Erosion of the Capital City Advantage in Child Survival and Reproductive, Maternal, Newborn, and Child Health Intervention Coverage in Sub-Saharan Africa.

The place of residence is a major determinant of RMNCH outcomes, with rural areas often lagging in sub-Saharan Africa. This long-held pattern may be changing given differential progress across areas and increasing urbanization. We assessed inequalities in child mortality and RMNCH coverage across capital cities and other urban and rural areas. We analyzed mortality data from 163 DHS and MICS in 39 countries with the most recent survey conducted between 1990 and 2020 and RMNCH coverage data from 39 countries. We assessed inequality trends in neonatal and under-five mortality and in RMNCH coverage using multilevel linear regression models. Under-five mortality rates and RMNCH service coverage inequalities by place of residence have reduced substantially in sub-Saharan Africa, with rural areas experiencing faster progress than other areas. The absolute gap in child mortality between rural areas and capital cities and that between rural and other urban areas reduced respectively from 41 and 26 deaths per 1000 live births in 2000 to 23 and 15 by 2015. Capital cities are losing their primacy in child survival and RMNCH coverage over other urban areas and rural areas, especially in Eastern Africa where under-five mortality gap between capital cities and rural areas closed almost completely by 2015. While child mortality and RMNCH coverage inequalities are closing rapidly by place of residence, slower trends in capital cities and urban areas suggest gradual erosion of capital city and urban health advantage. Monitoring child mortality and RMNCH coverage trends in urban areas, especially among the urban poor, and addressing factors of within urban inequalities are urgently needed.

Identifying and Characterizing the Poorest Urban Population Using National Household Surveys in 38 Cities in Sub-Saharan Africa.

Identifying and classifying poor and rich groups in cities depends on several factors. Using data from available nationally representative surveys from 38 sub-Saharan African countries, we aimed to identify, through different poverty classifications, the best classification in urban and large city contexts. Additionally, we characterized the poor and rich groups in terms of living standards and schooling. We relied on absolute and relative measures in the identification process. For absolute ones, we selected people living below the poverty line, socioeconomic deprivation status and the UN-Habitat slum definition. We used different cut-off points for relative measures based on wealth distribution: 30%, 40%, 50%, and 60%. We analyzed all these measures according to the absence of electricity, improved drinking water and sanitation facilities, the proportion of children out-of-school, and any household member aged 10 or more with less than 6 years of education. We used the sample size, the gap between the poorest and richest groups, and the observed agreement between absolute and relative measures to identify the best measure. The best classification was based on 40% of the wealth since it has good discriminatory power between groups and median observed agreement higher than 60% in all selected cities. Using this measure, the median prevalence of absence of improved sanitation facilities was 82% among the poorer, and this indicator presented the highest inequalities. Educational indicators presented the lower prevalence and inequalities. Luanda, Ouagadougou, and N'Djaména were considered the worst performers, while Lagos, Douala, and Nairobi were the best performers. The higher the human development index, the lower the observed inequalities. When analyzing cities using nationally representative surveys, we recommend using the relative measure of 40% of wealth to characterize the poorest group. This classification presented large gaps in the selected outcomes and good agreement with absolute measures.

Climate shocks and nutrition: The role of food security policies and programs in enhancing maternal and neonatal survival in Niger.

Niger is afflicted with high rates of poverty, high fertility rates, frequent environmental crises, and climate change. Recurrent droughts and floods have led to chronic food insecurity linked to poor maternal and neonatal nutrition outcomes in vulnerable regions. We analyzed maternal and neonatal nutrition trends and subnational variability between 2000 and 2021 with a focus on the implementation of policies and programs surrounding two acute climate shocks in 2005 and 2010. We used four sources of data: (a) national household surveys for maternal and newborn nutritional indicators allowing computation of trends and differences at national and regional levels; (b) document review of food security reports; (c) 30 key informant interviews and; (d) one focus group discussion. Many food security policies and nutrition programs were enacted from 2000 to 2020. Gains in maternal and neonatal nutrition indicators were more significant in targeted vulnerable regions of Maradi, Zinder, Tahoua and Tillabéri, from 2006 to 2021. However, poor access to financial resources for policy execution and suboptimal implementation of plans have hindered progress. In response to the chronic climate crisis over the last 20 years, the Nigerien government and program implementers have demonstrated their commitment to reducing food insecurity and enhancing resilience to climate shocks by adopting a deliberate multisectoral effort. However, there is more that can be achieved with a continued focus on vulnerable regions to build resilience, targeting high risk populations, and investing in infrastructure to improve health systems, food systems, agriculture systems, education systems, and social protection.

