The associations were not

statistically significant on univariate or multivariable analysis between the risk of childhood

cancer and hypertensive disorders, antepartum haemorrhage, previous history of

miscarriage or IUGR. Unlike the Apgar score at 5 minutes, the score at 1 minute did not

show any association with childhood cancer.

We further investigated the types of preterm delivery (spontaneous or induced) and

caesarean section (elective or emergency) as risk factors for childhood cancer and found

that both spontaneous and induced preterm delivery were significantly associated in the

adjusted model but only delivery by emergency caesarean section remained significant on

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subgroup analysis (AOR 1.43, 95% CI 1.20, 2.18). Further, we found that the commonest

indication for caesarean delivery in the babies who were subsequently diagnosed with

cancer was fetal distress (data not shown).

Table 4 shows the distribution of cancer sites in the 176 cases. As this table shows, the

commonest sites were the brain and haemopoietic organs, especially leukaemia, but the

numbers in the subgroups were too small to allow any meaningful analysis.

Discussion:

We aimed to study the maternal and perinatal risk factors at the time of birth associated with

the diagnosis of childhood cancer using record linkage between two high quality registers in

Scotland. We found a positive association between younger maternal age at delivery and

maternal smoking with childhood cancer. In addition, preterm birth before 37 weeks of

gestation, Apgar score below 7 at 5 minutes and delivery by emergency caesarean section

showed statistically significant associations with childhood cancer the last two of which

remained significant in the adjusted models.

Childhood cancer is a rare condition. Case control studies are therefore the most efficient

epidemiological study design to study several risk factors at the time of birth. Cancer

registries across the world have been utilised to identify cases, but finding appropriate

controls remains problematic. Moreover, data collections regarding exposures by means of

interviews or questionnaires are subject to recall and reporting bias. More recently, linkage

of birth registers with cancer registries has been utilised to design large scale cohort studies.

However, the routine data collection is liable to lack sufficiently detailed data regarding

exposure and potential confounding factors. We have tried to minimise these problems by

linking two high quality registers in Scotland. Previous validation projects have shown these

databases to be 100% complete and over 97% accurate15. Detailed and contemporaneous

recording of obstetric data in the AMND eliminated recall and reporting bias. The large

number of social and demographic variables recorded in the AMND enabled incorporation of

most potential covariates in the analysis. Despite these strengths to our study design, we

were limited by the small number of cases and it is possible that we did not have sufficient

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power to detect some weak associations reported previously in the literature. Maternal and

perinatal risk factors for childhood cancer appear to differ by the site of cancer in the

published literature. The number of cases according to site specific cancer diagnosis was

too small in our sample to allow any subgroup analysis. Further, morphology codes were not

available for us to carry out more appropriate groupings of childhood cancers. This, coupled

with the fact that we had to conduct our analyses on all cancers would have made it less

likely for us to find associations that exist with site specific cancers. This could be a major

limitation of the current analysis.

The association of parental age with the diagnosis of cancer in general as well as in specific

sites has been studied before. Johnson et al16 in a pooled analysis of register linkage data

from several US states, found that the risk of childhood cancer increased with increasing

maternal age, while paternal age appeared to have no effect on the risk. On the other hand

several other studies, similar to the current analysis have shown that younger maternal age

was associated with increased childhood cancer risk2,17. There could be several

explanations for the disparate findings. In a register linkage study carried out in Sweden18,19,

researchers found that advancing maternal age was positively associated with childhood

cancer risk but only in a historical cohort. This association disappeared in a more recent

cohort of women although the reasons for this are unknown. Moreover, Schutz20 suggests

that the association of lower maternal age at the time of delivery with leukaemia in the

offspring could be explained by non-response bias, although this is not applicable to the

present study.

The relationship between maternal smoking and childhood cancer in the offspring is complex

and controversial. While Sorahan et al21 - 23 and Edraki24 found an increased overall risk of

childhood cancer with paternal cigarette smoking, there did not appear to be an association

with maternal smoking after adjusting for birthweight. Further, Pang et al9 did not find

evidence of smoking as a risk factor for childhood cancer after adjusting for parental age.

Similar associations were reported by Chang et al25 with regard to Acute Lymphoblastic

Leukaemia (ALL). The evidence appears to indicate that neonatal passive smoking plays a

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more important role than in utero transfer of maternal smoke related toxins, although we

cannot rule out the possibility of an association between maternal smoking and site-specific

cancers26,27. For the current analysis, we did not have access to data on paternal smoking

habits and the association seen with maternal smoking could be due to this variable acting

as proxy for paternal smoking.

Other associations noted in this study have been reported before – preterm birth28, and low

Apgar score2,28. Birthweight has received a lot of attention as a risk factor for childhood

cancer. While brain tumours and retinoblastoma appear to be associated with high

birthweight29 - 31 others have found hepatoblastomas7,32 and gliomas33 to be associated with

very low birthweight infants. Schmidt28 et al observed a U-shaped relationship between

birthweight and cancer risk, while Podvin34 found birthweight adjusted for gestational age to

be a better predictor than birthweight alone for the diagnosis of ALL, lending support to our

findings. It is however, important to note, that we did not find an association with intrauterine

growth restriction as measured by the z-score or standardized birthweight score.

Few studies have assessed mode of delivery, specifically caesarean delivery, as a possible

risk factor for the development of childhood cancer. Those that have done, have found a

weak to moderate association7,35,36 between caesarean delivery and subsequent risk of

developing ALL. Several hypotheses can be developed regarding the biological mechanism

underpinning this association. First, caesarean delivery is likely to be a marker of adverse

pregnancy and delivery events – indeed, our finding of increased emergency caesarean

rates indicated by fetal distress seems to support this hypothesis. However, the association

remained and actually became stronger, after adjusting for most other possible pregnancy

complications. It was customary to use 100% oxygen to resuscitate babies born by

caesarean section in the past. It is possible that this could have played a role in the

subsequent development of cancer. The last explanation involves epigenetic modulations at

birth. Schlinzig et al37 have demonstrated altered DNA-methylation in cord white blood cells

after caesarean delivery and suggested that this may be the basis of increased risk of

asthma, diabetes and ALL seen in infants born by caesarean section.

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The association of caesarean delivery with childhood cancer seen in this analysis, is likely to

have far reaching consequences for obstetric practice. The recent NICE guidelines38

recommends caesarean delivery on maternal request, further evidence to support a link

between caesarean section and subsequent cancer in the offspring would seriously question

the ethics of such practice. Although, we have to remember that the majority of the

caesarean deliveries seen in the cases of childhood cancer in the current analysis were

emergency procedures with strong indications such as fetal distress. Our finding of the

strong association of childhood cancer with caesarean delivery certainly warrants further

research using record linkage of larger cohorts or prospective follow up of birth cohorts.

From the point of view of Public Health interventions, the only other modifiable risk factor

appears to be parental smoking. Several population based lifestyle interventions are already

underway to reduce the prevalence of smoking in pregnancy.

Conclusion: We found a positive association between younger maternal age at delivery and

maternal smoking with childhood cancer. In addition, preterm birth, low Apgar score at 5

minutes and delivery by caesarean section showed associations with childhood cancer,

which remained significant even after controlling for various covariates. While maternal age

and smoking, preterm birth and low Apgar Score have all been previously shown to be

associated with childhood cancer, delivery by caesarean section is a novel finding and

warrants further investigation in larger cohorts. We also propose a mechanistic study

exploring epigenetic changes associated with caesarean delivery as the underlying

mechanism linking the two conditions.

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What is already known on this topic

Extremes of maternal age at delivery, parental smoking, preterm birth and low birthweight

have all been reported to be risk factors for childhood cancer.

What this study adds

The large effect of delivery by caesarean section on the increased risk of childhood cancer is

a novel finding in this study.

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Conflict of Interest: All authors have completed the Unified Competing Interest form at http://www.icmje.org/coi_disclosure.pdf and declare: NHS Grampian Endowment funded the study; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, a worldwide licence to the Publishers and its licensees in perpetuity, in all forms, formats and media (whether known now or created in the future), to (i) publish, reproduce, distribute, display and store the Contribution, (ii) translate the Contribution into other languages, create adaptations, reprints, include within collections and create summaries, extracts and/or, abstracts of the Contribution, (iii) create any other derivative work(s) based on the Contribution, (iv) to exploit all subsidiary rights in the Contribution, (v) the inclusion of electronic links from the Contribution to third party material where-ever it may be located; and, (vi) licence any third party to do any or all of the above. Contributorship: SB was responsible for designing the study, facilitating data extraction, supervising data analysis and writing of the first draft of the paper; MB analysed the data; SB, GJM and DP conceived of the research idea and GJM was responsible for overall supervision. All authors contributed to the writing of the final draft of the paper. SB is the guarantor of this paper. Ethics: This research proposal was approved by the Privacy Advisory Committee of the Information and Services Division NHS Scotland and the steering group of the Aberdeen Maternity and Neonatal Databank. Formal ethical approval was not considered necessary by North of Scotland Research Ethics Service as only anonymised data were analysed in this study. Funding: This research was funded by the NHS Grampian Endowment Fund (Project no. 10/15) Role of sponsors: The University of Aberdeen acted as sponsors for this research project, but the findings and their interpretation in this study are the authors’ own. Independence of authors from funders: All authors were employed by the University of Aberdeen at the time of conducting this research and are independent from the funders.

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11. Gold EB, Leviton A, Lopez R, et al. Parental smoking and risk of childhood brain

tumors. Am J Epidemiol. 1993;137:620-8.

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12. Milne E, Laurvick CL, Blair E et al. Fetal growth and the risk of childhood CNS

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population in the 1980s. BJOG 1993; May;100:436-45.

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16. Johnson KJ, Carozza SE, Chow EJ, et al. Parental age and risk of childhood cancer:

A pooled analysis. Epidemiology 2009; 20: 475-483.

17. Schüz J, Kaatsch P, Kaletsch U, et al. Association of childhood cancer with factors

related to pregnancy and birth. Int J Epidemiol 1999; 28:631-9.

18. Maule MM, Merletti F, Pastore G et al. Effects of maternal age and cohort of birth on

incidence time trends of childhood acute lymphoblastic leukemia. Can Epi Bio Prev

2007;16:347-51.

19. 22. Maule MM, Vizzini L, Czene K, et al. How the effect of maternal age on the risk of

childhood leukemia changed over time in Sweden, 1960-2004. Environ Health

Perspect 2009;117:299-302.

20. Schüz J. Non-response bias as a likely cause of the association between young

maternal age at the time of delivery and the risk of cancer in the offspring. Paediatr

Perinat Epidemiol 2003;17:106-12.

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22. Sorahan T, McKinney PA, Mann JR, et al. Childhood cancer and parental use of

tobacco: Findings from the inter-regional epidemiological study of childhood cancer

(IRESCC). Br J Cancer 2001;84:141-6.

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23. Sorahan T, Prior P, Lancashire RJ, et al. Childhood cancer and parental use of

tobacco: Deaths from 1971 to 1976. Br J Cancer 1997;76:1525-31.

24. Edraki M, Rambod M. Parental smoking and risk of childhood cancer: Hospital-based

case-control study in Shiraz. Eastern Mediterranean Health Journal 2011;17:303-8.

25. Chang JS, Selvin S, Metayer C, et al. Parental smoking and the risk of childhood

leukemia. Am J Epidemiol 2006;163:1091-100.

26. Mucci LA, Granath F, Cnattingius S. Maternal smoking and childhood leukemia and

lymphoma risk among 1,440,542 Swedish children. Can Epi Bio Prev. 2004;13:1528-

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27. Stavrou EP, Baker DF, Bishop JF. Maternal smoking during pregnancy and

childhood cancer in New South Wales: A record linkage investigation. Cancer

Causes Control 2009;20:1551-8

28. Schmidt LS, Schüz J, Lähteenmäki P, et al. Fetal Growth, Preterm Birth, Neonatal

Stress and Risk for CNS Tumors in Children: A Nordic Population- and Register-

Based Case-Control Study. Can Epi Bio Prev. 2010; 19: 1042-1052.

29. Harder T, Plagemann A, Harder A. Birth weight and risk of neuroblastoma: a meta-

analysis. Int J Epidemiol 2010; 39: 746-756

30. Daling JR, Starzyk P, Olshan AF, et al. Birth weight and the incidence of childhood

cancer. J Natl Cancer Inst 1984;72:1039-41.

31. MacLean J, Partap S, Reynolds P, et al. Birth weight and order as risk factors for

childhood central nervous system tumors. J Pediatr 2010;157:450-5.

32. Spector LG, Johnson KJ, Soler JT, et al. Perinatal risk factors for hepatoblastoma. Br

J Cancer 2008; 98: 1570-1573.

33. Spector LG, Puumala SE, Carozza SE, et al. Cancer risk among children with very

low birth weights. Pediatrics 2009;124:96-104.

34. Podvin D, Kuehn CM, Mueller BA, et al. Maternal and birth characteristics in relation

to childhood leukaemia. Paediatr Perinat Epidemiol 2006;20:312-22.

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35. Cnattingius S, Zack M, Ekbom A et al. Prenatal and neonatal risk factors for

childhood myeloid leukaemia. Cancer Epidemiol Biomarkers and Prev 1995; 4:441 -

445.

36. Kaye SA, Robinson LL, Anthony Smithson W et al. Maternal reproductive history and

birth characteristics in childhood acute lymphoblastic leukaemia. Cancer 1991;

68:1351 – 1355.

37. Schlinzig T, Johansson S, Gunnar A et al. Epigenetic modulation at birth – altered

DNA methylation in white blood cells after caesarean section. Acta Paediatrica. 2009;

98:1096 – 1099.

38. National Institute for Health and Clinical Excellence. CG132 Caesarean Section.

Available at: http://guidance.nice.org.uk/CG132 [accessed March 2012].

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Table 1. Comparison of maternal baseline characteristics between case children and control children

Characteristics Cases Controls p-

value

Age at delivery (mean, s.d.) 28.9 (5.6) 30.2 (4.6) 0.002

Maternal social class

Manual 26 (14.8%) 79 (11.2%)

0.187 Non-Manual 62 (35.2%) 295 (41.9%)

Single/widowed 87 (49.4%) 325 (46.2%)

Missing 1 (0.6%) 5 (0.7%)

Paternal social class

Manual 71 (40.3%) 329 (46.7%)

0.193 Non-manual 47 (26.7%) 183 (26.0%)

Single/widowed 57 (32.4%) 184 (26.1%)

Missing 1 (0.6%) 8 (1.1%)

Marital status

Single/Widowed/Divorced/Separated/Cohabiting 62 (35.2%) 222 (31.5%) 0.324

Married 113 (64.2%) 482 (68.4%)

Missing 1 (0.6%) 0 (0%)

BMI (mean, s.d.) (Missing cases = 12, Missing controls = 39) 25.2 (5.1) 25.5 (5.1) 0.407

Smoking

Non-smoker 107 (60.8%) 477 (67.8%) 0.034

Smoker/ex-smoker 68 (38.6%) 209 (29.7%)

Missing 1 (0.6%) 18 (2.6%)

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Table 2. Comparison of perinatal factors between cases and controls with statistically significant odds ratios shown in bold

Perinatal factors Cases N=176 Controls N=704 Unadjusted odds ratio

(95% CI)

Age and smoking adjusted

odds ratio (95% CI) – listwise

deletion

Age and smoking adjusted

odds ratio (95% CI) –

imputation of missing value

Preeclampsia 11 (6.3%) 23 (3.3%) 1.98 (0.94-4.18) 1.94 (0.88-4.28) 1.92 (0.91-4.09)

Gestational hypertension 19 (10.8%) 71 (10.1%) 1.09 (0.62-1.89) 1.21 (0.67-2.17) 1.13 (0.64-2.01)

Placenta praevia 3 (1.7%) 4 (0.6%) 3.00 (0.67-13.40) 3.46 (0.76-15.65) 3.45 (0.76-15.62)

Abruption 1 (0.6%) 4 (0.6%) 1.00 (0.11-8.95) 1.31 (0.14-12.66) 1.04 (0.12-9.41)

Other APH 19 (10.8%) 77 (10.9%) 0.99 (0.58-1.68) 0.98 (0.56-1.72) 0.96 (0.56-1.65)

Previous miscarriage 18 (10.2%) 103 (14.6%) 0.67 (0.39-1.13) 0.83 (0.48-1.43) 0.70 (0.41-1.19)

Preterm birth 24 (13.6%) 47 (6.7%) 2.23 (1.31-3.79) 2.09 (1.16-3.76) 2.23 (1.29-3.85)

Low birthweight 17 (9.7%) 38 (5.4%) 1.87 (1.03-3.39) 1.81 (0.94-3.45) 1.78 (0.97-3.28)

Low apgar at 1 minute 30 (17.1%) 107 (15.4%) 1.14 (0.73-1.78) 1.14 (0.71-1.84) 1.15 (0.73-1.81)

Low apgar at 5 minutes 8 (4.6%) 7 (1.0%) 5.01 (1.73-14.54) 4.91 (1.46-16.51) 5.70 (1.93-16.78)

Delivery by caesarean 55 (31.3%) 143 (20.4%) 1.77 (1.23-2.56) 2.25 (1.50-3.36) 2.07 (1.41-3.05)

Instrumental delivery 26 (14.8%) 144 (20.5%) 0.66 (0.41-1.04) 0.68 (0.41-1.13) 0.67 (0.42-1.08)

Intrauterine Growth

Restriction 23 (13.4%) 71 (10.3%) 1.41 (0.85-2.36) 1.20 (0.68-2.12) 1.35 (0.80-2.23)

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Table 3. Odds ratios from multivariable model

*All variables adjusted for maternal age and smoking and for other variables in the model

Statistically significant odds ratios are shown in bold.

Perinatal factors OR (95%CI) from multivariable model – listwise deletion* OR (95% CI) from multivariable model – imputation of missing

value*

Preeclampsia 1.56 (0.68-3.59) 1.55 (0.70-3.44)

Placenta praevia 1.64 (0.32-8.34) 1.65 (0.32-8.43)

Preterm birth 1.60 (0.76-3.37) 1.85 (0.92-3.72)

Low birthweight 1.00 (0.44-2.28) 0.90 (0.41-1.97)

Low apgar at 5 minutes 3.91 (1.13-13.61) 4.59 (1.52-13.87)

Delivery by caesarean 2.11 (1.38-3.23) 1.95 (1.30-2.92)

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Table 4. Distribution of sites of cancer

Cancer site No. %

C22 – Liver and intrahepatic bile ducts 2 1.14

C34 – Bronchus and lung 2 1.14

C41 – Bone and articular cartilage of other and unspecified sites 10

5.68

C49 – Other connective and soft tissue 7

3.98

C52 – Vagina 5 2.84

C56 – Ovary 3 1.70

C62 – Testis 12 6.82

C64 – Kidney except renal pelvis 7 3.98

C69 – Eye and adnexa 6 3.41

C71 – Brain 27

15.34

C72 – Spinal cord, cranial nerves, other CNS 3 1.70

C74 – Adrenal gland 6

3.41

C75 – Other endocrine glands and related structures 4

2.27

C76 – Other and ill-defined sites 2 1.14

C83 – Diffuse non-Hodgkin’s lymphoma 3 1.70

C85 – Other and unspec. non-Hodgkin’s 2 1.14

C91 – Lymphoid Leukaemia 37 21.02

C92 – Myeloid leukaemia 10 5.68

C94 – Other leukaemias of specified cell type 2 1.14

D32 - Meninges 3 1.70

D40 – Uncertain/uknown bhvr male genital 2 1.14

D43 – Uncertain/unknown bhvr. brain and CNS 2 1.14

D44 – Uncertain/unknown bhvr. endocrine 1 0.57

D47 – Uncertain/uknown bhvr. of lymphoid, haematopoietic and related tissue 9

5.11

D48 – Uncertain/unknown bhvr. unknown sites 9 5.11

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Maternal and Perinatal Risk Factors for Childhood Cancer

Sohinee Bhattacharya1* Marcus Beasley1 Dong Pang2 Gary J Macfarlane1

1Epidemiology Group, Division of Applied Health Sciences, University of Aberdeen 2 Institute of Health Research, University of Bedfordshire, Luton

*Corresponding author: Sohinee Bhattacharya Dugald Baird Centre for Research on Women’s Health Aberdeen Maternity Hospital Aberdeen AB25 2ZL Tel: +44 1224 438441 e-mail: [email protected] Running title: Risk factors for childhood cancer

Conflict of Interest: All authors have completed the Unified Competing Interest form at http://www.icmje.org/coi_disclosure.pdf and declare: NHS Grampian Endowment funded the study; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, a worldwide licence to the Publishers and its licensees in perpetuity, in all forms, formats and media (whether known now or created in the future), to (i) publish, reproduce, distribute, display and store the Contribution, (ii) translate the Contribution into other languages, create adaptations, reprints, include within collections and create summaries, extracts and/or, abstracts of the Contribution, (iii) create any other derivative work(s) based on the Contribution, (iv) to exploit all subsidiary rights in the Contribution, (v) the inclusion of electronic links from the Contribution to third party material where-ever it may be located; and, (vi) licence any third party to do any or all of the above. Contributorship: SB was responsible for designing the study, facilitating data extraction, supervising data analysis and writing of the first draft of the paper; MB analysed the data; SB, GJM and DP conceived of the research idea and GJM was responsible for overall supervision. All authors contributed to the writing of the final draft of the paper. SB is the guarantor of this paper. Ethics: This research proposal was approved by the Privacy Advisory Committee of the Information and Services Division NHS Scotland and the steering group of the Aberdeen Maternity and Neonatal Databank. Formal ethical approval was not considered necessary by North of Scotland Research Ethics Service as only anonymised data were analysed in this study. Funding: This research was funded by the NHS Grampian Endowment Fund (Project no. 10/15) Role of sponsors: The University of Aberdeen acted as sponsors for this research project, but the findings and their interpretation in this study are the authors’ own. Independence of authors from funders: All authors were employed by the University of Aberdeen at the time of conducting this research and are independent from the funders. Data sharing: There is no additional data available for sharing

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Abstract Objective: To investigate maternal and perinatal risk factors for childhood cancer.

Study Design: Case control analysis of linked records from the Aberdeen Maternity and

Neonatal Databank with the Scottish Cancer Registry and the General Registry of Births and

Deaths in Scotland was carried out.

Setting: Aberdeen, Scotland

Participants: Cases (n=176) comprised children diagnosed with cancer under 15 years or

recorded as having died of cancer. Four controls per case were matched by age and gender.

Risk factors tested: Maternal age, BMI, social class, marital status and smoking as well as

preeclampsia, antepartum haemorrhage and previous miscarriage, gestational age,

birthweight, and Apgar scores were compared between groups to test for association with

cancer. Odds ratios with 95% Confidence Intervals were calculated using conditional logistic

regression in both univariable and multivariable models.

Results: Of the maternal characteristics tested, mother’s age at delivery {cases mean

28.9(S.D.5.6) years versus controls mean 30.2(S.D4.6), p = 0.002} and smoking status

(38.6% smokers among cases, 29.7% among controls, p=0.034) were found to be different

between groups. Of the perinatal factors tested, low Apgar score at 5 minutes (AOR 4.59,

95% CI 1.52, 13.87) and delivery by caesarean section (AOR 1.95, 95% CI 1.30, 2.92)

showed statistically significant associations with childhood cancer in the multivariable model.

Conclusions: Younger maternal age, maternal smoking, delivery by caesarean section and

low Apgar score at 5 minutes were independently associated with increased risk of

childhood cancer. The association with caesarean delivery may be mediated through

epigenetic mechanism and warrants further investigation.

Key words: childhood cancer, perinatal risk factors, smoking, caesarean delivery

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Introduction:

Childhood cancer has been increasing in Scotland. A published report estimates that its

incidence has risen from 108.3 per million child-years in 1976 to 160.6 per million child-years

in 20071. The reason for this increasing trend remains unexplained as the etiopathogenesis

of childhood cancer is poorly understood. As most present in the first few years of life,

epidemiologists hypothesize that prenatal and perinatal exposures may have a part to play in

its pathogenesis. The evidence surrounding this is however, conflicting. While some

researchers have found associations of younger maternal age at delivery2 maternal

anaemia3,4, previous history of miscarriage2,5,6 maternal overweight7, and smoking8, with

some childhood cancers, others have found no such associations9-11. Fetal growth is

perhaps the most investigated perinatal risk factor for childhood cancer7,12,13 ; and yet the

authors report conflicting results. While specific central nervous system tumours have been

found to be associated with intrauterine growth restriction, the overall risk was small12.

Therefore, apart from the associations with Down’s syndrome and in utero exposure to

radiation, research into the maternal and perinatal risk factors has remained inconsistent, the

results limited by small sample sizes and recall or reporting bias.

Our objective was therefore to investigate maternal and perinatal risk factors for childhood

cancer, specifically to examine the effects of intrauterine growth restriction, preterm birth and

birth asphyxia on the development of childhood cancer in the offspring, taking advantage of

the opportunities offered by record linkage of a cancer registry with a local birth register.

Methods:

Data Sources:

The Aberdeen Maternity and Neonatal Databank (AMND) holds data for all Aberdeen City

births from 1950 to the present, and includes all reproductive events to women resident in a

defined geographical area with a relatively stable population. The exposure variables in

terms of potential maternal and perinatal risk factors were derived from the AMND. The

Scottish Cancer Registry has been in existence since 1951 and was complete up to 2010, at

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the time of the present analysis. The cases of childhood cancer were identified from this

register.

Data Linkage:

All children born between 1993 and 2006 were identified from the AMND. Their records were

linked to the Cancer Registry in Scotland (SMR 06) and the General Registry of Births and

Deaths in Scotland (GRO-S), using deterministic matching. The linkage was carried out by

data analysts from the Information and Services Division of NHS Scotland using Community

Health Index (CHI) numbers. The CHI number is a number unique to all individuals

registered with a general practice in Scotland and recorded in both databases used in this

study. In a small proportion of cases where CHI number was not available, probabilistic

matching using surname, date of birth and postcode was used. After data linkage, all

identifying information, including CHI numbers were removed and an anonymised dataset

was provided for analysis.

Study design:

A case control study design was employed. Cases comprised all children identified as above

from the AMND who were diagnosed with cancer under 15 years of age in Scotland as

recorded in the Scottish Cancer Registry or recorded as having died of cancer. Controls

were selected from the pool of children not diagnosed as having cancer, matched by age

and gender using four controls per case.

Twins and multiple births were excluded as were stillbirths and early neonatal deaths. As

Down’s syndrome is known to be associated with a higher risk of Acute Lymphoblastic

Leukaemia (ALL), all cases of diagnosed Down’s syndrome were excluded. Moreover, those

children who had died of non-cancer causes prior to their 15th birthday, as identified from

GRO-S were also excluded.

Exposure and outcome variables used in the analysis:

Maternal sociodemographic factors such as age at delivery, body mass index (BMI),

Registrar General’s occupation-based social class, marital status, previous history of

miscarriage and smoking habits were extracted from the AMND. Any complications recorded

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during the index pregnancy such as preeclampsia, gestational hypertension, and antepartum

haemorrhage as well as mode of delivery, gestational age at delivery, birthweight,

Standardised Birthweight Score14, and Apgar score at 1 and 5 minutes were also extracted.

Data extractors were blind to the case-control status of the individual children.

The outcome variables obtained from the Cancer Registry in Scotland were in the form of a

binary variable (yes/no) indicating whether or not a cancer record was present and if

present, the site of cancer given as International Classification of Diseases (ICD) codes.

Similarly, death records with up to 10 different causes of death given by ICD codes were

obtained from linking with GRO-S.

Statistical Analysis:

All analyses were conducted using STATA version 11 (STATA Corp, Texas, USA).

Maternal baseline characteristics were compared between children diagnosed with cancer

and controls using independent two-sample t-tests and chi-square tests. Maternal

complications such as gestational hypertension, pre-eclampsia, antepartum haemorrhage

and previous history of miscarriage were compared between the cases and controls using

univariate conditional regression to calculate odds ratios (OR) with 95% confidence intervals

(CI). Similarly, perinatal factors like gestation at birth, birth weight, intrauterine growth

restriction measured by standardised birthweight score, Apgar score at 1 and 5 minutes

were also tested in univariate models for any association with childhood cancer. Then a

multivariable conditional logistic regression model was fitted that included as independent

variables all risk factors tested on univariate analysis. The possibility of cancer subgroup

analysis was considered according to the International Classification of Childhood Cancer,

but the number of cases in each subgroup was too small to warrant this.

Missing data:

Apart from the variables describing maternal baseline characteristics, the other risk factors

did not have any missing values. There were 18 controls and 1 case with missing smoking

data. The multivariable model was repeated including and excluding the individuals with

missing information. We used two methodological approaches to handle this - listwise

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deletion – ie, not including any group where one person in that group has missing data, and

imputation by attaching a value to the missing data so that all cases and controls were

included in the analysis. The odds ratios obtained by both methods are presented.

Ethical considerations:

Approval to carry out the study was obtained from the AMND steering committee and the

Privacy Advisory Committee for the Information Services Division of National Health

Services, Scotland. As the study involved the analysis of routinely collected anonymised

data, formal ethical approval was not required as declared by the North of Scotland

Research Ethics Service.

Results:

There were 62375 deliveries between 1993 and 2006 as identified from the AMND. After

excluding Down’s syndrome cases, twins and multiple births, stillbirths and early neonatal

deaths, there were 60117 children eligible for linkage with the Cancer Registry. It was

possible to link 43591 of these children to the cancer and GRO-S databases. Amongst the

children with linked data, 106 had died of non-cancer causes before they reached the age of

15 and were therefore excluded from the analysis. Of the remainder, 176 were found to have

a record in the Cancer Registry, giving a cumulative incidence rate of childhood cancer up to

15 years of 4.05 per 1000 deliveries. They constituted the cases for the analysis and were

matched in 1:4 ratio by year of birth and sex from the pool of remaining children without any

records of cancer to obtain 704 controls.

Maternal baseline characteristics were compared between cases and matched controls in

Table 1. Of the maternal characteristics tested, mother’s age at delivery (cases mean 28.9

years, s.d. 5.6; controls mean 30.2, s.d. 4.6; p = 0.002) and smoking status (38.6% current

or ex-smokers among cases, 29.7% among controls, p=0.022) were found to be significantly

different between the two groups.

Table 2 presents the unadjusted odds ratios with 95% confidence intervals for all the

perinatal potential risk factors for childhood cancer. Of the factors tested, preterm birth {OR

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2.23(1.31 – 3.79)}; low birth weight {OR 1.87(1.03 – 3.39)}, low Apgar score at 5 minutes

{OR 5.01(1.73 – 14.54)} and delivery by caesarean section {OR 1.77(1.23 – 2.56)} were

found to be statistically significant. Subsequently, these factors were adjusted for maternal

age at delivery and smoking. As the maternal smoking variable had some missing data, we

handled this using two approaches – listwise deletion and imputation of missing value. After

these adjustments, low birthweight no longer remained significant, but the other associations

were strengthened.

After conducting the univariate analyses multivariable models were fitted including maternal

age, smoking status, preeclampsia, placenta praevia, preterm birth, low birthweight, low

Apgar at 5 minutes and delivery by caesarean as independent variables (results in Table 3).

