Child Mortality Estimation Research Articles

Levels, trends and inequalities in mortality among 5-19-year-olds in Tanzania: Magu Health and Demographic Surveillance Study (1995-2022).

For the past two decades, health priorities in Tanzania have focussed on children under-five, leaving behind the older children and adolescents (5-19 years). Understanding mortality patterns beyond 5 years is important in bridging a healthy gap between childhood to adulthood. We aimed to estimate mortality levels, trends, and inequalities among 5-19-year-olds using population data from the Magu Health and Demographic Surveillance Site (HDSS) in Tanzania and further compare the population level estimates with global estimates. Using data from the Magu HDSS from 1995 to 2022, from Kaplan Meir survival probabilities, we computed annual mortality probabilities for ages 5-9, 10-14 and 15-19 and determined the average annual rate of change in mortality by fitting the variance weighted least square regression on annual mortality probabilities. We compared 5-19 trends with younger children aged 1-4 years. We further disaggregated mortality by sex, area of residence and wealth tertiles, and we computed age-stratified risk ratios with respective 95% confidence intervals (CIs) using Cox proportional hazard model to determine inequalities. We further compared population-level estimates in all-cause mortality with global estimates from the United Nations Inter-agency Group for Child Mortality Estimation and the Global Burden of Disease study by computing the relative differences to the estimates. Mortality declined steadily among the three age groups from 1995 to 2022, whereby the average annual rate of decline increased with age (2.2%, 2.7%, and 2.9% for 5-9-, 10-14-, and 15-19-year-old age groups, respectively). The pace of this decline was lower than that of younger children aged 1-4 years (4.8% decline). We observed significant mortality inequalities with boys, those residing in rural areas, and those from poorest wealth tertiles lagging behind. While Magu estimates were close to global estimates for the 5-9-year-old age group, we observed divergent results for adolescents (10-19 years), with Magu estimates lying between the global estimates. The pace of mortality decline was lower for the 5-19-year-old age group compared to younger children, with observable inequalities by socio-demographic characteristics. Determining the burden of disease across different strata is important in the development of evidence-based targeted interventions to address the mortality burden and inequalities in this age group, as it is an important transition period to adulthood.

Impact of rural-urban migration on indirect child mortality estimation in Kenya

When estimating child mortality rates using the indirect method, it is assumed that all reported births and deaths occurred in the place where the mothers resided at the time of the survey. However, the migration of women can result in transferring data about deceased children from one place to another. In many developing countries, substantial migration happens between rural and urban regions, where child mortality disparities are significant. This migration creates challenges as child mortality estimates for rural and urban areas computed under the assumption of non-migration are likely to be erroneous. Our study pooled data from six Kenya Demographic and Health Surveys between 1989 and 2014. The study aimed to establish statistical evidence of the impact of rural-urban migration on indirect child mortality estimates. Our findings indicate that the inclusion of deceased children born to women who migrated from rural to urban regions led to a significant overestimation of infant, one-to-four, and under-five mortality rates in urban areas. On average, the overestimation of infant mortality rates ranged from 2.5% to 21.7%, while one-to-four mortality rate overestimation ranged from 4.0% to 41.2%. The average overestimation of under five mortality rate was between 3.0% and 26.8%. Based on these results, future indirect estimates of child mortality for rural and urban regions should be adjusted to account for the impacts of migration between these areas. Furthermore, it is essential to consider re-estimating trends of child mortality for rural and urban regions in Kenya to better understand the timing of mortality convergence between these regions.

Modernizing Demographic Computations: Some Illustrative Examples

Although the use of computers and sophisticated software, particularly R, has become common in demography, this has not led to a revision of some traditional demographic algorithms, which were originally designed to overcome computational obstacles that nowadays no longer exist. This article argues that, rather than implementing the existing algorithms in today’s powerful software, it is time to take advantage of this software to modify the algorithms themselves. It illustrates this idea with three examples: Sprague interpolation, the Relational Gompertz method for fertility estimation, and the estimation of infant and child mortality from proportions of surviving children by mother’s age. In each case, it is shown that the analysis can be made simpler, more direct,intuitive, transparent, and precise by making use of the resources offered by software such as R. It is also shown that the greater flexibility of these algorithms creates opportunities for extending each method.

