Correlated mortality risks of siblings in Kenya: The role of state dependence

Neonatal and Postneonatal Death Clustering Among Siblings in Bangladesh: Evidence from Bangladesh Demographic and Health Survey 2017-2018

Despite knowledge of neonatal and postneonatal mortality determinants in Bangladesh, some families continue to lose a larger share of children, a phenomenon known as early-life mortality clustering. This study uses the random intercept Weibull survival regression model to explore the correlation of mortality risk among siblings at the family (or, mother) and community levels. Utilizing the Bangladesh Demographic and Health Survey 2017-2018, we found evidence of death scarring, where children whose previous sibling was not alive at the time of conception had significantly higher odds of neonatal mortality. Moreover, the neonatal (and postneonatal) mortality hazard was highest for children with a birth interval of fewer than 19 months, corresponding to the preceding sibling. The intraclass correlation coefficient's statistically significant values show that neonatal and postneonatal mortality risk is correlated among children of the same family and community. The findings suggest focusing on high-risk families and communities to reduce the mortality level effectively.

Clustering of child deaths among families in low and middle-income countries: A meta-analysis

Background and Aims

Several studies have examined the phenomenon of "death clustering," in which two or more children born to the same mother or from the same family die at an early age. Therefore, a scientific examination of the results is essential to understand how the survival status of the older siblings affects the survival of the younger siblings. By using meta-analysis, this study aims to provide a quantitative synthesis of the results of studies on "child death clustering" in low- and middle-income countries (LMICs).

Methods

This study followed the PRISMA-P 2015 guidelines. We used four electronic databases-PubMed, Medline, Scopus, and Google Scholar with search and citation analysis capabilities. Initially, 140 studies were identified, but only 27 met the eligibility criteria eventually. These were studies that had used the death of a previous child as a covariate to determine the survival status of the index child. The heterogeneity and the publication bias of the studies were examined using the Cochran test, I 2 statistic, and Egger's meta-regression test.

Results

The pooled estimate of 114 study estimates for LMICs contains some bias. India's 37 study estimates were distributed more or less equally along the middle line, indicating no publication bias, while there was a slight bias in the estimates for Africa, Latin America, and Bangladesh. The odds of experiencing the death of the index child in the selected LMICs were 2.3 times higher for mothers who had lost any prior child as compared to those mothers who had not had any prior child loss. For African mothers, the odds were five times higher, whereas for Indian mothers, the odds were 1.66 times higher. Mothers' characteristics, such as education, occupation, health-seeking behavior, and maternal competence, significantly affect the child's survival status.

Conclusion

Achieving the sustainable development goals would not be possible if mothers in countries experiencing high levels of under-five mortality are not provided with better health and nutrition facilities. Mothers who have lost multiple children should be targeted for assistance.

Household structure, composition and child mortality in the unfolding antiretroviral therapy era in rural South Africa: comparative evidence from population surveillance, 2000-2015

OBJECTIVES

The structure and composition of the household has important influences on child mortality. However, little is known about these factors in HIV-endemic areas and how associations may change with the introduction and widespread availability of antiretroviral treatment (ART). We use comparative, longitudinal data from two demographic surveillance sites in rural South Africa (2000-2015) on mortality of children younger than 5 years (n=101 105).

DESIGN

We use multilevel discrete time event history analysis to estimate children's probability of dying by their matrilineal residential arrangements. We also test if associations have changed over time with ART availability.

SETTING

Rural South Africa.

PARTICIPANTS

Children younger than 5 years (n=101 105).

RESULTS

3603 children died between 2000 and 2015. Mortality risks differed by co-residence patterns along with different types of kin present in the household. Children in nuclear households with both parents had the lowest risk of dying compared with all other household types. Associations with kin and child mortality were moderated by parental status. Having older siblings lowered the probability of dying only for children in a household with both parents (relative risk ratio (RRR)=0.736, 95% CI (0.633 to 0.855)). Only in the later ART period was there evidence that older adult kin lowered the probability of dying for children in single parent households (RRR=0.753, 95% CI (0.664 to 0.853)).