Similar to the previous analyses, we used two methods of listwise deletion and imputation of

missing value to adjust for smoking status. Of the perinatal factors tested, Apgar score below

7 at 5 minutes {AOR 3.91, 95% CI 1.13 – 13.61(listwise deletion); AOR 4.59, 95% CI 1.52,

13.87 (imputation)} and delivery by caesarean section {AOR 2.11, 95% CI 1.38, 3.23

(listwise deletion); AOR 1.95, 95% CI 1.30, 2.92 (imputation)} showed statistically significant

associations with childhood cancer in both multivariable models adjusted for maternal age,

smoking and other factors simultaneously included in the models. Preterm birth (delivery

before 37 completed weeks of gestation) and low birth weight defined as a birth weight

below 2500g, showed a significant association in the univariate analysis, but these

associations were no longer significant in the multivariable model. The associations were not

statistically significant on univariate or multivariable analysis between the risk of childhood

cancer and hypertensive disorders, antepartum haemorrhage, previous history of

miscarriage or IUGR. Unlike the Apgar score at 5 minutes, the score at 1 minute did not

show any association with childhood cancer.

We further investigated the types of preterm delivery (spontaneous or induced) and

caesarean section (elective or emergency) as risk factors for childhood cancer and found

that both spontaneous and induced preterm delivery were significantly associated in the

adjusted model but only delivery by emergency caesarean section remained significant on

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subgroup analysis (AOR 1.43, 95% CI 1.20, 2.18). Further, we found that the commonest

indication for caesarean delivery in the babies who were subsequently diagnosed with

cancer was fetal distress (data not shown).

Table 4 shows the distribution of cancer sites in the 176 cases. As this table shows, the

commonest sites were the brain and haemopoietic organs, especially leukaemia, but the

numbers in the subgroups were too small to allow any meaningful analysis.

Discussion:

We aimed to study the maternal and perinatal risk factors at the time of birth associated with

the diagnosis of childhood cancer using record linkage between two high quality registers in

Scotland. We found a positive association between younger maternal age at delivery and

maternal smoking with childhood cancer. In addition, preterm birth before 37 weeks of

gestation, Apgar score below 7 at 5 minutes and delivery by emergency caesarean section

showed statistically significant associations with childhood cancer the last two of which

remained significant in the adjusted models.

Childhood cancer is a rare condition. Case control studies are therefore the most efficient

epidemiological study design to study several risk factors at the time of birth. Cancer

registries across the world have been utilised to identify cases, but finding appropriate

controls remains problematic. Moreover, data collections regarding exposures by means of

interviews or questionnaires are subject to recall and reporting bias. More recently, linkage

of birth registers with cancer registries has been utilised to design large scale cohort studies.

However, the routine data collection is liable to lack sufficiently detailed data regarding

exposure and potential confounding factors. We have tried to minimise these problems by

linking two high quality registers in Scotland. Previous validation projects have shown these

databases to be 100% complete and over 97% accurate15. Detailed and contemporaneous

recording of obstetric data in the AMND eliminated recall and reporting bias. The large

number of social and demographic variables recorded in the AMND enabled incorporation of

most potential covariates in the analysis. Despite these strengths to our study design, we

were limited by the small number of cases and it is possible that we did not have sufficient

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power to detect some weak associations reported previously in the literature. Maternal and

perinatal risk factors for childhood cancer appear to differ by the site of cancer in the

published literature. The number of cases according to site specific cancer diagnosis was

too small in our sample to allow any subgroup analysis. Further, morphology codes were not

available for us to carry out more appropriate groupings of childhood cancers. This, coupled

with the fact that we had to conduct our analyses on all cancers would have made it less

likely for us to find associations that exist with site specific cancers. This could be a major

limitation of the current analysis.

The association of parental age with the diagnosis of cancer in general as well as in specific

sites has been studied before. Johnson et al16 in a pooled analysis of register linkage data

from several US states, found that the risk of childhood cancer increased with increasing

maternal age, while paternal age appeared to have no effect on the risk. On the other hand

several other studies, similar to the current analysis have shown that younger maternal age

was associated with increased childhood cancer risk2,17. There could be several

explanations for the disparate findings. In a register linkage study carried out in Sweden18,19,

researchers found that advancing maternal age was positively associated with childhood

cancer risk but only in a historical cohort. This association disappeared in a more recent

cohort of women although the reasons for this are unknown. Moreover, Schutz20 suggests

that the association of lower maternal age at the time of delivery with leukaemia in the

offspring could be explained by non-response bias, although this is not applicable to the

present study.

The relationship between maternal smoking and childhood cancer in the offspring is complex

and controversial. While Sorahan et al21 - 23 and Edraki24 found an increased overall risk of

childhood cancer with paternal cigarette smoking, there did not appear to be an association

with maternal smoking after adjusting for birthweight. Further, Pang et al9 did not find

evidence of smoking as a risk factor for childhood cancer after adjusting for parental age.

Similar associations were reported by Chang et al25 with regard to Acute Lymphoblastic

Leukaemia (ALL). The evidence appears to indicate that neonatal passive smoking plays a

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more important role than in utero transfer of maternal smoke related toxins, although we

cannot rule out the possibility of an association between maternal smoking and site-specific

cancers26,27. For the current analysis, we did not have access to data on paternal smoking

habits and the association seen with maternal smoking could be due to this variable acting

as proxy for paternal smoking.

Other associations noted in this study have been reported before – preterm birth28, and low

Apgar score2,28. Birthweight has received a lot of attention as a risk factor for childhood

cancer. While brain tumours and retinoblastoma appear to be associated with high

birthweight29 - 31 others have found hepatoblastomas7,32 and gliomas33 to be associated with

very low birthweight infants. Schmidt28 et al observed a U-shaped relationship between

birthweight and cancer risk, while Podvin34 found birthweight adjusted for gestational age to

be a better predictor than birthweight alone for the diagnosis of ALL, lending support to our

findings. It is however, important to note, that we did not find an association with intrauterine

growth restriction as measured by the z-score or standardized birthweight score.

Few studies have assessed mode of delivery, specifically caesarean delivery, as a possible

risk factor for the development of childhood cancer. Those that have done, have found a

weak to moderate association7,35,36 between caesarean delivery and subsequent risk of

developing ALL. Several hypotheses can be developed regarding the biological mechanism

underpinning this association. First, caesarean delivery is likely to be a marker of adverse

pregnancy and delivery events – indeed, our finding of increased emergency caesarean

rates indicated by fetal distress seems to support this hypothesis. However, the association

remained and actually became stronger, after adjusting for most other possible pregnancy

complications. It was customary to use 100% oxygen to resuscitate babies born by

caesarean section in the past. It is possible that this could have played a role in the

subsequent development of cancer. The last explanation involves epigenetic modulations at

birth. Schlinzig et al37 have demonstrated altered DNA-methylation in cord white blood cells

after caesarean delivery and suggested that this may be the basis of increased risk of

asthma, diabetes and ALL seen in infants born by caesarean section.

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The association of caesarean delivery with childhood cancer seen in this analysis, is likely to

have far reaching consequences for obstetric practice. The recent NICE guidelines38

recommends caesarean delivery on maternal request, further evidence to support a link

between caesarean section and subsequent cancer in the offspring would seriously question

the ethics of such practice. Although, we have to remember that the majority of the

caesarean deliveries seen in the cases of childhood cancer in the current analysis were

emergency procedures with strong indications such as fetal distress. Our finding of the

strong association of childhood cancer with caesarean delivery certainly warrants further

research using record linkage of larger cohorts or prospective follow up of birth cohorts.

From the point of view of Public Health interventions, the only other modifiable risk factor

appears to be parental smoking. Several population based lifestyle interventions are already

underway to reduce the prevalence of smoking in pregnancy.

Conclusion: We found a positive association between younger maternal age at delivery and

maternal smoking with childhood cancer. In addition, preterm birth, low Apgar score at 5

minutes and delivery by caesarean section showed associations with childhood cancer,

which remained significant even after controlling for various covariates. While maternal age

and smoking, preterm birth and low Apgar Score have all been previously shown to be

associated with childhood cancer, delivery by caesarean section is a novel finding and

warrants further investigation in larger cohorts. We also propose a mechanistic study

exploring epigenetic changes associated with caesarean delivery as the underlying

mechanism linking the two conditions.

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What is already known on this topic

Extremes of maternal age at delivery, parental smoking, preterm birth and low birthweight

have all been reported to be risk factors for childhood cancer.

What this study adds

The large effect of delivery by caesarean section on the increased risk of childhood cancer is

a novel finding in this study.

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Table 1. Comparison of maternal baseline characteristics between case children and control children

Characteristics Cases Controls p-

value

Age at delivery (mean, s.d.) 28.9 (5.6) 30.2 (4.6) 0.002

Maternal social class

Manual 26 (14.8%) 79 (11.2%)

0.187 Non-Manual 62 (35.2%) 295 (41.9%)

Single/widowed 87 (49.4%) 325 (46.2%)

Missing 1 (0.6%) 5 (0.7%)

Paternal social class

Manual 71 (40.3%) 329 (46.7%)

0.193 Non-manual 47 (26.7%) 183 (26.0%)

Single/widowed 57 (32.4%) 184 (26.1%)

Missing 1 (0.6%) 8 (1.1%)

Marital status

Single/Widowed/Divorced/Separated/Cohabiting 62 (35.2%) 222 (31.5%) 0.324

Married 113 (64.2%) 482 (68.4%)

Missing 1 (0.6%) 0 (0%)

BMI (mean, s.d.) (Missing cases = 12, Missing controls = 39) 25.2 (5.1) 25.5 (5.1) 0.407

Smoking

Non-smoker 107 (60.8%) 477 (67.8%) 0.034

Smoker/ex-smoker 68 (38.6%) 209 (29.7%)

Missing 1 (0.6%) 18 (2.6%)

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Table 2. Comparison of perinatal factors between cases and controls with statistically significant odds ratios shown in bold

Perinatal factors Cases N=176 Controls N=704 Unadjusted odds ratio

(95% CI)

Age and smoking adjusted

odds ratio (95% CI) – listwise

deletion

Age and smoking adjusted

odds ratio (95% CI) –

imputation of missing value

Preeclampsia 11 (6.3%) 23 (3.3%) 1.98 (0.94-4.18) 1.94 (0.88-4.28) 1.92 (0.91-4.09)

Gestational hypertension 19 (10.8%) 71 (10.1%) 1.09 (0.62-1.89) 1.21 (0.67-2.17) 1.13 (0.64-2.01)

Placenta praevia 3 (1.7%) 4 (0.6%) 3.00 (0.67-13.40) 3.46 (0.76-15.65) 3.45 (0.76-15.62)

Abruption 1 (0.6%) 4 (0.6%) 1.00 (0.11-8.95) 1.31 (0.14-12.66) 1.04 (0.12-9.41)

Other APH 19 (10.8%) 77 (10.9%) 0.99 (0.58-1.68) 0.98 (0.56-1.72) 0.96 (0.56-1.65)

Previous miscarriage 18 (10.2%) 103 (14.6%) 0.67 (0.39-1.13) 0.83 (0.48-1.43) 0.70 (0.41-1.19)

Preterm birth 24 (13.6%) 47 (6.7%) 2.23 (1.31-3.79) 2.09 (1.16-3.76) 2.23 (1.29-3.85)

Low birthweight 17 (9.7%) 38 (5.4%) 1.87 (1.03-3.39) 1.81 (0.94-3.45) 1.78 (0.97-3.28)

Low apgar at 1 minute 30 (17.1%) 107 (15.4%) 1.14 (0.73-1.78) 1.14 (0.71-1.84) 1.15 (0.73-1.81)

Low apgar at 5 minutes 8 (4.6%) 7 (1.0%) 5.01 (1.73-14.54) 4.91 (1.46-16.51) 5.70 (1.93-16.78)

Delivery by caesarean 55 (31.3%) 143 (20.4%) 1.77 (1.23-2.56) 2.25 (1.50-3.36) 2.07 (1.41-3.05)

Instrumental delivery 26 (14.8%) 144 (20.5%) 0.66 (0.41-1.04) 0.68 (0.41-1.13) 0.67 (0.42-1.08)

Intrauterine Growth

Restriction 23 (13.4%) 71 (10.3%) 1.41 (0.85-2.36) 1.20 (0.68-2.12) 1.35 (0.80-2.23)

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Table 3. Odds ratios from multivariable model

*All variables adjusted for maternal age and smoking and for other variables in the model

Statistically significant odds ratios are shown in bold.

Perinatal factors OR (95%CI) from multivariable model – listwise deletion* OR (95% CI) from multivariable model – imputation by missing

value*

Preeclampsia 1.56 (0.68-3.59) 1.55 (0.70-3.44)

Placenta praevia 1.64 (0.32-8.34) 1.65 (0.32-8.43)

Preterm birth 1.60 (0.76-3.37) 1.85 (0.92-3.72)

Low birthweight 1.00 (0.44-2.28) 0.90 (0.41-1.97)

Low apgar at 5 minutes 3.91 (1.13-13.61) 4.59 (1.52-13.87)

Delivery by caesarean 2.11 (1.38-3.23) 1.95 (1.30-2.92)

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Table 4. Distribution of sites of cancer

Cancer site No. %

C22 – Liver and intrahepatic bile ducts 2 1.14

C34 – Bronchus and lung 2 1.14

C41 – Bone and articular cartilage of other and unspecified sites 10

5.68

C49 – Other connective and soft tissue 7

3.98

C52 – Vagina 5 2.84

C56 – Ovary 3 1.70

C62 – Testis 12 6.82

C64 – Kidney except renal pelvis 7 3.98

C69 – Eye and adnexa 6 3.41

C71 – Brain 27

15.34

C72 – Spinal cord, cranial nerves, other CNS 3 1.70

C74 – Adrenal gland 6

3.41

C75 – Other endocrine glands and related structures 4

2.27

C76 – Other and ill-defined sites 2 1.14

C83 – Diffuse non-Hodgkin’s lymphoma 3 1.70

C85 – Other and unspec. non-Hodgkin’s 2 1.14

C91 – Lymphoid Leukaemia 37 21.02

C92 – Myeloid leukaemia 10 5.68

C94 – Other leukaemias of specified cell type 2 1.14

D32 - Meninges 3 1.70

D40 – Uncertain/uknown bhvr male genital 2 1.14

D43 – Uncertain/unknown bhvr. brain and CNS 2 1.14

D44 – Uncertain/unknown bhvr. endocrine 1 0.57

D47 – Uncertain/uknown bhvr. of lymphoid, haematopoietic and related tissue 9

5.11

D48 – Uncertain/unknown bhvr. unknown sites 9 5.11

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Maternal and perinatal risk factors for childhood cancer

Supplemental file: STROBE Statement

Checklist of items that should be included in reports of case control studies

Item No Recommendation

Location within manuscript

Title and

abstract

1 (a) Indicate the study’s design with a

commonly used term in the title or the

abstract

Abstract: Methods

(b) Provide in the abstract an

informative and balanced summary of

what was done and what was found

Abstract: Methods and

Results

Introduction

Background/

rationale

2 Explain the scientific background and

rationale for the investigation being

reported

Introduction: Lines 2 -

17

Objectives 3 State specific objectives, including

any prespecified hypotheses

Introduction: Lines 18 -

22

Methods

Study design 4 Present key elements of study design

early in the paper

Methods: Lines 41-51

Setting 5 Describe the setting, locations, and

relevant dates, including periods of

recruitment, exposure, follow-up, and

data collection

Methods, Lines 24 - 64

Participants 6 (a) Give the eligibility criteria, and the

sources and methods of selection of

participants. Describe methods of

follow-up

Methods, Lines 47 - 51

(b) For matched studies, give

matching criteria and number of

exposed and unexposed

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Variables 7 Clearly define all outcomes,

exposures, predictors, potential

confounders, and effect modifiers.

Give diagnostic criteria, if applicable

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Data

sources/

measuremen

t

8* For each variable of interest, give

sources of data and details of

methods of assessment

(measurement). Describe

comparability of assessment methods

if there is more than one group

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Bias 9 Describe any efforts to address

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Study size 10 Explain how the study size was

arrived at

Results Lines 90 - 99

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variables

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were handled in the analyses. If

applicable, describe which groupings

were chosen and why

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Statistical

methods

12 (a) Describe all statistical methods,

including those used to control for

confounding

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(b) Describe any methods used to

examine subgroups and interactions

Not specified

(c) Explain how missing data were

addressed

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(d) If applicable, explain how loss to

follow-up was addressed

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(e) Describe any sensitivity analyses Not conducted

Results

Participants 13* (a) Report numbers of individuals at

each stage of study—eg numbers

potentially eligible, examined for

eligibility, confirmed eligible, included

in the study, completing follow-up,

and analysed

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at each stage

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Descriptive

data

14* (a) Give characteristics of study

participants (eg demographic, clinical,

social) and information on exposures

and potential confounders

Table 1 and Results:

Lines 104 - 114

Outcome

data

15* Report numbers of outcome events or

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Tables 2, Results: 115

- 131

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and why they were included

Table 2

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Other

analyses

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analyses of subgroups and

interactions, and sensitivity analyses

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Discussion

Key results 18 Summarise key results with reference

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143

Limitations 19 Discuss limitations of the study, taking

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or imprecision. Discuss both direction

and magnitude of any potential bias

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164

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224

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Generalis-

ability

21 Discuss the generalisability (external

validity) of the study results

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164

Other information

Funding 22 Give the source of funding and the role of the funders

for the present study and, if applicable, for the

original study on which the present article is based

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Maternal and Perinatal Risk Factors for Childhood Cancer: Record Linkage Study

Sohinee Bhattacharya1* Marcus Beasley1 Dong Pang2 Gary J Macfarlane1

1Epidemiology Group, Division of Applied Health Sciences, University of Aberdeen 2 Institute of Health Research, University of Bedfordshire, Luton *Corresponding author: Sohinee Bhattacharya Dugald Baird Centre for Research on Women’s Health Aberdeen Maternity Hospital Aberdeen AB25 2ZL Tel: +44 1224 438441 e-mail: [email protected] Running title: Risk factors for childhood cancer

Conflict of Interest: All authors have completed the Unified Competing Interest form at http://www.icmje.org/coi_disclosure.pdf and declare: NHS Grampian Endowment funded the study; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, a worldwide licence to the Publishers and its licensees in perpetuity, in all forms, formats and media (whether known now or created in the future), to (i) publish, reproduce, distribute, display and store the Contribution, (ii) translate the Contribution into other languages, create adaptations, reprints, include within collections and create summaries, extracts and/or, abstracts of the Contribution, (iii) create any other derivative work(s) based on the Contribution, (iv) to exploit all subsidiary rights in the Contribution, (v) the inclusion of electronic links from the Contribution to third party material where-ever it may be located; and, (vi) licence any third party to do any or all of the above. Contributorship: SB was responsible for designing the study, facilitating data extraction, supervising data analysis and writing of the first draft of the paper; MB analysed the data; SB, GJM and DP conceived of the research idea and GJM was responsible for overall supervision. All authors contributed to the writing of the final draft of the paper. SB is the guarantor of this paper. Ethics: This research proposal was approved by the Privacy Advisory Committee of the Information and Services Division NHS Scotland and the steering group of the Aberdeen Maternity and Neonatal Databank. Formal ethical approval was not considered necessary by North of Scotland Research Ethics Service as only anonymised data were analysed in this study. Funding: This research was funded by the NHS Grampian Endowment Fund (Project no. 10/15) Role of sponsors: The University of Aberdeen acted as sponsors for this research project, but the findings and their interpretation in this study are the authors’ own. Independence of authors from funders: All authors were employed by the University of Aberdeen at the time of conducting this research and are independent from the funders.

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Abstract Objective: To investigate maternal and perinatal risk factors for childhood cancer.

Study Design: Case control analysis of linked records from the Aberdeen Maternity and

Neonatal Databank with the Scottish Cancer Registry and the General Registry of Births and

Deaths in Scotland was carried out.

Setting: Aberdeen, Scotland

Participants: Cases (n=176) comprised children diagnosed with cancer under 15 years or

recorded as having died of cancer. Four controls per case were matched by age and gender.

Risk factors tested: Maternal age, BMI, social class, marital status and smoking as well as

preeclampsia, antepartum haemorrhage and previous miscarriage, gestational age,

birthweight, and Apgar scores were compared between groups to test for association with

cancer. Odds ratios with 95% Confidence Intervals were calculated using conditional logistic

regression in both univariable and multivariable models.

Results: Of the maternal characteristics tested, mother’s age at delivery {cases mean

28.9(S.D.5.6) years versus controls mean 30.2(S.D4.6), p = 0.002} and smoking status

(38.6% smokers among cases, 29.7% among controls, p=0.034) were found to be different

between groups. Of the perinatal factors tested, low Apgar score at 5 minutes (AOR 4.59,

95% CI 1.52, 13.87) and delivery by caesarean section (AOR 1.95, 95% CI 1.30, 2.92)

showed statistically significant associations with childhood cancer in the multivariable model.

Conclusions: Younger maternal age, maternal smoking, delivery by caesarean section and

low Apgar score at 5 minutes were independently associated with increased risk of

childhood cancer. .

Key words: childhood cancer, perinatal risk factors, smoking, caesarean delivery

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Introduction:

Childhood cancer has been increasing in Scotland. A published report estimates that its

incidence has risen from 108.3 per million child-years in 1976 to 160.6 per million child-years

in 20071. The reason for this increasing trend remains unexplained as the etiopathogenesis

of childhood cancer is poorly understood. As most present in the first few years of life,

epidemiologists hypothesize that prenatal and perinatal exposures may have a part to play in

its pathogenesis. The evidence surrounding this is however, conflicting. While some

researchers have found associations of younger maternal age at delivery2 maternal

anaemia3,4, previous history of miscarriage2,5,6 maternal overweight7, and smoking8, with

some childhood cancers, others have found no such associations9-11. Fetal growth is

perhaps the most investigated perinatal risk factor for childhood cancer7,12,13 ; but the authors

report conflicting results. While specific central nervous system tumours have been found to

be associated with intrauterine growth restriction, the overall risk was small12. Therefore,

apart from the associations with Down’s syndrome and in utero exposure to radiation,

research into the maternal and perinatal risk factors has remained inconsistent, the results

limited by small sample sizes and recall or reporting bias.

Our objective was therefore to investigate maternal and perinatal risk factors for childhood

cancer, specifically to examine the effects of intrauterine growth restriction, preterm birth and

birth asphyxia on the development of childhood cancer in the offspring, taking advantage of

the opportunities offered by record linkage of a cancer registry with a local birth register.

Methods:

Data Sources:

The Aberdeen Maternity and Neonatal Databank (AMND) holds data for all Aberdeen City

births from 1950 to the present, and includes all reproductive events to women resident in a

defined geographical area with a relatively stable population. The AMND records all births

occurring at the Aberdeen Maternity Hospital, the only maternity hospital serving the

population of Aberdeen city and district. The exposure variables in terms of potential

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maternal and perinatal risk factors were derived from the AMND. The Scottish Cancer

Registry has been in existence since 1951 and was complete up to 2010, at the time of the

present analysis. The cases of childhood cancer were identified from this register.

Data Linkage:

All children born between 1993 and 2006 were identified from the AMND. Their records were

linked to the Cancer Registry in Scotland (SMR 06) and the General Registry of Births and

Deaths in Scotland (GRO-S), using deterministic matching. The linkage was carried out by

data analysts from the Information and Services Division of NHS Scotland using Community

Health Index (CHI) numbers. The CHI number is a number unique to all individuals

registered with a general practice in Scotland and recorded in both databases used in this

study. In a small proportion of cases where CHI number was not available (6%), probabilistic

matching using surname, date of birth and postcode was used. After data linkage, all

identifying information, including CHI numbers were removed and an anonymised dataset

was provided for analysis.

Study design:

A case control study design was employed. Cases comprised all children identified as above

from the AMND who were diagnosed with cancer under 15 years of age in Scotland as

recorded in the Scottish Cancer Registry or recorded as having died of cancer. Controls

were selected from the pool of children not diagnosed as having cancer, matched by age

and gender using four controls per case.

Twins and multiple births were excluded as were stillbirths and early neonatal deaths. As

Down’s syndrome is known to be associated with a higher risk of Acute Lymphoblastic

Leukaemia (ALL) as well as Myeloid Leukaemia of Down’s syndrome, all cases of diagnosed

Down’s syndrome were excluded. Moreover, those children who had died of non-cancer

causes prior to their 15th birthday, as identified from GRO-S were also excluded.

Exposure and outcome variables used in the analysis:

Maternal sociodemographic factors such as age at delivery, body mass index (BMI),

Registrar General’s occupation-based social class, marital status, previous history of

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miscarriage and smoking habits were extracted from the AMND. Any complications recorded

during the index pregnancy such as preeclampsia, gestational hypertension, and antepartum

haemorrhage as well as mode of delivery, gestational age at delivery, birthweight,

Standardised Birthweight Score14, and Apgar score at 1 and 5 minutes were also extracted.

Data extractors were blind to the case-control status of the individual children.

The outcome variables obtained from the Cancer Registry in Scotland were in the form of a

binary variable (yes/no) indicating whether or not a cancer record was present and if

present, the site of cancer given as International Classification of Diseases (ICD) codes.

Similarly, death records with up to 10 different causes of death given by ICD codes were

obtained from linking with GRO-S.

Statistical Analysis:

All analyses were conducted using STATA version 11 (STATA Corp, Texas, USA).

Maternal baseline characteristics were compared between children diagnosed with cancer

and controls using independent two-sample t-tests and chi-square tests. Maternal

complications such as gestational hypertension, pre-eclampsia, antepartum haemorrhage

and previous history of miscarriage were compared between the cases and controls using

univariate conditional regression to calculate odds ratios (OR) with 95% confidence intervals

(CI). Similarly, perinatal factors like gestation at birth, birth weight, intrauterine growth

restriction measured by standardised birthweight score, Apgar score at 1 and 5 minutes

were also tested in univariate models for any association with childhood cancer. Then a

multivariable conditional logistic regression model was fitted that included as independent

variables all risk factors tested on univariate analysis. The possibility of cancer subgroup

analysis was considered according to the International Classification of Childhood Cancer,

but the number of cases in each subgroup was too small to warrant this.

Missing data:

Apart from the variables describing maternal baseline characteristics, the other risk factors

did not have any missing values. There were 18 controls and 1 case with missing smoking

data. The multivariable model was repeated including and excluding the individuals with

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missing information. We used two methodological approaches to handle this - listwise

deletion – ie, not including any group where one person in that group has missing data, and

imputation by creation of a missing value (999) so that all cases and controls were included

in the analyses. The odds ratios obtained by both methods are presented.

Ethical considerations:

Approval to carry out the study was obtained from the AMND steering committee and the

Privacy Advisory Committee for the Information Services Division of National Health

Services, Scotland. As the study involved the analysis of routinely collected anonymised

data, formal ethical approval was not required as declared by the North of Scotland

Research Ethics Service.

Results:

There were 62375 deliveries between 1993 and 2006 as identified from the AMND. After

excluding Down’s syndrome cases, twins and multiple births, stillbirths and early neonatal

deaths, there were 60117 children eligible for linkage with the Cancer Registry. It was

possible to link 43591 of these children to the cancer and GRO-S databases. Amongst the

children with linked data, 106 had died of non-cancer causes before they reached the age of

15 and were therefore excluded from the analysis. Of the remainder, 176 were found to have

a record in the Cancer Registry, giving a cumulative incidence rate of childhood cancer up to

15 years of 4.05 per 1000 deliveries. They constituted the cases for the analysis and were

matched in 1:4 ratio by year of birth and sex from the pool of remaining children without any

records of cancer to obtain 704 controls. As D40, D44, D47 and D48 codes in ICD-10 do not

correspond to cancer diagnosis in International Classification of Childhood Cancer (ICCC),

the analyses were repeated excluding these codes.

Maternal baseline characteristics were compared between cases and matched controls in

Table 1. Of the maternal characteristics tested, mother’s age at delivery (cases mean 28.9

years, s.d. 5.6; controls mean 30.2, s.d. 4.6; p = 0.002) and smoking status (38.6% current

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or ex-smokers among cases, 29.7% among controls, p=0.022) were found to be significantly

different between the two groups.

Table 2 presents the unadjusted odds ratios with 95% confidence intervals for all the

perinatal potential risk factors for childhood cancer. Of the factors tested, preterm birth {OR

2.23(1.31 – 3.79)}; low birth weight {OR 1.87(1.03 – 3.39)}, low Apgar score at 5 minutes

{OR 5.01(1.73 – 14.54)} and delivery by caesarean section {OR 1.77(1.23 – 2.56)} were

found to be statistically significant. Subsequently, these factors were adjusted for maternal

age at delivery and smoking. As the maternal smoking variable had some missing data, we

handled this using two approaches – listwise deletion and imputation of a missing value.

After these adjustments, low birthweight no longer remained significant, but the other

associations were strengthened.

After conducting the univariate analyses multivariable models were fitted including maternal

age, smoking status, preeclampsia, placenta praevia, preterm birth, low birthweight, low

Apgar at 5 minutes and delivery by caesarean as independent variables (results in Table 3).

Similar to the previous analyses, we used two methods of listwise deletion and imputation of

the missing value to adjust for smoking status. Of the perinatal factors tested, Apgar score

below 7 at 5 minutes {AOR 3.91, 95% CI 1.13 – 13.61(listwise deletion); AOR 4.59, 95% CI

1.52, 13.87 (imputation)} and delivery by caesarean section {AOR 2.11, 95% CI 1.38, 3.23

(listwise deletion); AOR 1.95, 95% CI 1.30, 2.92 (imputation)} showed statistically significant

associations with childhood cancer in both multivariable models adjusted for maternal age,

smoking and other factors simultaneously included in the models. Preterm birth (delivery

before 37 completed weeks of gestation) and low birth weight defined as a birth weight

below 2500g, showed a significant association in the univariate analysis, but these

associations were no longer significant in the multivariable model. The associations were not

statistically significant on univariate or multivariable analysis between the risk of childhood

cancer and hypertensive disorders, antepartum haemorrhage, previous history of

miscarriage or IUGR. Unlike the Apgar score at 5 minutes, the score at 1 minute did not

show any association with childhood cancer.

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We further investigated the types of preterm delivery (spontaneous or induced) and

caesarean section (elective or emergency) as risk factors for childhood cancer and found

that both spontaneous and induced preterm delivery were significantly associated in the

adjusted model but only delivery by emergency caesarean section remained significant on

subgroup analysis (AOR 1.43, 95% CI 1.20, 2.18). Further, we found that the commonest

indication for caesarean delivery in the babies who were subsequently diagnosed with

cancer was fetal distress (data not shown).

Table 4 shows the distribution of cancer sites in the 176 cases. As this table shows, the

commonest sites were the brain and haemopoietic organs, especially leukaemia, but the

numbers in the subgroups were too small to allow any meaningful analysis.

Discussion:

We aimed to study the maternal and perinatal risk factors at the time of birth associated with

the diagnosis of childhood cancer using record linkage between two high quality registers in

Scotland. We found a positive association between younger maternal age at delivery and

maternal smoking with childhood cancer. In addition, preterm birth before 37 weeks of

gestation, Apgar score below 7 at 5 minutes and delivery by emergency caesarean section

showed statistically significant associations with childhood cancer the last two of which

remained significant in the adjusted models.