Income inequality as a determinant of neonatal mortality in the Americas during 2000–2019: implications for the attainment of Sustainable Development Goal target 3.2

BackgroundThe work of the WHO Commission on the Social Determinants of Health has been fundamental to provide a conceptual framework of the social determinants of health. Based on this framework, this study assesses the relationship of income inequality as a determinant of neonatal mortality in the Americas and relates it to the achievement of the Sustainable Development Goal target 3.2 (reduce neonatal mortality to at least as low as 12 deaths per 1,000 live births). The rationale is to evaluate if income inequality may be considered a social factor that influences neonatal mortality in the Americas.MethodsYearly data from 35 countries in the Americas during 2000–2019 was collected. Data sources include the United Nations Inter-agency Group for Child Mortality Estimation for the neonatal mortality rate (measured as neonatal deaths per 1,000 live births) and the United Nations University World Institute for Development Economics Research for the Gini index (measured in a scale from 0 to 100). This is an ecological study that employs a linear regression model that relates the neonatal mortality rate (dependent variable) to the Gini index (independent variable), while controlling for other factors that influence neonatal mortality. Coefficient estimates and their robust standard errors were obtained using panel data techniques.ResultsA positive relationship between income inequality and neonatal mortality is found in countries in the Americas during the period studied. In particular, the analysis suggests that a unit increase in a country’s Gini index during 2000–2019 is associated with a 0.27 (95% CI [− 0.04, 0.57], P =.09) increase in the neonatal mortality rate.ConclusionThe analysis suggests that income inequality may be positively associated with the neonatal mortality rate in the Americas. Nonetheless, given the modest magnitude of the estimates and Gini values and trends during 2000–2019, the findings suggest a potential limited scope for redistributive policies to support reductions in neonatal mortality in the region. Thus, policies and interventions that address higher coverage and quality of services provided by national health systems and reductions in socio-economic inequalities in health are of utmost importance.

Inter-district and Wealth-related Inequalities in Maternal and Child Health Service Coverage and Child Mortality within Addis Ababa City.

In sub-Saharan Africa, urban areas generally have better access to and use of maternal, newborn, and child health (MNCH) services than rural areas, but previous research indicates that there are significant intra-urban disparities. This study aims to investigate temporal trends and geographic differences in maternal, newborn, and child health service utilization between Addis Ababa's poorest and richest districts and households. A World Bank district-based poverty index was used to classify districts into the top 60% (non-poor) and bottom 40% (poor), and wealth index data from the Ethiopian Demographic and Health Survey (EDHS) was used to classify households into the top 60% (non-poor) and bottom 40% (poor). Essential maternal, newborn, and child health service coverage was estimated from routine health facility data for 2019-2021, and five rounds of the EDHS (2000-2019) were used to estimate child mortality. The results showed that service coverage was substantially higher in the top 60% than in the bottom 40% of districts. Coverage of four antenatal care visits, skill birth attendance, and postnatal care all exceeded 90% in the non-poor districts but only ranged from 54 to 67% in the poor districts. Inter-district inequalities were less pronounced for childhood vaccinations, with over 90% coverage levels across all districts. Inter-district inequalities in mortality rates were considerable. The neonatal mortality rate was nearly twice as high in the bottom 40% of households' as in the top 60% of households. Similarly, the under-5 mortality rate was three times higher in the bottom 40% compared to the top 60% of households. The substantial inequalities in MNCH service utilization and child mortality in Addis Ababa highlight the need for greater focus on the city's women and children living in the poorest households and districts in maternal, newborn, and child health programs.

International progress on stillbirth reduction: Changes in Stillbirth Rates in Selected Low and Middle-Income Countries from 2000 to 2021

In this paper, we attempted to determine if there were reductions in low and middle – income country stillbirth rates since 2000 - focusing on sub-Saharan Africa, Asia and Latin America and the Caribbean. We used data made available by the United Nations Inter-agency Group for Child Mortality Estimation and the World Health Organization as well as the National Institute of Child Health and Human Development Global Network for Women's and Children's Health Research.. Overall, nearly every country evaluated had at least a small reduction in stillbirth rate from the year 2000 to 2021, but the reductions varied substantially between regions. Asia and Latin America/Caribbean had similar levels of reductions with a number of countries in each of those regions having rates in 2021 that were 40 % or more lower than those documented in 2000. No country in Africa documented a reduction in stillbirths of 40 % and many had stillbirth reductions of less than 15 %.