Regularized Bayesian transfer learning for population-level etiological distributions.

Computer-coded verbal autopsy (CCVA) algorithms predict cause of death from high-dimensional family questionnaire data (verbal autopsy) of a deceased individual, which are then aggregated to generate national and regional estimates of cause-specific mortality fractions. These estimates may be inaccurate if CCVA is trained on non-local training data different from the local population of interest. This problem is a special case of transfer learning, i.e., improving classification within a target domain (e.g., a particular population) with the classifier trained in a source-domain. Most transfer learning approaches concern individual-level (e.g., a person's) classification. Social and health scientists such as epidemiologists are often more interested with understanding etiological distributions at the population-level. The sample sizes of their data sets are typically orders of magnitude smaller than those used for common transfer learning applications like image classification, document identification, etc. We present a parsimonious hierarchical Bayesian transfer learning framework to directly estimate population-level class probabilities in a target domain, using any baseline classifier trained on source-domain, and a small labeled target-domain dataset. To address small sample sizes, we introduce a novel shrinkage prior for the transfer error rates guaranteeing that, in absence of any labeled target-domain data or when the baseline classifier is perfectly accurate, our transfer learning agrees with direct aggregation of predictions from the baseline classifier, thereby subsuming the default practice as a special case. We then extend our approach to use an ensemble of baseline classifiers producing an unified estimate. Theoretical and empirical results demonstrate how the ensemble model favors the most accurate baseline classifier. We present data analyses demonstrating the utility of our approach.

Immediate newborn care and breastfeeding: EN-BIRTH multi-country validation study.

BACKGROUND: Immediate newborn care (INC) practices, notably early initiation of breastfeeding (EIBF), are fundamental for newborn health. However, coverage tracking currently relies on household survey data in many settings. "Every Newborn Birth Indicators Research Tracking in Hospitals" (EN-BIRTH) was an observational study validating selected maternal and newborn health indicators. This paper reports results for EIBF. METHODS: The EN-BIRTH study was conducted in five public hospitals in Bangladesh, Nepal, and Tanzania, from July 2017 to July 2018. Clinical observers collected tablet-based, time-stamped data on EIBF and INC practices (skin-to-skin within 1 h of birth, drying, and delayed cord clamping). To assess validity of EIBF measurement, we compared observation as gold standard to register records and women's exit-interview survey reports. Percent agreement was used to assess agreement between EIBF and INC practices. Kaplan Meier survival curves showed timing. Qualitative interviews were conducted to explore barriers/enablers to register recording. RESULTS: Coverage of EIBF among 7802 newborns observed for ≥1 h was low (10.9, 95% CI 3.8-21.0). Survey-reported (53.2, 95% CI 39.4-66.8) and register-recorded results (85.9, 95% CI 58.1-99.6) overestimated coverage compared to observed levels across all hospitals. Registers did not capture other INC practices apart from breastfeeding. Agreement of EIBF with other INC practices was high for skin-to-skin (69.5-93.9%) at four sites, but fair/poor for delayed cord-clamping (47.3-73.5%) and drying (7.3-29.0%). EIBF and skin-to-skin were the most delayed and EIBF rarely happened after caesarean section (0.5-3.6%). Qualitative findings suggested that focusing on accuracy, as well as completeness, contributes to higher quality with register reporting. CONCLUSIONS: Our study highlights the importance of tracking EIBF despite measurement challenges and found low coverage levels, particularly after caesarean births. Both survey-reported and register-recorded data over-estimated coverage. EIBF had a strong agreement with skin-to-skin but is not a simple tracer for other INC indicators. Other INC practices are challenging to measure in surveys, not included in registers, and are likely to require special studies or audits. Continued focus on EIBF is crucial to inform efforts to improve provider practices and increase coverage. Investment and innovation are required to improve measurement.