Childhood cancer is a rare condition. Case control studies are therefore the most efficient

epidemiological study design to study several risk factors at the time of birth. Cancer

registries across the world have been utilised to identify cases, but finding appropriate

controls remains problematic. Moreover, data collections regarding exposures by means of

interviews or questionnaires are subject to recall and reporting bias. More recently, linkage

of birth registers with cancer registries has been utilised to design large scale cohort studies.

However, the routine data collection is liable to lack sufficiently detailed data regarding

exposure and potential confounding factors. We have tried to minimise these problems by

linking two high quality registers in Scotland. Previous validation projects have shown these

databases to be 100% complete and over 97% accurate15. Detailed and contemporaneous

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recording of obstetric data in the AMND eliminated recall and reporting bias. The large

number of social and demographic variables recorded in the AMND enabled incorporation of

most potential covariates in the analysis. Despite these strengths to our study design, we

were limited by the small number of cases and it is possible that we did not have sufficient

power to detect some weak associations reported previously in the literature. Maternal and

perinatal risk factors for childhood cancer appear to differ by the site of cancer in the

published literature. The number of cases according to site specific cancer diagnosis was

too small in our sample to allow any subgroup analysis. Further, morphology codes were not

available for us to carry out more appropriate groupings of childhood cancers. This, coupled

with the fact that we had to conduct our analyses on all cancers would have made it less

likely for us to find associations that exist with site specific cancers. This could be a major

limitation of the current analysis. There was a single case of cancer that occurred within the

first year of delivery. It is possible that this could be the result of the cancer being already

present at birth.

The association of parental age with the diagnosis of cancer in general as well as in specific

sites has been studied before. Johnson et al16 in a pooled analysis of register linkage data

from several US states, found that the risk of childhood cancer increased with increasing

maternal age, while paternal age appeared to have no effect on the risk. On the other hand

several other studies, similar to the current analysis have shown that younger maternal age

was associated with increased childhood cancer risk2,17. There could be several

explanations for the disparate findings. In a register linkage study carried out in Sweden18,19,

researchers found that advancing maternal age was positively associated with childhood

cancer risk but only in a historical cohort. This association disappeared in a more recent

cohort of women although the reasons for this are unknown. Moreover, Schutz20 suggests

that the association of lower maternal age at the time of delivery with leukaemia in the

offspring could be explained by non-response bias, although this is not applicable to the

present study.

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The relationship between maternal smoking and childhood cancer in the offspring is complex

and controversial. While Sorahan et al21 - 23 and Edraki24 found an increased overall risk of

childhood cancer with paternal cigarette smoking, there did not appear to be an association

with maternal smoking after adjusting for birthweight. Further, Pang et al9 did not find

evidence of smoking as a risk factor for childhood cancer after adjusting for parental age.

Similar associations were reported by Chang et al25 with regard to Acute Lymphoblastic

Leukaemia (ALL). The evidence appears to indicate that neonatal passive smoking plays a

more important role than in utero transfer of maternal smoke related toxins, although we

cannot rule out the possibility of an association between maternal smoking and site-specific

cancers26,27. For the current analysis, we did not have access to data on paternal smoking

habits and the association seen with maternal smoking could be due to this variable acting

as proxy for paternal smoking.

Other associations noted in this study have been reported before – preterm birth28, and low

Apgar score2,28. Birthweight has received a lot of attention as a risk factor for childhood

cancer. While brain tumours and retinoblastoma appear to be associated with high

birthweight29 - 31 others have found hepatoblastomas7,32 and gliomas33 to be associated with

very low birthweight infants. Schmidt28 et al observed a U-shaped relationship between

birthweight and cancer risk, while Podvin34 found birthweight adjusted for gestational age to

be a better predictor than birthweight alone for the diagnosis of ALL, lending support to our

findings. It is however, important to note, that we did not find an association with intrauterine

growth restriction as measured by the z-score or standardized birthweight score.

Few studies have assessed mode of delivery, specifically caesarean delivery, as a possible

risk factor for the development of childhood cancer. Those that have done, have found a

weak to moderate association 3,7,10,,35,36 between caesarean delivery and subsequent risk of

developing ALL. Several hypotheses can be developed regarding the biological mechanism

underpinning this association. First, caesarean delivery is likely to be a marker of adverse

pregnancy and delivery events – indeed, our finding of increased emergency caesarean

rates indicated by fetal distress seems to support this hypothesis. However, the association

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remained and actually became stronger, after adjusting for most other possible pregnancy

complications. It was customary to use 100% oxygen to resuscitate babies born by

caesarean section in the past. It is possible that this could have played a role in the

subsequent development of cancer. The last explanation involves epigenetic modulations at

birth. Schlinzig et al37 have demonstrated altered DNA-methylation in cord white blood cells

after caesarean delivery and suggested that this may be the basis of increased risk of

asthma, diabetes and ALL seen in infants born by caesarean section.

The association of caesarean delivery with childhood cancer seen in this analysis should be

treated with caution given the small numbers of childhood cancer cases in the study. The

recent NICE guidelines38 recommends caesarean delivery on maternal request. Although,

we have to remember that the majority of the caesarean deliveries seen in the cases of

childhood cancer in the current analysis were emergency procedures with strong indications

such as fetal distress. Our finding of the strong association of childhood cancer with

caesarean delivery warrants further research using record linkage of larger cohorts or

prospective follow up of birth cohorts. From the point of view of Public Health interventions,

the only other modifiable risk factor appears to be parental smoking. Several population

based lifestyle interventions are already underway to reduce the prevalence of smoking in

pregnancy.

Conclusion: We found a positive association between younger maternal age at delivery and

maternal smoking with childhood cancer. In addition, preterm birth, low Apgar score at 5

minutes and delivery by caesarean section showed associations with childhood cancer,

which remained significant even after controlling for various covariates.

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What is already known on this topic

Extremes of maternal age at delivery, parental smoking, preterm birth and low birthweight

have all been reported to be risk factors for childhood cancer.

What this study adds

The large effect of delivery by caesarean section on the increased risk of childhood cancer is

a novel finding in this study.

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12. Milne E, Laurvick CL, Blair E et al. Fetal growth and the risk of childhood CNS

tumours and lymphomas in Western Australia. Int J Cancer 2008;123:436-443.

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23. Sorahan T, Prior P, Lancashire RJ, et al. Childhood cancer and parental use of

tobacco: Deaths from 1971 to 1976. Br J Cancer 1997;76:1525-31.

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Based Case-Control Study. Can Epi Bio Prev. 2010; 19: 1042-1052.

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analysis. Int J Epidemiol 2010; 39: 746-756

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cancer. J Natl Cancer Inst 1984;72:1039-41.

31. MacLean J, Partap S, Reynolds P, et al. Birth weight and order as risk factors for

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32. Spector LG, Johnson KJ, Soler JT, et al. Perinatal risk factors for hepatoblastoma. Br

J Cancer 2008; 98: 1570-1573.

33. Spector LG, Puumala SE, Carozza SE, et al. Cancer risk among children with very

low birth weights. Pediatrics 2009;124:96-104.

34. Podvin D, Kuehn CM, Mueller BA, et al. Maternal and birth characteristics in relation

to childhood leukaemia. Paediatr Perinat Epidemiol 2006;20:312-22.

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35. Cnattingius S, Zack M, Ekbom A et al. Prenatal and neonatal risk factors for

childhood myeloid leukaemia. Cancer Epidemiol Biomarkers and Prev 1995; 4:441 -

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36. Kaye SA, Robinson LL, Anthony Smithson W et al. Maternal reproductive history and

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38. National Institute for Health and Clinical Excellence. CG132 Caesarean Section.

Available at: http://guidance.nice.org.uk/CG132 [accessed March 2012].

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Table 1. Comparison of maternal baseline characteristics between case children and control children

Characteristics Cases Controls p-

value

Age at delivery (mean, s.d.) 28.9 (5.6) 30.2 (4.6) 0.002

Maternal social class

Manual 26 (14.8%) 79 (11.2%)

0.187 Non-Manual 62 (35.2%) 295 (41.9%)

Single/widowed 87 (49.4%) 325 (46.2%)

Missing 1 (0.6%) 5 (0.7%)

Paternal social class

Paternal Manual 71 (40.3%) 329 (46.7%)

0.193 Paternal Non-manual 47 (26.7%) 183 (26.0%)

Maternal non-manual 57 (32.4%) 184 (26.1%)

Missing 1 (0.6%) 8 (1.1%)

Marital status

Single/Widowed/Divorced/Separated/ 62 (35.2%) 222 (31.5%) 0.324

Married 113 (64.2%) 482 (68.4%)

Missing 1 (0.6%) 0 (0%)

BMI (mean, s.d.) (Missing cases = 12, Missing controls = 39) 25.2 (5.1) 25.5 (5.1) 0.407

Smoking

Non-smoker 107 (60.8%) 477 (67.8%) 0.034

Smoker/ex-smoker 68 (38.6%) 209 (29.7%)

Missing 1 (0.6%) 18 (2.6%)

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Table 2. Comparison of perinatal factors between cases and controls with statistically significant odds ratios shown in bold

Perinatal factors Cases N=176 Controls N=704 Unadjusted odds ratio

(95% CI)

Age and smoking adjusted

odds ratio (95% CI) – listwise

deletion

Age and smoking adjusted

odds ratio (95% CI) –

imputation of missing value

Preeclampsia 11 (6.3%) 23 (3.3%) 1.98 (0.94-4.18) 1.94 (0.88-4.28) 1.92 (0.91-4.09)

Gestational hypertension 19 (10.8%) 71 (10.1%) 1.09 (0.62-1.89) 1.21 (0.67-2.17) 1.13 (0.64-2.01)

Placenta praevia 3 (1.7%) 4 (0.6%) 3.00 (0.67-13.40) 3.46 (0.76-15.65) 3.45 (0.76-15.62)

Abruption 1 (0.6%) 4 (0.6%) 1.00 (0.11-8.95) 1.31 (0.14-12.66) 1.04 (0.12-9.41)

Other APH 19 (10.8%) 77 (10.9%) 0.99 (0.58-1.68) 0.98 (0.56-1.72) 0.96 (0.56-1.65)

Previous miscarriage 18 (10.2%) 103 (14.6%) 0.67 (0.39-1.13) 0.83 (0.48-1.43) 0.70 (0.41-1.19)

Preterm birth 24 (13.6%) 47 (6.7%) 2.23 (1.31-3.79) 2.09 (1.16-3.76) 2.23 (1.29-3.85)

Low birthweight 17 (9.7%) 38 (5.4%) 1.87 (1.03-3.39) 1.81 (0.94-3.45) 1.78 (0.97-3.28)

Low apgar at 1 minute 30 (17.1%) 107 (15.4%) 1.14 (0.73-1.78) 1.14 (0.71-1.84) 1.15 (0.73-1.81)

Low apgar at 5 minutes 8 (4.6%) 7 (1.0%) 5.01 (1.73-14.54) 4.91 (1.46-16.51) 5.70 (1.93-16.78)

Delivery by caesarean 55 (31.3%) 143 (20.4%) 1.77 (1.23-2.56) 2.25 (1.50-3.36) 2.07 (1.41-3.05)

Instrumental delivery 26 (14.8%) 144 (20.5%) 0.66 (0.41-1.04) 0.68 (0.41-1.13) 0.67 (0.42-1.08)

Intrauterine Growth

Restriction 23 (13.4%) 71 (10.3%) 1.41 (0.85-2.36) 1.20 (0.68-2.12) 1.35 (0.80-2.23)

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Table 3. Odds ratios from multivariable model

*All variables adjusted for maternal age and smoking and for other variables in the model

Statistically significant odds ratios are shown in bold.

Perinatal factors OR (95%CI) from multivariable model – listwise deletion* OR (95% CI) from multivariable model – imputation of missing

value*

Preeclampsia 1.56 (0.68-3.59) 1.55 (0.70-3.44)

Placenta praevia 1.64 (0.32-8.34) 1.65 (0.32-8.43)

Preterm birth 1.60 (0.76-3.37) 1.85 (0.92-3.72)

Low birthweight 1.00 (0.44-2.28) 0.90 (0.41-1.97)

Low apgar at 5 minutes 3.91 (1.13-13.61) 4.59 (1.52-13.87)

Delivery by caesarean 2.11 (1.38-3.23) 1.95 (1.30-2.92)

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Table 4. Distribution of sites of cancer

Cancer site No. %

C22 – Liver and intrahepatic bile ducts 2 1.14

C34 – Bronchus and lung 2 1.14

C41 – Bone and articular cartilage of other and unspecified sites 10

5.68

C49 – Other connective and soft tissue 7

3.98

C52 – Vagina 5 2.84

C56 – Ovary 3 1.70

C62 – Testis 12 6.82

C64 – Kidney except renal pelvis 7 3.98

C69 – Eye and adnexa 6 3.41

C71 – Brain 27

15.34

C72 – Spinal cord, cranial nerves, other CNS 3 1.70

C74 – Adrenal gland 6

3.41

C75 – Other endocrine glands and related structures 4

2.27

C76 – Other and ill-defined sites 2 1.14

C83 – Diffuse non-Hodgkin’s lymphoma 3 1.70

C85 – Other and unspec. non-Hodgkin’s 2 1.14

C91 – Lymphoid Leukaemia 37 21.02

C92 – Myeloid leukaemia 10 5.68

C94 – Other leukaemias of specified cell type 2 1.14

D32 - Meninges 3 1.70

D40 – Uncertain/uknown bhvr male genital 2 1.14

D43 – Uncertain/unknown bhvr. brain and CNS 2 1.14

D44 – Uncertain/unknown bhvr. endocrine 1 0.57

D47 – Uncertain/uknown bhvr. of lymphoid, haematopoietic and related tissue 9

5.11

D48 – Uncertain/unknown bhvr. unknown sites 9 5.11

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Maternal and Perinatal Risk Factors for Childhood Cancer: Record Linkage Study

Sohinee Bhattacharya1* Marcus Beasley1 Dong Pang2 Gary J Macfarlane1

1Epidemiology Group, Division of Applied Health Sciences, University of Aberdeen 2 Institute of Health Research, University of Bedfordshire, Luton *Corresponding author: Sohinee Bhattacharya Dugald Baird Centre for Research on Women’s Health Aberdeen Maternity Hospital Aberdeen AB25 2ZL Tel: +44 1224 438441 e-mail: [email protected] Running title: Risk factors for childhood cancer

Conflict of Interest: All authors have completed the Unified Competing Interest form at http://www.icmje.org/coi_disclosure.pdf and declare: NHS Grampian Endowment funded the study; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, a worldwide licence to the Publishers and its licensees in perpetuity, in all forms, formats and media (whether known now or created in the future), to (i) publish, reproduce, distribute, display and store the Contribution, (ii) translate the Contribution into other languages, create adaptations, reprints, include within collections and create summaries, extracts and/or, abstracts of the Contribution, (iii) create any other derivative work(s) based on the Contribution, (iv) to exploit all subsidiary rights in the Contribution, (v) the inclusion of electronic links from the Contribution to third party material where-ever it may be located; and, (vi) licence any third party to do any or all of the above. Contributorship: SB was responsible for designing the study, facilitating data extraction, supervising data analysis and writing of the first draft of the paper; MB analysed the data; SB, GJM and DP conceived of the research idea and GJM was responsible for overall supervision. All authors contributed to the writing of the final draft of the paper. SB is the guarantor of this paper. Ethics: This research proposal was approved by the Privacy Advisory Committee of the Information and Services Division NHS Scotland and the steering group of the Aberdeen Maternity and Neonatal Databank. Formal ethical approval was not considered necessary by North of Scotland Research Ethics Service as only anonymised data were analysed in this study. Funding: This research was funded by the NHS Grampian Endowment Fund (Project no. 10/15) Role of sponsors: The University of Aberdeen acted as sponsors for this research project, but the findings and their interpretation in this study are the authors’ own. Independence of authors from funders: All authors were employed by the University of Aberdeen at the time of conducting this research and are independent from the funders.

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Abstract Objective: To investigate maternal and perinatal risk factors for childhood cancer.

Study Design: Case control analysis of linked records from the Aberdeen Maternity and

Neonatal Databank with the Scottish Cancer Registry and the General Registry of Births and

Deaths in Scotland was carried out.

Setting: Aberdeen, Scotland

Participants: Cases (n=176) comprised children diagnosed with cancer under 15 years or

recorded as having died of cancer. Four controls per case were matched by age and gender.

Risk factors tested: Maternal age, BMI, social class, marital status and smoking as well as

preeclampsia, antepartum haemorrhage and previous miscarriage, gestational age,

birthweight, and Apgar scores were compared between groups to test for association with

cancer. Odds ratios with 95% Confidence Intervals were calculated using conditional logistic

regression in both univariable and multivariable models.

Results: Of the maternal characteristics tested, mother’s age at delivery {cases mean

28.9(S.D.5.6) years versus controls mean 30.2(S.D4.6), p = 0.002} and smoking status

(38.6% smokers among cases, 29.7% among controls, p=0.034) were found to be different

between groups. Of the perinatal factors tested, low Apgar score at 5 minutes (AOR 4.59,

95% CI 1.52, 13.87) and delivery by caesarean section (AOR 1.95, 95% CI 1.30, 2.92)

showed statistically significant associations with childhood cancer in the multivariable model.

Conclusions: Younger maternal age, maternal smoking, delivery by caesarean section and

low Apgar score at 5 minutes were independently associated with increased risk of

childhood cancer. The association with caesarean delivery may be mediated through

epigenetic mechanism and warrants further investigation.

Key words: childhood cancer, perinatal risk factors, smoking, caesarean delivery

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Introduction:

Childhood cancer has been increasing in Scotland. A published report estimates that its

incidence has risen from 108.3 per million child-years in 1976 to 160.6 per million child-years

in 20071. The reason for this increasing trend remains unexplained as the etiopathogenesis

of childhood cancer is poorly understood. As most present in the first few years of life,

epidemiologists hypothesize that prenatal and perinatal exposures may have a part to play in

its pathogenesis. The evidence surrounding this is however, conflicting. While some

researchers have found associations of younger maternal age at delivery2 maternal

anaemia3,4, previous history of miscarriage2,5,6 maternal overweight7, and smoking8, with

some childhood cancers, others have found no such associations9-11. Fetal growth is

perhaps the most investigated perinatal risk factor for childhood cancer7,12,13 ; but the authors

report conflicting results. While specific central nervous system tumours have been found to

be associated with intrauterine growth restriction, the overall risk was small12. Therefore,

apart from the associations with Down’s syndrome and in utero exposure to radiation,

research into the maternal and perinatal risk factors has remained inconsistent, the results

limited by small sample sizes and recall or reporting bias.

Our objective was therefore to investigate maternal and perinatal risk factors for childhood

cancer, specifically to examine the effects of intrauterine growth restriction, preterm birth and

birth asphyxia on the development of childhood cancer in the offspring, taking advantage of

the opportunities offered by record linkage of a cancer registry with a local birth register.

Methods:

Data Sources:

The Aberdeen Maternity and Neonatal Databank (AMND) holds data for all Aberdeen City

births from 1950 to the present, and includes all reproductive events to women resident in a

defined geographical area with a relatively stable population. The AMND records all births

occurring at the Aberdeen Maternity Hospital, the only maternity hospital serving the

population of Aberdeen city and district. The exposure variables in terms of potential

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maternal and perinatal risk factors were derived from the AMND. The Scottish Cancer

Registry has been in existence since 1951 and was complete up to 2010, at the time of the

present analysis. The cases of childhood cancer were identified from this register.

Data Linkage:

All children born between 1993 and 2006 were identified from the AMND. Their records were

linked to the Cancer Registry in Scotland (SMR 06) and the General Registry of Births and

Deaths in Scotland (GRO-S), using deterministic matching. The linkage was carried out by

data analysts from the Information and Services Division of NHS Scotland using Community

Health Index (CHI) numbers. The CHI number is a number unique to all individuals

registered with a general practice in Scotland and recorded in both databases used in this

study. In a small proportion of cases where CHI number was not available (6%), probabilistic

matching using surname, date of birth and postcode was used. After data linkage, all

identifying information, including CHI numbers were removed and an anonymised dataset

was provided for analysis.

Study design:

A case control study design was employed. Cases comprised all children identified as above

from the AMND who were diagnosed with cancer under 15 years of age in Scotland as

recorded in the Scottish Cancer Registry or recorded as having died of cancer. Controls

were selected from the pool of children not diagnosed as having cancer, matched by age

and gender using four controls per case.

Twins and multiple births were excluded as were stillbirths and early neonatal deaths. As

Down’s syndrome is known to be associated with a higher risk of Acute Lymphoblastic

Leukaemia (ALL) as well as Myeloid Leukaemia of Down’s syndrome, all cases of diagnosed

Down’s syndrome were excluded. Moreover, those children who had died of non-cancer

causes prior to their 15th birthday, as identified from GRO-S were also excluded.

Exposure and outcome variables used in the analysis:

Maternal sociodemographic factors such as age at delivery, body mass index (BMI),

Registrar General’s occupation-based social class, marital status, previous history of

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miscarriage and smoking habits were extracted from the AMND. Any complications recorded

during the index pregnancy such as preeclampsia, gestational hypertension, and antepartum

haemorrhage as well as mode of delivery, gestational age at delivery, birthweight,

Standardised Birthweight Score14, and Apgar score at 1 and 5 minutes were also extracted.

Data extractors were blind to the case-control status of the individual children.

The outcome variables obtained from the Cancer Registry in Scotland were in the form of a

binary variable (yes/no) indicating whether or not a cancer record was present and if

present, the site of cancer given as International Classification of Diseases (ICD) codes.

Similarly, death records with up to 10 different causes of death given by ICD codes were

obtained from linking with GRO-S.

Statistical Analysis:

All analyses were conducted using STATA version 11 (STATA Corp, Texas, USA).

Maternal baseline characteristics were compared between children diagnosed with cancer

and controls using independent two-sample t-tests and chi-square tests. Maternal

complications such as gestational hypertension, pre-eclampsia, antepartum haemorrhage

and previous history of miscarriage were compared between the cases and controls using

univariate conditional regression to calculate odds ratios (OR) with 95% confidence intervals

(CI). Similarly, perinatal factors like gestation at birth, birth weight, intrauterine growth

restriction measured by standardised birthweight score, Apgar score at 1 and 5 minutes

were also tested in univariate models for any association with childhood cancer. Then a

multivariable conditional logistic regression model was fitted that included as independent

variables all risk factors tested on univariate analysis. The possibility of cancer subgroup

analysis was considered according to the International Classification of Childhood Cancer,

but the number of cases in each subgroup was too small to warrant this.

Missing data:

Apart from the variables describing maternal baseline characteristics, the other risk factors

did not have any missing values. There were 18 controls and 1 case with missing smoking

data. The multivariable model was repeated including and excluding the individuals with

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missing information. We used two methodological approaches to handle this - listwise

deletion – ie, not including any group where one person in that group has missing data, and

imputation by creation of a missing value (999) so that all cases and controls were included

in the analyses. The odds ratios obtained by both methods are presented.

Ethical considerations:

Approval to carry out the study was obtained from the AMND steering committee and the

Privacy Advisory Committee for the Information Services Division of National Health

Services, Scotland. As the study involved the analysis of routinely collected anonymised

data, formal ethical approval was not required as declared by the North of Scotland

Research Ethics Service.

Results:

There were 62375 deliveries between 1993 and 2006 as identified from the AMND. After

excluding Down’s syndrome cases, twins and multiple births, stillbirths and early neonatal

deaths, there were 60117 children eligible for linkage with the Cancer Registry. It was

possible to link 43591 of these children to the cancer and GRO-S databases. Amongst the

children with linked data, 106 had died of non-cancer causes before they reached the age of

15 and were therefore excluded from the analysis. Of the remainder, 176 were found to have

a record in the Cancer Registry, giving a cumulative incidence rate of childhood cancer up to

15 years of 4.05 per 1000 deliveries. They constituted the cases for the analysis and were

matched in 1:4 ratio by year of birth and sex from the pool of remaining children without any

records of cancer to obtain 704 controls. As D40, D44, D47 and D48 codes in ICD-10 do not

correspond to cancer diagnosis in International Classification of Childhood Cancer (ICCC),

the analyses were repeated excluding these codes.

Maternal baseline characteristics were compared between cases and matched controls in

Table 1. Of the maternal characteristics tested, mother’s age at delivery (cases mean 28.9

years, s.d. 5.6; controls mean 30.2, s.d. 4.6; p = 0.002) and smoking status (38.6% current

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or ex-smokers among cases, 29.7% among controls, p=0.022) were found to be significantly

different between the two groups.

Table 2 presents the unadjusted odds ratios with 95% confidence intervals for all the

perinatal potential risk factors for childhood cancer. Of the factors tested, preterm birth {OR

2.23(1.31 – 3.79)}; low birth weight {OR 1.87(1.03 – 3.39)}, low Apgar score at 5 minutes

{OR 5.01(1.73 – 14.54)} and delivery by caesarean section {OR 1.77(1.23 – 2.56)} were

found to be statistically significant. Subsequently, these factors were adjusted for maternal

age at delivery and smoking. As the maternal smoking variable had some missing data, we

handled this using two approaches – listwise deletion and imputation of a missing value.

After these adjustments, low birthweight no longer remained significant, but the other

associations were strengthened.

After conducting the univariate analyses multivariable models were fitted including maternal

age, smoking status, preeclampsia, placenta praevia, preterm birth, low birthweight, low

Apgar at 5 minutes and delivery by caesarean as independent variables (results in Table 3).

Similar to the previous analyses, we used two methods of listwise deletion and imputation of

the missing value to adjust for smoking status. Of the perinatal factors tested, Apgar score

below 7 at 5 minutes {AOR 3.91, 95% CI 1.13 – 13.61(listwise deletion); AOR 4.59, 95% CI

1.52, 13.87 (imputation)} and delivery by caesarean section {AOR 2.11, 95% CI 1.38, 3.23

(listwise deletion); AOR 1.95, 95% CI 1.30, 2.92 (imputation)} showed statistically significant

associations with childhood cancer in both multivariable models adjusted for maternal age,

smoking and other factors simultaneously included in the models. Preterm birth (delivery

before 37 completed weeks of gestation) and low birth weight defined as a birth weight

below 2500g, showed a significant association in the univariate analysis, but these

associations were no longer significant in the multivariable model. The associations were not

statistically significant on univariate or multivariable analysis between the risk of childhood

cancer and hypertensive disorders, antepartum haemorrhage, previous history of

miscarriage or IUGR. Unlike the Apgar score at 5 minutes, the score at 1 minute did not

show any association with childhood cancer.

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We further investigated the types of preterm delivery (spontaneous or induced) and

caesarean section (elective or emergency) as risk factors for childhood cancer and found

that both spontaneous and induced preterm delivery were significantly associated in the

adjusted model but only delivery by emergency caesarean section remained significant on

subgroup analysis (AOR 1.43, 95% CI 1.20, 2.18). Further, we found that the commonest

indication for caesarean delivery in the babies who were subsequently diagnosed with

cancer was fetal distress (data not shown).

Table 4 shows the distribution of cancer sites in the 176 cases. As this table shows, the

commonest sites were the brain and haemopoietic organs, especially leukaemia, but the

numbers in the subgroups were too small to allow any meaningful analysis.

Discussion:

We aimed to study the maternal and perinatal risk factors at the time of birth associated with

the diagnosis of childhood cancer using record linkage between two high quality registers in

Scotland. We found a positive association between younger maternal age at delivery and

maternal smoking with childhood cancer. In addition, preterm birth before 37 weeks of

gestation, Apgar score below 7 at 5 minutes and delivery by emergency caesarean section

showed statistically significant associations with childhood cancer the last two of which

remained significant in the adjusted models.

Childhood cancer is a rare condition. Case control studies are therefore the most efficient

epidemiological study design to study several risk factors at the time of birth. Cancer

registries across the world have been utilised to identify cases, but finding appropriate

controls remains problematic. Moreover, data collections regarding exposures by means of

interviews or questionnaires are subject to recall and reporting bias. More recently, linkage

of birth registers with cancer registries has been utilised to design large scale cohort studies.

However, the routine data collection is liable to lack sufficiently detailed data regarding

exposure and potential confounding factors. We have tried to minimise these problems by

linking two high quality registers in Scotland. Previous validation projects have shown these

databases to be 100% complete and over 97% accurate15. Detailed and contemporaneous

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recording of obstetric data in the AMND eliminated recall and reporting bias. The large

number of social and demographic variables recorded in the AMND enabled incorporation of

most potential covariates in the analysis. Despite these strengths to our study design, we

were limited by the small number of cases and it is possible that we did not have sufficient

power to detect some weak associations reported previously in the literature. Maternal and

perinatal risk factors for childhood cancer appear to differ by the site of cancer in the

published literature. The number of cases according to site specific cancer diagnosis was

too small in our sample to allow any subgroup analysis. Further, morphology codes were not

available for us to carry out more appropriate groupings of childhood cancers. This, coupled

with the fact that we had to conduct our analyses on all cancers would have made it less

likely for us to find associations that exist with site specific cancers. This could be a major

limitation of the current analysis. There was a single case of cancer that occurred within the

first year of delivery. It is possible that this could be the result of the cancer being already

present at birth.

The association of parental age with the diagnosis of cancer in general as well as in specific

sites has been studied before. Johnson et al16 in a pooled analysis of register linkage data

from several US states, found that the risk of childhood cancer increased with increasing

maternal age, while paternal age appeared to have no effect on the risk. On the other hand

several other studies, similar to the current analysis have shown that younger maternal age

was associated with increased childhood cancer risk2,17. There could be several

explanations for the disparate findings. In a register linkage study carried out in Sweden18,19,

researchers found that advancing maternal age was positively associated with childhood

cancer risk but only in a historical cohort. This association disappeared in a more recent

cohort of women although the reasons for this are unknown. Moreover, Schutz20 suggests

that the association of lower maternal age at the time of delivery with leukaemia in the

offspring could be explained by non-response bias, although this is not applicable to the

present study.

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The relationship between maternal smoking and childhood cancer in the offspring is complex

and controversial. While Sorahan et al21 - 23 and Edraki24 found an increased overall risk of

childhood cancer with paternal cigarette smoking, there did not appear to be an association

with maternal smoking after adjusting for birthweight. Further, Pang et al9 did not find

evidence of smoking as a risk factor for childhood cancer after adjusting for parental age.

Similar associations were reported by Chang et al25 with regard to Acute Lymphoblastic

Leukaemia (ALL). The evidence appears to indicate that neonatal passive smoking plays a

more important role than in utero transfer of maternal smoke related toxins, although we

cannot rule out the possibility of an association between maternal smoking and site-specific

cancers26,27. For the current analysis, we did not have access to data on paternal smoking

habits and the association seen with maternal smoking could be due to this variable acting

as proxy for paternal smoking.