Racial residential segregation and child mortality in the southern United States at the turn of the 20th century

AbstractA growing body of research considers racial residential segregation to be a form of systemic racism and a fundamental cause of persistent racial disparities in health and mortality. Historical research examining the impact of segregation on health and mortality, however, is limited to a few studies with poor data and inconsistent results. In this study, we examine the association between racial residential segregation and child mortality in the South at the turn of the 20th century. We rely on the new IPUMS 1900 and 1910 complete‐count databases to estimate child mortality in the 5 years before each census and construct segregation measures at the census enumeration district (ED), the lowest level of geography consistently available in the census. We calculate the proportion of households headed by Black individuals in each ED, and the Sequence Index of Segregation (SIS), which is based on the racial sequencing of household heads within each district. We construct models of child mortality for rural and urban areas, controlling for a wide variety of demographic and socioeconomic variables. The results indicate thatproportion BlackandSISwere strongly and positively associated with the mortality of Black children in most models and in both rural and urban areas.Proportion Blackwas also positively but more moderately correlated with the mortality of White children, whileSISwas not correlated or negatively correlated. These results suggest that racial segregation was a long‐standing fundamental cause of race disparities in health and mortality in the United States.

Spatiotemporal analysis of the effect of global development indicators on child mortality

BackgroundChild mortality continue to be a major public health issue in most developing countries; albeit there has been a decline in global under-five deaths. The differences in child mortality can best be explained by socioeconomic and environmental inequalities among countries. In this study, we explore the effect of country-level development indicators on under-five mortality rates. Specifically, we examine potential spatio-temporal heterogeneity in the association between major world development indicators on under-five mortality, as well as, visualize the global differential time trend of under-five mortality rates.MethodsThe data from 195 countries were curated from the World Bank’s World Development Indicators (WDI) spanning from 2000 to 2017 and national estimates for under-five mortality from the UN Inter-agency Group for Child Mortality Estimation (UN IGME).We built parametric and non-parametric Bayesian space-time interaction models to examine the effect of development indicators on under-five mortality rates. We also used employed Bayesian spatio-temporal varying coefficient models to assess the spatial and temporal variations in the effect of development indicators on under-five mortality rates.ResultsIn both parametric and non-parametric models, the results show indicators of good socioeconomic development were associated with a reduction in under-five mortality rates while poor indicators were associated with an increase in under-five mortality rates. For instance, the parametric model shows that gross domestic product (GDP) (β = − 1.26, [CI − 1.51; − 1.01]), current healthcare expenditure (β = − 0.40, [CI − 0.55; − 0.26]) and access to basic sanitation (β = − 0.03, [CI − 0.05; − 0.01]) were associated with a reduction under-five mortality. An increase in the proportion practising open defecation (β = 0.14, [CI 0.08; 0.20]) an increase under-five mortality rate. The result of the spatial components spatial variation in the effect of the development indicators on under-five mortality rates. The spatial patterns of the effect also change over time for some indicators, such as PM2.5.ConclusionThe findings show that the burden of under-five mortality rates was considerably higher among sub-Saharan African countries and some southern Asian countries. The findings also reveal the trend in reduction in the sub-Saharan African region has been slower than the global trend.

Wealth and Child Mortality in the Nineteenth-Century United States: Evidence from Three Panels of American Couples, 1850-1880.