Kangaroo mother care: EN-BIRTH multi-country validation study.

BACKGROUND: Kangaroo mother care (KMC) reduces mortality among stable neonates ≤2000 g. Lack of data tracking coverage and quality of KMC in both surveys and routine information systems impedes scale-up. This paper evaluates KMC measurement as part of the Every Newborn Birth Indicators Research Tracking in Hospitals (EN-BIRTH) study. METHODS: The EN-BIRTH observational mixed-methods study was conducted in five hospitals in Bangladesh, Nepal and Tanzania from 2017 to 2018. Clinical observers collected time-stamped data as gold standard for mother-baby pairs in KMC wards/corners. To assess accuracy, we compared routine register-recorded and women's exit survey-reported coverage to observed data, using different recommended denominator options (≤2000 g and ≤ 2499 g). We analysed gaps in quality of provision and experience of KMC. In the Tanzanian hospitals, we assessed daily skin-to-skin duration/dose and feeding frequency. Qualitative data were collected from health workers and data collectors regarding barriers and enablers to routine register design, filling and use. RESULTS: Among 840 mother-baby pairs, compared to observed 100% coverage, both exit-survey reported (99.9%) and register-recorded coverage (92.9%) were highly valid measures with high sensitivity. KMC specific registers outperformed general registers. Enablers to register recording included perceptions of data usefulness, while barriers included duplication of data elements and overburdened health workers. Gaps in KMC quality were identified for position components including wearing a hat. In Temeke Tanzania, 10.6% of babies received daily KMC skin-to-skin duration/dose of ≥20 h and a further 75.3% received 12-19 h. Regular feeding ≥8 times/day was observed for 36.5% babies in Temeke Tanzania and 14.6% in Muhimbili Tanzania. Cup-feeding was the predominant assisted feeding method. Family support during admission was variable, grandmothers co-provided KMC more often in Bangladesh. No facility arrangements for other family members were reported by 45% of women at exit survey. CONCLUSIONS: Routine hospital KMC register data have potential to track coverage from hospital KMC wards/corners. Women accurately reported KMC at exit survey and evaluation for population-based surveys could be considered. Measurement of content, quality and experience of KMC need consensus on definitions. Prioritising further KMC measurement research is important so that high quality data can be used to accelerate scale-up of high impact care for the most vulnerable.

Estimating population-based coverage of reproductive, maternal, newborn, and child health (RMNCH) interventions from health management information systems: a comprehensive review.

BACKGROUND: Routinely collected health facility data usually captured and stored in Health Management Information Systems (HMIS) are potential sources of data for frequent and local disaggregated estimation of the coverage of reproductive, maternal, newborn, and child health interventions (RMNCH), but have been under-utilized due to concerns over data quality. We reviewed methods for estimation of national or subnational coverage of RMNCH interventions using HMIS data exclusively or in conjunction with survey data from low- and middle-income countries (LMICs). METHODS: We conducted a comprehensive review of studies indexed in PubMed and Scopus to identify potential papers based on predefined search terms. Two reviewers screened the papers using defined inclusion and exclusion criteria. Following sequences of title, abstract and full paper reviews, we retained 18 relevant papers. RESULTS: 12 papers used only HMIS data and 6 used both HMIS and survey data. There is enormous lack of standards in the existing methods for estimating RMNCH intervention coverage; all appearing to be highly author dependent. The denominators for coverage measures were estimated using census, non-census and combined projection-based methods. No satisfactory methods were found for treatment-based coverage indicators for which the estimation of target population requires the population prevalence of underlying conditions. The estimates of numerators for the coverage measures were obtained from the count of users or visits and in some cases correction for completeness of reporting in the HMIS following an assessment of data quality. CONCLUSIONS: Standard methods for correcting numerators from HMIS data for accurate estimation of coverage of RMNCH interventions are needed to expand the use of these data. More research and investments are required to improve denominators for health facility-derived statistics. Improvement in routine data quality and analytical methods would allow for timely estimation of RMNCH intervention coverage at the national and subnational levels.

