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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
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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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References:
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3. Bluhm E, McNeil DE, Cnattingius S, et al. Prenatal and perinatal risk factors for
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7. McLaughlin CC, Baptiste MS, Schymura MJ et al. Birth weight, maternal weight and
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9. Pang D, Birch JM. Reply: Smoking and hepatoblastoma: confounding by birth
weight? Br J of Cancer. 2003; 89: 603-603.
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with Non-Hodgkin's lymphoma among children. Int J of Cancer. 1996; 65:774-777.
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
tumours and lymphomas in Western Australia. Int J Cancer 2008;123:436-443.
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leukaemia in the Jerusalem Perinatal Study cohort. Can Epi Bio Prev 2004; 13: 1057
- 1064.
14. Campbell D, Hall M, Lemon J, et al. Clinical birthweight standards for a total
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15. Cole, S. Scottish maternity and neonatal records, 8th Study Group of the Royal
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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-
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 -
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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12. Milne E, Laurvick CL, Blair E et al. Fetal growth and the risk of childhood CNS
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20. Schüz J. Non-response bias as a likely cause of the association between young
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35. Cnattingius S, Zack M, Ekbom A et al. Prenatal and neonatal risk factors for
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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
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Title page
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Maternal and perinatal risk factors for childhood cancer
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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35. Cnattingius S, Zack M, Ekbom A et al. Prenatal and neonatal risk factors for
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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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2. Johnson KJ, Puumala SE, Soler JT et al. Perinatal characteristics and the risk of
neuroblastoma. Int J of Cancer. 2008; 123: 1166- 1172.
3. Bluhm E, McNeil DE, Cnattingius S, et al. Prenatal and perinatal risk factors for
neuroblastoma. Int J of Cancer. 2008; 123: 2885 - 2890.
4. Roman E, Simpson J, Ansell P et al. Perinatal and reproductive factors: A report on
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5. Cantwell MM, Forman MR, Middleton RJ et al. Association of early life factors and
brain tumour risk in a cohort study. Br J of Cancer. 2008; 99:796-799.
6. Mallol-Mesnard N, Menegaux F, Lacour B et al. Birth Characteristics and childhood
malignant central nervous system tumours: The ESCALE study. Cancer Det Prev.
2008; 32: 79 - 86.
7. McLaughlin CC, Baptiste MS, Schymura MJ et al. Birth weight, maternal weight and
childhood leukaemia. Br J of Cancer. 2006; 94: 1738 - 1744.
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with parental smoking and alcohol consumption prior to conception and during
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9. Pang D, Birch JM. Reply: Smoking and hepatoblastoma: confounding by birth
weight? Br J of Cancer. 2003; 89: 603-603.
10. Adami J, Glimelius B, Cnattingius S et al. Maternal and perinatal factors associated
with Non-Hodgkin's lymphoma among children. Int J of Cancer. 1996; 65:774-777.
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
tumours and lymphomas in Western Australia. Int J Cancer 2008;123:436-443.
13. Paltiel O, Harlap s, Deutsch L et al. Birth weight and other risk factors for acute
leukaemia in the Jerusalem Perinatal Study cohort. Can Epi Bio Prev 2004; 13: 1057
- 1064.
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
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
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 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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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
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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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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1
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.
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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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References:
1. Information and Services Division, NHS Scotland. Cancer Incidence and Mortality
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2. Johnson KJ, Puumala SE, Soler JT et al. Perinatal characteristics and the risk of
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3. Bluhm E, McNeil DE, Cnattingius S, et al. Prenatal and perinatal risk factors for
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4. Roman E, Simpson J, Ansell P et al. Perinatal and reproductive factors: A report on
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5. Cantwell MM, Forman MR, Middleton RJ et al. Association of early life factors and
brain tumour risk in a cohort study. Br J of Cancer. 2008; 99:796-799.
6. Mallol-Mesnard N, Menegaux F, Lacour B et al. Birth Characteristics and childhood
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7. McLaughlin CC, Baptiste MS, Schymura MJ et al. Birth weight, maternal weight and
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8. MacArthur AC, McBride ML, Spinelli JJ et al. Risk of childhood leukaemia associated
with parental smoking and alcohol consumption prior to conception and during
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9. Pang D, MacNally R, Birch JM. Parental smoking and childhood cancer: results from
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Smoking and hepatoblastoma: confounding by birth weight? Br J of Cancer. 2003;
88(3)9: 373 - 381603-603.
10. Adami J, Glimelius B, Cnattingius S et al. Maternal and perinatal factors associated
with Non-Hodgkin's lymphoma among children. Int J of Cancer. 1996; 65:774-777.
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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.
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.
13. Paltiel O, Harlap s, Deutsch L et al. Birth weight and other risk factors for acute
leukaemia in the Jerusalem Perinatal Study cohort. Can Epi Bio Prev 2004; 13: 1057
- 1064.
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
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.
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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.
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.
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.
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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.
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.
36. Dorak MT, Pearce MS, Hammal DM et al. Examination of gender effect in birthweight
and miscarriage associations with childhood cancer (United Kingdom). Cancer
Causes Control 2007; 18: 219 – 228.
34.
35.37. 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.
36.38. 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.
37.39. 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.
38.40. National Institute for Health and Clinical Excellence. CG132 Caesarean
Section. Available at: http://guidance.nice.org.uk/CG132 [accessed March 2012].
Formatted: No bullets or numbering
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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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12. Milne E, Laurvick CL, Blair E et al. Fetal growth and the risk of childhood CNS
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20. Schüz J. Non-response bias as a likely cause of the association between young
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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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35. Cnattingius S, Zack M, Ekbom A et al. Prenatal and neonatal risk factors for
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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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7. McLaughlin CC, Baptiste MS, Schymura MJ et al. Birth weight, maternal weight and
childhood leukaemia. Br J of Cancer. 2006; 94: 1738 - 1744.
8. MacArthur AC, McBride ML, Spinelli JJ et al. Risk of childhood leukaemia associated
with parental smoking and alcohol consumption prior to conception and during
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9. Pang D, Birch JM. Reply: Smoking and hepatoblastoma: confounding by birth
weight? Br J of Cancer. 2003; 88(3)9: 373 - 381603-603.
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with Non-Hodgkin's lymphoma among children. Int J of Cancer. 1996; 65:774-777.
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
tumours and lymphomas in Western Australia. Int J Cancer 2008;123:436-443.
13. Paltiel O, Harlap s, Deutsch L et al. Birth weight and other risk factors for acute
leukaemia in the Jerusalem Perinatal Study cohort. Can Epi Bio Prev 2004; 13: 1057
- 1064.
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
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
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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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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low birth weights. Pediatrics 2009;124:96-104.
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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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