With only a few exceptions, the historical study of individual-level correlates of child mortality in the United States has been limited to the period surrounding the turn of the twentieth century, when children ever born and children surviving data collected by the 1900 and 1910 censuses allow indirect estimation of child mortality. The recent release of linked census data, such as the IPUMS MLP datasets, allows a different type of indirect estimation over a longer period. By following couples across subsequent decennial censuses, it is possible to infer child mortality by measuring whether couples' own children in the first census were still present in the second census. We focus our analysis on children aged 1-3 in the first of two linked censuses, who were less likely to be undercounted by the census than infants, and unlikely to be living apart from their parents in the second census. We estimate child mortality over the intervening decade and use OLS regression to correlate that mortality to the residence location and socioeconomic characteristics of their parents' households. We limit our analysis to three panel datasets for married couples linked between the 1850-60, 1860-70, and 1870-80 censuses, when real estate and personal estate wealth data were collected. Our results indicate a significant negative relationship between wealth and child mortality across all regions of the United States and over the entire period examined.

Fatal Years: Background and Aftermath

AbstractThis is a history of the creation of the book Fatal Years: Child Mortality in late-Nineteenth-Century America (1991) by the authors. The data were a sample of households from the 1900 United States Census manuscripts. The primary method used was indirect estimation of child mortality (approximately ages 0–4) using information on the age and marriage duration of women. Among the findings were overall lower overall mortality than in the 1900/1902 Glover life tables for the Death Registration Area, and very large variations in mortality by race and size of place of residence.

Estimating the stillbirth rate for 195 countries using a Bayesian sparse regression model with temporal smoothing

Estimation of stillbirth rates globally is complicated because of the paucity of reliable data from countries where most stillbirths occur. We compiled data and developed a Bayesian hierarchical temporal sparse regression model for estimating stillbirth rates for 195 countries from 2000 to 2019. The model combines covariates with a temporal smoothing process so that estimates are data-driven in country-periods with high-quality data and determined by covariates for country-periods with limited or no data. Horseshoe priors are used to encourage sparseness. The model adjusts observations with alternative stillbirth definitions and accounts for various sources of uncertainty. In-sample goodness of fit and out-of-sample validation results suggest that the model is reasonably well calibrated. The model is used by the UN Interagency Group for Child Mortality Estimation to monitor the stillbirth rate for 195 countries.

Estimates of child mortality reductions attributed to vitamin A supplementation in sub-Saharan Africa: scale up, scale back, or refocus?

Vitamin A supplementation (VAS) has been implemented in over 82 countries globally, primarily because of its beneficial effect in preventing child mortality. Secular reductions in child mortality and the implementation of alternative programs to promote vitamin A intake have led to questions on the need for national VAS programs. This study aimed to estimate child mortality changes related to VAS using current, scale-back, and scale-up coverage scenarios. Data related to demographic characteristics, fertility, intervention coverage, anthropometry, child mortality and cause-of-death structure were integrated into the Lives Saved Tool (LiST). We estimated the cause-specific (LiST model) and all-cause mortality reductions related to VAS based on evidence from recent meta-analyses. Between 2008 and 2018, VAS coverage declined in most sub-Saharan African (SSA) countries. In 2019 alone, 12% and 24% reductions in all-cause mortality related to VAS were expected to avert from 105,332 to 234,704 child deaths, respectively, in SSA; whereas the cause-specific mortality model (LiST) estimated that 141,670 child deaths were averted in 2019. Estimates of VAS-related child mortality reductions were highly variable among countries. Our scaling-back scenario led to highly variable country-level results, with expected increases in mortality rates, from a low of 0.04/1000 live births to as high as 49.3/1000 live births, suggesting that some countries could start considering scaling back, while others need to scale up. Excess child mortality that would be preventable by VAS has declined, but is still significant in many SSA countries. While scale-up of VAS is needed for most of the countries, scaling back can also be considered in some countries. Policy decisions, however, should be guided by more recent data on food consumption, vitamin A statuses, child health, and vitamin A fortification coverage.

Maternal Height-standardized Prevalence of Stunting in 67 Low- and Middle-income Countries.

