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Maternal and Child Health Journal ISSN 1092-7875 Matern Child Health JDOI 10.1007/s10995-015-1758-2

The Effects of Maternal Mortality on Infantand Child Survival in Rural Tanzania: ACohort Study

Jocelyn E. Finlay, Corrina Moucheraud,Simo Goshev, Francis Levira, SigilbertMrema, David Canning, HonoratiMasanja, et al.

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The Effects of Maternal Mortality on Infant and Child Survivalin Rural Tanzania: A Cohort Study

Jocelyn E. Finlay1 • Corrina Moucheraud2 • Simo Goshev3 • Francis Levira4 •

Sigilbert Mrema4 • David Canning1,2 • Honorati Masanja4 • Alicia Ely Yamin2

� Springer Science+Business Media New York 2015

Abstract

Objectives The full impact of a maternal death includes

consequences faced by orphaned children. This analysis

adds evidence to a literature on the magnitude of the

association between a woman’s death during or shortly

after childbirth, and survival outcomes for her children.

Methods The Ifakara and Rufiji Health and Demographic

Surveillance Sites in rural Tanzania conduct longitudinal,

frequent data collection of key demographic events at the

household level. Using a subset of the data from these sites

(1996–2012), this survival analysis compared outcomes for

children who experienced a maternal death (42 and

365 days definitions) during or near birth to those children

whose mothers survived.

Results There were 111 maternal deaths (or 229 late

maternal deaths) during the study period, and 46.28 % of

the index children also subsequently died (40.73 % of

children in the late maternal death group) before their

tenth birthday—a much higher prevalence of child mor-

tality than in the population of children whose mothers

survived (7.88 %, p value \0.001). Children orphaned by

early maternal deaths had a 51.54 % chance of surviving

to their first birthday, compared to a 94.42 % probability

for children of surviving mothers. A significant, but

lesser, child survival effect was also found for paternal

deaths in this study period.

Conclusions The death of a mother compromises the sur-

vival of index children. Reducing maternal mortality through

improved health care—especially provision of high-quality

skilled birth attendance, emergency obstetric services and

neonatal care—will also help save children’s lives.

Keywords Maternal mortality � Infant mortality �Survival analysis � Orphanhood � Tanzania � Cohort study

Significance

Maternal mortality remains a global challenge: approxi-

mately 289,000 maternal deaths occurred in 2013, and

the maternal mortality ratio in developing countries is 14

times greater than in developed regions. The full toll of

maternal mortality extends beyond such aggregate num-

bers, however, as the death of a mother can have detri-

mental effects on the survival of her children. In two

rural communities in Tanzania, an infant orphaned within

42 days of birth had a probability of surviving to 1 year

of only 51.5 %. If a child survived to one month fol-

lowing the death of its mother, their survival probability

to one year increased to 67.7 %. These results suggest

that child survival probability is severely diminished if

the mother dies, and the infant mortality risk is con-

centrated in the early months.

Electronic supplementary material The online version of thisarticle (doi:10.1007/s10995-015-1758-2) contains supplementarymaterial, which is available to authorized users.

& Jocelyn E. Finlay

jfinlay@hsph.harvard.edu

1 Harvard Center for Population and Development Studies,

Harvard University, Cambridge, MA, USA

2 Department of Global Health and Population, Harvard School

of Public Health, Boston, MA, USA

3 Institute for Quantitative Social Science, Harvard University,

Cambridge, MA, USA

4 Ifakara Health Institute, Ifakara, Tanzania

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Introduction

Maternal mortality remains a global challenge: approxi-

mately 289,000 maternal deaths occurred in 2013, and the

maternal mortality ratio in developing countries is 14 times

greater than in developed regions [1]. The full toll of

maternal mortality extends beyond such aggregate numbers,

however, as the death of a mother can have detrimental

effects on the survival of her children. The fourth and fifth

Millennium Development Goals—to reduce child mortality

and to improve maternal health—are thus linked, and this

analysis aims to contribute to the emerging body of evidence

around this association. Improvements in childhood mor-

tality have been slowest among infants [2], so it is critically

important to better understand how to reduce this burden.