CONCLUSIONS

Our findings provide comparative evidence of how differential household profiles may place children at higher mortality risk. Formative research is needed to understand the role of other household kin in promoting child well-being, particularly in one-parent households that are increasingly prevalent.

Infant Death Clustering in the Quarter of a Century in India: A Decomposition Analysis

The study aims to examine the clustering of infant deaths in India and the relative contribution of infant death clustering after accounting for the socio-economic and biodemographic factors that explain the decline in infant deaths. The study utilized 10 years of birth history data from three rounds of the National Family Health Survey (NFHS). The random effects dynamic probit model was used to decompose the decline in infant deaths into the contributions by the socio-economic and demographic factors, including the lagged independent variable, the previous infant death measuring the clustering of infant deaths in families. The study found that there has been a decline in the clustering of infant deaths among families during the past two and half decades. The simulation result shows that if the clustering of infant deaths in families in India was completely removed, there would be a decline of nearly 30 percent in the infant mortality rate (IMR). A decomposition analysis based on the dynamic probit model shows that for NFHS-1 and NFHS-3, in the total change of the probability of infant deaths, the rate of change for a given population composition contributed around 45 percent, and about 44 percent was explained by a compositional shift. Between NFHS-3 and NFHS-4, the rate of change for a given population composition contributed 86%, and the population composition for a given rate contributed 10% to the total change in the probability of infant deaths. Within this rate, the contribution of a previous infant was 0.8% and the mother's age was 10%; nearly 31% was contributed by the region of residence, 69% by the mother's education, and around 20% was contributed by the wealth index and around 8.7% by the sex of the child. The mother's unobserved factors contributed more than 50 percent to the variability of infant deaths in all the survey rounds and was also statistically significant (p < 0.01). Bivariate analysis suggests that women with two or more infant losses were much less likely to have full immunization (10%) than women with no infant loss (62%), although institutional delivery was high among both groups of women.

Examining infant and child death clustering among families in the cross-sectional and nationally representative Bangladesh Demographic and Health Survey 2017-2018

OBJECTIVES

We aim to examine the phenomenon of infant and child death clustering while considering the unobserved heterogeneity (frailty) at the family level.

DESIGN, SETTING, AND PARTICIPANTS

We analysed Bangladesh Demographic and Health Survey 2017-2018 data, including the birth history information for 47 828 children born to 18 134 women. We used Gompertz shared frailty model to control the correlation between event times at the mother level and capture the unobserved risks in infant and child deaths.

OUTCOME MEASURES

We estimated two sets of survival regression models where the failure event is the survival status of the index child during the infancy period, that is, from birth to 11 months, and childhood period, that is, between 12 and 59 months, respectively. All children who died during infancy and childhood were coded as 'yes'; otherwise, they were coded as 'no'.

RESULTS

About 2% of mothers experienced two or more infant deaths, and cumulatively these mothers account for 20% of all infant deaths in the sample. Children whose previous sibling was not alive at the time of their conception had 1.86 times (95% CI 1.59 to 2.17) more risk of dying as an infant. However, we did not find a statistically significant effect of death scarring on the risk of child mortality among siblings. Statistically significant frailty effect with a variance of 0.33 (95% CI CI 0.17 to 0.65) and 0.54 (95% CI 0.14 to 2.03)] in infancy and childhood, respectively, indicates the clustering of survival risks within families due to unobserved family-level characteristics shared by the siblings.

CONCLUSION

This study suggests that preceding birth interval, mother's age at first birth and mother's education are the most critical factors which can help in reducing scaring effect on infant mortality. Additionally, women from poor socioeconomic strata should be focused on as still an infant, and child mortality is concentrated among poor households.