BackgroundPrevalence of stunting is frequently used as a marker of population-level child undernutrition. Parental height varies widely in low- and middle-income countries (LMIC) and is also a major determinant of stunting. While stunting is a useful measure of child health, with multiple causal components, removing the component attributable to parental height may in some cases be helpful to identify shortcoming in current environments.MethodsWe estimated maternal height-standardized prevalence of stunting (SPS) in 67 LMICs and parental height-SPS in 20 LMICs and compared with crude prevalence of stunting (CPS) using data on 575,767 children under-five from 67 Demographic and Health Surveys (DHS). We supplemented the DHS with population-level measures of other child health outcomes from the World Health Organization’s (WHO) Global Health Observatory and the United Nations’ Inter-Agency Group for Child Mortality Estimation. Prevalence of stunting was defined as percentage of children with height-for-age falling below −2 z-scores from the median of the 2006 WHO growth standard.ResultsThe average CPS across countries was 27.8% (95% confidence interval [CI], 27.5–28.1%) and the average SPS was 23.3% (95% CI, 23.0–23.6%). The rank of countries according to SPS differed substantially from the rank according to CPS. Guatemala, Bangladesh, and Nepal had the biggest improvement in ranking according to SPS compared to CPS, while Gambia, Mali, and Senegal had the biggest decline in ranking. Guatemala had the largest difference between CPS and SPS with a CPS of 45.2 (95% CI, 43.7–46.9%) and SPS of 14.1 (95% CI, 12.6–15.8%). Senegal had the largest increase in the prevalence after standardizing maternal height, with a CPS of 28.0% (95% CI, 25.8–30.2%) and SPS of 31.6% (95% CI, 29.5–33.8%). SPS correlated better than CPS with other population-level measures of child health.ConclusionOur study suggests that CPS is sensitive to adjustment for maternal height. Maternal height, while a strong predictor of child stunting, is not amenable to policy interventions. We showed the plausibility of SPS in capturing current exposures to undernutrition and infections in children.

Can administrative health data be used to estimate population level birth and child mortality estimates? A comparison of India's Health Information Management System data with nationally representative survey data

•HMIS covers a large proportion of births, but a smaller fraction of child deaths compared to estimates from surveys.•Birth and death coverage in HMIS, while incomplete, has been improving nationally and for many states.•States that have improved HMIS reporting, should be studied for replicating best practices.•HMIS can provide signals for real time policy decisions, if used with due consideration of its limitations.•Including patient socioeconomic and demographic traits in HMIS, could further bolster its utility in population health.

Microbial antigen in human milk: a natural vaccine?

Microbial antigen in human milk: a natural vaccine?

Accumulating Birth Histories Across Surveys for Improved Estimates of Child Mortality

Producing reliable estimates for childhood mortality rates is essential to monitor progress towards the United Nations Sustainable Development Goals (UN SDGs) and correctly evaluate policies designed to reduce childhood mortality rates. Different model-based approaches have been proposed to assess levels and trends in childhood mortality indicators. In this paper, we propose a design-based complement that accumulates birth histories across different household surveys to increase the precision of childhood mortality rates estimates. We accumulate birth histories across different cross-sectional Demographic Health Surveys/Multiple Cluster Indicator Surveys collected in Senegal and Malawi and estimate pooled childhood mortality rates based on calendar years. We show that accumulating birth histories smoothens fluctuations in time series for national and sub-national mortality rates, establishes more stable and reliable time trends, and results in estimated standard errors of the cumulated rates that are about 50–60% lower than their counterparts from separate surveys.

Estimating Child Mortality at the Sub-national Level in Papua New Guinea: Evidence From the Integrated Health and Demographic Surveillance System.

BackgroundChild mortality is an important indication of an effective public health system. Data sources available for the estimation of child mortality in Papua New Guinea (PNG) are limited.ObjectiveThe objective of this study was to provide child mortality estimates at the sub-national level in PNG using new data from the integrated Health and Demographic Surveillance System (iHDSS).MethodUsing direct estimation and indirect estimation methods, household vital statistics and maternal birth history data were analysed to estimate three key child health indicators: Under 5 Mortality Rate (U5MR), Infant Mortality Rate (IMR) and Neonatal Mortality Rate (NMR) for the period 2014–2017. Differentials of estimates were evaluated by comparing the mean relative differences between the two methods.ResultsThe direct estimations showed U5MR of 93, IMR of 51 and NMR of 34 per 1000 live births for all the sites in the period 2014–2017. The indirect estimations reported an U5MR of 105 and IMR of 67 per 1000 live births for all the sites in 2014. The mean relative differences in U5MR and IMR estimates between the two methods were 3 and 24 percentage points, respectively. U5MR estimates varied across the surveillance sites, with the highest level observed in Hela Province (136), and followed by Eastern Highlands (122), Madang (105), and Central (42).DiscussionThe indirect estimations showed higher estimates for U5MR and IMR than the direct estimations. The differentials between IMR estimates were larger than between U5MR estimates, implying the U5MR estimates are more reliable than IMR estimates. The variations in child mortality estimates between provinces highlight the impact of contextual factors on child mortality. The high U5MR estimates were likely associated with inequality in socioeconomic development, limited access to healthcare services, and a result of the measles outbreaks that occurred in the highlands region from 2014-2017.ConclusionThe iHDSS has provided reliable data for the direct and indirect estimations of child mortality at the sub-national level. This data source is complementary to the existing national data sources for monitoring and reporting child mortality in PNG.