Infant outcomes are directly related to maternal mor-

tality via obstetric complications. Key risk factors for death

of a mother during the intrapartum period—including

hemorrhage, obstructed labor and sepsis [3]—are also

associated with increased risk of neonatal mortality [4–7].

Additionally, a maternal orphaned infant sees increased

mortality risk following lack of breastfeeding: directly via

malnutrition, and indirectly due to increased susceptibility

to infection [8, 9]. In recent qualitative work from Tanza-

nia, girls who were orphaned following a maternal death

were particularly vulnerable to undernourishment (in

infancy and beyond), and faced compromised health care

as well as education-related challenges [10].

The adverse effects of orphanhood can also extend into

later childhood, via increased risk of child labor, lower

educational attainment, and disrupted living arrangements

[11–14]. Additionally, households may experience eco-

nomic challenges following a maternal death, and some

authors have shown the long-term impacts on health and

well-being [15–17].

The spillover effects of a maternal death on family and

community is the focus within the literature and authors

quantify the magnitude of this effect. Previous research has

explored the effect of maternal mortality on child survival

in Bangladesh [18], Benin [19], Haiti [20], Kenya [21] and

South Africa [22]. An earlier analysis that incorporated

data from Tanzania and the authors found an elevated risk

of child mortality during the 2-year period surrounding a

maternal death, but did not isolate the risk attributable to

maternal mortality alone [23].

This research applies survival analysis methods to assess

child outcomes following a mother’s death in rural Tan-

zania. We examine maternal mortality defined as occurring

within 42 days of childbirth, as well as an expanded defi-

nition that includes deaths up to 365 after childbirth.

Additionally, we examine the impact of paternal deaths. By

using a longitudinal dataset with information collected

frequently at the household level, infants whose mothers

died during or shortly after their birth can be tracked over a

long period of time, and their survival outcomes can be

compared with outcomes of children born during the same

period but whose mothers survived childbirth and through

the end of the study period. This comparison aims to isolate

the potential effect of a maternal death—during or shortly

after childbirth—on infant and child survival in two rural

communities in Tanzania.

Methods

Study Setting and Data Collection

The datasets used in this analysis are from two comparable

Health and Demographic Surveillance System (HDSS)

sites in rural Tanzania: Ifakara and Rufiji. The Ifakara site

is located approximately 400 km west of Dar es Salam, and

the Rufiji site is approximately 200 km south of Dar es

Salam. All households in each community participate in

quarterly censuses, providing information on births, deaths

and migration. All individuals who migrate out of study

communities are lost to follow-up, unless they return for a

subsequent census. Migration within the study sites is

tracked throughout data collection. The sample from Ifa-

kara includes all births between September 14, 1996 and

December 14, 2012; the Rufiji sample includes all births

between January 1, 1999 and December 31, 2010.

Ethical Clearance

Approval to conduct this study using de-identified data

administered by the Ifakara Health Institute was granted by

the Harvard T.H. Chan School of Public Health Office of

Human Research Administration, Protocol #CR-21805-02,

and the Ifakara Health Institute Institutional Review Board,

IHI/IRB/No: 31-2012. At the time of interview, the indi-

viduals provided written consent to the Ifakara Health

Institute to conduct the survey.

Variable Definition

The frequency of data collection at the Tanzania HDSS

sites enables a time-based definition of maternal mortality:

a death was classified as maternal if it occurred within

42 days of childbirth. Likewise, the expanded definition of

late maternal death includes deaths occurring up to

365 days postpartum [1], and that classification is used

here as well, and are referred to as ‘‘early’’ and ‘‘late’’

maternal deaths throughout the manuscript. By definition,

all women who are included in the early group (42-day) are

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also included in the late group (365-day). Although deaths

during pregnancy are included in the ICD-10 definition of

maternal mortality, such deaths were not included here,

since these events and their timing would be subject to

recall and measurement bias. Paternal orphanhood was

included whenever a father’s death preceded that of his

child, irrespective of child’s age. Mother’s educational

attainment was measured at baseline. Household assets

were assessed at baseline, and principal component anal-

ysis was used to categorize households into wealth quin-

tiles [24].

The ‘‘index child’’ is an infant whose birth was associ-

ated with the maternal death and whose birthdate was used

as the reference point for the 42- or 365-day window.