Mapping of mothers' suffering and child mortality in Sub-Saharan Africa

Child death and mothers who suffer from child death are a public health concern in Sub-Saharan Africa. The location and associated factors of child death and mothers who suffer child death were not identified. To monitor and prioritize effective interventions, it is important to identify hotspots areas and associated factors. Data from nationally representative demographic and health survey and Multiple Indicator Cluster administrated in 42 Sub-Sahara Africa countries, which comprised a total of 398,574 mothers with 1,521,312 children. Spatial heterogeneity conducted hotspot regions identified. A mixed-effect regression model was run, and the adjusted ratio with corresponding 95% confidence intervals was estimated. The prevalence of mothers who suffer child death 27% and 45-49 year of age mother 48%. In Niger, 47% of mothers were suffering child death. Women being without HIV knowledge, stunted, wasted, uneducated, not household head, poor, from rural, and from subtropical significantly increased the odds of the case (P < 0.05). The spatial analysis can support the design and prioritization of interventions. Multispectral interventions for mothers who suffer from child death are urgently needed, improve maternal health and it will reduce the future risk of cases.

Differential in infant, childhood and under-five death clustering among the empowered and non-empowered action group regions in India

Background

With 8,82,000 deaths in the under-five period, India observed varied intra-state and inter-regional differences across infant and child mortality in 2018. However, scarce literature is present to capture this unusual concentration of mortality in certain families by examining the association of the mortality risks among the siblings of those families along with various unobserved characteristics of the mother. Looking towards the regional and age differential in mortality, this paper attempts to provide evidence for the differential in mortality clustering among infants (aged 0–11 months), children (12–59 months) and under-five (0–59 months) period among mothers from the Empowered Action Group (EAG) and non-EAG regions of India.

Methods

The study used data from the National Family Health Survey (2015–16) which includes all the birth histories of 475,457 women aged 15–49 years. Bivariate and multivariate analyses were used to fulfil the objectives of the study. A two-level random intercept Weibull regression model was used to account for the unexplained mother (family) level heterogeneity.

Results

About 3.3% and 5.9% of infant deaths and 0.8% and 1.6% of childhood deaths were observed in non-EAG and EAG regions respectively. Among them, a higher percentage of infant and child death was observed due to the death of a previous sibling. There were 1.67 times [95% CI: 1.55–1.80] and 1.46 times [CI: 1.37–1.56] higher odds of infant and under-five mortality of index child respectively when the previous sibling at the time of conception of the index child was dead in the non-EAG regions. In contrast, the odds of death scarring (death of previous sibling scars the survival of index child) were 1.38 times [CI: 1.32–1.44] and 1.24 times [CI: 1.20–1.29] higher for infant and under-five mortality respectively in the EAG regions.

Conclusion

The extent of infant and child mortality clustering and unobserved heterogeneity was higher among mothers in the non-EAG regions in comparison to their EAG region counterparts. With the growing situation of under-five mortality clustering in non-EAG states, region-wise interventions are recommended. Additionally, proper care is needed to ameliorate the inter-family variation in mortality risk among the children of both EAG and non-EAG regions throughout their childhood.

Clustering of Infant Mortality Within Families in Rural Burkina Faso

In this study, we analyze clustering of infant deaths within families living in a rural part of western Burkina Faso. The study included 9,220 infants, born between 1993 and 2009 in Nouna Health and Demographic Surveillance System (HDSS). A clustering of infant deaths in families was explored by calculating observed versus expected number of infant deaths within families for a given family size. In addition, risk ratios were calculated for infant death depending on the vital status of the previous sibling. We observed 470 infant deaths, yielding an overall infant mortality risk of 51/1,000 births. Clustering of infant deaths within families was observed (P = 0.004). In smaller families, the mortality of firstborns was higher than for the following siblings. The infant mortality risk was higher when the preceding sibling died in infancy (P = 0.03). The study supports the hypothesis of infant death clustering existing within rural families in West Africa. Further studies are needed to shed more light on these findings with the goal to develop effective interventions directed toward the families who already lost a child.