Global, regional, and national trends in under-5 mortality between 1990 and 2019 with scenario-based projections until 2030: a systematic analysis by the UN Inter-agency Group for Child Mortality Estimation

SummaryBackgroundThe Sustainable Development Goals (SDGs), set in 2015 by the UN General Assembly, call for all countries to reach an under-5 mortality rate (U5MR) of at least as low as 25 deaths per 1000 livebirths and a neonatal mortality rate (NMR) of at least as low as 12 deaths per 1000 livebirths by 2030. We estimated levels and trends in under-5 mortality for 195 countries from 1990 to 2019, and conducted scenario-based projections of the U5MR and NMR from 2020 to 2030 to assess country progress in, and potential for, reaching SDG targets on child survival and the potential under-5 and neonatal deaths over the next decade.MethodsLevels and trends in under-5 mortality are based on the UN Inter-agency Group for Child Mortality Estimation (UN IGME) database on under-5 mortality, which contains around 18 000 country-year datapoints for 195 countries—nearly 10 000 of those datapoints since 1990. The database includes nationally representative mortality data from vital registration systems, sample registration systems, population censuses, and household surveys. As with previous sets of national UN IGME estimates, a Bayesian B-spline bias-reduction model (B3) that considers the systematic biases associated with the different data source types was fitted to these data to generate estimates of under-5 (age 0–4 years) mortality with uncertainty intervals for 1990–2019 for all countries. Levels and trends in the neonatal mortality rate (0–27 days) are modelled separately as the log ratio of the neonatal mortality rate to the under-5 mortality rate using a Bayesian model. Estimated mortality rates are combined with livebirths data to calculate the number of under-5 and neonatal deaths. To assess the regional and global burden of under-5 deaths in the present decade and progress towards SDG targets, we constructed several scenario-based projections of under-5 mortality from 2020 to 2030 and estimated national, regional, and global under-5 mortality trends up to 2030 for each scenario.FindingsThe global U5MR decreased by 59% (90% uncertainty interval [UI] 56–61) from 93·0 (91·7–94·5) deaths per 1000 livebirths in 1990 to 37·7 (36·1–40·8) in 2019, while the annual number of global under-5 deaths declined from 12·5 (12·3–12·7) million in 1990 to 5·2 (5·0–5·6) million in 2019—a 58% (55–60) reduction. The global NMR decreased by 52% (90% UI 48–55) from 36·6 (35·6–37·8) deaths per 1000 livebirths in 1990, to 17·5 (16·6–19·0) in 2019, and the annual number of global neonatal deaths declined from 5·0 (4·9–5·2) million in 1990, to 2·4 (2·3–2·7) million in 2019, a 51% (47–54) reduction. As of 2019, 122 of 195 countries have achieved the SDG U5MR target, and 20 countries are on track to achieve the target by 2030, while 53 will need to accelerate progress to meet the target by 2030. 116 countries have reached the SDG NMR target with 16 on track, leaving 63 at risk of missing the target. If current trends continue, 48·1 million under-5 deaths are projected to occur between 2020 and 2030, almost half of them projected to occur during the neonatal period. If all countries met the SDG target on under-5 mortality, 11 million under-5 deaths could be averted between 2020 and 2030.InterpretationAs a result of effective global health initiatives, millions of child deaths have been prevented since 1990. However, the task of ending all preventable child deaths is not done and millions more deaths could be averted by meeting international targets. Geographical and economic variation demonstrate the possibility of even lower mortality rates for children under age 5 years and point to the regions and countries with highest mortality rates and in greatest need of resources and action.FundingBill & Melinda Gates Foundation, US Agency for International Development.