Other associations noted in this study have been reported before – preterm birth28, and low

Apgar score2,28. Li et al found a 46% increased risk of childhood cancer in infants who had a

low 5 minute Apgar score29. Birthweight has received a lot of attention as a risk factor for

childhood cancer. While brain tumours and retinoblastoma appear to be associated with high

birthweight3029 - 312 others have found hepatoblastomas7,323 and gliomas334 to be associated

with very low birthweight infants. Schmidt28 et al observed a U-shaped relationship between

birthweight and cancer risk, while Podvin354 found birthweight adjusted for gestational age to

be a better predictor than birthweight alone for the diagnosis of ALL, lending support to our

findings. It is however, important to note, that we did not find an association with intrauterine

growth restriction as measured by the z-score or standardized birthweight score.

Few studies have assessed mode of delivery, specifically caesarean delivery, as a possible

risk factor for the development of childhood cancer. Those that have done, have found a

weak to moderate association 3,7,10,,365,376 between caesarean delivery and subsequent risk of

developing ALL. Several hypotheses can be developed regarding the biological mechanism

underpinning this association. First, caesarean delivery is likely to be a marker of adverse

pregnancy and delivery events – indeed, our finding of increased emergency caesarean

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rates indicated by fetal distress seems to support this hypothesis. However, the association

remained and actually became stronger, after adjusting for most other possible pregnancy

complications. It was customary to use 100% oxygen to resuscitate babies born by

caesarean section in the past. It is possible that this could have played a role in the

subsequent development of cancer. The last explanation involves epigenetic modulations at

birth. Schlinzig et al387 have demonstrated altered DNA-methylation in cord white blood cells

after caesarean delivery and suggested that this may be the basis of increased risk of

asthma, diabetes and ALL seen in infants born by caesarean section.

The association of caesarean delivery with childhood cancer seen in this analysis should be

treated with caution given the small numbers of childhood cancer cases in the study., is

likely to have far reaching consequences for obstetric practice. The recent NICE

guidelines398 recommends caesarean delivery on maternal request., further evidence to

support a link between caesarean section and subsequent cancer in the offspring would

seriously question the ethics of such practice. Although, we have to remember that the

majority of the caesarean deliveries seen in the cases of childhood cancer in the current

analysis were emergency procedures with strong indications such as fetal distress. Our

finding of the strong association of childhood cancer with caesarean delivery certainly

warrants further research using record linkage of larger cohorts or prospective follow up of

birth cohorts. From the point of view of Public Health interventions, the only other modifiable

risk factor appears to be parental smoking. Several population based lifestyle interventions

are already underway to reduce the prevalence of smoking in pregnancy.

Conclusion: We found a positive association between younger maternal age at delivery and

maternal smoking with childhood cancer. In addition, preterm birth, low Apgar score at 5

minutes and delivery by caesarean section showed associations with childhood cancer,

which remained significant even after controlling for various covariates. While maternal age

and smoking, preterm birth and low Apgar Score have all been previously shown to be

associated with childhood cancer, delivery by caesarean section is a novel finding and

warrants further investigation in larger cohorts. We also propose a mechanistic study

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exploring epigenetic changes associated with caesarean delivery as the underlying

mechanism linking the two conditions.

What is already known on this topic

Extremes of maternal age at delivery, parental smoking, preterm birth and low birthweight

have all been reported to be risk factors for childhood cancer.

What this study adds

The large effect of delivery by caesarean section on the increased risk of childhood cancer is

a novel finding in this study.

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34.35. Podvin D, Kuehn CM, Mueller BA, et al. Maternal and birth characteristics in

relation to childhood leukaemia. Paediatr Perinat Epidemiol 2006;20:312-22.

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Table 1. Comparison of maternal baseline characteristics between case children and control children

Characteristics Cases Controls p-

value

Age at delivery (mean, s.d.) 28.9 (5.6) 30.2 (4.6) 0.002

Maternal social class

Manual 26 (14.8%) 79 (11.2%)

0.187 Non-Manual 62 (35.2%) 295 (41.9%)

Single/widowed 87 (49.4%) 325 (46.2%)

Missing 1 (0.6%) 5 (0.7%)

Paternal social class

Paternal Manual 71 (40.3%) 329 (46.7%)

0.193 Paternal Non-manual 47 (26.7%) 183 (26.0%)

Single/widowed Maternal non-manual 57 (32.4%) 184 (26.1%)

Missing 1 (0.6%) 8 (1.1%)

Marital status

Single/Widowed/Divorced/Separated/Cohabiting 62 (35.2%) 222 (31.5%) 0.324

Married 113 (64.2%) 482 (68.4%)

Missing 1 (0.6%) 0 (0%)

BMI (mean, s.d.) (Missing cases = 12, Missing controls = 39) 25.2 (5.1) 25.5 (5.1) 0.407

Smoking

Non-smoker 107 (60.8%) 477 (67.8%) 0.034

Smoker/ex-smoker 68 (38.6%) 209 (29.7%)

Missing 1 (0.6%) 18 (2.6%)

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Table 2. Comparison of perinatal factors between cases and controls with statistically significant odds ratios shown in bold

Perinatal factors Cases N=176 Controls N=704 Unadjusted odds ratio

(95% CI)

Age and smoking adjusted

odds ratio (95% CI) – listwise

deletion

Age and smoking adjusted

odds ratio (95% CI) –

imputation of missing value

Preeclampsia 11 (6.3%) 23 (3.3%) 1.98 (0.94-4.18) 1.94 (0.88-4.28) 1.92 (0.91-4.09)

Gestational hypertension 19 (10.8%) 71 (10.1%) 1.09 (0.62-1.89) 1.21 (0.67-2.17) 1.13 (0.64-2.01)

Placenta praevia 3 (1.7%) 4 (0.6%) 3.00 (0.67-13.40) 3.46 (0.76-15.65) 3.45 (0.76-15.62)

Abruption 1 (0.6%) 4 (0.6%) 1.00 (0.11-8.95) 1.31 (0.14-12.66) 1.04 (0.12-9.41)

Other APH 19 (10.8%) 77 (10.9%) 0.99 (0.58-1.68) 0.98 (0.56-1.72) 0.96 (0.56-1.65)

Previous miscarriage 18 (10.2%) 103 (14.6%) 0.67 (0.39-1.13) 0.83 (0.48-1.43) 0.70 (0.41-1.19)

Preterm birth 24 (13.6%) 47 (6.7%) 2.23 (1.31-3.79) 2.09 (1.16-3.76) 2.23 (1.29-3.85)

Low birthweight 17 (9.7%) 38 (5.4%) 1.87 (1.03-3.39) 1.81 (0.94-3.45) 1.78 (0.97-3.28)

Low apgar at 1 minute 30 (17.1%) 107 (15.4%) 1.14 (0.73-1.78) 1.14 (0.71-1.84) 1.15 (0.73-1.81)

Low apgar at 5 minutes 8 (4.6%) 7 (1.0%) 5.01 (1.73-14.54) 4.91 (1.46-16.51) 5.70 (1.93-16.78)

Delivery by caesarean 55 (31.3%) 143 (20.4%) 1.77 (1.23-2.56) 2.25 (1.50-3.36) 2.07 (1.41-3.05)

Instrumental delivery 26 (14.8%) 144 (20.5%) 0.66 (0.41-1.04) 0.68 (0.41-1.13) 0.67 (0.42-1.08)

Intrauterine Growth

Restriction 23 (13.4%) 71 (10.3%) 1.41 (0.85-2.36) 1.20 (0.68-2.12) 1.35 (0.80-2.23)

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Table 3. Odds ratios from multivariable model

*All variables adjusted for maternal age and smoking and for other variables in the model

Statistically significant odds ratios are shown in bold.

Perinatal factors OR (95%CI) from multivariable model – listwise deletion* OR (95% CI) from multivariable model – imputation of missing

value*

Preeclampsia 1.56 (0.68-3.59) 1.55 (0.70-3.44)

Placenta praevia 1.64 (0.32-8.34) 1.65 (0.32-8.43)

Preterm birth 1.60 (0.76-3.37) 1.85 (0.92-3.72)

Low birthweight 1.00 (0.44-2.28) 0.90 (0.41-1.97)

Low apgar at 5 minutes 3.91 (1.13-13.61) 4.59 (1.52-13.87)

Delivery by caesarean 2.11 (1.38-3.23) 1.95 (1.30-2.92)

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Table 4. Distribution of sites of cancer

Cancer site No. %

C22 – Liver and intrahepatic bile ducts 2 1.14

C34 – Bronchus and lung 2 1.14

C41 – Bone and articular cartilage of other and unspecified sites 10

5.68

C49 – Other connective and soft tissue 7

3.98

C52 – Vagina 5 2.84

C56 – Ovary 3 1.70

C62 – Testis 12 6.82

C64 – Kidney except renal pelvis 7 3.98

C69 – Eye and adnexa 6 3.41

C71 – Brain 27

15.34

C72 – Spinal cord, cranial nerves, other CNS 3 1.70

C74 – Adrenal gland 6

3.41

C75 – Other endocrine glands and related structures 4

2.27

C76 – Other and ill-defined sites 2 1.14

C83 – Diffuse non-Hodgkin’s lymphoma 3 1.70

C85 – Other and unspec. non-Hodgkin’s 2 1.14

C91 – Lymphoid Leukaemia 37 21.02

C92 – Myeloid leukaemia 10 5.68

C94 – Other leukaemias of specified cell type 2 1.14

D32 - Meninges 3 1.70

D40 – Uncertain/uknown bhvr male genital 2 1.14

D43 – Uncertain/unknown bhvr. brain and CNS 2 1.14

D44 – Uncertain/unknown bhvr. endocrine 1 0.57

D47 – Uncertain/uknown bhvr. of lymphoid, haematopoietic and related tissue 9

5.11

D48 – Uncertain/unknown bhvr. unknown sites 9 5.11

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Maternal and perinatal risk factors for childhood cancer

Journal: BMJ Open

Manuscript ID: bmjopen-2013-003656.R2

Article Type: Research

Date Submitted by the Author: 05-Nov-2013

Complete List of Authors: Bhattacharya, Sohinee; University of Aberdeen, Public Health

Beasley, Marcus; University of Aberdeen, Epidemiology Group Pang, Dong; University of Bedfordshire, Institute of Health Research Macfarlane, Gary; University of Aberdeen, Epidemiology Group

<b>Primary Subject Heading</b>:

Epidemiology

Secondary Subject Heading: Obstetrics and gynaecology, Oncology

Keywords: EPIDEMIOLOGY, Fetal medicine < OBSTETRICS, Paediatric oncology < ONCOLOGY

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Maternal and Perinatal Risk Factors for Childhood Cancer: Record Linkage Study

Sohinee Bhattacharya1* Marcus Beasley1 Dong Pang2 Gary J Macfarlane1

1Epidemiology Group, Division of Applied Health Sciences, University of Aberdeen 2 Institute of Health Research, University of Bedfordshire, Luton *Corresponding author: Sohinee Bhattacharya Dugald Baird Centre for Research on Women’s Health Aberdeen Maternity Hospital Aberdeen AB25 2ZL Tel: +44 1224 438441 e-mail: [email protected] Running title: Risk factors for childhood cancer

Conflict of Interest: All authors have completed the Unified Competing Interest form at http://www.icmje.org/coi_disclosure.pdf and declare: NHS Grampian Endowment funded the study; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, a worldwide licence to the Publishers and its licensees in perpetuity, in all forms, formats and media (whether known now or created in the future), to (i) publish, reproduce, distribute, display and store the Contribution, (ii) translate the Contribution into other languages, create adaptations, reprints, include within collections and create summaries, extracts and/or, abstracts of the Contribution, (iii) create any other derivative work(s) based on the Contribution, (iv) to exploit all subsidiary rights in the Contribution, (v) the inclusion of electronic links from the Contribution to third party material where-ever it may be located; and, (vi) licence any third party to do any or all of the above. Contributorship: SB was responsible for designing the study, facilitating data extraction, supervising data analysis and writing of the first draft of the paper; MB analysed the data; SB, GJM and DP conceived of the research idea and GJM was responsible for overall supervision. All authors contributed to the writing of the final draft of the paper. SB is the guarantor of this paper. Ethics: This research proposal was approved by the Privacy Advisory Committee of the Information and Services Division NHS Scotland and the steering group of the Aberdeen Maternity and Neonatal Databank. Formal ethical approval was not considered necessary by North of Scotland Research Ethics Service as only anonymised data were analysed in this study. Funding: This research was funded by the NHS Grampian Endowment Fund (Project no. 10/15) Role of sponsors: The University of Aberdeen acted as sponsors for this research project, but the findings and their interpretation in this study are the authors’ own. Independence of authors from funders: All authors were employed by the University of Aberdeen at the time of conducting this research and are independent from the funders.

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Abstract Objective: To investigate maternal and perinatal risk factors for childhood cancer.

Study Design: Case control analysis of linked records from the Aberdeen Maternity and

Neonatal Databank with the Scottish Cancer Registry and the General Registry of Births and

Deaths in Scotland was carried out.

Setting: Aberdeen, Scotland

Participants: Cases (n=176) comprised children diagnosed with cancer under 15 years or

recorded as having died of cancer. Four controls per case were matched by age and gender.

Risk factors tested: Maternal age, BMI, social class, marital status and smoking as well as

preeclampsia, antepartum haemorrhage and previous miscarriage, gestational age,

birthweight, and Apgar scores were compared between groups to test for association with

cancer. Odds ratios with 95% Confidence Intervals were calculated using conditional logistic

regression in both univariable and multivariable models.

Results: Of the maternal characteristics tested, mother’s age at delivery {cases mean

28.9(S.D.5.6) years versus controls mean 30.2(S.D4.6), p = 0.002} and smoking status

(38.6% smokers among cases, 29.7% among controls, p=0.034) were found to be different

between groups. Of the perinatal factors tested, low Apgar score at 5 minutes (AOR 4.59,

95% CI 1.52, 13.87) and delivery by caesarean section (AOR 1.95, 95% CI 1.30, 2.92)

showed statistically significant associations with childhood cancer in the multivariable model.

Conclusions: Younger maternal age, maternal smoking, delivery by caesarean section and

low Apgar score at 5 minutes were independently associated with increased risk of

childhood cancer. The association with caesarean delivery may be mediated through

epigenetic mechanism and warrants further investigation. These general findings should be

interpreted with caution as this study did not have the power to detect any association with

individual diagnostic categories of childhood cancer.

Key words: childhood cancer, perinatal risk factors, smoking, caesarean delivery

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Introduction:

Childhood cancer has been increasing in Scotland. A published report estimates that its

incidence has risen from an age standardised rate of 120 cases per million population in the

time period 1983 to 1987 to 161 cases per million in the period 2003 -20071.108.3 per million

child-years in 1976 to 160.6 per million child-years in 20071. The reason for this increasing

trend remains unexplained as the etiopathogenesis of childhood cancer is poorly

understood. As most present in the first few years of life, epidemiologists hypothesize that

prenatal and perinatal exposures may have a part to play in its pathogenesis. The evidence

surrounding this is however, conflicting. While some researchers have found associations of

younger maternal age at delivery2 maternal anaemia3,4, previous history of miscarriage2,5,6

maternal overweight7, and smoking8, with some childhood cancers, others have found no

such associations9-11. Fetal growth is perhaps the most investigated perinatal risk factor for

childhood cancer7,12,13 ; but the authors report conflicting results. While specific central

nervous system tumours have been found to be associated with intrauterine growth

restriction, the overall risk was small12. Therefore, apart from the associations with Down’s

syndrome and in utero exposure to radiation, research into the maternal and perinatal risk

factors has remained inconsistent, the results limited by small sample sizes and recall or

reporting bias.

Our objective was therefore to investigate maternal and perinatal risk factors for childhood

cancer, specifically to examine the effects of intrauterine growth restriction, preterm birth and

birth asphyxia on the development of childhood cancer in the offspring, taking advantage of

the opportunities offered by record linkage of a cancer registry with a local birth register.

Methods:

Data Sources:

The Aberdeen Maternity and Neonatal Databank (AMND) holds data for all Aberdeen City

births from 1950 to the present, and includes all reproductive events to women resident in a

defined geographical area with a relatively stable population. The AMND records all births

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occurring at the Aberdeen Maternity Hospital, the only maternity hospital serving the

population of Aberdeen city and district. The exposure variables in terms of potential

maternal and perinatal risk factors were derived from the AMND. The Scottish Cancer

Registry has been in existence since 1951 and was complete up to 2010, at the time of the

present analysis. The cases of childhood cancer were identified from this register.

Data Linkage:

All children born between 1993 and 2006 were identified from the AMND. Their records were

linked to the Cancer Registry in Scotland (SMR 06) and the General Registry of Births and

Deaths in Scotland (GRO-S), using deterministic matching. The linkage was carried out by

data analysts from the Information and Services Division of NHS Scotland using Community

Health Index (CHI) numbers. The CHI number is a number unique to all individuals

registered with a general practice in Scotland and recorded in both databases used in this

study. In a small proportion of cases where CHI number was not available (6%), probabilistic

matching using surname, date of birth and postcode was used. After data linkage, all

identifying information, including CHI numbers were removed and an anonymised dataset

was provided for analysis.

Study design:

A case control study design was employed. Cases comprised all children identified as above

from the AMND who were diagnosed with cancer under 15 years of age in Scotland as

recorded in the Scottish Cancer Registry or recorded as having died of cancer. Controls

were selected from the pool of children not diagnosed as having cancer, matched by age

and gender using four controls per case.

Twins and multiple births were excluded as were stillbirths and early neonatal deaths. As

Down’s syndrome is known to be associated with a higher risk of Acute Lymphoblastic

Leukaemia (ALL) as well as Myeloid Leukaemia of Down’s syndrome, all cases of diagnosed

Down’s syndrome were excluded. Moreover, those children who had died of non-cancer

causes prior to their 15th birthday, as identified from GRO-S were also excluded.

Exposure and outcome variables used in the analysis:

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Maternal sociodemographic factors such as age at delivery, body mass index (BMI),

Registrar General’s occupation-based social class, marital status, previous history of

miscarriage and smoking habits were extracted from the AMND. Any complications recorded

during the index pregnancy such as preeclampsia, gestational hypertension, and antepartum

haemorrhage as well as mode of delivery, gestational age at delivery, birthweight,

Standardised Birthweight Score14, and Apgar score at 1 and 5 minutes were also extracted.

Data extractors were blind to the case-control status of the individual children.

The outcome variables obtained from the Cancer Registry in Scotland were in the form of a

binary variable (yes/no) indicating whether or not a cancer record was present and if

present, the site of cancer given as International Classification of Diseases (ICD) codes.

Similarly, death records with up to 10 different causes of death given by ICD codes were

obtained from linking with GRO-S.

Statistical Analysis:

All analyses were conducted using STATA version 11 (STATA Corp, Texas, USA).

Maternal baseline characteristics were compared between children diagnosed with cancer

and controls using independent two-sample t-tests and chi-square tests. Maternal

complications such as gestational hypertension, pre-eclampsia, antepartum haemorrhage

and previous history of miscarriage were compared between the cases and controls using

univariate conditional regression to calculate odds ratios (OR) with 95% confidence intervals

(CI). Similarly, perinatal factors like gestation at birth, birth weight, intrauterine growth

restriction measured by standardised birthweight score, Apgar score at 1 and 5 minutes

were also tested in univariate models for any association with childhood cancer. Then a

multivariable conditional logistic regression model was fitted that included as independent

variables all risk factors tested on univariate analysis. The possibility of cancer subgroup

analysis was considered according to the International Classification of Childhood Cancer,

but the number of cases in each subgroup was too small to warrant this.

Missing data:

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Apart from the variables describing maternal baseline characteristics, the other risk factors

did not have any missing values. There were 18 controls and 1 case with missing smoking

data. The multivariable model was repeated including and excluding the individuals with

missing information. We used two methodological approaches to handle this - listwise

deletion – ie, not including any group where one person in that group has missing data, and

imputation by creation of a missing value (999) so that all cases and controls were included

in the analyses. The odds ratios obtained by both methods are presented.

Ethical considerations:

Approval to carry out the study was obtained from the AMND steering committee and the

Privacy Advisory Committee for the Information Services Division of National Health

Services, Scotland. As the study involved the analysis of routinely collected anonymised

data, formal ethical approval was not required as declared by the North of Scotland

Research Ethics Service.

Results:

There were 62375 deliveries between 1993 and 2006 as identified from the AMND. After

excluding Down’s syndrome cases, twins and multiple births, stillbirths and early neonatal

deaths, there were 60117 children eligible for linkage with the Cancer Registry. It was

possible to link 43591 of these children to the cancer and GRO-S databases. Amongst the

children with linked data, 106 had died of non-cancer causes before they reached the age of

15 and were therefore excluded from the analysis. Of the remainder, 176 were found to have

a record in the Cancer Registry, giving a cumulative incidence rate of childhood cancer up to

15 years of 4.05 per 1000 deliveries. They constituted the cases for the analysis and were

matched in 1:4 ratio by year of birth and sex from the pool of remaining children without any

records of cancer to obtain 704 controls. As D40, D44, D47 and D48 codes in ICD-10 do not

correspond to cancer diagnosis in International Classification of Childhood Cancer (ICCC),

the analyses were repeated excluding these codes.

Formatted: Font: (Default) Arial, 11 pt

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Maternal baseline characteristics were compared between cases and matched controls in

Table 1. Of the maternal characteristics tested, mother’s age at delivery (cases mean 28.9

years, s.d. 5.6; controls mean 30.2, s.d. 4.6; p = 0.002) and smoking status (38.6% current

or ex-smokers among cases, 29.7% among controls, p=0.022) were found to be significantly

different between the two groups.

Table 2 presents the unadjusted odds ratios with 95% confidence intervals for all the

perinatal potential risk factors for childhood cancer. Of the factors tested, preterm birth {OR

2.23(1.31 – 3.79)}; low birth weight {OR 1.87(1.03 – 3.39)}, low Apgar score at 5 minutes

{OR 5.01(1.73 – 14.54)} and delivery by caesarean section {OR 1.77(1.23 – 2.56)} were

found to be statistically significant. Subsequently, these factors were adjusted for maternal

age at delivery and smoking. As the maternal smoking variable had some missing data, we

handled this using two approaches – listwise deletion and imputation of a missing value.

After these adjustments, low birthweight no longer remained significant, but the other

associations were strengthened.

After conducting the univariate analyses multivariable models were fitted including maternal

age, smoking status, preeclampsia, placenta praevia, preterm birth, low birthweight, low

Apgar at 5 minutes and delivery by caesarean as independent variables (results in Table 3).

Similar to the previous analyses, we used two methods of listwise deletion and imputation of

the missing value to adjust for smoking status. Of the perinatal factors tested, Apgar score

below 7 at 5 minutes {AOR 3.91, 95% CI 1.13 – 13.61(listwise deletion); AOR 4.59, 95% CI

1.52, 13.87 (imputation)} and delivery by caesarean section {AOR 2.11, 95% CI 1.38, 3.23

(listwise deletion); AOR 1.95, 95% CI 1.30, 2.92 (imputation)} showed statistically significant

associations with childhood cancer in both multivariable models adjusted for maternal age,

smoking and other factors simultaneously included in the models. Preterm birth (delivery

before 37 completed weeks of gestation) and low birth weight defined as a birth weight

below 2500g, showed a significant association in the univariate analysis, but these

associations were no longer significant in the multivariable model. The associations were not

statistically significant on univariate or multivariable analysis between the risk of childhood

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cancer and hypertensive disorders, antepartum haemorrhage, previous history of

miscarriage or IUGR. Unlike the Apgar score at 5 minutes, the score at 1 minute did not

show any association with childhood cancer.

We further investigated the types of preterm delivery (spontaneous or induced) and

caesarean section (elective or emergency) as risk factors for childhood cancer and found

that both spontaneous and induced preterm delivery were significantly associated in the

adjusted model but only delivery by emergency caesarean section remained significant on

subgroup analysis (AOR 1.43, 95% CI 1.20, 2.18). Further, we found that the commonest

indication for caesarean delivery in the babies who were subsequently diagnosed with

cancer was fetal distress (data not shown).

Table 4 shows the distribution of cancer sites in the 176 cases. As this table shows, the

commonest sites were the brain and haemopoietic organs, especially leukaemia, but the

numbers in the subgroups were too small to allow any meaningful analysis.

Discussion:

We aimed to study the maternal and perinatal risk factors at the time of birth associated with

the diagnosis of childhood cancer using record linkage between two high quality registers in

Scotland. We found a positive association between younger maternal age at delivery and

maternal smoking with childhood cancer. In addition, preterm birth before 37 weeks of

gestation, Apgar score below 7 at 5 minutes and delivery by emergency caesarean section

showed statistically significant associations with childhood cancer the last two of which

remained significant in the adjusted models.

Childhood cancer is a rare condition. Case control studies are therefore the most efficient

epidemiological study design to study several risk factors at the time of birth. Cancer

registries across the world have been utilised to identify cases, but finding appropriate

controls remains problematic. Moreover, data collections regarding exposures by means of

interviews or questionnaires are subject to recall and reporting bias. More recently, linkage

of birth registers with cancer registries has been utilised to design large scale cohort studies.

However, the routine data collection is liable to lack sufficiently detailed data regarding

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exposure and potential confounding factors. We have tried to minimise these problems by

linking two high quality registers in Scotland. Previous validation projects have shown these

databases to be 100% complete and over 97% accurate15. Detailed and contemporaneous

recording of obstetric data in the AMND eliminated recall and reporting bias. The large

number of social and demographic variables recorded in the AMND enabled incorporation of

most potential covariates in the analysis. Despite these strengths to our study design, we

were limited by the small number of cases and it is possible that we did not have sufficient

power to detect some weak associations reported previously in the literature. Maternal and

perinatal risk factors for childhood cancer appear to differ by the site of cancer in the

published literature. The number of cases according to site specific cancer diagnosis was

too small in our sample to allow any subgroup analysis. Further, morphology codes were not

available for us to carry out more appropriate groupings of childhood cancers. This, coupled

with the fact that we had to conduct our analyses on all cancers would have made it less

likely for us to find associations that exist with site specific cancers. This could be a major

limitation of the current analysis. There was a single case of cancer that occurred within the

first year of delivery. It is possible that this could be the result of the cancer being already

present at birth.

The association of parental age with the diagnosis of cancer in general as well as in specific

sites has been studied before. Johnson et al16 in a pooled analysis of register linkage data

from several US states, found that the risk of childhood cancer increased with increasing

maternal age, while paternal age appeared to have no effect on the risk. On the other hand

several other studies, similar to the current analysis have shown that younger maternal age

was associated with increased childhood cancer risk2,17. There could be several

explanations for the disparate findings. In a register linkage study carried out in Sweden18,19,

researchers found that advancing maternal age was positively associated with childhood

cancer risk but only in a historical cohort. This association disappeared in a more recent

cohort of women although the reasons for this are unknown. Moreover, Schutz20 suggests

that the association of lower maternal age at the time of delivery with leukaemia in the

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offspring could be explained by non-response bias, although this is not applicable to the

present study.

The relationship between maternal smoking and childhood cancer in the offspring is complex

and controversial. While Sorahan et al21 - 23 and Edraki24 found an increased overall risk of

childhood cancer with paternal cigarette smoking, there did not appear to be an association

with maternal smoking after adjusting for birthweight. Further, Pang et al9 did not find

evidence of smoking as a risk factor for childhood cancer after adjusting for parental age.

Similar associations were reported by Chang et al25 with regard to Acute Lymphoblastic

Leukaemia (ALL). The evidence appears to indicate that neonatal passive smoking plays a

more important role than in utero transfer of maternal smoke related toxins, although we

cannot rule out the possibility of an association between maternal smoking and site-specific

cancers26,27. For the current analysis, we did not have access to data on paternal smoking

habits and the association seen with maternal smoking could be due to this variable acting

as proxy for paternal smoking.

Other associations noted in this study have been reported before – preterm birth28, and low

Apgar score2,28. Li et al found a 46% increased risk of childhood cancer in infants who had a

low 5 minute Apgar score29. Birthweight has received a lot of attention as a risk factor for

childhood cancer. While brain tumours and retinoblastoma appear to be associated with high

birthweight3029 - 312 others have found hepatoblastomas7,323 and gliomas334 to be associated

with very low birthweight infants. Schmidt28 et al observed a U-shaped relationship between

birthweight and cancer risk, while Podvin354 found birthweight adjusted for gestational age to

be a better predictor than birthweight alone for the diagnosis of ALL, lending support to our

findings. It is however, important to note, that we did not find an association with intrauterine

growth restriction as measured by the z-score or standardized birthweight score. Dorak et

al36 noted an association between birthweight and a diagnosis of ALL which was gender

dependent, showing a non-linear association in boys.

Few studies have assessed mode of delivery, specifically caesarean delivery, as a possible

risk factor for the development of childhood cancer. Those that have done, have found a

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weak to moderate association 3,7,10,,365,376,37 between caesarean delivery and subsequent risk

of developing ALL. Several hypotheses can be developed regarding the biological

mechanism underpinning this association. First, caesarean delivery is likely to be a marker

of adverse pregnancy and delivery events – indeed, our finding of increased emergency

caesarean rates indicated by fetal distress seems to support this hypothesis. However, the

association remained and actually became stronger, after adjusting for most other possible

pregnancy complications. It was customary to use 100% oxygen to resuscitate babies born

by caesarean section in the past. It is possible that this could have played a role in the

subsequent development of cancer. The last explanation involves epigenetic modulations at

birth. Schlinzig et al39387 have demonstrated altered DNA-methylation in cord white blood

cells after caesarean delivery and suggested that this may be the basis of increased risk of

asthma, diabetes and ALL seen in infants born by caesarean section.

The association of caesarean delivery with childhood cancer seen in this analysis should be

treated with caution given the small numbers of childhood cancer cases in the study., is

likely to have far reaching consequences for obstetric practice. The recent NICE

guidelines40398 recommends caesarean delivery on maternal request., further evidence to

support a link between caesarean section and subsequent cancer in the offspring would

seriously question the ethics of such practice. Although, we have to remember that the

majority of the caesarean deliveries seen in the cases of childhood cancer in the current

analysis were emergency procedures with strong indications such as fetal distress. Our

finding of the strong association of childhood cancer with caesarean delivery certainly

warrants further research using record linkage of larger cohorts or prospective follow up of

birth cohorts. From the point of view of Public Health interventions, the only other modifiable

risk factor appears to be parental smoking. Several population based lifestyle interventions

are already underway to reduce the prevalence of smoking in pregnancy.

Conclusion: We found a positive association between younger maternal age at delivery and

maternal smoking with childhood cancer. In addition, preterm birth, low Apgar score at 5

minutes and delivery by caesarean section showed associations with childhood cancer,

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which remained significant even after controlling for various covariates. While maternal age

and smoking, preterm birth and low Apgar Score have all been previously shown to be

associated with childhood cancer, delivery by caesarean section is a novel finding and

warrants further investigation in larger cohorts. We also propose a mechanistic study

exploring epigenetic changes associated with caesarean delivery as the underlying

mechanism linking the two conditions.

What is already known on this topic

Extremes of maternal age at delivery, parental smoking, preterm birth and low birthweight

have all been reported to be risk factors for childhood cancer.

What this study adds

The large effect of delivery by caesarean section on the increased risk of childhood cancer is

a novel finding in this study.