Efforts to alter the trajectory of neonatal mortality in Malawi: evaluating relative effects of access to maternal care services and birth history risk factors

BACKGROUND

The neonatal mortality rate (NMR) in Malawi has remained stagnant at around 27 per 1000 live births over the last 15 years, despite an increase in the uptake of targeted health care interventions. We used the nationally representative 2015/16 Demographic Health Survey data set to evaluate the effect of two types of maternal exposures, namely, lack of access to maternal or intra-partum care services and birth history factors, on the risk of neonatal mortality.

METHODS

A causal inference approach was used to estimate a population attributable risk parameter for each exposure, adjusting for co-exposures and household, maternal and child-specific covariates. The maternal exposures evaluated were unmet family planning needs, less than 4+ antenatal care visits, lack of institutional delivery or skilled birth attendance, having prior neonatal mortality, short (8-24 months) birth interval preceding the index birth, first pregnancy, and two or more pregnancy outcomes within the preceding five years of the survey interview.

RESULTS

We included 9553 women and their most recent live birth within 3 years of the survey. The sample's overall neonatal mortality rate was 18.5 per 1000 live births. The adjusted population attributable risk for first pregnancies was 3.9/1000 (P < 0.001), while non-institutional deliveries and the shortest preceding birth interval (8-24 months) each had an attributable risk of 1.3/1000 (Ps = 0.01). Having 2 or more pregnancy outcomes within the last 5 years had an attributable risk of 3/1000 (P = 0.006). Attending less than 4 ANC visits had, a relatively large attributable risk (2.1/1,000), and it was not statistically significant at alpha level 0.05.

CONCLUSIONS

Our analysis addresses the gap in the literature on evaluating the effect of these exposures on neonatal mortality in Malawi. It also helps inform programs and current efforts such as the Every Newborn Action 2020 Plan. Increasing access to maternal care interventions has an important role to play in changing the trajectory of neonatal mortality, and women who are at an increased risk may not be receiving adequate care. Recent studies indicate an urgent need to assess gaps in service readiness and quality of care at the antenatal and obstetric care facilities.

Early-life mortality clustering in families: A literature review

Research on early-life mortality in contemporary and historical populations has shown that infant and child mortality tend to cluster in a limited number of high-mortality families, a phenomenon known as 'mortality clustering'. This paper is the first to review the literature on the role of the family in early-life mortality. Contemporary results, methodological and theoretical shortfalls, recent developments, and opportunities for future research are all discussed in this review. Four methodological approaches are distinguished: those based on sibling deaths, mother heterogeneity, thresholds, and excess deaths in populations. It has become clear from research to date that the death of an older child harms the survival chances of younger children in that family, and that fertility behaviour, earlier stillbirths, remarriages, and socio-economic status all explain mortality clustering to some extent.

Relationships between infant mortality, birth spacing and fertility in Matlab, Bangladesh

Although research on the fertility response to childhood mortality is widespread in demographic literature, very few studies focused on the two-way causal relationships between infant mortality and fertility. Understanding the nature of such relationships is important in order to design effective policies to reduce child mortality and improve family planning. In this study, we use dynamic panel data techniques to analyse the causal effects of infant mortality on birth intervals and fertility, as well as the causal effects of birth intervals on mortality in rural Bangladesh, accounting for unobserved heterogeneity and reverse causality. Simulations based upon the estimated model show whether (and to what extent) mortality and fertility can be reduced by breaking the causal links between short birth intervals and infant mortality. We find a replacement effect of infant mortality on total fertility of about 0.54 children for each infant death in the comparison area with standard health services. Eliminating the replacement effect would lengthen birth intervals and reduce the total number of births, resulting in a fall in mortality by 2.45 children per 1000 live births. These effects are much smaller in the treatment area with extensive health services and information on family planning, where infant mortality is smaller, birth intervals are longer, and total fertility is lower. In both areas, we find evidence of boy preference in family planning.