‘‘Non-index children’’ are the older siblings of this index

child, born to the same mother. Note the dataset only

includes children born during the study period, not all

children who may have been born previously to women in

the sample. All outcomes (beyond Table 1) are reported for

the index children of maternal deaths only. Child survival

was examined both dichotomously (alive vs. deceased),

and as a censored continuous variable (days from birth

until death, out-migration, or end of study period).

Statistical Methods

To examine the empirical link between a maternal death

and child survival, we first outline the descriptive break-

down of the number of maternal deaths, the number of

index children, and where these children are at the time of

interview (Table 1). We plot the maternal deaths across

time within the study period, and in the case of a suc-

ceeding child death we map the time-lapse between the

maternal death and the child death (Figs. 1, 2). We then

Table 1 Characteristics of

mothers and children in the

Ifakara and Rufiji cohorts

Group Status n %

Early maternal deaths

Maternal death within 42 days (number of women),

n = 111

Index children (number of children), n = 121 Deceased 56 46.28

Survived 24 19.83

Out-migrated 41 33.88

Non-index children, n = 47 Deceased 10 21.28

Survived 21 44.68

Out-migrated 16 34.04

Non-maternal deaths, n = 843

Children, n = 1173 Deceased 364 31.03

Survived 380 32.40

Out-migrated 429 36.57

Surviving women, n = 45,623

Children, n = 76,365 Deceased 6014 7.88

Survived 46,752 61.22

Out-migrated 23,599 30.90

Late maternal deaths

Maternal death within 365 days,

n = 229

Index children, n = 248 Deceased 101 40.73

Survived 61 24.60

Out-migrated 86 34.68

Non-index children, n = 121 Deceased 28 23.14

Survived 53 43.80

Out-migrated 40 33.06

Non-maternal deaths, n = 775

Children, n = 1046 Deceased 319 30.50

Survived 343 32.79

Out-migrated 384 36.71

Surviving women, n = 45,671

Children, n = 76,362 Deceased 6014 7.88

Survived 46,750 61.22

Out-migrated 23,598 30.90

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consider the characteristics of women, and whether there is

a significant difference between the characteristics of the

women who die and the women who survive (Table 2). In

Table 3 we collate the raw data illustrated in Figs. 1 and 2,

and calculate the cumulative probability of survival to a

specified month conditional on survival to a specified

month. Row one, ‘‘at birth’’ is the numbers corresponding

to the survival curve illustrated in Figs. 3 and 4. The sec-

ond row, ‘‘1 month’’ answers the question, given the child

survived to 1 month, what is the probability of survival to

5 months? We also represent the child survival probability

following a paternal death, and Table 4 provides the fig-

ures behind Fig. 5. Child mortality outcomes were ana-

lyzed using Kaplan–Meier survival analysis. Mortality

rates for children were calculated, and statistically com-

pared (conditional on mother’s survival status) using a

Poisson regression, with robust standard errors to adjust for

multiple births per mother. Adjusted mortality rate ratios

included covariates for child sex, twinship, mother’s age,

mother’s educational attainment, and household wealth.

Confidence intervals are reported at the 95 % level. All

analyses were conducted using Stata v12.1 (StataCorp

2014).

All main results reported here are for the two sites

combined datasets. Site differences were statistically tes-

ted, for exposure and outcome variables, as well as possible

covariates—and no significant differences were found, so

the data were pooled for greater statistical power. Site-

specific summary statistics and comparative p values are

provided in supplementary files, and noted throughout the

‘‘Results’’ section as such.

Results

During the study period, 111 women died within 42 days

of childbirth; these women gave birth to 121 children, of

whom 46.28 % died before the end of the study period—

which was a higher mortality percentage than that among

children orphaned beyond 42 days (i.e., not attributed as

maternal deaths), and was much higher than that among

children with surviving mothers (p values\0.001 for both

050

100

150

Wom

an li

ne n

umbe

r

01jan1997 01jan1998 01jan1999 01jan2000 01jan2001 01jan2002 01jan2003 01jan2004 01jan2005 01jan2006 01jan2007 01jan2008 01jan2009 01jan2010 01jan2011 01jan2012

Ifakara: Maternal Death Date Rufiji: Maternal Death Date

Ifakara: Maternal then Child Death Data Rufiji: Maternal then Child Death Data

Fig. 1 Time between death of mother and death of children—women with early maternal death (within 42 days of childbirth)

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differences). Likewise, in the late-maternal death group

(i.e., up to 365 days postpartum), 40.73 % of the 248

infants died, which was a higher proportion of deaths than

among children orphaned for non-maternal reasons and

among children with surviving mothers (p values \0.001

for both). The prevalence of out-migration was not statis-

tically different for any subgroup (p values [0.2 for all).