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22. Sorahan T, McKinney PA, Mann JR, et al. Childhood cancer and parental use of

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Table 1. Comparison of maternal baseline characteristics between case children and control children

Characteristics Cases Controls p-

value

Age at delivery (mean, s.d.) 28.9 (5.6) 30.2 (4.6) 0.002

Maternal social class

Manual 26 (14.8%) 79 (11.2%)

0.187 Non-Manual 62 (35.2%) 295 (41.9%)

Single/widowed 87 (49.4%) 325 (46.2%)

Missing 1 (0.6%) 5 (0.7%)

Paternal social class

Paternal Manual 71 (40.3%) 329 (46.7%)

0.193 Paternal Non-manual 47 (26.7%) 183 (26.0%)

Single/widowed Maternal non-manual 57 (32.4%) 184 (26.1%)

Missing 1 (0.6%) 8 (1.1%)

Marital status

Single/Widowed/Divorced/Separated/Cohabiting 62 (35.2%) 222 (31.5%) 0.324

Married 113 (64.2%) 482 (68.4%)

Missing 1 (0.6%) 0 (0%)

BMI (mean, s.d.) (Missing cases = 12, Missing controls = 39) 25.2 (5.1) 25.5 (5.1) 0.407

Smoking

Non-smoker 107 (60.8%) 477 (67.8%) 0.034

Smoker/ex-smoker 68 (38.6%) 209 (29.7%)

Missing 1 (0.6%) 18 (2.6%)

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Table 2. Comparison of perinatal factors between cases and controls with statistically significant odds ratios shown in bold

Perinatal factors Cases N=176 Controls N=704 Unadjusted odds ratio

(95% CI)

Age and smoking adjusted

odds ratio (95% CI) – listwise

deletion

Age and smoking adjusted

odds ratio (95% CI) –

imputation of missing value

Preeclampsia 11 (6.3%) 23 (3.3%) 1.98 (0.94-4.18) 1.94 (0.88-4.28) 1.92 (0.91-4.09)

Gestational hypertension 19 (10.8%) 71 (10.1%) 1.09 (0.62-1.89) 1.21 (0.67-2.17) 1.13 (0.64-2.01)

Placenta praevia 3 (1.7%) 4 (0.6%) 3.00 (0.67-13.40) 3.46 (0.76-15.65) 3.45 (0.76-15.62)

Abruption 1 (0.6%) 4 (0.6%) 1.00 (0.11-8.95) 1.31 (0.14-12.66) 1.04 (0.12-9.41)

Other APH 19 (10.8%) 77 (10.9%) 0.99 (0.58-1.68) 0.98 (0.56-1.72) 0.96 (0.56-1.65)

Previous miscarriage 18 (10.2%) 103 (14.6%) 0.67 (0.39-1.13) 0.83 (0.48-1.43) 0.70 (0.41-1.19)

Preterm birth 24 (13.6%) 47 (6.7%) 2.23 (1.31-3.79) 2.09 (1.16-3.76) 2.23 (1.29-3.85)

Low birthweight 17 (9.7%) 38 (5.4%) 1.87 (1.03-3.39) 1.81 (0.94-3.45) 1.78 (0.97-3.28)

Low apgar at 1 minute 30 (17.1%) 107 (15.4%) 1.14 (0.73-1.78) 1.14 (0.71-1.84) 1.15 (0.73-1.81)

Low apgar at 5 minutes 8 (4.6%) 7 (1.0%) 5.01 (1.73-14.54) 4.91 (1.46-16.51) 5.70 (1.93-16.78)

Delivery by caesarean 55 (31.3%) 143 (20.4%) 1.77 (1.23-2.56) 2.25 (1.50-3.36) 2.07 (1.41-3.05)

Instrumental delivery 26 (14.8%) 144 (20.5%) 0.66 (0.41-1.04) 0.68 (0.41-1.13) 0.67 (0.42-1.08)

Intrauterine Growth

Restriction 23 (13.4%) 71 (10.3%) 1.41 (0.85-2.36) 1.20 (0.68-2.12) 1.35 (0.80-2.23)

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Table 3. Odds ratios from multivariable model

*All variables adjusted for maternal age and smoking and for other variables in the model

Statistically significant odds ratios are shown in bold.

Perinatal factors OR (95%CI) from multivariable model – listwise deletion* OR (95% CI) from multivariable model – imputation of missing

value*

Preeclampsia 1.56 (0.68-3.59) 1.55 (0.70-3.44)

Placenta praevia 1.64 (0.32-8.34) 1.65 (0.32-8.43)

Preterm birth 1.60 (0.76-3.37) 1.85 (0.92-3.72)

Low birthweight 1.00 (0.44-2.28) 0.90 (0.41-1.97)

Low apgar at 5 minutes 3.91 (1.13-13.61) 4.59 (1.52-13.87)

Delivery by caesarean 2.11 (1.38-3.23) 1.95 (1.30-2.92)

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Table 4. Distribution of sites of cancer

Cancer site No. %

C22 – Liver and intrahepatic bile ducts 2 1.14

C34 – Bronchus and lung 2 1.14

C41 – Bone and articular cartilage of other and unspecified sites 10

5.68

C49 – Other connective and soft tissue 7

3.98

C52 – Vagina 5 2.84

C56 – Ovary 3 1.70

C62 – Testis 12 6.82

C64 – Kidney except renal pelvis 7 3.98

C69 – Eye and adnexa 6 3.41

C71 – Brain 27

15.34

C72 – Spinal cord, cranial nerves, other CNS 3 1.70

C74 – Adrenal gland 6

3.41

C75 – Other endocrine glands and related structures 4

2.27

C76 – Other and ill-defined sites 2 1.14

C83 – Diffuse non-Hodgkin’s lymphoma 3 1.70

C85 – Other and unspec. non-Hodgkin’s 2 1.14

C91 – Lymphoid Leukaemia 37 21.02

C92 – Myeloid leukaemia 10 5.68

C94 – Other leukaemias of specified cell type 2 1.14

D32 - Meninges 3 1.70

D40 – Uncertain/uknown bhvr male genital 2 1.14

D43 – Uncertain/unknown bhvr. brain and CNS 2 1.14

D44 – Uncertain/unknown bhvr. endocrine 1 0.57

D47 – Uncertain/uknown bhvr. of lymphoid, haematopoietic and related tissue 9

5.11

D48 – Uncertain/unknown bhvr. unknown sites 9 5.11

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Maternal and Perinatal Risk Factors for Childhood Cancer

Sohinee Bhattacharya1* Marcus Beasley1 Dong Pang2 Gary J Macfarlane1

1Epidemiology Group, Division of Applied Health Sciences, University of Aberdeen 2 Institute of Health Research, University of Bedfordshire, Luton

*Corresponding author: Sohinee Bhattacharya Dugald Baird Centre for Research on Women’s Health Aberdeen Maternity Hospital Aberdeen AB25 2ZL Tel: +44 1224 438441 e-mail: [email protected] Running title: Risk factors for childhood cancer

Conflict of Interest: All authors have completed the Unified Competing Interest form at http://www.icmje.org/coi_disclosure.pdf and declare: NHS Grampian Endowment funded the study; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, a worldwide licence to the Publishers and its licensees in perpetuity, in all forms, formats and media (whether known now or created in the future), to (i) publish, reproduce, distribute, display and store the Contribution, (ii) translate the Contribution into other languages, create adaptations, reprints, include within collections and create summaries, extracts and/or, abstracts of the Contribution, (iii) create any other derivative work(s) based on the Contribution, (iv) to exploit all subsidiary rights in the Contribution, (v) the inclusion of electronic links from the Contribution to third party material where-ever it may be located; and, (vi) licence any third party to do any or all of the above. Contributorship: SB was responsible for designing the study, facilitating data extraction, supervising data analysis and writing of the first draft of the paper; MB analysed the data; SB, GJM and DP conceived of the research idea and GJM was responsible for overall supervision. All authors contributed to the writing of the final draft of the paper. SB is the guarantor of this paper. Ethics: This research proposal was approved by the Privacy Advisory Committee of the Information and Services Division NHS Scotland and the steering group of the Aberdeen Maternity and Neonatal Databank. Formal ethical approval was not considered necessary by North of Scotland Research Ethics Service as only anonymised data were analysed in this study. Funding: This research was funded by the NHS Grampian Endowment Fund (Project no. 10/15) Role of sponsors: The University of Aberdeen acted as sponsors for this research project, but the findings and their interpretation in this study are the authors’ own. Independence of authors from funders: All authors were employed by the University of Aberdeen at the time of conducting this research and are independent from the funders. Data sharing: There is no additional data available for sharing

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Abstract Objective: To investigate maternal and perinatal risk factors for childhood cancer.

Study Design: Case control analysis of linked records from the Aberdeen Maternity and

Neonatal Databank with the Scottish Cancer Registry and the General Registry of Births and

Deaths in Scotland was carried out.

Setting: Aberdeen, Scotland

Participants: Cases (n=176) comprised children diagnosed with cancer under 15 years or

recorded as having died of cancer. Four controls per case were matched by age and gender.

Risk factors tested: Maternal age, BMI, social class, marital status and smoking as well as

preeclampsia, antepartum haemorrhage and previous miscarriage, gestational age,

birthweight, and Apgar scores were compared between groups to test for association with

cancer. Odds ratios with 95% Confidence Intervals were calculated using conditional logistic

regression in both univariable and multivariable models.

Results: Of the maternal characteristics tested, mother’s age at delivery {cases mean

28.9(S.D.5.6) years versus controls mean 30.2(S.D4.6), p = 0.002} and smoking status

(38.6% smokers among cases, 29.7% among controls, p=0.034) were found to be different

between groups. Of the perinatal factors tested, low Apgar score at 5 minutes (AOR 4.59,

95% CI 1.52, 13.87) and delivery by caesarean section (AOR 1.95, 95% CI 1.30, 2.92)

showed statistically significant associations with childhood cancer in the multivariable model.

Conclusions: Younger maternal age, maternal smoking, delivery by caesarean section and

low Apgar score at 5 minutes were independently associated with increased risk of

childhood cancer. The association with caesarean delivery may be mediated through

epigenetic mechanism and warrants further investigation.

Key words: childhood cancer, perinatal risk factors, smoking, caesarean delivery

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Introduction:

Childhood cancer has been increasing in Scotland. A published report estimates that its

incidence has risen from 108.3 per million child-years in 1976 to 160.6 per million child-years

in 20071. The reason for this increasing trend remains unexplained as the etiopathogenesis

of childhood cancer is poorly understood. As most present in the first few years of life,

epidemiologists hypothesize that prenatal and perinatal exposures may have a part to play in

its pathogenesis. The evidence surrounding this is however, conflicting. While some

researchers have found associations of younger maternal age at delivery2 maternal

anaemia3,4, previous history of miscarriage2,5,6 maternal overweight7, and smoking8, with

some childhood cancers, others have found no such associations9-11. Fetal growth is

perhaps the most investigated perinatal risk factor for childhood cancer7,12,13 ; and yet the

authors report conflicting results. While specific central nervous system tumours have been

found to be associated with intrauterine growth restriction, the overall risk was small12.

Therefore, apart from the associations with Down’s syndrome and in utero exposure to

radiation, research into the maternal and perinatal risk factors has remained inconsistent, the

results limited by small sample sizes and recall or reporting bias.

Our objective was therefore to investigate maternal and perinatal risk factors for childhood

cancer, specifically to examine the effects of intrauterine growth restriction, preterm birth and

birth asphyxia on the development of childhood cancer in the offspring, taking advantage of

the opportunities offered by record linkage of a cancer registry with a local birth register.

Methods:

Data Sources:

The Aberdeen Maternity and Neonatal Databank (AMND) holds data for all Aberdeen City

births from 1950 to the present, and includes all reproductive events to women resident in a

defined geographical area with a relatively stable population. The exposure variables in

terms of potential maternal and perinatal risk factors were derived from the AMND. The

Scottish Cancer Registry has been in existence since 1951 and was complete up to 2010, at

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the time of the present analysis. The cases of childhood cancer were identified from this

register.

Data Linkage:

All children born between 1993 and 2006 were identified from the AMND. Their records were

linked to the Cancer Registry in Scotland (SMR 06) and the General Registry of Births and

Deaths in Scotland (GRO-S), using deterministic matching. The linkage was carried out by

data analysts from the Information and Services Division of NHS Scotland using Community

Health Index (CHI) numbers. The CHI number is a number unique to all individuals

registered with a general practice in Scotland and recorded in both databases used in this

study. In a small proportion of cases where CHI number was not available, probabilistic

matching using surname, date of birth and postcode was used. After data linkage, all

identifying information, including CHI numbers were removed and an anonymised dataset

was provided for analysis.

Study design:

A case control study design was employed. Cases comprised all children identified as above

from the AMND who were diagnosed with cancer under 15 years of age in Scotland as

recorded in the Scottish Cancer Registry or recorded as having died of cancer. Controls

were selected from the pool of children not diagnosed as having cancer, matched by age

and gender using four controls per case.

Twins and multiple births were excluded as were stillbirths and early neonatal deaths. As

Down’s syndrome is known to be associated with a higher risk of Acute Lymphoblastic

Leukaemia (ALL), all cases of diagnosed Down’s syndrome were excluded. Moreover, those

children who had died of non-cancer causes prior to their 15th birthday, as identified from

GRO-S were also excluded.

Exposure and outcome variables used in the analysis:

Maternal sociodemographic factors such as age at delivery, body mass index (BMI),

Registrar General’s occupation-based social class, marital status, previous history of

miscarriage and smoking habits were extracted from the AMND. Any complications recorded

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during the index pregnancy such as preeclampsia, gestational hypertension, and antepartum

haemorrhage as well as mode of delivery, gestational age at delivery, birthweight,

Standardised Birthweight Score14, and Apgar score at 1 and 5 minutes were also extracted.

Data extractors were blind to the case-control status of the individual children.

The outcome variables obtained from the Cancer Registry in Scotland were in the form of a

binary variable (yes/no) indicating whether or not a cancer record was present and if

present, the site of cancer given as International Classification of Diseases (ICD) codes.

Similarly, death records with up to 10 different causes of death given by ICD codes were

obtained from linking with GRO-S.

Statistical Analysis:

All analyses were conducted using STATA version 11 (STATA Corp, Texas, USA).

Maternal baseline characteristics were compared between children diagnosed with cancer

and controls using independent two-sample t-tests and chi-square tests. Maternal

complications such as gestational hypertension, pre-eclampsia, antepartum haemorrhage

and previous history of miscarriage were compared between the cases and controls using

univariate conditional regression to calculate odds ratios (OR) with 95% confidence intervals

(CI). Similarly, perinatal factors like gestation at birth, birth weight, intrauterine growth

restriction measured by standardised birthweight score, Apgar score at 1 and 5 minutes

were also tested in univariate models for any association with childhood cancer. Then a

multivariable conditional logistic regression model was fitted that included as independent

variables all risk factors tested on univariate analysis. The possibility of cancer subgroup

analysis was considered according to the International Classification of Childhood Cancer,

but the number of cases in each subgroup was too small to warrant this.

Missing data:

Apart from the variables describing maternal baseline characteristics, the other risk factors

did not have any missing values. There were 18 controls and 1 case with missing smoking

data. The multivariable model was repeated including and excluding the individuals with

missing information. We used two methodological approaches to handle this - listwise

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deletion – ie, not including any group where one person in that group has missing data, and

imputation by attaching a value to the missing data so that all cases and controls were

included in the analysis. The odds ratios obtained by both methods are presented.

Ethical considerations:

Approval to carry out the study was obtained from the AMND steering committee and the

Privacy Advisory Committee for the Information Services Division of National Health

Services, Scotland. As the study involved the analysis of routinely collected anonymised

data, formal ethical approval was not required as declared by the North of Scotland

Research Ethics Service.

Results:

There were 62375 deliveries between 1993 and 2006 as identified from the AMND. After

excluding Down’s syndrome cases, twins and multiple births, stillbirths and early neonatal

deaths, there were 60117 children eligible for linkage with the Cancer Registry. It was

possible to link 43591 of these children to the cancer and GRO-S databases. Amongst the

children with linked data, 106 had died of non-cancer causes before they reached the age of

15 and were therefore excluded from the analysis. Of the remainder, 176 were found to have

a record in the Cancer Registry, giving a cumulative incidence rate of childhood cancer up to

15 years of 4.05 per 1000 deliveries. They constituted the cases for the analysis and were

matched in 1:4 ratio by year of birth and sex from the pool of remaining children without any

records of cancer to obtain 704 controls.

Maternal baseline characteristics were compared between cases and matched controls in

Table 1. Of the maternal characteristics tested, mother’s age at delivery (cases mean 28.9

years, s.d. 5.6; controls mean 30.2, s.d. 4.6; p = 0.002) and smoking status (38.6% current

or ex-smokers among cases, 29.7% among controls, p=0.022) were found to be significantly

different between the two groups.

Table 2 presents the unadjusted odds ratios with 95% confidence intervals for all the

perinatal potential risk factors for childhood cancer. Of the factors tested, preterm birth {OR

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2.23(1.31 – 3.79)}; low birth weight {OR 1.87(1.03 – 3.39)}, low Apgar score at 5 minutes

{OR 5.01(1.73 – 14.54)} and delivery by caesarean section {OR 1.77(1.23 – 2.56)} were

found to be statistically significant. Subsequently, these factors were adjusted for maternal

age at delivery and smoking. As the maternal smoking variable had some missing data, we

handled this using two approaches – listwise deletion and imputation of missing value. After

these adjustments, low birthweight no longer remained significant, but the other associations

were strengthened.

After conducting the univariate analyses multivariable models were fitted including maternal

age, smoking status, preeclampsia, placenta praevia, preterm birth, low birthweight, low

Apgar at 5 minutes and delivery by caesarean as independent variables (results in Table 3).

Similar to the previous analyses, we used two methods of listwise deletion and imputation of

missing value to adjust for smoking status. Of the perinatal factors tested, Apgar score below

7 at 5 minutes {AOR 3.91, 95% CI 1.13 – 13.61(listwise deletion); AOR 4.59, 95% CI 1.52,

13.87 (imputation)} and delivery by caesarean section {AOR 2.11, 95% CI 1.38, 3.23

(listwise deletion); AOR 1.95, 95% CI 1.30, 2.92 (imputation)} showed statistically significant

associations with childhood cancer in both multivariable models adjusted for maternal age,

smoking and other factors simultaneously included in the models. Preterm birth (delivery

before 37 completed weeks of gestation) and low birth weight defined as a birth weight

below 2500g, showed a significant association in the univariate analysis, but these

associations were no longer significant in the multivariable model. The associations were not

statistically significant on univariate or multivariable analysis between the risk of childhood

cancer and hypertensive disorders, antepartum haemorrhage, previous history of

miscarriage or IUGR. Unlike the Apgar score at 5 minutes, the score at 1 minute did not

show any association with childhood cancer.

We further investigated the types of preterm delivery (spontaneous or induced) and

caesarean section (elective or emergency) as risk factors for childhood cancer and found

that both spontaneous and induced preterm delivery were significantly associated in the

adjusted model but only delivery by emergency caesarean section remained significant on

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subgroup analysis (AOR 1.43, 95% CI 1.20, 2.18). Further, we found that the commonest

indication for caesarean delivery in the babies who were subsequently diagnosed with

cancer was fetal distress (data not shown).

Table 4 shows the distribution of cancer sites in the 176 cases. As this table shows, the

commonest sites were the brain and haemopoietic organs, especially leukaemia, but the

numbers in the subgroups were too small to allow any meaningful analysis.

Discussion:

We aimed to study the maternal and perinatal risk factors at the time of birth associated with

the diagnosis of childhood cancer using record linkage between two high quality registers in

Scotland. We found a positive association between younger maternal age at delivery and

maternal smoking with childhood cancer. In addition, preterm birth before 37 weeks of

gestation, Apgar score below 7 at 5 minutes and delivery by emergency caesarean section

showed statistically significant associations with childhood cancer the last two of which

remained significant in the adjusted models.

Childhood cancer is a rare condition. Case control studies are therefore the most efficient

epidemiological study design to study several risk factors at the time of birth. Cancer

registries across the world have been utilised to identify cases, but finding appropriate

controls remains problematic. Moreover, data collections regarding exposures by means of

interviews or questionnaires are subject to recall and reporting bias. More recently, linkage

of birth registers with cancer registries has been utilised to design large scale cohort studies.

However, the routine data collection is liable to lack sufficiently detailed data regarding

exposure and potential confounding factors. We have tried to minimise these problems by

linking two high quality registers in Scotland. Previous validation projects have shown these

databases to be 100% complete and over 97% accurate15. Detailed and contemporaneous

recording of obstetric data in the AMND eliminated recall and reporting bias. The large

number of social and demographic variables recorded in the AMND enabled incorporation of

most potential covariates in the analysis. Despite these strengths to our study design, we

were limited by the small number of cases and it is possible that we did not have sufficient

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power to detect some weak associations reported previously in the literature. Maternal and

perinatal risk factors for childhood cancer appear to differ by the site of cancer in the

published literature. The number of cases according to site specific cancer diagnosis was

too small in our sample to allow any subgroup analysis. Further, morphology codes were not

available for us to carry out more appropriate groupings of childhood cancers. This, coupled

with the fact that we had to conduct our analyses on all cancers would have made it less

likely for us to find associations that exist with site specific cancers. This could be a major

limitation of the current analysis.

The association of parental age with the diagnosis of cancer in general as well as in specific

sites has been studied before. Johnson et al16 in a pooled analysis of register linkage data

from several US states, found that the risk of childhood cancer increased with increasing

maternal age, while paternal age appeared to have no effect on the risk. On the other hand

several other studies, similar to the current analysis have shown that younger maternal age

was associated with increased childhood cancer risk2,17. There could be several

explanations for the disparate findings. In a register linkage study carried out in Sweden18,19,

researchers found that advancing maternal age was positively associated with childhood

cancer risk but only in a historical cohort. This association disappeared in a more recent

cohort of women although the reasons for this are unknown. Moreover, Schutz20 suggests

that the association of lower maternal age at the time of delivery with leukaemia in the

offspring could be explained by non-response bias, although this is not applicable to the

present study.

The relationship between maternal smoking and childhood cancer in the offspring is complex

and controversial. While Sorahan et al21 - 23 and Edraki24 found an increased overall risk of

childhood cancer with paternal cigarette smoking, there did not appear to be an association

with maternal smoking after adjusting for birthweight. Further, Pang et al9 did not find

evidence of smoking as a risk factor for childhood cancer after adjusting for parental age.

Similar associations were reported by Chang et al25 with regard to Acute Lymphoblastic

Leukaemia (ALL). The evidence appears to indicate that neonatal passive smoking plays a

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more important role than in utero transfer of maternal smoke related toxins, although we

cannot rule out the possibility of an association between maternal smoking and site-specific

cancers26,27. For the current analysis, we did not have access to data on paternal smoking

habits and the association seen with maternal smoking could be due to this variable acting

as proxy for paternal smoking.

Other associations noted in this study have been reported before – preterm birth28, and low

Apgar score2,28. Birthweight has received a lot of attention as a risk factor for childhood

cancer. While brain tumours and retinoblastoma appear to be associated with high

birthweight29 - 31 others have found hepatoblastomas7,32 and gliomas33 to be associated with

very low birthweight infants. Schmidt28 et al observed a U-shaped relationship between

birthweight and cancer risk, while Podvin34 found birthweight adjusted for gestational age to

be a better predictor than birthweight alone for the diagnosis of ALL, lending support to our

findings. It is however, important to note, that we did not find an association with intrauterine

growth restriction as measured by the z-score or standardized birthweight score.

Few studies have assessed mode of delivery, specifically caesarean delivery, as a possible

risk factor for the development of childhood cancer. Those that have done, have found a

weak to moderate association7,35,36 between caesarean delivery and subsequent risk of

developing ALL. Several hypotheses can be developed regarding the biological mechanism

underpinning this association. First, caesarean delivery is likely to be a marker of adverse

pregnancy and delivery events – indeed, our finding of increased emergency caesarean

rates indicated by fetal distress seems to support this hypothesis. However, the association

remained and actually became stronger, after adjusting for most other possible pregnancy

complications. It was customary to use 100% oxygen to resuscitate babies born by

caesarean section in the past. It is possible that this could have played a role in the

subsequent development of cancer. The last explanation involves epigenetic modulations at

birth. Schlinzig et al37 have demonstrated altered DNA-methylation in cord white blood cells

after caesarean delivery and suggested that this may be the basis of increased risk of

asthma, diabetes and ALL seen in infants born by caesarean section.

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The association of caesarean delivery with childhood cancer seen in this analysis, is likely to

have far reaching consequences for obstetric practice. The recent NICE guidelines38

recommends caesarean delivery on maternal request, further evidence to support a link

between caesarean section and subsequent cancer in the offspring would seriously question

the ethics of such practice. Although, we have to remember that the majority of the

caesarean deliveries seen in the cases of childhood cancer in the current analysis were

emergency procedures with strong indications such as fetal distress. Our finding of the

strong association of childhood cancer with caesarean delivery certainly warrants further

research using record linkage of larger cohorts or prospective follow up of birth cohorts.

From the point of view of Public Health interventions, the only other modifiable risk factor

appears to be parental smoking. Several population based lifestyle interventions are already

underway to reduce the prevalence of smoking in pregnancy.

Conclusion: We found a positive association between younger maternal age at delivery and

maternal smoking with childhood cancer. In addition, preterm birth, low Apgar score at 5

minutes and delivery by caesarean section showed associations with childhood cancer,

which remained significant even after controlling for various covariates. While maternal age

and smoking, preterm birth and low Apgar Score have all been previously shown to be

associated with childhood cancer, delivery by caesarean section is a novel finding and

warrants further investigation in larger cohorts. We also propose a mechanistic study

exploring epigenetic changes associated with caesarean delivery as the underlying

mechanism linking the two conditions.

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What is already known on this topic

Extremes of maternal age at delivery, parental smoking, preterm birth and low birthweight

have all been reported to be risk factors for childhood cancer.

What this study adds

The large effect of delivery by caesarean section on the increased risk of childhood cancer is

a novel finding in this study.

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References:

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12. Milne E, Laurvick CL, Blair E et al. Fetal growth and the risk of childhood CNS

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14. Campbell D, Hall M, Lemon J, et al. Clinical birthweight standards for a total

population in the 1980s. BJOG 1993; May;100:436-45.

15. Cole, S. Scottish maternity and neonatal records, 8th Study Group of the Royal

College of Obstetricians and Gynaecologists 1980; 39–52.

16. Johnson KJ, Carozza SE, Chow EJ, et al. Parental age and risk of childhood cancer:

A pooled analysis. Epidemiology 2009; 20: 475-483.

17. Schüz J, Kaatsch P, Kaletsch U, et al. Association of childhood cancer with factors

related to pregnancy and birth. Int J Epidemiol 1999; 28:631-9.

18. Maule MM, Merletti F, Pastore G et al. Effects of maternal age and cohort of birth on

incidence time trends of childhood acute lymphoblastic leukemia. Can Epi Bio Prev

2007;16:347-51.

19. 22. Maule MM, Vizzini L, Czene K, et al. How the effect of maternal age on the risk of

childhood leukemia changed over time in Sweden, 1960-2004. Environ Health

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20. Schüz J. Non-response bias as a likely cause of the association between young

maternal age at the time of delivery and the risk of cancer in the offspring. Paediatr

Perinat Epidemiol 2003;17:106-12.

21. Sorahan T, Lancashire RJ, Hultén MA, et al. Childhood cancer and parental use of

tobacco: Deaths from 1953 to 1955. Br J Cancer 1997;75:134-8.

22. Sorahan T, McKinney PA, Mann JR, et al. Childhood cancer and parental use of

tobacco: Findings from the inter-regional epidemiological study of childhood cancer

(IRESCC). Br J Cancer 2001;84:141-6.

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23. Sorahan T, Prior P, Lancashire RJ, et al. Childhood cancer and parental use of

tobacco: Deaths from 1971 to 1976. Br J Cancer 1997;76:1525-31.

24. Edraki M, Rambod M. Parental smoking and risk of childhood cancer: Hospital-based

case-control study in Shiraz. Eastern Mediterranean Health Journal 2011;17:303-8.

25. Chang JS, Selvin S, Metayer C, et al. Parental smoking and the risk of childhood

leukemia. Am J Epidemiol 2006;163:1091-100.

26. Mucci LA, Granath F, Cnattingius S. Maternal smoking and childhood leukemia and

lymphoma risk among 1,440,542 Swedish children. Can Epi Bio Prev. 2004;13:1528-

33.

27. Stavrou EP, Baker DF, Bishop JF. Maternal smoking during pregnancy and

childhood cancer in New South Wales: A record linkage investigation. Cancer

Causes Control 2009;20:1551-8

28. Schmidt LS, Schüz J, Lähteenmäki P, et al. Fetal Growth, Preterm Birth, Neonatal

Stress and Risk for CNS Tumors in Children: A Nordic Population- and Register-

Based Case-Control Study. Can Epi Bio Prev. 2010; 19: 1042-1052.

29. Harder T, Plagemann A, Harder A. Birth weight and risk of neuroblastoma: a meta-

analysis. Int J Epidemiol 2010; 39: 746-756

30. Daling JR, Starzyk P, Olshan AF, et al. Birth weight and the incidence of childhood

cancer. J Natl Cancer Inst 1984;72:1039-41.

31. MacLean J, Partap S, Reynolds P, et al. Birth weight and order as risk factors for

childhood central nervous system tumors. J Pediatr 2010;157:450-5.

32. Spector LG, Johnson KJ, Soler JT, et al. Perinatal risk factors for hepatoblastoma. Br

J Cancer 2008; 98: 1570-1573.

33. Spector LG, Puumala SE, Carozza SE, et al. Cancer risk among children with very

low birth weights. Pediatrics 2009;124:96-104.

34. Podvin D, Kuehn CM, Mueller BA, et al. Maternal and birth characteristics in relation

to childhood leukaemia. Paediatr Perinat Epidemiol 2006;20:312-22.

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35. Cnattingius S, Zack M, Ekbom A et al. Prenatal and neonatal risk factors for

childhood myeloid leukaemia. Cancer Epidemiol Biomarkers and Prev 1995; 4:441 -

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36. Kaye SA, Robinson LL, Anthony Smithson W et al. Maternal reproductive history and

birth characteristics in childhood acute lymphoblastic leukaemia. Cancer 1991;

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37. Schlinzig T, Johansson S, Gunnar A et al. Epigenetic modulation at birth – altered

DNA methylation in white blood cells after caesarean section. Acta Paediatrica. 2009;

98:1096 – 1099.

38. National Institute for Health and Clinical Excellence. CG132 Caesarean Section.

Available at: http://guidance.nice.org.uk/CG132 [accessed March 2012].