New evidence about effects of reproductive variables on child mortality in sub-Saharan Africa

There is still considerable uncertainty about how reproductive factors affect child mortality. This study, based on Demographic and Health Survey data from 28 countries in sub-Saharan Africa, shows that mortality is highest for firstborn children with very young mothers. Other children with young mothers, or of high birth order, also experience high mortality. Net of maternal age and birth order, a short preceding birth interval is associated with above average mortality. These patterns change, however, if time-invariant unobserved mother-level characteristics of importance for both mortality and fertility are controlled for in a multilevel-multiprocess model. Most importantly, there are smaller advantages associated with longer birth intervals and being older at first birth. The implications of alternative reproductive 'strategies' are discussed, taking into account that if the mother is older at birth, the child will also be born in a later calendar year, when mortality may be lower.

SIBLING- AND FAMILY-LEVEL CLUSTERING OF UNDERWEIGHT CHILDREN IN NORTHERN INDIA

Child undernutrition remains a major child health and developmental issue in low- and middle-income countries. The concentration (clustering) of underweight children among siblings at the family level is known to exist in India. This study examined the extent and covariates of clustering of underweight children at the sibling and family level in Uttar Pradesh, the largest state of northern India. Clustering of underweight (low weight-for-age) children was assessed using data on 7533 under-five children from the National Family Health Survey (NFHS) conducted in 2005-06, analysed using binary logistic and binomial regression models. Related bio-demographic, socioeconomic and health care variables were used as covariates in the models. The odds of being underweight for the index child were about two times higher (OR=2.34, p<0.001) if any of the siblings within the household was malnourished or underweight. A longer birth interval increased the odds of a child being underweight. The odds of underweight were significantly lower (OR=0.69, p<0.001) for children born to normal-weight mothers compared with those born to underweight mothers. Similarly, the odds of underweight were significantly lower (OR=0.49, p=0.01) for children born to educated mothers (high school and above) compared with those born to illiterate mothers. The results of the binomial regression model suggested that the deviations between observed and expected number of children were positive (3.09, 3.78 and 2.71) for 1, 2 and 2+ underweight children within the households of underweight women, indicating the concentration of underweight children among underweight/malnourished mothers. Underweight children were found to be clustered among underweight mothers with multiple underweight siblings. The findings suggest that policy interventions need to focus on underweight mothers with multiple underweight children.

Household context and child mortality in rural South Africa: the effects of birth spacing, shared mortality, household composition and socio-economic status

BACKGROUND

Household characteristics are important influences on the risk of child death. However, little is known about this influence in HIV-endemic areas. We describe the effects of household characteristics on children's risk of dying in rural South Africa.

METHODS

We use data describing the mortality of children younger than 5 years living in the Agincourt health and socio-demographic surveillance system study population in rural northeast South Africa during the period 1994-2008. Using discrete time event history analysis we estimate children's probability of dying by child characteristics and household composition (other children and adults other than parents) (N=924,818 child-months), and household socio-economic status (N=501,732 child-months).

RESULTS

Children under 24 months of age whose subsequent sibling was born within 11 months experience increased odds of dying (OR 2.5; 95% CI 1.1-5.7). Children also experience increased odds of dying in the period 6 months (OR 2.1; 95% CI 1.2-3.6), 3-5 months (OR 3.0; 95% CI 1.5-5.9), and 2 months (OR 11.8; 95% CI 7.6-18.3) before another household child dies. The odds of dying remain high at the time of another child's death (OR 11.7; 95% CI 6.3-21.7) and for the 2 months following (OR 4.0; 95% CI 1.9-8.6). Having a related but non-parent adult aged 20-59 years in the household reduces the odds (OR 0.6; 95% CI 0.5-0.8). There is an inverse relationship between a child's odds of dying and household socio-economic status.