The p values for the statistical comparisons are not reported

in Table 1 and only in the text here. Site-specific mortality

values are provided in Supplementary Tables 1 and 2 for

Ifakara and Rufiji, respectively; results of statistical tests of

differences between these values are in Supplementary

Table 3.

For women who died within 42 days of delivery (and

365 days), and for children who died following a maternal

death, the time lapse between these events is shown in

Figs. 1 and 2. Results from Ifakara are presented in blue

and Rufiji is displayed in red. Maternal deaths with sub-

sequent survival of the index child are marked as an ‘‘x’’ at

the date of the mother’s death. Maternal deaths followed by

the death of the index child is marked as two solid circles,

one for each date of death, and joined by a line. The dis-

tance of the line thus represents time between the mother’s

and the child’s deaths. Maternal deaths, with and without

subsequent child mortality, occurred throughout the study

period. As shown in Fig. 1, infants born to women who

experienced an early maternal death were particularly

likely to die soon thereafter; among late maternal deaths

(shown in Fig. 2), a greater number of orphans had longer

durations of survival.

Characteristics of mothers and of children born during

the study period are presented in Table 2. We test whether

the fraction of women in each category are the same for the

two groups of women: women who die and women who

survive. Women who experienced a maternal death, par-

ticularly shortly after birth (42-day window) were more

commonly adolescents than their surviving counterparts

(p = 0.01), which corresponds to a period of known higher

maternal mortality risk [25]. There was not a strong cor-

relation between household wealth and maternal death, and

the fraction poorest and richest within the two groups of

women were not statistically different (p value = 0.968 for

050

100

150

200

250

Wom

an li

ne n

umbe

r

01jan1997 01jan1998 01jan1999 01jan2000 01jan2001 01jan2002 01jan2003 01jan2004 01jan2005 01jan2006 01jan2007 01jan2008 01jan2009 01jan2010 01jan2011 01jan2012

Ifakara: Maternal Death Date Rufiji: Maternal Death Date

Ifakara: Maternal then Child Death Data Rufiji: Maternal then Child Death Data

Fig. 2 Time between death of mother and death of children—women with late maternal death (within 365 days of childbirth)

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poorest, 0.16 for richest). More boys than girls were born

during this period, which corresponds to general trends of

sex ratios at birth [1, but the gender mix was not statis-

tically different between the two groups of women

(p value = 0.12). Teenage women were not more vulner-

able to late-maternal death (p value 0.5862), but older

women were (p value = 0.0974). There was no significant

difference in the distribution of wealth amongst women

who died a late-maternal death and those who survived.

Table 3 presents survival probabilities for children born

to a woman with a maternal death (early or late definition)

as well as for children whose mothers survived. In cases of

a maternal death, whether early or late, neonates faced far

worse survival probabilities over childhood. As shown in

the first row of each section in Table 3 (‘‘At birth’’), an

infant orphaned within 42 days of birth had a probability of

surviving to 1 year of only 51.5 % (40.2 % for late

maternal deaths), and likelihood of only 46.4 % (33.0 %

for late maternal deaths) for surviving to age 5—compared

with probabilities over 90 % for infants whose mothers

survived childbirth. The cumulative survival probabilities

at birth are also displayed graphically in Figs. 3 and 4;

when tested statistically with a log-rank test, the survival

trajectory for children orphaned by maternal death was

significantly worse than that of children whose mothers

survived (p\ 0.001).

However, if an orphaned infant survived the neonatal

period, its chances of survival through infancy and child-

hood increased (though were still lower than their peers

whose mothers survived). Rows two, three and four of

Table 3 display these conditional cumulative survival

probabilities. If a child survived to 1 month, their survival

probability to 1 year increased to 67.7 % for children of

early maternal deaths; and, conditional on survival to

6 months, index children of early maternal deaths had a

94.6 % chance of survival to 1 year.