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Table 1. Comparison of maternal baseline characteristics between case children and control children

Characteristics Cases Controls p-

value

Age at delivery (mean, s.d.) 28.9 (5.6) 30.2 (4.6) 0.002

Maternal social class

Manual 26 (14.8%) 79 (11.2%)

0.187 Non-Manual 62 (35.2%) 295 (41.9%)

Single/widowed 87 (49.4%) 325 (46.2%)

Missing 1 (0.6%) 5 (0.7%)

Paternal social class

Manual 71 (40.3%) 329 (46.7%)

0.193 Non-manual 47 (26.7%) 183 (26.0%)

Single/widowed 57 (32.4%) 184 (26.1%)

Missing 1 (0.6%) 8 (1.1%)

Marital status

Single/Widowed/Divorced/Separated/Cohabiting 62 (35.2%) 222 (31.5%) 0.324

Married 113 (64.2%) 482 (68.4%)

Missing 1 (0.6%) 0 (0%)

BMI (mean, s.d.) (Missing cases = 12, Missing controls = 39) 25.2 (5.1) 25.5 (5.1) 0.407

Smoking

Non-smoker 107 (60.8%) 477 (67.8%) 0.034

Smoker/ex-smoker 68 (38.6%) 209 (29.7%)

Missing 1 (0.6%) 18 (2.6%)

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Table 2. Comparison of perinatal factors between cases and controls with statistically significant odds ratios shown in bold

Perinatal factors Cases N=176 Controls N=704 Unadjusted odds ratio

(95% CI)

Age and smoking adjusted

odds ratio (95% CI) – listwise

deletion

Age and smoking adjusted

odds ratio (95% CI) –

imputation of missing value

Preeclampsia 11 (6.3%) 23 (3.3%) 1.98 (0.94-4.18) 1.94 (0.88-4.28) 1.92 (0.91-4.09)

Gestational hypertension 19 (10.8%) 71 (10.1%) 1.09 (0.62-1.89) 1.21 (0.67-2.17) 1.13 (0.64-2.01)

Placenta praevia 3 (1.7%) 4 (0.6%) 3.00 (0.67-13.40) 3.46 (0.76-15.65) 3.45 (0.76-15.62)

Abruption 1 (0.6%) 4 (0.6%) 1.00 (0.11-8.95) 1.31 (0.14-12.66) 1.04 (0.12-9.41)

Other APH 19 (10.8%) 77 (10.9%) 0.99 (0.58-1.68) 0.98 (0.56-1.72) 0.96 (0.56-1.65)

Previous miscarriage 18 (10.2%) 103 (14.6%) 0.67 (0.39-1.13) 0.83 (0.48-1.43) 0.70 (0.41-1.19)

Preterm birth 24 (13.6%) 47 (6.7%) 2.23 (1.31-3.79) 2.09 (1.16-3.76) 2.23 (1.29-3.85)

Low birthweight 17 (9.7%) 38 (5.4%) 1.87 (1.03-3.39) 1.81 (0.94-3.45) 1.78 (0.97-3.28)

Low apgar at 1 minute 30 (17.1%) 107 (15.4%) 1.14 (0.73-1.78) 1.14 (0.71-1.84) 1.15 (0.73-1.81)

Low apgar at 5 minutes 8 (4.6%) 7 (1.0%) 5.01 (1.73-14.54) 4.91 (1.46-16.51) 5.70 (1.93-16.78)

Delivery by caesarean 55 (31.3%) 143 (20.4%) 1.77 (1.23-2.56) 2.25 (1.50-3.36) 2.07 (1.41-3.05)

Instrumental delivery 26 (14.8%) 144 (20.5%) 0.66 (0.41-1.04) 0.68 (0.41-1.13) 0.67 (0.42-1.08)

Intrauterine Growth

Restriction 23 (13.4%) 71 (10.3%) 1.41 (0.85-2.36) 1.20 (0.68-2.12) 1.35 (0.80-2.23)

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Table 3. Odds ratios from multivariable model

*All variables adjusted for maternal age and smoking and for other variables in the model

Statistically significant odds ratios are shown in bold.

Perinatal factors OR (95%CI) from multivariable model – listwise deletion* OR (95% CI) from multivariable model – imputation by missing

value*

Preeclampsia 1.56 (0.68-3.59) 1.55 (0.70-3.44)

Placenta praevia 1.64 (0.32-8.34) 1.65 (0.32-8.43)

Preterm birth 1.60 (0.76-3.37) 1.85 (0.92-3.72)

Low birthweight 1.00 (0.44-2.28) 0.90 (0.41-1.97)

Low apgar at 5 minutes 3.91 (1.13-13.61) 4.59 (1.52-13.87)

Delivery by caesarean 2.11 (1.38-3.23) 1.95 (1.30-2.92)

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Table 4. Distribution of sites of cancer

Cancer site No. %

C22 – Liver and intrahepatic bile ducts 2 1.14

C34 – Bronchus and lung 2 1.14

C41 – Bone and articular cartilage of other and unspecified sites 10

5.68

C49 – Other connective and soft tissue 7

3.98

C52 – Vagina 5 2.84

C56 – Ovary 3 1.70

C62 – Testis 12 6.82

C64 – Kidney except renal pelvis 7 3.98

C69 – Eye and adnexa 6 3.41

C71 – Brain 27

15.34

C72 – Spinal cord, cranial nerves, other CNS 3 1.70

C74 – Adrenal gland 6

3.41

C75 – Other endocrine glands and related structures 4

2.27

C76 – Other and ill-defined sites 2 1.14

C83 – Diffuse non-Hodgkin’s lymphoma 3 1.70

C85 – Other and unspec. non-Hodgkin’s 2 1.14

C91 – Lymphoid Leukaemia 37 21.02

C92 – Myeloid leukaemia 10 5.68

C94 – Other leukaemias of specified cell type 2 1.14

D32 - Meninges 3 1.70

D40 – Uncertain/uknown bhvr male genital 2 1.14

D43 – Uncertain/unknown bhvr. brain and CNS 2 1.14

D44 – Uncertain/unknown bhvr. endocrine 1 0.57

D47 – Uncertain/uknown bhvr. of lymphoid, haematopoietic and related tissue 9

5.11

D48 – Uncertain/unknown bhvr. unknown sites 9 5.11

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Maternal and perinatal risk factors for childhood cancer

Supplemental file: STROBE Statement

Checklist of items that should be included in reports of case control studies

Item No Recommendation

Location within manuscript

Title and

abstract

1 (a) Indicate the study’s design with a

commonly used term in the title or the

abstract

Abstract: Methods

(b) Provide in the abstract an

informative and balanced summary of

what was done and what was found

Abstract: Methods and

Results

Introduction

Background/

rationale

2 Explain the scientific background and

rationale for the investigation being

reported

Introduction: Lines 2 -

17

Objectives 3 State specific objectives, including

any prespecified hypotheses

Introduction: Lines 18 -

22

Methods

Study design 4 Present key elements of study design

early in the paper

Methods: Lines 41-51

Setting 5 Describe the setting, locations, and

relevant dates, including periods of

recruitment, exposure, follow-up, and

data collection

Methods, Lines 24 - 64

Participants 6 (a) Give the eligibility criteria, and the

sources and methods of selection of

participants. Describe methods of

follow-up

Methods, Lines 47 - 51

(b) For matched studies, give

matching criteria and number of

exposed and unexposed

Methods, Lines 41 - 47

Variables 7 Clearly define all outcomes,

exposures, predictors, potential

confounders, and effect modifiers.

Give diagnostic criteria, if applicable

Methods, Lines 52 - 64

Data

sources/

measuremen

t

8* For each variable of interest, give

sources of data and details of

methods of assessment

(measurement). Describe

comparability of assessment methods

if there is more than one group

Methods: Lines 24 - 40

Bias 9 Describe any efforts to address

potential sources of bias

Lines 141 - 161

Study size 10 Explain how the study size was

arrived at

Results Lines 90 - 99

Quantitative

variables

11 Explain how quantitative variables

were handled in the analyses. If

applicable, describe which groupings

were chosen and why

Methods: Lines 65 - 81

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Statistical

methods

12 (a) Describe all statistical methods,

including those used to control for

confounding

Lines 65 - 81

(b) Describe any methods used to

examine subgroups and interactions

Not specified

(c) Explain how missing data were

addressed

Methods lines 81 - 84

(d) If applicable, explain how loss to

follow-up was addressed

Not applicable.

(e) Describe any sensitivity analyses Not conducted

Results

Participants 13* (a) Report numbers of individuals at

each stage of study—eg numbers

potentially eligible, examined for

eligibility, confirmed eligible, included

in the study, completing follow-up,

and analysed

Results: Lines 90 - 99

(b) Give reasons for non-participation

at each stage

Not applicable

Descriptive

data

14* (a) Give characteristics of study

participants (eg demographic, clinical,

social) and information on exposures

and potential confounders

Table 1 and Results:

Lines 104 - 114

Outcome

data

15* Report numbers of outcome events or

summary measures over time

Tables 2, Results: 115

- 131

Main results 16 (a) Give unadjusted estimates and, if

applicable, confounder-adjusted

estimates and their precision (eg,

95% confidence interval). Make clear

which confounders were adjusted for

and why they were included

Table 2

(b) Report category boundaries when

continuous variables were

categorized

Not applicable

Other

analyses

17 Report other analyses done—eg

analyses of subgroups and

interactions, and sensitivity analyses

Lines 125 - 134

Discussion

Key results 18 Summarise key results with reference

to study objectives

Discussion: Lines 136 -

143

Limitations 19 Discuss limitations of the study, taking

into account sources of potential bias

or imprecision. Discuss both direction

and magnitude of any potential bias

Discussion: Lines 144 -

164

Interpretation 20 Give a cautious overall interpretation

of results considering objectives,

limitations, multiplicity of analyses,

results from similar studies, and other

relevant evidence

Discussion: Lines 213 -

224

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Generalis-

ability

21 Discuss the generalisability (external

validity) of the study results

Discussion: Lines 156 -

164

Other information

Funding 22 Give the source of funding and the role of the funders

for the present study and, if applicable, for the

original study on which the present article is based

Title page

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Maternal and Perinatal Risk Factors for Childhood Cancer: Record Linkage Study

Sohinee Bhattacharya1* Marcus Beasley1 Dong Pang2 Gary J Macfarlane1

1Epidemiology Group, Division of Applied Health Sciences, University of Aberdeen 2 Institute of Health Research, University of Bedfordshire, Luton *Corresponding author: Sohinee Bhattacharya Dugald Baird Centre for Research on Women’s Health Aberdeen Maternity Hospital Aberdeen AB25 2ZL Tel: +44 1224 438441 e-mail: [email protected] Running title: Risk factors for childhood cancer

Conflict of Interest: All authors have completed the Unified Competing Interest form at http://www.icmje.org/coi_disclosure.pdf and declare: NHS Grampian Endowment funded the study; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, a worldwide licence to the Publishers and its licensees in perpetuity, in all forms, formats and media (whether known now or created in the future), to (i) publish, reproduce, distribute, display and store the Contribution, (ii) translate the Contribution into other languages, create adaptations, reprints, include within collections and create summaries, extracts and/or, abstracts of the Contribution, (iii) create any other derivative work(s) based on the Contribution, (iv) to exploit all subsidiary rights in the Contribution, (v) the inclusion of electronic links from the Contribution to third party material where-ever it may be located; and, (vi) licence any third party to do any or all of the above. Contributorship: SB was responsible for designing the study, facilitating data extraction, supervising data analysis and writing of the first draft of the paper; MB analysed the data; SB, GJM and DP conceived of the research idea and GJM was responsible for overall supervision. All authors contributed to the writing of the final draft of the paper. SB is the guarantor of this paper. Ethics: This research proposal was approved by the Privacy Advisory Committee of the Information and Services Division NHS Scotland and the steering group of the Aberdeen Maternity and Neonatal Databank. Formal ethical approval was not considered necessary by North of Scotland Research Ethics Service as only anonymised data were analysed in this study. Funding: This research was funded by the NHS Grampian Endowment Fund (Project no. 10/15) Role of sponsors: The University of Aberdeen acted as sponsors for this research project, but the findings and their interpretation in this study are the authors’ own. Independence of authors from funders: All authors were employed by the University of Aberdeen at the time of conducting this research and are independent from the funders.

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Abstract Objective: To investigate maternal and perinatal risk factors for childhood cancer.

Study Design: Case control analysis of linked records from the Aberdeen Maternity and

Neonatal Databank with the Scottish Cancer Registry and the General Registry of Births and

Deaths in Scotland was carried out.

Setting: Aberdeen, Scotland

Participants: Cases (n=176) comprised children diagnosed with cancer under 15 years or

recorded as having died of cancer. Four controls per case were matched by age and gender.

Risk factors tested: Maternal age, BMI, social class, marital status and smoking as well as

preeclampsia, antepartum haemorrhage and previous miscarriage, gestational age,

birthweight, and Apgar scores were compared between groups to test for association with

cancer. Odds ratios with 95% Confidence Intervals were calculated using conditional logistic

regression in both univariable and multivariable models.

Results: Of the maternal characteristics tested, mother’s age at delivery {cases mean

28.9(S.D.5.6) years versus controls mean 30.2(S.D4.6), p = 0.002} and smoking status

(38.6% smokers among cases, 29.7% among controls, p=0.034) were found to be different

between groups. Of the perinatal factors tested, low Apgar score at 5 minutes (AOR 4.59,

95% CI 1.52, 13.87) and delivery by caesarean section (AOR 1.95, 95% CI 1.30, 2.92)

showed statistically significant associations with childhood cancer in the multivariable model.

Conclusions: Younger maternal age, maternal smoking, delivery by caesarean section and

low Apgar score at 5 minutes were independently associated with increased risk of

childhood cancer. .

Key words: childhood cancer, perinatal risk factors, smoking, caesarean delivery

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Introduction:

Childhood cancer has been increasing in Scotland. A published report estimates that its

incidence has risen from 108.3 per million child-years in 1976 to 160.6 per million child-years

in 20071. The reason for this increasing trend remains unexplained as the etiopathogenesis

of childhood cancer is poorly understood. As most present in the first few years of life,

epidemiologists hypothesize that prenatal and perinatal exposures may have a part to play in

its pathogenesis. The evidence surrounding this is however, conflicting. While some

researchers have found associations of younger maternal age at delivery2 maternal

anaemia3,4, previous history of miscarriage2,5,6 maternal overweight7, and smoking8, with

some childhood cancers, others have found no such associations9-11. Fetal growth is

perhaps the most investigated perinatal risk factor for childhood cancer7,12,13 ; but the authors

report conflicting results. While specific central nervous system tumours have been found to

be associated with intrauterine growth restriction, the overall risk was small12. Therefore,

apart from the associations with Down’s syndrome and in utero exposure to radiation,

research into the maternal and perinatal risk factors has remained inconsistent, the results

limited by small sample sizes and recall or reporting bias.

Our objective was therefore to investigate maternal and perinatal risk factors for childhood

cancer, specifically to examine the effects of intrauterine growth restriction, preterm birth and

birth asphyxia on the development of childhood cancer in the offspring, taking advantage of

the opportunities offered by record linkage of a cancer registry with a local birth register.

Methods:

Data Sources:

The Aberdeen Maternity and Neonatal Databank (AMND) holds data for all Aberdeen City

births from 1950 to the present, and includes all reproductive events to women resident in a

defined geographical area with a relatively stable population. The AMND records all births

occurring at the Aberdeen Maternity Hospital, the only maternity hospital serving the

population of Aberdeen city and district. The exposure variables in terms of potential

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maternal and perinatal risk factors were derived from the AMND. The Scottish Cancer

Registry has been in existence since 1951 and was complete up to 2010, at the time of the

present analysis. The cases of childhood cancer were identified from this register.

Data Linkage:

All children born between 1993 and 2006 were identified from the AMND. Their records were

linked to the Cancer Registry in Scotland (SMR 06) and the General Registry of Births and

Deaths in Scotland (GRO-S), using deterministic matching. The linkage was carried out by

data analysts from the Information and Services Division of NHS Scotland using Community

Health Index (CHI) numbers. The CHI number is a number unique to all individuals

registered with a general practice in Scotland and recorded in both databases used in this

study. In a small proportion of cases where CHI number was not available (6%), probabilistic

matching using surname, date of birth and postcode was used. After data linkage, all

identifying information, including CHI numbers were removed and an anonymised dataset

was provided for analysis.

Study design:

A case control study design was employed. Cases comprised all children identified as above

from the AMND who were diagnosed with cancer under 15 years of age in Scotland as

recorded in the Scottish Cancer Registry or recorded as having died of cancer. Controls

were selected from the pool of children not diagnosed as having cancer, matched by age

and gender using four controls per case.

Twins and multiple births were excluded as were stillbirths and early neonatal deaths. As

Down’s syndrome is known to be associated with a higher risk of Acute Lymphoblastic

Leukaemia (ALL) as well as Myeloid Leukaemia of Down’s syndrome, all cases of diagnosed

Down’s syndrome were excluded. Moreover, those children who had died of non-cancer

causes prior to their 15th birthday, as identified from GRO-S were also excluded.

Exposure and outcome variables used in the analysis:

Maternal sociodemographic factors such as age at delivery, body mass index (BMI),

Registrar General’s occupation-based social class, marital status, previous history of

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miscarriage and smoking habits were extracted from the AMND. Any complications recorded

during the index pregnancy such as preeclampsia, gestational hypertension, and antepartum

haemorrhage as well as mode of delivery, gestational age at delivery, birthweight,

Standardised Birthweight Score14, and Apgar score at 1 and 5 minutes were also extracted.

Data extractors were blind to the case-control status of the individual children.

The outcome variables obtained from the Cancer Registry in Scotland were in the form of a

binary variable (yes/no) indicating whether or not a cancer record was present and if

present, the site of cancer given as International Classification of Diseases (ICD) codes.

Similarly, death records with up to 10 different causes of death given by ICD codes were

obtained from linking with GRO-S.

Statistical Analysis:

All analyses were conducted using STATA version 11 (STATA Corp, Texas, USA).

Maternal baseline characteristics were compared between children diagnosed with cancer

and controls using independent two-sample t-tests and chi-square tests. Maternal

complications such as gestational hypertension, pre-eclampsia, antepartum haemorrhage

and previous history of miscarriage were compared between the cases and controls using

univariate conditional regression to calculate odds ratios (OR) with 95% confidence intervals

(CI). Similarly, perinatal factors like gestation at birth, birth weight, intrauterine growth

restriction measured by standardised birthweight score, Apgar score at 1 and 5 minutes

were also tested in univariate models for any association with childhood cancer. Then a

multivariable conditional logistic regression model was fitted that included as independent

variables all risk factors tested on univariate analysis. The possibility of cancer subgroup

analysis was considered according to the International Classification of Childhood Cancer,

but the number of cases in each subgroup was too small to warrant this.

Missing data:

Apart from the variables describing maternal baseline characteristics, the other risk factors

did not have any missing values. There were 18 controls and 1 case with missing smoking

data. The multivariable model was repeated including and excluding the individuals with

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missing information. We used two methodological approaches to handle this - listwise

deletion – ie, not including any group where one person in that group has missing data, and

imputation by creation of a missing value (999) so that all cases and controls were included

in the analyses. The odds ratios obtained by both methods are presented.

Ethical considerations:

Approval to carry out the study was obtained from the AMND steering committee and the

Privacy Advisory Committee for the Information Services Division of National Health

Services, Scotland. As the study involved the analysis of routinely collected anonymised

data, formal ethical approval was not required as declared by the North of Scotland

Research Ethics Service.

Results:

There were 62375 deliveries between 1993 and 2006 as identified from the AMND. After

excluding Down’s syndrome cases, twins and multiple births, stillbirths and early neonatal

deaths, there were 60117 children eligible for linkage with the Cancer Registry. It was

possible to link 43591 of these children to the cancer and GRO-S databases. Amongst the

children with linked data, 106 had died of non-cancer causes before they reached the age of

15 and were therefore excluded from the analysis. Of the remainder, 176 were found to have

a record in the Cancer Registry, giving a cumulative incidence rate of childhood cancer up to

15 years of 4.05 per 1000 deliveries. They constituted the cases for the analysis and were

matched in 1:4 ratio by year of birth and sex from the pool of remaining children without any

records of cancer to obtain 704 controls. As D40, D44, D47 and D48 codes in ICD-10 do not

correspond to cancer diagnosis in International Classification of Childhood Cancer (ICCC),

the analyses were repeated excluding these codes.

Maternal baseline characteristics were compared between cases and matched controls in

Table 1. Of the maternal characteristics tested, mother’s age at delivery (cases mean 28.9

years, s.d. 5.6; controls mean 30.2, s.d. 4.6; p = 0.002) and smoking status (38.6% current

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or ex-smokers among cases, 29.7% among controls, p=0.022) were found to be significantly

different between the two groups.

Table 2 presents the unadjusted odds ratios with 95% confidence intervals for all the

perinatal potential risk factors for childhood cancer. Of the factors tested, preterm birth {OR

2.23(1.31 – 3.79)}; low birth weight {OR 1.87(1.03 – 3.39)}, low Apgar score at 5 minutes

{OR 5.01(1.73 – 14.54)} and delivery by caesarean section {OR 1.77(1.23 – 2.56)} were

found to be statistically significant. Subsequently, these factors were adjusted for maternal

age at delivery and smoking. As the maternal smoking variable had some missing data, we

handled this using two approaches – listwise deletion and imputation of a missing value.

After these adjustments, low birthweight no longer remained significant, but the other

associations were strengthened.

After conducting the univariate analyses multivariable models were fitted including maternal

age, smoking status, preeclampsia, placenta praevia, preterm birth, low birthweight, low

Apgar at 5 minutes and delivery by caesarean as independent variables (results in Table 3).

Similar to the previous analyses, we used two methods of listwise deletion and imputation of

the missing value to adjust for smoking status. Of the perinatal factors tested, Apgar score

below 7 at 5 minutes {AOR 3.91, 95% CI 1.13 – 13.61(listwise deletion); AOR 4.59, 95% CI

1.52, 13.87 (imputation)} and delivery by caesarean section {AOR 2.11, 95% CI 1.38, 3.23

(listwise deletion); AOR 1.95, 95% CI 1.30, 2.92 (imputation)} showed statistically significant

associations with childhood cancer in both multivariable models adjusted for maternal age,

smoking and other factors simultaneously included in the models. Preterm birth (delivery

before 37 completed weeks of gestation) and low birth weight defined as a birth weight

below 2500g, showed a significant association in the univariate analysis, but these

associations were no longer significant in the multivariable model. The associations were not

statistically significant on univariate or multivariable analysis between the risk of childhood

cancer and hypertensive disorders, antepartum haemorrhage, previous history of

miscarriage or IUGR. Unlike the Apgar score at 5 minutes, the score at 1 minute did not

show any association with childhood cancer.

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We further investigated the types of preterm delivery (spontaneous or induced) and

caesarean section (elective or emergency) as risk factors for childhood cancer and found

that both spontaneous and induced preterm delivery were significantly associated in the

adjusted model but only delivery by emergency caesarean section remained significant on

subgroup analysis (AOR 1.43, 95% CI 1.20, 2.18). Further, we found that the commonest

indication for caesarean delivery in the babies who were subsequently diagnosed with

cancer was fetal distress (data not shown).

Table 4 shows the distribution of cancer sites in the 176 cases. As this table shows, the

commonest sites were the brain and haemopoietic organs, especially leukaemia, but the

numbers in the subgroups were too small to allow any meaningful analysis.

Discussion:

We aimed to study the maternal and perinatal risk factors at the time of birth associated with

the diagnosis of childhood cancer using record linkage between two high quality registers in

Scotland. We found a positive association between younger maternal age at delivery and

maternal smoking with childhood cancer. In addition, preterm birth before 37 weeks of

gestation, Apgar score below 7 at 5 minutes and delivery by emergency caesarean section

showed statistically significant associations with childhood cancer the last two of which

remained significant in the adjusted models.

Childhood cancer is a rare condition. Case control studies are therefore the most efficient

epidemiological study design to study several risk factors at the time of birth. Cancer

registries across the world have been utilised to identify cases, but finding appropriate

controls remains problematic. Moreover, data collections regarding exposures by means of

interviews or questionnaires are subject to recall and reporting bias. More recently, linkage

of birth registers with cancer registries has been utilised to design large scale cohort studies.

However, the routine data collection is liable to lack sufficiently detailed data regarding

exposure and potential confounding factors. We have tried to minimise these problems by

linking two high quality registers in Scotland. Previous validation projects have shown these

databases to be 100% complete and over 97% accurate15. Detailed and contemporaneous

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recording of obstetric data in the AMND eliminated recall and reporting bias. The large

number of social and demographic variables recorded in the AMND enabled incorporation of

most potential covariates in the analysis. Despite these strengths to our study design, we

were limited by the small number of cases and it is possible that we did not have sufficient

power to detect some weak associations reported previously in the literature. Maternal and

perinatal risk factors for childhood cancer appear to differ by the site of cancer in the

published literature. The number of cases according to site specific cancer diagnosis was

too small in our sample to allow any subgroup analysis. Further, morphology codes were not

available for us to carry out more appropriate groupings of childhood cancers. This, coupled

with the fact that we had to conduct our analyses on all cancers would have made it less

likely for us to find associations that exist with site specific cancers. This could be a major

limitation of the current analysis. There was a single case of cancer that occurred within the

first year of delivery. It is possible that this could be the result of the cancer being already

present at birth.

The association of parental age with the diagnosis of cancer in general as well as in specific

sites has been studied before. Johnson et al16 in a pooled analysis of register linkage data

from several US states, found that the risk of childhood cancer increased with increasing

maternal age, while paternal age appeared to have no effect on the risk. On the other hand

several other studies, similar to the current analysis have shown that younger maternal age

was associated with increased childhood cancer risk2,17. There could be several

explanations for the disparate findings. In a register linkage study carried out in Sweden18,19,

researchers found that advancing maternal age was positively associated with childhood

cancer risk but only in a historical cohort. This association disappeared in a more recent

cohort of women although the reasons for this are unknown. Moreover, Schutz20 suggests

that the association of lower maternal age at the time of delivery with leukaemia in the

offspring could be explained by non-response bias, although this is not applicable to the

present study.

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The relationship between maternal smoking and childhood cancer in the offspring is complex

and controversial. While Sorahan et al21 - 23 and Edraki24 found an increased overall risk of

childhood cancer with paternal cigarette smoking, there did not appear to be an association

with maternal smoking after adjusting for birthweight. Further, Pang et al9 did not find

evidence of smoking as a risk factor for childhood cancer after adjusting for parental age.

Similar associations were reported by Chang et al25 with regard to Acute Lymphoblastic

Leukaemia (ALL). The evidence appears to indicate that neonatal passive smoking plays a

more important role than in utero transfer of maternal smoke related toxins, although we

cannot rule out the possibility of an association between maternal smoking and site-specific

cancers26,27. For the current analysis, we did not have access to data on paternal smoking

habits and the association seen with maternal smoking could be due to this variable acting

as proxy for paternal smoking.

Other associations noted in this study have been reported before – preterm birth28, and low

Apgar score2,28. Birthweight has received a lot of attention as a risk factor for childhood

cancer. While brain tumours and retinoblastoma appear to be associated with high

birthweight29 - 31 others have found hepatoblastomas7,32 and gliomas33 to be associated with

very low birthweight infants. Schmidt28 et al observed a U-shaped relationship between

birthweight and cancer risk, while Podvin34 found birthweight adjusted for gestational age to

be a better predictor than birthweight alone for the diagnosis of ALL, lending support to our

findings. It is however, important to note, that we did not find an association with intrauterine

growth restriction as measured by the z-score or standardized birthweight score.

Few studies have assessed mode of delivery, specifically caesarean delivery, as a possible

risk factor for the development of childhood cancer. Those that have done, have found a

weak to moderate association 3,7,10,,35,36 between caesarean delivery and subsequent risk of

developing ALL. Several hypotheses can be developed regarding the biological mechanism

underpinning this association. First, caesarean delivery is likely to be a marker of adverse

pregnancy and delivery events – indeed, our finding of increased emergency caesarean

rates indicated by fetal distress seems to support this hypothesis. However, the association

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remained and actually became stronger, after adjusting for most other possible pregnancy

complications. It was customary to use 100% oxygen to resuscitate babies born by

caesarean section in the past. It is possible that this could have played a role in the

subsequent development of cancer. The last explanation involves epigenetic modulations at

birth. Schlinzig et al37 have demonstrated altered DNA-methylation in cord white blood cells

after caesarean delivery and suggested that this may be the basis of increased risk of

asthma, diabetes and ALL seen in infants born by caesarean section.

The association of caesarean delivery with childhood cancer seen in this analysis should be

treated with caution given the small numbers of childhood cancer cases in the study. The

recent NICE guidelines38 recommends caesarean delivery on maternal request. Although,

we have to remember that the majority of the caesarean deliveries seen in the cases of

childhood cancer in the current analysis were emergency procedures with strong indications

such as fetal distress. Our finding of the strong association of childhood cancer with

caesarean delivery warrants further research using record linkage of larger cohorts or

prospective follow up of birth cohorts. From the point of view of Public Health interventions,

the only other modifiable risk factor appears to be parental smoking. Several population

based lifestyle interventions are already underway to reduce the prevalence of smoking in

pregnancy.

Conclusion: We found a positive association between younger maternal age at delivery and

maternal smoking with childhood cancer. In addition, preterm birth, low Apgar score at 5

minutes and delivery by caesarean section showed associations with childhood cancer,

which remained significant even after controlling for various covariates.

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What is already known on this topic

Extremes of maternal age at delivery, parental smoking, preterm birth and low birthweight

have all been reported to be risk factors for childhood cancer.

What this study adds

The large effect of delivery by caesarean section on the increased risk of childhood cancer is

a novel finding in this study.

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12. Milne E, Laurvick CL, Blair E et al. Fetal growth and the risk of childhood CNS

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23. Sorahan T, Prior P, Lancashire RJ, et al. Childhood cancer and parental use of

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26. Mucci LA, Granath F, Cnattingius S. Maternal smoking and childhood leukemia and

lymphoma risk among 1,440,542 Swedish children. Can Epi Bio Prev. 2004;13:1528-

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childhood cancer in New South Wales: A record linkage investigation. Cancer

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28. Schmidt LS, Schüz J, Lähteenmäki P, et al. Fetal Growth, Preterm Birth, Neonatal

Stress and Risk for CNS Tumors in Children: A Nordic Population- and Register-

Based Case-Control Study. Can Epi Bio Prev. 2010; 19: 1042-1052.

29. Harder T, Plagemann A, Harder A. Birth weight and risk of neuroblastoma: a meta-

analysis. Int J Epidemiol 2010; 39: 746-756

30. Daling JR, Starzyk P, Olshan AF, et al. Birth weight and the incidence of childhood

cancer. J Natl Cancer Inst 1984;72:1039-41.

31. MacLean J, Partap S, Reynolds P, et al. Birth weight and order as risk factors for

childhood central nervous system tumors. J Pediatr 2010;157:450-5.

32. Spector LG, Johnson KJ, Soler JT, et al. Perinatal risk factors for hepatoblastoma. Br

J Cancer 2008; 98: 1570-1573.

33. Spector LG, Puumala SE, Carozza SE, et al. Cancer risk among children with very

low birth weights. Pediatrics 2009;124:96-104.

34. Podvin D, Kuehn CM, Mueller BA, et al. Maternal and birth characteristics in relation

to childhood leukaemia. Paediatr Perinat Epidemiol 2006;20:312-22.

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35. Cnattingius S, Zack M, Ekbom A et al. Prenatal and neonatal risk factors for

childhood myeloid leukaemia. Cancer Epidemiol Biomarkers and Prev 1995; 4:441 -

445.