CONCLUSIONS

This detailed household profile from a poor rural setting where HIV infection is endemic indicates that children are at high risk of dying when another child is very ill or has recently died. Short birth intervals and additional children in the household are further risk factors. Presence of a related adult is protective, as is higher socio-economic status. Such evidence can inform primary health care practice and facilitate targeting of community health worker efforts, especially when covering defined catchment areas.

Contraceptive use, birth spacing, and child survival in Matlab, Bangladesh

To reduce infant mortality through improved family planning, a better understanding of the factors driving contraceptive use and how this decision affects infant survival is needed. Using dynamic panel-data models of infant deaths, birth intervals, and contraceptive use, this study analyzes the causal effects of birth spacing on subsequent infant mortality and of infant mortality on the use of contraceptives and the length of the next birth interval. Data are drawn from the Health and Demographic Surveillance System in Matlab, Bangladesh, where almost 32,000 births have been observed from 1982 to 2005. Our main finding is that complete contraceptive use could reduce infant mortality of birth order two and higher by 7.9 percent. The net effect of complete contraceptive use on the total infant mortality rate is small (2.9 percent), however, because the favorable effect on higher order births is partly offset by the rise in the proportion of high-risk first births.

Clustering of neonatal deaths in Bangladesh: results from the Projahnmo studies

BACKGROUND

Neonatal mortality (NM) tends to be clustered within a small subset of mothers, households and/or geographical areas. Knowledge of the maternal and newborn factors associated with NM can help identify high-risk mothers and guide the targeting of intervention programmes.

METHOD

Data from pregnancy history surveys conducted as part of the Project for Advancing the Health of Newborns and Mothers (Projahnmo) in Sylhet and Mirzapur districts of Bangladesh were used to investigate risk factors for NM. We analysed data from babies born between 2001 and 2005 in the control clusters of the Projahnmo trials. Generalised linear mixed models were applied to quantify the heterogeneity among mothers and to investigate factors that contribute to this heterogeneity.

RESULTS

There was an indication of correlation among siblings' outcomes. Neonates whose preceding sibling had died as a neonate in the mothers' lifetime pregnancy history were more likely (up to 1.9 times) to die than those with a living sibling. Factors that varied at the child and mother levels as well as the preceding siblings' outcome explained a large proportion (60% in Sylhet and 70% in Mirzapur) of the between-mother variation in NM.

CONCLUSION

The preceding sibling's outcome may be a surrogate for genetic and other maternal health factors such as nutrition, infection or environmental factors that were not measured within Projahnmo. Further research into these factors is required in order to explain the variation in the risk for NM.

Historical trends in the correlation of sibling deaths in infancy in the Netherlands

In this article, we study temporal, regional, and social variation in infant and childhood death clustering in The Netherlands, using data from three provinces. The data relate to children born in 90,000 marriages contracted between the beginning and the last quarter of the nineteenth century. Descriptive indicators show that death clustering was more frequent in the province of Zeeland and more common in the lower classes, and that it increased in two provinces over time. Shared frailty hazard models make it clear that the number of children who died before the birth of an index child had a negative effect on the mortality of index children, whereas earlier stillbirths and the number of children who died when the index child was at a young age had an increasing effect on the mortality of index children.

Infant death clustering in families: magnitude, causes, and the influence of better health services, Bangladesh 1982-2005

This analysis of infant mortality in Bangladesh focuses on explaining death clustering within families, using prospective data from a rural region in Bangladesh, split into areas with and without extensive health services (the area covered by the International Centre for Diarrhoeal Disease Research and the comparison area, respectively). The modelling framework distinguishes between two explanations of death clustering: (observed and unobserved) heterogeneity across families and a causal 'scarring' effect of the death of one infant on the survival chances of the next to be born. Keeping observed and unobserved characteristics constant, we find scarring in the comparison area only. There the likelihood of infant death is about 29 per cent greater if the previous sibling died in infancy than otherwise. This effect mainly works through birth intervals: infant deaths are followed by shorter birth intervals, which increases the risk of infant death for the next child.