To explore whether poor survival outcomes were due to

general orphanhood versus maternal-specific loss, survival

outcomes were examined for children who experienced a

paternal death versus children whose fathers survived.

Table 4 shows the cumulative survival probability, from

birth to 10 years, for these two groups. Comparing these

Table 2 Characteristics of mothers and children in the Ifakara and Rufiji cohorts

Mothers—n Early maternal deaths (42 days) p value Late maternal deaths (365 days) p value

Maternal death Mother survived Maternal death Mother survived

111 45,623 H0:

xi(death) = xi(survived)

229 45,671 H0:

xi(death) = xi(survived)

Mother’s age at most recent childbirth (years)

\20 26 (23.4 %) 6786 (14.9 %) 0.0115 37 (16.2 %) 6793 (14.9 %) 0.5862

20–24 21 (18.9 %) 10,591 (23.2 %) 0.2843 47 (20.5 %) 10,603 (23.2 %) 0.3357

25–29 17 (15.3 %) 9999 (21.9 %) 0.093 46 (20.1 %) 10,012 (21.9 %) 0.5032

30–34 26 (23.4 %) 7498 (16.4 %) 0.0473 57 (24.9 %) 7506 (16.4 %) 0.0006

35–39 12 (10.8 %) 5341 (11.7 %) 0.7693 23 (10.0 %) 5348 (11.7 %) 0.4340

40? 9 (8.1 %) 5408 (11.9 %) 0.2226 19 (8.3 %) 5409 (11.8 %) 0.0974

Household asset group (at baseline)

Poorest 15 (13.5 %) 6225 (13.6 %) 0.968 31 (13.5 %) 6230 (13.6 %) 0.9635

Poor 18 (16.2 %) 6083 (13.3 %) 0.3723 33 (14.4 %) 6091 (13.3 %) 0.6336

Middle 18 (16.2 %) 7381 (16.2 %) 0.9913 34 (14.8 %) 7388 (16.2 %) 0.5857

Richer 14 (12.6 %) 7036 (15.4 %) 0.413 29 (12.7 %) 7044 (15.4 %) 0.2486

Richest 11 (9.9 %) 6678 (14.6 %) 0.1592 29 (12.7 %) 6683 (14.6 %) 0.4002

Missing 35 (31.5 %) 12,220 (26.8 %) 0.2594 73 (31.9 %) 12,235 (26.8 %) 0.0830

Mother’s educational attainment (at baseline)

No schooling 20 (18.0 %) 7363 (16.1 %) 0.591 38 (16.6 %) 7371 (16.1 %) 0.8521

1–4 years 8 (7.2 %) 3258 (7.1 %) 0.9785 19 (8.3 %) 3262 (7.1 %) 0.4987

5–8 years 45 (45.5 %) 15,205 (33.3 %) 0.1074 94 (41.0 %) 15,228 (33.3 %) 0.0136

9? years 1 (0.9 %) 1270 (2.8 %) 0.2281 5 (2.2 %) 1271 (2.8 %) 0.5820

Missing 37 (33.3 %) 18,527 (40.6 %) 0.119 73 (31.9 %) 18,539 (40.6 %) 0.0074

Children—n 121 76,381 248 76,431

Sex of child

Boy 70 (57.9 %) 38,294 (50.1 %) 0.117 137 (55.2 %) 38,320 (50.1 %) 0.1132

Girl 51 (42.1 %) 38,087 (49.9 %) 0.117 111 (44.8 %) 38,111 (49.9 %) 0.1132

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results to the above findings, child survival from birth is

compromised to a lesser extent following a paternal (vs.

maternal) death, but a log-rank test indicates a significantly

worse survival trajectory for paternal orphans when com-

pared to children with surviving fathers (p value\0.001).

These data are represented pictorially in a Kaplan–Meier

curve (Fig. 5).

As shown in Tables 5 and 6, maternal death was asso-

ciated with increased mortality across childhood. The

higher mortality rates among orphaned children (both early

and late maternal death) were statistically significant for

nearly all age groups (exceptions are categories during

which no or few deaths occurred). The results indicate

particularly elevated risk of dying among orphans during

the first year of life; for children who experience a late

maternal death, this higher risk extended into the second

year as well. Thus children who were orphaned following a

maternal death faced a much greater chance of dying

themselves than children whose mothers survived.