36. Kaye SA, Robinson LL, Anthony Smithson W et al. Maternal reproductive history and

birth characteristics in childhood acute lymphoblastic leukaemia. Cancer 1991;

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37. Schlinzig T, Johansson S, Gunnar A et al. Epigenetic modulation at birth – altered

DNA methylation in white blood cells after caesarean section. Acta Paediatrica. 2009;

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38. National Institute for Health and Clinical Excellence. CG132 Caesarean Section.

Available at: http://guidance.nice.org.uk/CG132 [accessed March 2012].

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Table 1. Comparison of maternal baseline characteristics between case children and control children

Characteristics Cases Controls p-

value

Age at delivery (mean, s.d.) 28.9 (5.6) 30.2 (4.6) 0.002

Maternal social class

Manual 26 (14.8%) 79 (11.2%)

0.187 Non-Manual 62 (35.2%) 295 (41.9%)

Single/widowed 87 (49.4%) 325 (46.2%)

Missing 1 (0.6%) 5 (0.7%)

Paternal social class

Paternal Manual 71 (40.3%) 329 (46.7%)

0.193 Paternal Non-manual 47 (26.7%) 183 (26.0%)

Maternal non-manual 57 (32.4%) 184 (26.1%)

Missing 1 (0.6%) 8 (1.1%)

Marital status

Single/Widowed/Divorced/Separated/ 62 (35.2%) 222 (31.5%) 0.324

Married 113 (64.2%) 482 (68.4%)

Missing 1 (0.6%) 0 (0%)

BMI (mean, s.d.) (Missing cases = 12, Missing controls = 39) 25.2 (5.1) 25.5 (5.1) 0.407

Smoking

Non-smoker 107 (60.8%) 477 (67.8%) 0.034

Smoker/ex-smoker 68 (38.6%) 209 (29.7%)

Missing 1 (0.6%) 18 (2.6%)

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Table 2. Comparison of perinatal factors between cases and controls with statistically significant odds ratios shown in bold

Perinatal factors Cases N=176 Controls N=704 Unadjusted odds ratio

(95% CI)

Age and smoking adjusted

odds ratio (95% CI) – listwise

deletion

Age and smoking adjusted

odds ratio (95% CI) –

imputation of missing value

Preeclampsia 11 (6.3%) 23 (3.3%) 1.98 (0.94-4.18) 1.94 (0.88-4.28) 1.92 (0.91-4.09)

Gestational hypertension 19 (10.8%) 71 (10.1%) 1.09 (0.62-1.89) 1.21 (0.67-2.17) 1.13 (0.64-2.01)

Placenta praevia 3 (1.7%) 4 (0.6%) 3.00 (0.67-13.40) 3.46 (0.76-15.65) 3.45 (0.76-15.62)

Abruption 1 (0.6%) 4 (0.6%) 1.00 (0.11-8.95) 1.31 (0.14-12.66) 1.04 (0.12-9.41)

Other APH 19 (10.8%) 77 (10.9%) 0.99 (0.58-1.68) 0.98 (0.56-1.72) 0.96 (0.56-1.65)

Previous miscarriage 18 (10.2%) 103 (14.6%) 0.67 (0.39-1.13) 0.83 (0.48-1.43) 0.70 (0.41-1.19)

Preterm birth 24 (13.6%) 47 (6.7%) 2.23 (1.31-3.79) 2.09 (1.16-3.76) 2.23 (1.29-3.85)

Low birthweight 17 (9.7%) 38 (5.4%) 1.87 (1.03-3.39) 1.81 (0.94-3.45) 1.78 (0.97-3.28)

Low apgar at 1 minute 30 (17.1%) 107 (15.4%) 1.14 (0.73-1.78) 1.14 (0.71-1.84) 1.15 (0.73-1.81)

Low apgar at 5 minutes 8 (4.6%) 7 (1.0%) 5.01 (1.73-14.54) 4.91 (1.46-16.51) 5.70 (1.93-16.78)

Delivery by caesarean 55 (31.3%) 143 (20.4%) 1.77 (1.23-2.56) 2.25 (1.50-3.36) 2.07 (1.41-3.05)

Instrumental delivery 26 (14.8%) 144 (20.5%) 0.66 (0.41-1.04) 0.68 (0.41-1.13) 0.67 (0.42-1.08)

Intrauterine Growth

Restriction 23 (13.4%) 71 (10.3%) 1.41 (0.85-2.36) 1.20 (0.68-2.12) 1.35 (0.80-2.23)

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Table 3. Odds ratios from multivariable model

*All variables adjusted for maternal age and smoking and for other variables in the model

Statistically significant odds ratios are shown in bold.

Perinatal factors OR (95%CI) from multivariable model – listwise deletion* OR (95% CI) from multivariable model – imputation of missing

value*

Preeclampsia 1.56 (0.68-3.59) 1.55 (0.70-3.44)

Placenta praevia 1.64 (0.32-8.34) 1.65 (0.32-8.43)

Preterm birth 1.60 (0.76-3.37) 1.85 (0.92-3.72)

Low birthweight 1.00 (0.44-2.28) 0.90 (0.41-1.97)

Low apgar at 5 minutes 3.91 (1.13-13.61) 4.59 (1.52-13.87)

Delivery by caesarean 2.11 (1.38-3.23) 1.95 (1.30-2.92)

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Table 4. Distribution of sites of cancer

Cancer site No. %

C22 – Liver and intrahepatic bile ducts 2 1.14

C34 – Bronchus and lung 2 1.14

C41 – Bone and articular cartilage of other and unspecified sites 10

5.68

C49 – Other connective and soft tissue 7

3.98

C52 – Vagina 5 2.84

C56 – Ovary 3 1.70

C62 – Testis 12 6.82

C64 – Kidney except renal pelvis 7 3.98

C69 – Eye and adnexa 6 3.41

C71 – Brain 27

15.34

C72 – Spinal cord, cranial nerves, other CNS 3 1.70

C74 – Adrenal gland 6

3.41

C75 – Other endocrine glands and related structures 4

2.27

C76 – Other and ill-defined sites 2 1.14

C83 – Diffuse non-Hodgkin’s lymphoma 3 1.70

C85 – Other and unspec. non-Hodgkin’s 2 1.14

C91 – Lymphoid Leukaemia 37 21.02

C92 – Myeloid leukaemia 10 5.68

C94 – Other leukaemias of specified cell type 2 1.14

D32 - Meninges 3 1.70

D40 – Uncertain/uknown bhvr male genital 2 1.14

D43 – Uncertain/unknown bhvr. brain and CNS 2 1.14

D44 – Uncertain/unknown bhvr. endocrine 1 0.57

D47 – Uncertain/uknown bhvr. of lymphoid, haematopoietic and related tissue 9

5.11

D48 – Uncertain/unknown bhvr. unknown sites 9 5.11

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Maternal and Perinatal Risk Factors for Childhood Cancer: Record Linkage Study

Sohinee Bhattacharya1* Marcus Beasley1 Dong Pang2 Gary J Macfarlane1

1Epidemiology Group, Division of Applied Health Sciences, University of Aberdeen 2 Institute of Health Research, University of Bedfordshire, Luton *Corresponding author: Sohinee Bhattacharya Dugald Baird Centre for Research on Women’s Health Aberdeen Maternity Hospital Aberdeen AB25 2ZL Tel: +44 1224 438441 e-mail: [email protected] Running title: Risk factors for childhood cancer

Conflict of Interest: All authors have completed the Unified Competing Interest form at http://www.icmje.org/coi_disclosure.pdf and declare: NHS Grampian Endowment funded the study; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, a worldwide licence to the Publishers and its licensees in perpetuity, in all forms, formats and media (whether known now or created in the future), to (i) publish, reproduce, distribute, display and store the Contribution, (ii) translate the Contribution into other languages, create adaptations, reprints, include within collections and create summaries, extracts and/or, abstracts of the Contribution, (iii) create any other derivative work(s) based on the Contribution, (iv) to exploit all subsidiary rights in the Contribution, (v) the inclusion of electronic links from the Contribution to third party material where-ever it may be located; and, (vi) licence any third party to do any or all of the above. Contributorship: SB was responsible for designing the study, facilitating data extraction, supervising data analysis and writing of the first draft of the paper; MB analysed the data; SB, GJM and DP conceived of the research idea and GJM was responsible for overall supervision. All authors contributed to the writing of the final draft of the paper. SB is the guarantor of this paper. Ethics: This research proposal was approved by the Privacy Advisory Committee of the Information and Services Division NHS Scotland and the steering group of the Aberdeen Maternity and Neonatal Databank. Formal ethical approval was not considered necessary by North of Scotland Research Ethics Service as only anonymised data were analysed in this study. Funding: This research was funded by the NHS Grampian Endowment Fund (Project no. 10/15) Role of sponsors: The University of Aberdeen acted as sponsors for this research project, but the findings and their interpretation in this study are the authors’ own. Independence of authors from funders: All authors were employed by the University of Aberdeen at the time of conducting this research and are independent from the funders.

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Abstract Objective: To investigate maternal and perinatal risk factors for childhood cancer.

Study Design: Case control analysis of linked records from the Aberdeen Maternity and

Neonatal Databank with the Scottish Cancer Registry and the General Registry of Births and

Deaths in Scotland was carried out.

Setting: Aberdeen, Scotland

Participants: Cases (n=176) comprised children diagnosed with cancer under 15 years or

recorded as having died of cancer. Four controls per case were matched by age and gender.

Risk factors tested: Maternal age, BMI, social class, marital status and smoking as well as

preeclampsia, antepartum haemorrhage and previous miscarriage, gestational age,

birthweight, and Apgar scores were compared between groups to test for association with

cancer. Odds ratios with 95% Confidence Intervals were calculated using conditional logistic

regression in both univariable and multivariable models.

Results: Of the maternal characteristics tested, mother’s age at delivery {cases mean

28.9(S.D.5.6) years versus controls mean 30.2(S.D4.6), p = 0.002} and smoking status

(38.6% smokers among cases, 29.7% among controls, p=0.034) were found to be different

between groups. Of the perinatal factors tested, low Apgar score at 5 minutes (AOR 4.59,

95% CI 1.52, 13.87) and delivery by caesarean section (AOR 1.95, 95% CI 1.30, 2.92)

showed statistically significant associations with childhood cancer in the multivariable model.

Conclusions: Younger maternal age, maternal smoking, delivery by caesarean section and

low Apgar score at 5 minutes were independently associated with increased risk of

childhood cancer. The association with caesarean delivery may be mediated through

epigenetic mechanism and warrants further investigation.

Key words: childhood cancer, perinatal risk factors, smoking, caesarean delivery

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Introduction:

Childhood cancer has been increasing in Scotland. A published report estimates that its

incidence has risen from 108.3 per million child-years in 1976 to 160.6 per million child-years

in 20071. The reason for this increasing trend remains unexplained as the etiopathogenesis

of childhood cancer is poorly understood. As most present in the first few years of life,

epidemiologists hypothesize that prenatal and perinatal exposures may have a part to play in

its pathogenesis. The evidence surrounding this is however, conflicting. While some

researchers have found associations of younger maternal age at delivery2 maternal

anaemia3,4, previous history of miscarriage2,5,6 maternal overweight7, and smoking8, with

some childhood cancers, others have found no such associations9-11. Fetal growth is

perhaps the most investigated perinatal risk factor for childhood cancer7,12,13 ; but the authors

report conflicting results. While specific central nervous system tumours have been found to

be associated with intrauterine growth restriction, the overall risk was small12. Therefore,

apart from the associations with Down’s syndrome and in utero exposure to radiation,

research into the maternal and perinatal risk factors has remained inconsistent, the results

limited by small sample sizes and recall or reporting bias.

Our objective was therefore to investigate maternal and perinatal risk factors for childhood

cancer, specifically to examine the effects of intrauterine growth restriction, preterm birth and

birth asphyxia on the development of childhood cancer in the offspring, taking advantage of

the opportunities offered by record linkage of a cancer registry with a local birth register.

Methods:

Data Sources:

The Aberdeen Maternity and Neonatal Databank (AMND) holds data for all Aberdeen City

births from 1950 to the present, and includes all reproductive events to women resident in a

defined geographical area with a relatively stable population. The AMND records all births

occurring at the Aberdeen Maternity Hospital, the only maternity hospital serving the

population of Aberdeen city and district. The exposure variables in terms of potential

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maternal and perinatal risk factors were derived from the AMND. The Scottish Cancer

Registry has been in existence since 1951 and was complete up to 2010, at the time of the

present analysis. The cases of childhood cancer were identified from this register.

Data Linkage:

All children born between 1993 and 2006 were identified from the AMND. Their records were

linked to the Cancer Registry in Scotland (SMR 06) and the General Registry of Births and

Deaths in Scotland (GRO-S), using deterministic matching. The linkage was carried out by

data analysts from the Information and Services Division of NHS Scotland using Community

Health Index (CHI) numbers. The CHI number is a number unique to all individuals

registered with a general practice in Scotland and recorded in both databases used in this

study. In a small proportion of cases where CHI number was not available (6%), probabilistic

matching using surname, date of birth and postcode was used. After data linkage, all

identifying information, including CHI numbers were removed and an anonymised dataset

was provided for analysis.

Study design:

A case control study design was employed. Cases comprised all children identified as above

from the AMND who were diagnosed with cancer under 15 years of age in Scotland as

recorded in the Scottish Cancer Registry or recorded as having died of cancer. Controls

were selected from the pool of children not diagnosed as having cancer, matched by age

and gender using four controls per case.

Twins and multiple births were excluded as were stillbirths and early neonatal deaths. As

Down’s syndrome is known to be associated with a higher risk of Acute Lymphoblastic

Leukaemia (ALL) as well as Myeloid Leukaemia of Down’s syndrome, all cases of diagnosed

Down’s syndrome were excluded. Moreover, those children who had died of non-cancer

causes prior to their 15th birthday, as identified from GRO-S were also excluded.

Exposure and outcome variables used in the analysis:

Maternal sociodemographic factors such as age at delivery, body mass index (BMI),

Registrar General’s occupation-based social class, marital status, previous history of

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miscarriage and smoking habits were extracted from the AMND. Any complications recorded

during the index pregnancy such as preeclampsia, gestational hypertension, and antepartum

haemorrhage as well as mode of delivery, gestational age at delivery, birthweight,

Standardised Birthweight Score14, and Apgar score at 1 and 5 minutes were also extracted.

Data extractors were blind to the case-control status of the individual children.

The outcome variables obtained from the Cancer Registry in Scotland were in the form of a

binary variable (yes/no) indicating whether or not a cancer record was present and if

present, the site of cancer given as International Classification of Diseases (ICD) codes.

Similarly, death records with up to 10 different causes of death given by ICD codes were

obtained from linking with GRO-S.

Statistical Analysis:

All analyses were conducted using STATA version 11 (STATA Corp, Texas, USA).

Maternal baseline characteristics were compared between children diagnosed with cancer

and controls using independent two-sample t-tests and chi-square tests. Maternal

complications such as gestational hypertension, pre-eclampsia, antepartum haemorrhage

and previous history of miscarriage were compared between the cases and controls using

univariate conditional regression to calculate odds ratios (OR) with 95% confidence intervals

(CI). Similarly, perinatal factors like gestation at birth, birth weight, intrauterine growth

restriction measured by standardised birthweight score, Apgar score at 1 and 5 minutes

were also tested in univariate models for any association with childhood cancer. Then a

multivariable conditional logistic regression model was fitted that included as independent

variables all risk factors tested on univariate analysis. The possibility of cancer subgroup

analysis was considered according to the International Classification of Childhood Cancer,

but the number of cases in each subgroup was too small to warrant this.

Missing data:

Apart from the variables describing maternal baseline characteristics, the other risk factors

did not have any missing values. There were 18 controls and 1 case with missing smoking

data. The multivariable model was repeated including and excluding the individuals with

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missing information. We used two methodological approaches to handle this - listwise

deletion – ie, not including any group where one person in that group has missing data, and

imputation by creation of a missing value (999) so that all cases and controls were included

in the analyses. The odds ratios obtained by both methods are presented.

Ethical considerations:

Approval to carry out the study was obtained from the AMND steering committee and the

Privacy Advisory Committee for the Information Services Division of National Health

Services, Scotland. As the study involved the analysis of routinely collected anonymised

data, formal ethical approval was not required as declared by the North of Scotland

Research Ethics Service.

Results:

There were 62375 deliveries between 1993 and 2006 as identified from the AMND. After

excluding Down’s syndrome cases, twins and multiple births, stillbirths and early neonatal

deaths, there were 60117 children eligible for linkage with the Cancer Registry. It was

possible to link 43591 of these children to the cancer and GRO-S databases. Amongst the

children with linked data, 106 had died of non-cancer causes before they reached the age of

15 and were therefore excluded from the analysis. Of the remainder, 176 were found to have

a record in the Cancer Registry, giving a cumulative incidence rate of childhood cancer up to

15 years of 4.05 per 1000 deliveries. They constituted the cases for the analysis and were

matched in 1:4 ratio by year of birth and sex from the pool of remaining children without any

records of cancer to obtain 704 controls. As D40, D44, D47 and D48 codes in ICD-10 do not

correspond to cancer diagnosis in International Classification of Childhood Cancer (ICCC),

the analyses were repeated excluding these codes.

Maternal baseline characteristics were compared between cases and matched controls in

Table 1. Of the maternal characteristics tested, mother’s age at delivery (cases mean 28.9

years, s.d. 5.6; controls mean 30.2, s.d. 4.6; p = 0.002) and smoking status (38.6% current

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or ex-smokers among cases, 29.7% among controls, p=0.022) were found to be significantly

different between the two groups.

Table 2 presents the unadjusted odds ratios with 95% confidence intervals for all the

perinatal potential risk factors for childhood cancer. Of the factors tested, preterm birth {OR

2.23(1.31 – 3.79)}; low birth weight {OR 1.87(1.03 – 3.39)}, low Apgar score at 5 minutes

{OR 5.01(1.73 – 14.54)} and delivery by caesarean section {OR 1.77(1.23 – 2.56)} were

found to be statistically significant. Subsequently, these factors were adjusted for maternal

age at delivery and smoking. As the maternal smoking variable had some missing data, we

handled this using two approaches – listwise deletion and imputation of a missing value.

After these adjustments, low birthweight no longer remained significant, but the other

associations were strengthened.

After conducting the univariate analyses multivariable models were fitted including maternal

age, smoking status, preeclampsia, placenta praevia, preterm birth, low birthweight, low

Apgar at 5 minutes and delivery by caesarean as independent variables (results in Table 3).

Similar to the previous analyses, we used two methods of listwise deletion and imputation of

the missing value to adjust for smoking status. Of the perinatal factors tested, Apgar score

below 7 at 5 minutes {AOR 3.91, 95% CI 1.13 – 13.61(listwise deletion); AOR 4.59, 95% CI

1.52, 13.87 (imputation)} and delivery by caesarean section {AOR 2.11, 95% CI 1.38, 3.23

(listwise deletion); AOR 1.95, 95% CI 1.30, 2.92 (imputation)} showed statistically significant

associations with childhood cancer in both multivariable models adjusted for maternal age,

smoking and other factors simultaneously included in the models. Preterm birth (delivery

before 37 completed weeks of gestation) and low birth weight defined as a birth weight

below 2500g, showed a significant association in the univariate analysis, but these

associations were no longer significant in the multivariable model. The associations were not

statistically significant on univariate or multivariable analysis between the risk of childhood

cancer and hypertensive disorders, antepartum haemorrhage, previous history of

miscarriage or IUGR. Unlike the Apgar score at 5 minutes, the score at 1 minute did not

show any association with childhood cancer.

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We further investigated the types of preterm delivery (spontaneous or induced) and

caesarean section (elective or emergency) as risk factors for childhood cancer and found

that both spontaneous and induced preterm delivery were significantly associated in the

adjusted model but only delivery by emergency caesarean section remained significant on

subgroup analysis (AOR 1.43, 95% CI 1.20, 2.18). Further, we found that the commonest

indication for caesarean delivery in the babies who were subsequently diagnosed with

cancer was fetal distress (data not shown).

Table 4 shows the distribution of cancer sites in the 176 cases. As this table shows, the

commonest sites were the brain and haemopoietic organs, especially leukaemia, but the

numbers in the subgroups were too small to allow any meaningful analysis.

Discussion:

We aimed to study the maternal and perinatal risk factors at the time of birth associated with

the diagnosis of childhood cancer using record linkage between two high quality registers in

Scotland. We found a positive association between younger maternal age at delivery and

maternal smoking with childhood cancer. In addition, preterm birth before 37 weeks of

gestation, Apgar score below 7 at 5 minutes and delivery by emergency caesarean section

showed statistically significant associations with childhood cancer the last two of which

remained significant in the adjusted models.

Childhood cancer is a rare condition. Case control studies are therefore the most efficient

epidemiological study design to study several risk factors at the time of birth. Cancer

registries across the world have been utilised to identify cases, but finding appropriate

controls remains problematic. Moreover, data collections regarding exposures by means of

interviews or questionnaires are subject to recall and reporting bias. More recently, linkage

of birth registers with cancer registries has been utilised to design large scale cohort studies.

However, the routine data collection is liable to lack sufficiently detailed data regarding

exposure and potential confounding factors. We have tried to minimise these problems by

linking two high quality registers in Scotland. Previous validation projects have shown these

databases to be 100% complete and over 97% accurate15. Detailed and contemporaneous

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recording of obstetric data in the AMND eliminated recall and reporting bias. The large

number of social and demographic variables recorded in the AMND enabled incorporation of

most potential covariates in the analysis. Despite these strengths to our study design, we

were limited by the small number of cases and it is possible that we did not have sufficient

power to detect some weak associations reported previously in the literature. Maternal and

perinatal risk factors for childhood cancer appear to differ by the site of cancer in the

published literature. The number of cases according to site specific cancer diagnosis was

too small in our sample to allow any subgroup analysis. Further, morphology codes were not

available for us to carry out more appropriate groupings of childhood cancers. This, coupled

with the fact that we had to conduct our analyses on all cancers would have made it less

likely for us to find associations that exist with site specific cancers. This could be a major

limitation of the current analysis. There was a single case of cancer that occurred within the

first year of delivery. It is possible that this could be the result of the cancer being already

present at birth.

The association of parental age with the diagnosis of cancer in general as well as in specific

sites has been studied before. Johnson et al16 in a pooled analysis of register linkage data

from several US states, found that the risk of childhood cancer increased with increasing

maternal age, while paternal age appeared to have no effect on the risk. On the other hand

several other studies, similar to the current analysis have shown that younger maternal age

was associated with increased childhood cancer risk2,17. There could be several

explanations for the disparate findings. In a register linkage study carried out in Sweden18,19,

researchers found that advancing maternal age was positively associated with childhood

cancer risk but only in a historical cohort. This association disappeared in a more recent

cohort of women although the reasons for this are unknown. Moreover, Schutz20 suggests

that the association of lower maternal age at the time of delivery with leukaemia in the

offspring could be explained by non-response bias, although this is not applicable to the

present study.

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The relationship between maternal smoking and childhood cancer in the offspring is complex

and controversial. While Sorahan et al21 - 23 and Edraki24 found an increased overall risk of

childhood cancer with paternal cigarette smoking, there did not appear to be an association

with maternal smoking after adjusting for birthweight. Further, Pang et al9 did not find

evidence of smoking as a risk factor for childhood cancer after adjusting for parental age.

Similar associations were reported by Chang et al25 with regard to Acute Lymphoblastic

Leukaemia (ALL). The evidence appears to indicate that neonatal passive smoking plays a

more important role than in utero transfer of maternal smoke related toxins, although we

cannot rule out the possibility of an association between maternal smoking and site-specific

cancers26,27. For the current analysis, we did not have access to data on paternal smoking

habits and the association seen with maternal smoking could be due to this variable acting

as proxy for paternal smoking.

Other associations noted in this study have been reported before – preterm birth28, and low

Apgar score2,28. Li et al found a 46% increased risk of childhood cancer in infants who had a

low 5 minute Apgar score29. Birthweight has received a lot of attention as a risk factor for

childhood cancer. While brain tumours and retinoblastoma appear to be associated with high

birthweight3029 - 312 others have found hepatoblastomas7,323 and gliomas334 to be associated

with very low birthweight infants. Schmidt28 et al observed a U-shaped relationship between

birthweight and cancer risk, while Podvin354 found birthweight adjusted for gestational age to

be a better predictor than birthweight alone for the diagnosis of ALL, lending support to our

findings. It is however, important to note, that we did not find an association with intrauterine

growth restriction as measured by the z-score or standardized birthweight score.

Few studies have assessed mode of delivery, specifically caesarean delivery, as a possible

risk factor for the development of childhood cancer. Those that have done, have found a

weak to moderate association 3,7,10,,365,376 between caesarean delivery and subsequent risk of

developing ALL. Several hypotheses can be developed regarding the biological mechanism

underpinning this association. First, caesarean delivery is likely to be a marker of adverse

pregnancy and delivery events – indeed, our finding of increased emergency caesarean

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rates indicated by fetal distress seems to support this hypothesis. However, the association

remained and actually became stronger, after adjusting for most other possible pregnancy

complications. It was customary to use 100% oxygen to resuscitate babies born by

caesarean section in the past. It is possible that this could have played a role in the

subsequent development of cancer. The last explanation involves epigenetic modulations at

birth. Schlinzig et al387 have demonstrated altered DNA-methylation in cord white blood cells

after caesarean delivery and suggested that this may be the basis of increased risk of

asthma, diabetes and ALL seen in infants born by caesarean section.

The association of caesarean delivery with childhood cancer seen in this analysis should be

treated with caution given the small numbers of childhood cancer cases in the study., is

likely to have far reaching consequences for obstetric practice. The recent NICE

guidelines398 recommends caesarean delivery on maternal request., further evidence to

support a link between caesarean section and subsequent cancer in the offspring would

seriously question the ethics of such practice. Although, we have to remember that the

majority of the caesarean deliveries seen in the cases of childhood cancer in the current

analysis were emergency procedures with strong indications such as fetal distress. Our

finding of the strong association of childhood cancer with caesarean delivery certainly

warrants further research using record linkage of larger cohorts or prospective follow up of

birth cohorts. From the point of view of Public Health interventions, the only other modifiable

risk factor appears to be parental smoking. Several population based lifestyle interventions

are already underway to reduce the prevalence of smoking in pregnancy.

Conclusion: We found a positive association between younger maternal age at delivery and

maternal smoking with childhood cancer. In addition, preterm birth, low Apgar score at 5

minutes and delivery by caesarean section showed associations with childhood cancer,

which remained significant even after controlling for various covariates. While maternal age

and smoking, preterm birth and low Apgar Score have all been previously shown to be

associated with childhood cancer, delivery by caesarean section is a novel finding and

warrants further investigation in larger cohorts. We also propose a mechanistic study

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exploring epigenetic changes associated with caesarean delivery as the underlying

mechanism linking the two conditions.

What is already known on this topic

Extremes of maternal age at delivery, parental smoking, preterm birth and low birthweight

have all been reported to be risk factors for childhood cancer.

What this study adds

The large effect of delivery by caesarean section on the increased risk of childhood cancer is

a novel finding in this study.

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childhood cancer in New South Wales: A record linkage investigation. Cancer

Causes Control 2009;20:1551-8

28. Schmidt LS, Schüz J, Lähteenmäki P, et al. Fetal Growth, Preterm Birth, Neonatal

Stress and Risk for CNS Tumors in Children: A Nordic Population- and Register-

Based Case-Control Study. Can Epi Bio Prev. 2010; 19: 1042-1052.

28.29. Li J, Cnattingius S, Gissler M et al. The 5-minute Apgar Score as a predictor

of childhood cancer: A population-based cohort study in five million children. BMJ

Open 2012; 0:e001095.

29.30. Harder T, Plagemann A, Harder A. Birth weight and risk of neuroblastoma: a

meta-analysis. Int J Epidemiol 2010; 39: 746-756

30.31. Daling JR, Starzyk P, Olshan AF, et al. Birth weight and the incidence of

childhood cancer. J Natl Cancer Inst 1984;72:1039-41.

31.32. MacLean J, Partap S, Reynolds P, et al. Birth weight and order as risk factors

for childhood central nervous system tumors. J Pediatr 2010;157:450-5.

32.33. Spector LG, Johnson KJ, Soler JT, et al. Perinatal risk factors for

hepatoblastoma. Br J Cancer 2008; 98: 1570-1573.

33.34. Spector LG, Puumala SE, Carozza SE, et al. Cancer risk among children with

very low birth weights. Pediatrics 2009;124:96-104.

Formatted: Font: Arial, 11 pt, Italic

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Formatted: Font: Italic

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34.35. Podvin D, Kuehn CM, Mueller BA, et al. Maternal and birth characteristics in

relation to childhood leukaemia. Paediatr Perinat Epidemiol 2006;20:312-22.

35.36. Cnattingius S, Zack M, Ekbom A et al. Prenatal and neonatal risk factors for

childhood myeloid leukaemia. Cancer Epidemiol Biomarkers and Prev 1995; 4:441 -

445.

36.37. Kaye SA, Robinson LL, Anthony Smithson W et al. Maternal reproductive

history and birth characteristics in childhood acute lymphoblastic leukaemia. Cancer

1991; 68:1351 – 1355.

37.38. Schlinzig T, Johansson S, Gunnar A et al. Epigenetic modulation at birth –

altered DNA methylation in white blood cells after caesarean section. Acta

Paediatrica. 2009; 98:1096 – 1099.

38.39. National Institute for Health and Clinical Excellence. CG132 Caesarean

Section. Available at: http://guidance.nice.org.uk/CG132 [accessed March 2012].