PENGGUNAAN METODE UN-IGME UNTUK MENGESTIMASI KEMATIAN BAYI DAN BALITA DI PERKOTAAN DAN PERDESAAN DI INDONESIA

The estimation of child mortality is very important, especially for the countries with low quality of death registration. The child mortality (IMR (Infant Mortality Rate) and U5MR (Under Five Mortality Rate) will be important to plan, organize, and evaluate the development programs. This study aimed to estimate the child mortality (IMR and U5MR) in urban and rural area of Indonesia. The indirect estimation method with one census period data was used to estimate the child mortality by using the data of: children ever born, children still alive, and number of women in reproductive age. The child mortality declined from 1997 to 2006 in urban and rural area but the child mortality in rural area was higher compared to urban area. The quality of death registration in Indonesia remains low and need to be improved. The estimation of IMR and U5MR in urban were 18 and 27 per 1000 mortality, respectively. On the other hand, the estimation of IMR and U5MR in rural were 24 and 36 per 1000 mortality, respectively. The high gap of characteristics between urban and rural area need to be explored to prevent the increasing number of IMR and U5MR.

Child mortality from sickle cell disease in Nigeria: a model-estimated, population-level analysis of data from the 2018 Demographic and Health Survey

SummaryBackgroundChild mortality from sickle cell disease in sub-Saharan Africa is presumed to be high but is not well quantified. This uncertainty contributes to the neglect of sickle cell disease and delays the prioritisation of interventions. In this study, we estimated the mortality of children in Nigeria with sickle cell disease, and the proportion of national under-5 mortality attributable to sickle cell disease.MethodsWe did a model-estimated, population-level analysis of data from Nigeria's 2018 Demographic and Health Survey (DHS) to estimate the prevalence and geographical distribution of HbSS and HbSC genotypes assuming Hardy-Weinberg equilibrium near birth. Interviews for the survey were done between Aug 14 and Dec 29, 2018, and the embedded sickle cell disease survey was done in a randomly selected third of the overall survey's households. We developed an approach for estimating child mortality from sickle cell disease by combining information on tested children and their untested siblings. Tested children were aged 6–59 months at the time of the survey. Untested siblings born 0–14 years before the survey were also included in analyses. Testing as part of the DHS was done without regard to disease status. We analysed mortality differences using the inheritance-derived genotypic distribution of untested siblings older than the tested cohort, enabling us to estimate excess mortality from sickle cell disease for the older-sibling cohort (ie, those born between 2003 and 2013).FindingsWe analysed test results for 11 186 children aged 6–59 months from 7411 households in Nigeria. The estimated average birth prevalence of HbSS was 1·21% (95% CI 1·09–1·37) and was 0·24% (0·19–0·31) for HbSC. We obtained data for estimating child mortality from 10 195 tested children (who could be matched to the individual mother survey) and 17 205 of their untested siblings. 15 227 of the siblings were in the older-sibling cohort. The group of children with sickle cell disease born between 2003 and 2013 with at least one younger sibling in the survey had about 370 excess under-5 deaths per 1000 livebirths (95% CI 150–580; p=0·0008) than children with HbAA. The estimated national average under-5 mortality for children with sickle cell disease born between 2003 and 2013 was 490 per 1000 livebirths (95% CI 270–700), 4·0 times higher (95% CI 2·1–6·0) than children with HbAA. About 4·2% (95% CI 1·7–6·9) of national under-5 mortality was attributable to excess mortality from sickle cell disease.InterpretationThe burden of child mortality from sickle cell disease in Nigeria continues to be disproportionately higher than the burden of mortality of children without sickle cell disease. Most of these deaths could be prevented if adequate resources were allocated and available focused interventions were implemented. The methods developed in this study could be used to estimate the burden of sickle cell disease elsewhere in Africa and south Asia.FundingSickle Pan African Research Consortium, and the Bill & Melinda Gates Foundation.