Discussion

This analysis contributes to a growing body of literature

supporting the hypothesis that maternal death leaves

infants particularly vulnerable to poor health outcomes,

Table 3 Cumulative probability (and sample count) of survival to month x for index children by maternal mortality status, conditional on

surviving to month y

\1 month 5 months 11 months 59 months

MD-42 MS MD-42 MS MD-42 MS MD-42 MS

Early maternal deaths (42 days after childbirth)

At birth 0.7614 (15) 0.9758 (1842) 0.5449 (34) 0.9604 (2978) 0.5154 (36) 0.9442 (4095) 0.4643 (39) 0.9112 (5890)

1 month – – 0.7156 (19) 0.9842 (1136) 0.6769 (21) 0.9676 (2253) 0.6098 (24) 0.9338 (4048)

6 months – – – – 0.9459 (2) 0.9831 (1117) 0.8522 (5) 0.9488 (2912)

12 months – – – – – – 0.9009 (3) 0.9651 (1795)

\1 month 5 months 11 months 59 months

MD-365 MS MD-365 MS MD-365 MS MD-365 MS

Late maternal deaths (365 days after childbirth)

At birth 0.7614 (15) 0.9757 (1858) 0.4954 (45) 0.9600 (3013) 0.4024 (64) 0.9437 (4138) 0.3300 (79) 0.9108 (5933)

1 month – – 0.6507 (30) 0.9839 (1155) 0.5286 (49) 0.9672 (2280) 0.4334 (64) 0.9335 (4075)

6 months – – – – 0.8123 (19) 0.9830 (1125) 0.6660 (34) 0.9487 (2920)

12 months – – – – – – 0.8199 (15) 0.9651 (1795)

Data are cumulative probabilities (cumulative number of deaths). First column shows age at cohort start

MD-42 maternal death within 42 days, MD-365 maternal death within 365 days, MS maternal survival

0.000.100.200.300.400.500.600.700.800.901.00

Sur

viva

l Pro

babi

lity

1 6 12 60 120Months since Birth

Mother alive Mother deceased

Survival probablity of children in Tanzania

Fig. 3 Kaplan–Meier survival probability curve by maternal mortal-

ity status, women who die within 42 days of childbirth. Note: Log-

rank test for equality of survival functions: p value\0.001

0.000.100.200.300.400.500.600.700.800.901.00

Sur

viva

l Pro

babi

lity

1 6 12 60 120Months since Birth

Mother alive Mother deceased

Survival probablity of children in Tanzania

Fig. 4 Kaplan–Meier survival probability curve by maternal mortal-

ity status, women who die within 365 days of childbirth. Note: Log-

rank test for equality of survival functions: p value\0.001

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notably death. In the two Tanzanian communities, nearly

half of children who were orphaned during infancy them-

selves died. Children whose mothers died during or shortly

after childbirth experienced mortality rates before their first

birthday that were far greater than first-year mortality rates

among children with surviving mothers.

These results underscore the crucial importance of

providing care and improving outcomes during the

intrapartum period: saving a mother’s life has positive

spillover effects on child survival. Maternal mortality can

be reduced with high-quality childbirth care: skilled birth

attendants, and emergency obstetric care in case of com-

plications [26]. The important spillover effects of such

interventions onto infant and child mortality should not be

overlooked; indeed, a recent analysis concluded that large

reductions in neonatal mortality might be achieved via such

intrapartum strategies [27]. In the case of a maternal death,

babies’ lives could also be saved with strengthened

postpartum care, including nutritional support and medical

care [27].

The magnitude of results reported here is not unlike

those found in other settings: for example, using HDSS

data from Bangladesh, Ronsmans et al. found a cumulative

1-year survival probability from birth of 0.30 for orphaned

children versus 0.93 for their peers, and adjusted rate ratios

for the first year of between 8 and 27 [18]; these values are

strikingly similar to the results found here for both early-

and late-maternal deaths. This analysis thus expands the

evidence base around the grave consequences of maternal

death for infant survival.