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Table 1. Comparison of maternal baseline characteristics between case children and control children

Characteristics Cases Controls p-

value

Age at delivery (mean, s.d.) 28.9 (5.6) 30.2 (4.6) 0.002

Maternal social class

Manual 26 (14.8%) 79 (11.2%)

0.187 Non-Manual 62 (35.2%) 295 (41.9%)

Single/widowed 87 (49.4%) 325 (46.2%)

Missing 1 (0.6%) 5 (0.7%)

Paternal social class

Paternal Manual 71 (40.3%) 329 (46.7%)

0.193 Paternal Non-manual 47 (26.7%) 183 (26.0%)

Single/widowed Maternal non-manual 57 (32.4%) 184 (26.1%)

Missing 1 (0.6%) 8 (1.1%)

Marital status

Single/Widowed/Divorced/Separated/Cohabiting 62 (35.2%) 222 (31.5%) 0.324

Married 113 (64.2%) 482 (68.4%)

Missing 1 (0.6%) 0 (0%)

BMI (mean, s.d.) (Missing cases = 12, Missing controls = 39) 25.2 (5.1) 25.5 (5.1) 0.407

Smoking

Non-smoker 107 (60.8%) 477 (67.8%) 0.034

Smoker/ex-smoker 68 (38.6%) 209 (29.7%)

Missing 1 (0.6%) 18 (2.6%)

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Table 2. Comparison of perinatal factors between cases and controls with statistically significant odds ratios shown in bold

Perinatal factors Cases N=176 Controls N=704 Unadjusted odds ratio

(95% CI)

Age and smoking adjusted

odds ratio (95% CI) – listwise

deletion

Age and smoking adjusted

odds ratio (95% CI) –

imputation of missing value

Preeclampsia 11 (6.3%) 23 (3.3%) 1.98 (0.94-4.18) 1.94 (0.88-4.28) 1.92 (0.91-4.09)

Gestational hypertension 19 (10.8%) 71 (10.1%) 1.09 (0.62-1.89) 1.21 (0.67-2.17) 1.13 (0.64-2.01)

Placenta praevia 3 (1.7%) 4 (0.6%) 3.00 (0.67-13.40) 3.46 (0.76-15.65) 3.45 (0.76-15.62)

Abruption 1 (0.6%) 4 (0.6%) 1.00 (0.11-8.95) 1.31 (0.14-12.66) 1.04 (0.12-9.41)

Other APH 19 (10.8%) 77 (10.9%) 0.99 (0.58-1.68) 0.98 (0.56-1.72) 0.96 (0.56-1.65)

Previous miscarriage 18 (10.2%) 103 (14.6%) 0.67 (0.39-1.13) 0.83 (0.48-1.43) 0.70 (0.41-1.19)

Preterm birth 24 (13.6%) 47 (6.7%) 2.23 (1.31-3.79) 2.09 (1.16-3.76) 2.23 (1.29-3.85)

Low birthweight 17 (9.7%) 38 (5.4%) 1.87 (1.03-3.39) 1.81 (0.94-3.45) 1.78 (0.97-3.28)

Low apgar at 1 minute 30 (17.1%) 107 (15.4%) 1.14 (0.73-1.78) 1.14 (0.71-1.84) 1.15 (0.73-1.81)

Low apgar at 5 minutes 8 (4.6%) 7 (1.0%) 5.01 (1.73-14.54) 4.91 (1.46-16.51) 5.70 (1.93-16.78)

Delivery by caesarean 55 (31.3%) 143 (20.4%) 1.77 (1.23-2.56) 2.25 (1.50-3.36) 2.07 (1.41-3.05)

Instrumental delivery 26 (14.8%) 144 (20.5%) 0.66 (0.41-1.04) 0.68 (0.41-1.13) 0.67 (0.42-1.08)

Intrauterine Growth

Restriction 23 (13.4%) 71 (10.3%) 1.41 (0.85-2.36) 1.20 (0.68-2.12) 1.35 (0.80-2.23)

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Table 3. Odds ratios from multivariable model

*All variables adjusted for maternal age and smoking and for other variables in the model

Statistically significant odds ratios are shown in bold.

Perinatal factors OR (95%CI) from multivariable model – listwise deletion* OR (95% CI) from multivariable model – imputation of missing

value*

Preeclampsia 1.56 (0.68-3.59) 1.55 (0.70-3.44)

Placenta praevia 1.64 (0.32-8.34) 1.65 (0.32-8.43)

Preterm birth 1.60 (0.76-3.37) 1.85 (0.92-3.72)

Low birthweight 1.00 (0.44-2.28) 0.90 (0.41-1.97)

Low apgar at 5 minutes 3.91 (1.13-13.61) 4.59 (1.52-13.87)

Delivery by caesarean 2.11 (1.38-3.23) 1.95 (1.30-2.92)

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Table 4. Distribution of sites of cancer

Cancer site No. %

C22 – Liver and intrahepatic bile ducts 2 1.14

C34 – Bronchus and lung 2 1.14

C41 – Bone and articular cartilage of other and unspecified sites 10

5.68

C49 – Other connective and soft tissue 7

3.98

C52 – Vagina 5 2.84

C56 – Ovary 3 1.70

C62 – Testis 12 6.82

C64 – Kidney except renal pelvis 7 3.98

C69 – Eye and adnexa 6 3.41

C71 – Brain 27

15.34

C72 – Spinal cord, cranial nerves, other CNS 3 1.70

C74 – Adrenal gland 6

3.41

C75 – Other endocrine glands and related structures 4

2.27

C76 – Other and ill-defined sites 2 1.14

C83 – Diffuse non-Hodgkin’s lymphoma 3 1.70

C85 – Other and unspec. non-Hodgkin’s 2 1.14

C91 – Lymphoid Leukaemia 37 21.02

C92 – Myeloid leukaemia 10 5.68

C94 – Other leukaemias of specified cell type 2 1.14

D32 - Meninges 3 1.70

D40 – Uncertain/uknown bhvr male genital 2 1.14

D43 – Uncertain/unknown bhvr. brain and CNS 2 1.14

D44 – Uncertain/unknown bhvr. endocrine 1 0.57

D47 – Uncertain/uknown bhvr. of lymphoid, haematopoietic and related tissue 9

5.11

D48 – Uncertain/unknown bhvr. unknown sites 9 5.11

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Maternal and Perinatal Risk Factors for Childhood Cancer: Record Linkage Study

Sohinee Bhattacharya1* Marcus Beasley1 Dong Pang2 Gary J Macfarlane1

1Epidemiology Group, Division of Applied Health Sciences, University of Aberdeen 2 Institute of Health Research, University of Bedfordshire, Luton

*Corresponding author: Sohinee Bhattacharya

Dugald Baird Centre for Research on Women’s Health Aberdeen Maternity Hospital

Aberdeen AB25 2ZL

Tel: +44 1224 438441 e-mail: [email protected]

Running title: Risk factors for childhood cancer

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What is already known on this topic

Extremes of maternal age at delivery, parental smoking, preterm birth and low birthweight

have all been reported to be risk factors for childhood cancer.

What this study adds

The large effect of delivery by caesarean section on the increased risk of childhood cancer is

a novel finding in this study.

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Abstract Objective: To investigate maternal and perinatal risk factors for childhood cancer.

Study Design: Case control analysis of linked records from the Aberdeen Maternity and

Neonatal Databank with the Scottish Cancer Registry and the General Registry of Births and

Deaths in Scotland was carried out.

Setting: Aberdeen, Scotland

Participants: Cases (n=176) comprised children diagnosed with cancer under 15 years or

recorded as having died of cancer. Four controls per case were matched by age and gender.

Risk factors tested: Maternal age, BMI, social class, marital status and smoking as well as

preeclampsia, antepartum haemorrhage and previous miscarriage, gestational age,

birthweight, and Apgar scores were compared between groups to test for association with

cancer. Odds ratios with 95% Confidence Intervals were calculated using conditional logistic

regression in both univariable and multivariable models.

Results: Of the maternal characteristics tested, mother’s age at delivery {cases mean

28.9(S.D.5.6) years versus controls mean 30.2(S.D4.6), p = 0.002} and smoking status

(38.6% smokers among cases, 29.7% among controls, p=0.034) were found to be different

between groups. Of the perinatal factors tested, low Apgar score at 5 minutes (AOR 4.59,

95% CI 1.52, 13.87) and delivery by caesarean section (AOR 1.95, 95% CI 1.30, 2.92)

showed statistically significant associations with childhood cancer in the multivariable model.

Conclusions: Younger maternal age, maternal smoking, delivery by caesarean section and

low Apgar score at 5 minutes were independently associated with increased risk of

childhood cancer. These general findings should be interpreted with caution as this study did

not have the power to detect any association with individual diagnostic categories of

childhood cancer.

Key words: childhood cancer, perinatal risk factors, smoking, caesarean delivery

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Introduction:

Childhood cancer has been increasing in Scotland. A published report estimates that its

incidence has risen from an age standardised rate of 120 cases per million population in the

time period 1983 to 1987 to 161 cases per million in the period 2003 -20071. The reason for

this increasing trend remains unexplained as the etiopathogenesis of childhood cancer is

poorly understood. As most present in the first few years of life, epidemiologists hypothesize

that prenatal and perinatal exposures may have a part to play in its pathogenesis. The

evidence surrounding this is however, conflicting. While some researchers have found

associations of younger maternal age at delivery2 maternal anaemia3,4, previous history of

miscarriage2,5,6 maternal overweight7, and smoking8, with some childhood cancers, others

have found no such associations9-11. Fetal growth is perhaps the most investigated perinatal

risk factor for childhood cancer7,12,13 ; but the authors report conflicting results. While specific

central nervous system tumours have been found to be associated with intrauterine growth

restriction, the overall risk was small12. Therefore, apart from the associations with Down’s

syndrome and in utero exposure to radiation, research into the maternal and perinatal risk

factors has remained inconsistent, the results limited by small sample sizes and recall or

reporting bias.

Our objective was therefore to investigate maternal and perinatal risk factors for childhood

cancer, specifically to examine the effects of intrauterine growth restriction, preterm birth and

birth asphyxia on the development of childhood cancer in the offspring, taking advantage of

the opportunities offered by record linkage of a cancer registry with a local birth register.

Methods:

Data Sources:

The Aberdeen Maternity and Neonatal Databank (AMND) holds data for all Aberdeen City

births from 1950 to the present, and includes all reproductive events to women resident in a

defined geographical area with a relatively stable population. The AMND records all births

occurring at the Aberdeen Maternity Hospital, the only maternity hospital serving the

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population of Aberdeen city and district. The exposure variables in terms of potential

maternal and perinatal risk factors were derived from the AMND. The Scottish Cancer

Registry has been in existence since 1951 and was complete up to 2010, at the time of the

present analysis. The cases of childhood cancer were identified from this register.

Data Linkage:

All children born between 1993 and 2006 were identified from the AMND. Their records were

linked to the Cancer Registry in Scotland (SMR 06) and the General Registry of Births and

Deaths in Scotland (GRO-S), using deterministic matching. The linkage was carried out by

data analysts from the Information and Services Division of NHS Scotland using Community

Health Index (CHI) numbers. The CHI number is a number unique to all individuals

registered with a general practice in Scotland and recorded in both databases used in this

study. In a small proportion of cases where CHI number was not available (6%), probabilistic

matching using surname, date of birth and postcode was used. After data linkage, all

identifying information, including CHI numbers were removed and an anonymised dataset

was provided for analysis.

Study design:

A case control study design was employed. Cases comprised all children identified as above

from the AMND who were diagnosed with cancer under 15 years of age in Scotland as

recorded in the Scottish Cancer Registry or recorded as having died of cancer. Controls

were selected from the pool of children not diagnosed as having cancer, matched by age

and gender using four controls per case.

Twins and multiple births were excluded as were stillbirths and early neonatal deaths. As

Down’s syndrome is known to be associated with a higher risk of Acute Lymphoblastic

Leukaemia (ALL) as well as Myeloid Leukaemia of Down’s syndrome, all cases of diagnosed

Down’s syndrome were excluded. Moreover, those children who had died of non-cancer

causes prior to their 15th birthday, as identified from GRO-S were also excluded.

Exposure and outcome variables used in the analysis:

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Maternal sociodemographic factors such as age at delivery, body mass index (BMI),

Registrar General’s occupation-based social class, marital status, previous history of

miscarriage and smoking habits were extracted from the AMND. Any complications recorded

during the index pregnancy such as preeclampsia, gestational hypertension, and antepartum

haemorrhage as well as mode of delivery, gestational age at delivery, birthweight,

Standardised Birthweight Score14, and Apgar score at 1 and 5 minutes were also extracted.

Data extractors were blind to the case-control status of the individual children.

The outcome variables obtained from the Cancer Registry in Scotland were in the form of a

binary variable (yes/no) indicating whether or not a cancer record was present and if

present, the site of cancer given as International Classification of Diseases (ICD) codes.

Similarly, death records with up to 10 different causes of death given by ICD codes were

obtained from linking with GRO-S.

Statistical Analysis:

All analyses were conducted using STATA version 11 (STATA Corp, Texas, USA).

Maternal baseline characteristics were compared between children diagnosed with cancer

and controls using independent two-sample t-tests and chi-square tests. Maternal

complications such as gestational hypertension, pre-eclampsia, antepartum haemorrhage

and previous history of miscarriage were compared between the cases and controls using

univariate conditional regression to calculate odds ratios (OR) with 95% confidence intervals

(CI). Similarly, perinatal factors like gestation at birth, birth weight, intrauterine growth

restriction measured by standardised birthweight score, Apgar score at 1 and 5 minutes

were also tested in univariate models for any association with childhood cancer. Then a

multivariable conditional logistic regression model was fitted that included as independent

variables all risk factors tested on univariate analysis. The possibility of cancer subgroup

analysis was considered according to the International Classification of Childhood Cancer,

but the number of cases in each subgroup was too small to warrant this.

Missing data:

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Apart from the variables describing maternal baseline characteristics, the other risk factors

did not have any missing values. There were 18 controls and 1 case with missing smoking

data. The multivariable model was repeated including and excluding the individuals with

missing information. We used two methodological approaches to handle this - listwise

deletion – ie, not including any group where one person in that group has missing data, and

imputation by creation of a missing value (999) so that all cases and controls were included

in the analyses. The odds ratios obtained by both methods are presented.

Ethical considerations:

Approval to carry out the study was obtained from the AMND steering committee and the

Privacy Advisory Committee for the Information Services Division of National Health

Services, Scotland. As the study involved the analysis of routinely collected anonymised

data, formal ethical approval was not required as declared by the North of Scotland

Research Ethics Service.

Results:

There were 62375 deliveries between 1993 and 2006 as identified from the AMND. After

excluding Down’s syndrome cases, twins and multiple births, stillbirths and early neonatal

deaths, there were 60117 children eligible for linkage with the Cancer Registry. It was

possible to link 43591 of these children to the cancer and GRO-S databases. Amongst the

children with linked data, 106 had died of non-cancer causes before they reached the age of

15 and were therefore excluded from the analysis. Of the remainder, 176 were found to have

a record in the Cancer Registry, giving a cumulative incidence rate of childhood cancer up to

15 years of 4.05 per 1000 deliveries. They constituted the cases for the analysis and were

matched in 1:4 ratio by year of birth and sex from the pool of remaining children without any

records of cancer to obtain 704 controls. As D40, D44, D47 and D48 codes in ICD-10 do not

correspond to cancer diagnosis in International Classification of Childhood Cancer (ICCC),

the analyses were repeated excluding these codes.

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Maternal baseline characteristics were compared between cases and matched controls in

Table 1. Of the maternal characteristics tested, mother’s age at delivery (cases mean 28.9

years, s.d. 5.6; controls mean 30.2, s.d. 4.6; p = 0.002) and smoking status (38.6% current

or ex-smokers among cases, 29.7% among controls, p=0.022) were found to be significantly

different between the two groups.

Table 2 presents the unadjusted odds ratios with 95% confidence intervals for all the

perinatal potential risk factors for childhood cancer. Of the factors tested, preterm birth {OR

2.23(1.31 – 3.79)}; low birth weight {OR 1.87(1.03 – 3.39)}, low Apgar score at 5 minutes

{OR 5.01(1.73 – 14.54)} and delivery by caesarean section {OR 1.77(1.23 – 2.56)} were

found to be statistically significant. Subsequently, these factors were adjusted for maternal

age at delivery and smoking. As the maternal smoking variable had some missing data, we

handled this using two approaches – listwise deletion and imputation of a missing value.

After these adjustments, low birthweight no longer remained significant, but the other

associations were strengthened.

After conducting the univariate analyses multivariable models were fitted including maternal

age, smoking status, preeclampsia, placenta praevia, preterm birth, low birthweight, low

Apgar at 5 minutes and delivery by caesarean as independent variables (results in Table 3).

Similar to the previous analyses, we used two methods of listwise deletion and imputation of

the missing value to adjust for smoking status. Of the perinatal factors tested, Apgar score

below 7 at 5 minutes {AOR 3.91, 95% CI 1.13 – 13.61(listwise deletion); AOR 4.59, 95% CI

1.52, 13.87 (imputation)} and delivery by caesarean section {AOR 2.11, 95% CI 1.38, 3.23

(listwise deletion); AOR 1.95, 95% CI 1.30, 2.92 (imputation)} showed statistically significant

associations with childhood cancer in both multivariable models adjusted for maternal age,

smoking and other factors simultaneously included in the models. Preterm birth (delivery

before 37 completed weeks of gestation) and low birth weight defined as a birth weight

below 2500g, showed a significant association in the univariate analysis, but these

associations were no longer significant in the multivariable model. The associations were not

statistically significant on univariate or multivariable analysis between the risk of childhood

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cancer and hypertensive disorders, antepartum haemorrhage, previous history of

miscarriage or IUGR. Unlike the Apgar score at 5 minutes, the score at 1 minute did not

show any association with childhood cancer.

We further investigated the types of preterm delivery (spontaneous or induced) and

caesarean section (elective or emergency) as risk factors for childhood cancer and found

that both spontaneous and induced preterm delivery were significantly associated in the

adjusted model but only delivery by emergency caesarean section remained significant on

subgroup analysis (AOR 1.43, 95% CI 1.20, 2.18). Further, we found that the commonest

indication for caesarean delivery in the babies who were subsequently diagnosed with

cancer was fetal distress (data not shown).

Table 4 shows the distribution of cancer sites in the 176 cases. As this table shows, the

commonest sites were the brain and haemopoietic organs, especially leukaemia, but the

numbers in the subgroups were too small to allow any meaningful analysis.

Discussion:

We aimed to study the maternal and perinatal risk factors at the time of birth associated with

the diagnosis of childhood cancer using record linkage between two high quality registers in

Scotland. We found a positive association between younger maternal age at delivery and

maternal smoking with childhood cancer. In addition, preterm birth before 37 weeks of

gestation, Apgar score below 7 at 5 minutes and delivery by emergency caesarean section

showed statistically significant associations with childhood cancer the last two of which

remained significant in the adjusted models.

Childhood cancer is a rare condition. Case control studies are therefore the most efficient

epidemiological study design to study several risk factors at the time of birth. Cancer

registries across the world have been utilised to identify cases, but finding appropriate

controls remains problematic. Moreover, data collections regarding exposures by means of

interviews or questionnaires are subject to recall and reporting bias. More recently, linkage

of birth registers with cancer registries has been utilised to design large scale cohort studies.

However, the routine data collection is liable to lack sufficiently detailed data regarding

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exposure and potential confounding factors. We have tried to minimise these problems by

linking two high quality registers in Scotland. Previous validation projects have shown these

databases to be 100% complete and over 97% accurate15. Detailed and contemporaneous

recording of obstetric data in the AMND eliminated recall and reporting bias. The large

number of social and demographic variables recorded in the AMND enabled incorporation of

most potential covariates in the analysis. Despite these strengths to our study design, we

were limited by the small number of cases and it is possible that we did not have sufficient

power to detect some weak associations reported previously in the literature. Maternal and

perinatal risk factors for childhood cancer appear to differ by the site of cancer in the

published literature. The number of cases according to site specific cancer diagnosis was

too small in our sample to allow any subgroup analysis. Further, morphology codes were not

available for us to carry out more appropriate groupings of childhood cancers. This, coupled

with the fact that we had to conduct our analyses on all cancers would have made it less

likely for us to find associations that exist with site specific cancers. This could be a major

limitation of the current analysis. There was a single case of cancer that occurred within the

first year of delivery. It is possible that this could be the result of the cancer being already

present at birth.

The association of parental age with the diagnosis of cancer in general as well as in specific

sites has been studied before. Johnson et al16 in a pooled analysis of register linkage data

from several US states, found that the risk of childhood cancer increased with increasing

maternal age, while paternal age appeared to have no effect on the risk. On the other hand

several other studies, similar to the current analysis have shown that younger maternal age

was associated with increased childhood cancer risk2,17. There could be several

explanations for the disparate findings. In a register linkage study carried out in Sweden18,19,

researchers found that advancing maternal age was positively associated with childhood

cancer risk but only in a historical cohort. This association disappeared in a more recent

cohort of women although the reasons for this are unknown. Moreover, Schutz20 suggests

that the association of lower maternal age at the time of delivery with leukaemia in the

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offspring could be explained by non-response bias, although this is not applicable to the

present study.

The relationship between maternal smoking and childhood cancer in the offspring is complex

and controversial. While Sorahan et al21 - 23 and Edraki24 found an increased overall risk of

childhood cancer with paternal cigarette smoking, there did not appear to be an association

with maternal smoking after adjusting for birthweight. Further, Pang et al9 did not find

evidence of smoking as a risk factor for childhood cancer after adjusting for parental age.

Similar associations were reported by Chang et al25 with regard to Acute Lymphoblastic

Leukaemia (ALL). The evidence appears to indicate that neonatal passive smoking plays a

more important role than in utero transfer of maternal smoke related toxins, although we

cannot rule out the possibility of an association between maternal smoking and site-specific

cancers26,27. For the current analysis, we did not have access to data on paternal smoking

habits and the association seen with maternal smoking could be due to this variable acting

as proxy for paternal smoking.

Other associations noted in this study have been reported before – preterm birth28, and low

Apgar score2,28. Li et al found a 46% increased risk of childhood cancer in infants who had a

low 5 minute Apgar score29. Birthweight has received a lot of attention as a risk factor for

childhood cancer. While brain tumours and retinoblastoma appear to be associated with high

birthweight30 - 32 others have found hepatoblastomas7,33 and gliomas34 to be associated with

very low birthweight infants. Schmidt28 et al observed a U-shaped relationship between

birthweight and cancer risk, while Podvin35 found birthweight adjusted for gestational age to

be a better predictor than birthweight alone for the diagnosis of ALL, lending support to our

findings. It is however, important to note, that we did not find an association with intrauterine

growth restriction as measured by the z-score or standardized birthweight score. Dorak et

al36 noted an association between birthweight and a diagnosis of ALL which was gender

dependent, showing a non-linear association in boys.

Few studies have assessed mode of delivery, specifically caesarean delivery, as a possible

risk factor for the development of childhood cancer. Those that have done, have found a

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weak to moderate association 3,7,10,,,37,37 between caesarean delivery and subsequent risk of

developing ALL. Several hypotheses can be developed regarding the biological mechanism

underpinning this association. First, caesarean delivery is likely to be a marker of adverse

pregnancy and delivery events – indeed, our finding of increased emergency caesarean

rates indicated by fetal distress seems to support this hypothesis. However, the association

remained and actually became stronger, after adjusting for most other possible pregnancy

complications. It was customary to use 100% oxygen to resuscitate babies born by

caesarean section in the past. It is possible that this could have played a role in the

subsequent development of cancer. The last explanation involves epigenetic modulations at

birth. Schlinzig et al39 have demonstrated altered DNA-methylation in cord white blood cells

after caesarean delivery and suggested that this may be the basis of increased risk of

asthma, diabetes and ALL seen in infants born by caesarean section.

The association of caesarean delivery with childhood cancer seen in this analysis should be

treated with caution given the small numbers of childhood cancer cases in the study. The

recent NICE guidelines40 recommends caesarean delivery on maternal request. Although,

we have to remember that the majority of the caesarean deliveries seen in the cases of

childhood cancer in the current analysis were emergency procedures with strong indications

such as fetal distress. Our finding of the strong association of childhood cancer with

caesarean delivery warrants further research using record linkage of larger cohorts or

prospective follow up of birth cohorts. From the point of view of Public Health interventions,

the only other modifiable risk factor appears to be parental smoking. Several population

based lifestyle interventions are already underway to reduce the prevalence of smoking in

pregnancy.

Conclusion: We found a positive association between younger maternal age at delivery and

maternal smoking with childhood cancer. In addition, preterm birth, low Apgar score at 5

minutes and delivery by caesarean section showed associations with childhood cancer,

which remained significant even after controlling for various covariates. These general

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findings should be interpreted with caution as this study did not have the power to detect any

association with individual diagnostic categories of childhood cancer.

Conflict of Interest: All authors have completed the Unified Competing Interest form at http://www.icmje.org/coi_disclosure.pdf and declare: NHS Grampian Endowment funded the study; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, a worldwide licence to the Publishers and its licensees in perpetuity, in all forms, formats and media (whether known now or created in the future), to (i) publish, reproduce, distribute, display and store the Contribution, (ii) translate the Contribution into other languages, create adaptations, reprints, include within collections and create summaries, extracts and/or, abstracts of the Contribution, (iii) create any other derivative work(s) based on the Contribution, (iv) to exploit all subsidiary rights in the Contribution, (v) the inclusion of electronic links from the Contribution to third party material where-ever it may be located; and, (vi) licence any third party to do any or all of the above. Contributorship: SB was responsible for designing the study, facilitating data extraction, supervising data analysis and writing of the first draft of the paper; MB analysed the data; SB, GJM and DP conceived of the research idea and GJM was responsible for overall supervision. All authors contributed to the writing of the final draft of the paper. SB is the guarantor of this paper. Ethics: This research proposal was approved by the Privacy Advisory Committee of the Information and Services Division NHS Scotland and the steering group of the Aberdeen Maternity and Neonatal Databank. Formal ethical approval was not considered necessary by North of Scotland Research Ethics Service as only anonymised data were analysed in this study. Funding: This research was funded by the NHS Grampian Endowment Fund (Project no. 10/15) Role of sponsors: The University of Aberdeen acted as sponsors for this research project, but the findings and their interpretation in this study are the authors’ own. Independence of authors from funders: All authors were employed by the University of Aberdeen at the time of conducting this research and are independent from the funders. Data sharing: No additional data available for sharing.

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Table 1. Comparison of maternal baseline characteristics between case children and control children

Characteristics Cases Controls p-

value

Age at delivery (mean, s.d.) 28.9 (5.6) 30.2 (4.6) 0.002

Maternal social class

Manual 26 (14.8%) 79 (11.2%)

0.187 Non-Manual 62 (35.2%) 295 (41.9%)

Single/widowed 87 (49.4%) 325 (46.2%)

Missing 1 (0.6%) 5 (0.7%)

Paternal social class

Paternal Manual 71 (40.3%) 329 (46.7%)

0.193 Paternal Non-manual 47 (26.7%) 183 (26.0%)

Maternal non-manual 57 (32.4%) 184 (26.1%)

Missing 1 (0.6%) 8 (1.1%)

Marital status

Single/Widowed/Divorced/Separated/ 62 (35.2%) 222 (31.5%) 0.324

Married 113 (64.2%) 482 (68.4%)

Missing 1 (0.6%) 0 (0%)

BMI (mean, s.d.) (Missing cases = 12, Missing controls = 39) 25.2 (5.1) 25.5 (5.1) 0.407

Smoking

Non-smoker 107 (60.8%) 477 (67.8%) 0.034

Smoker/ex-smoker 68 (38.6%) 209 (29.7%)

Missing 1 (0.6%) 18 (2.6%)

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Perinatal factors Cases N=176 Controls N=704 Unadjusted odds ratio

(95% CI)

Age and smoking adjusted

odds ratio (95% CI) – listwise

deletion

Age and smoking adjusted

odds ratio (95% CI) –

imputation of missing value

Preeclampsia 11 (6.3%) 23 (3.3%) 1.98 (0.94-4.18) 1.94 (0.88-4.28) 1.92 (0.91-4.09)

Gestational hypertension 19 (10.8%) 71 (10.1%) 1.09 (0.62-1.89) 1.21 (0.67-2.17) 1.13 (0.64-2.01)

Placenta praevia 3 (1.7%) 4 (0.6%) 3.00 (0.67-13.40) 3.46 (0.76-15.65) 3.45 (0.76-15.62)

Abruption 1 (0.6%) 4 (0.6%) 1.00 (0.11-8.95) 1.31 (0.14-12.66) 1.04 (0.12-9.41)

Other APH 19 (10.8%) 77 (10.9%) 0.99 (0.58-1.68) 0.98 (0.56-1.72) 0.96 (0.56-1.65)

Previous miscarriage 18 (10.2%) 103 (14.6%) 0.67 (0.39-1.13) 0.83 (0.48-1.43) 0.70 (0.41-1.19)

Preterm birth 24 (13.6%) 47 (6.7%) 2.23 (1.31-3.79) 2.09 (1.16-3.76) 2.23 (1.29-3.85)

Low birthweight 17 (9.7%) 38 (5.4%) 1.87 (1.03-3.39) 1.81 (0.94-3.45) 1.78 (0.97-3.28)

Low apgar at 1 minute 30 (17.1%) 107 (15.4%) 1.14 (0.73-1.78) 1.14 (0.71-1.84) 1.15 (0.73-1.81)

Low apgar at 5 minutes 8 (4.6%) 7 (1.0%) 5.01 (1.73-14.54) 4.91 (1.46-16.51) 5.70 (1.93-16.78)

Delivery by caesarean 55 (31.3%) 143 (20.4%) 1.77 (1.23-2.56) 2.25 (1.50-3.36) 2.07 (1.41-3.05)

Instrumental delivery 26 (14.8%) 144 (20.5%) 0.66 (0.41-1.04) 0.68 (0.41-1.13) 0.67 (0.42-1.08)

Intrauterine Growth

Restriction 23 (13.4%) 71 (10.3%) 1.41 (0.85-2.36) 1.20 (0.68-2.12) 1.35 (0.80-2.23)

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Table 2. Comparison of perinatal factors between cases and controls with statistically significant odds ratios shown in bold

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Table 3. Odds ratios from multivariable model

*All variables adjusted for maternal age and smoking and for other variables in the model

Statistically significant odds ratios are shown in bold.

Perinatal factors OR (95%CI) from multivariable model – listwise deletion* OR (95% CI) from multivariable model – imputation of missing

value*

Preeclampsia 1.56 (0.68-3.59) 1.55 (0.70-3.44)

Placenta praevia 1.64 (0.32-8.34) 1.65 (0.32-8.43)

Preterm birth 1.60 (0.76-3.37) 1.85 (0.92-3.72)

Low birthweight 1.00 (0.44-2.28) 0.90 (0.41-1.97)

Low apgar at 5 minutes 3.91 (1.13-13.61) 4.59 (1.52-13.87)

Delivery by caesarean 2.11 (1.38-3.23) 1.95 (1.30-2.92)

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Table 4. Distribution of sites of cancer

Cancer site No. %

C22 – Liver and intrahepatic bile ducts 2 1.14

C34 – Bronchus and lung 2 1.14

C41 – Bone and articular cartilage of other and unspecified sites 10

5.68

C49 – Other connective and soft tissue 7

3.98

C52 – Vagina 5 2.84

C56 – Ovary 3 1.70

C62 – Testis 12 6.82

C64 – Kidney except renal pelvis 7 3.98

C69 – Eye and adnexa 6 3.41

C71 – Brain 27

15.34

C72 – Spinal cord, cranial nerves, other CNS 3 1.70

C74 – Adrenal gland 6

3.41

C75 – Other endocrine glands and related structures 4

2.27

C76 – Other and ill-defined sites 2 1.14

C83 – Diffuse non-Hodgkin’s lymphoma 3 1.70

C85 – Other and unspec. non-Hodgkin’s 2 1.14

C91 – Lymphoid Leukaemia 37 21.02

C92 – Myeloid leukaemia 10 5.68

C94 – Other leukaemias of specified cell type 2 1.14

D32 - Meninges 3 1.70

D40 – Uncertain/uknown bhvr male genital 2 1.14

D43 – Uncertain/unknown bhvr. brain and CNS 2 1.14

D44 – Uncertain/unknown bhvr. endocrine 1 0.57

D47 – Uncertain/uknown bhvr. of lymphoid, haematopoietic and related tissue 9

5.11

D48 – Uncertain/unknown bhvr. unknown sites 9 5.11

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