A key strength of this analysis is its use of a longitudinal

dataset, with frequent data collection around key demo-

graphic events over an extended time period and follow-up

within a household of orphaned children. Some limitations

should nonetheless be noted. First, maternal deaths are

generally a rare event, so even in relatively high-mortality

settings like this one, the number of women who die during

or after childbirth is small. This small sample size may

have effects on estimating survival trajectories: a concen-

trated mortality effect in infancy naturally shrinks the

already-small sample, so there are few orphans whose

survival can be estimated after age 1. Using the late defi-

nition of maternal death increased the sample size and

estimated more robust survival probabilities across infancy

and childhood, and larger samples would further stabilize

these estimates. Additionally, this analysis used a timing-

based definition of maternal deaths (i.e., all occurring up to

Table 4 Cumulative probability of survival from birth to month x for

children, by paternal mortality status

Days since birth Paternal death Paternal survival

Survival prob. n died Survival prob. n died

0 – 0 – 0

30 – 0 0.9778 1265

183 0.9693 3 0.9632 812

365 0.9097 9 0.9481 796

1825 0.8612 15 0.9164 1341

3652 0.8504 5 0.9102 120

0.000.100.200.300.400.500.600.700.800.901.00

Sur

viva

l Pro

babi

lity

1 6 12 60 120Months since Birth

Father alive Father deceased

Survival probablity of children in Tanzania

Fig. 5 Kaplan–Meier survival probability curve by paternal mortality

status. Note: Log-rank test for equality of survival functions: p value

\0.001

Table 5 Age specific death rates in children according to survival status of the mother, early maternal death (42 days after childbirth)

Child age

(days)

Deaths per 100,000 child-days (number of child deaths) Crude death rate ratio (95 %

CI)

Adjusted death rate ratio (95 %

CI)Mother

survived

Maternal deaths, 42 days (index

children)

0–30 82.737 (1842) 831.209 (15) 10.05 (5.974–16.90) 6.465 (3.247–12.87)

30–183 10.451 (1136) 251.452 (19) 24.06 (14.99–38.62) 20.68 (12.71–33.64)

183–365 9.378 (1117) 28.885 (2) 3.081 (0.792–11.98) 2.813 (0.738–10.73)

365–730 4.566 (957) 30.346 (3) 6.646 (2.096–21.08) 6.859 (2.194–21.45)

730–1095 2.885 (506) 0 (0) – –

Variables used for adjusted ratios include: child sex, twinship, mother’s age, mother’s educational attainment, and household wealth quintile

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42 and 365 days of childbirth) rather than a classification

based on cause of death data. Such an approach may over-

or under-classify deaths as maternal-related, although it

does conform to WHO definitions and conventions in set-

tings with poor vital registration. Although HDSS sites

collect cause of death data, these variables may be subject

to recall bias; because many of these data were missing or

unclear for these sites, cause of death analysis was not

conducted (for mothers or children) here. Likewise, other

variables included many missing values, so could not be

explored in this analysis (such as maternal parity). Lastly, a

key limitation of this analysis is the lack of data on any

older siblings born prior to baseline or enrollment at in-

migration. By only examining the impact of a maternal

death on children born within the study period, the analysis

loses the capability to robustly explore long-term outcomes

for orphaned children; further research should aim to

investigate this outcome as well as outcomes for non-index

children born outside the study period. Additionally, future

research may seek to resolve some of these greater data

challenges, by replicating the analyses for other HDSS

sites—or ideally by pooling comparable HDSS datasets

to increase the number of maternal deaths (thereby

adding statistical power to survival analyses)—or by using

other high-quality longitudinal datasets with demographic

events.

Children in the two rural Tanzanian communities in this

study have poor survival outcomes when their mother dies

within 42 or 365 days of their birth. This finding is con-

sistent with other studies in low-income countries. The toll

of maternal mortality extends beyond the mother, and

interventions to improve survival outcomes of the mother

will also improve survival outcomes of her children.

Acknowledgments We thank our collaborators at the Ifakara

Health Institute (IHI) for providing us with the data for this study. We

thank Vanessa Boulanger for coordinating between IHI and Harvard.

This Project has been conducted with support from The John and

Katie Hansen Family Foundation. The funders had no role in study

design, data collection and analysis, decision to publish, or prepara-

tion of the manuscript.

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