Measuring coverage of maternal and child health services using routine health facility data: a Sierra Leone case study.

BACKGROUND: There are limited existing approaches to generate estimates from Routine Health Information Systems (RHIS) data, despite the growing interest to these data. We calculated and assessed the consistency of maternal and child health service coverage estimates from RHIS data, using census-based and health service-based denominators in Sierra Leone. METHODS: We used Sierra Leone 2016 RHIS data to calculate coverage of first antenatal care contact (ANC1), institutional delivery and diphtheria-pertussis-tetanus 3 (DPT3) immunization service provision. For each indicator, national and district level coverages were calculated using denominators derived from two census-based and three health service-based methods. We compared the coverage estimates from RHIS data to estimates from MICS 2017. We considered the agreement adequate when estimates from RHIS fell within the 95% confidence interval of the survey estimate. RESULTS: We found an overall poor consistency of the coverage estimates calculated from the census-based methods. ANC1 and institutional delivery coverage estimates from these methods were greater than 100% in about half of the fourteen districts, and only 3 of the 14 districts had estimates consistent with the survey data. Health service-based methods generated better estimates. For institutional delivery coverage, five districts met the agreement criteria using BCG service-based method. We found better agreement for DPT3 coverage estimates using DPT1 service-based method as national coverage was close to survey data, and estimates were consistent for 8 out of 14 districts. DPT3 estimates were consistent in almost half of the districts (6/14) using ANC1 service-based method. CONCLUSION: The study highlighted the challenge in determining an appropriate denominator for RHIS-based coverage estimates. Systematic and transparent data quality check and correction, as well as rigorous approaches to determining denominators are key considerations to generate accurate coverage statistics using RHIS data.

Using health facility deaths to estimate population causes of neonatal and child mortality in four African countries.

BACKGROUND: Verbal autopsy is the main method used in countries with weak civil registration systems for estimating community causes of neonatal and 1-59-month-old deaths. However, validation studies of verbal autopsy methods are limited and assessment has been dependent on hospital-based studies, with uncertain implications for its validity in community settings. If the distribution of community deaths by cause was similar to that of facility deaths, or could be adjusted according to related demographic factors, then the causes of facility deaths could be used to estimate population causes. METHODS: Causes of neonatal and 1-59-month-old deaths from verbal/social autopsy (VASA) surveys in four African countries were estimated using expert algorithms (EAVA) and physician coding (PCVA). Differences between facility and community deaths in individual causes and cause distributions were examined using chi-square and cause-specific mortality fractions (CSMF) accuracy, respectively. Multinomial logistic regression and random forest models including factors from the VASA studies that are commonly available in Demographic and Health Surveys were built to predict population causes from facility deaths. RESULTS: Levels of facility and community deaths in the four countries differed for one to four of 10 EAVA or PCVA neonatal causes and zero to three of 12 child causes. CSMF accuracy for facility compared to community deaths in the four countries ranged from 0.74 to 0.87 for neonates and 0.85 to 0.95 for 1-59-month-olds. Crude CSMF accuracy in the prediction models averaged 0.86 to 0.88 for neonates and 0.93 for 1-59-month-olds. Adjusted random forest prediction models increased average CSMF accuracy for neonates to, at most, 0.90, based on small increases in all countries. CONCLUSIONS: There were few differences in facility and community causes of neonatal and 1-59-month-old deaths in the four countries, and it was possible to project the population CSMF from facility deaths with accuracy greater than the validity of verbal autopsy diagnoses. Confirmation of these findings in additional settings would warrant research into how medical causes of deaths in a representative sample of health facilities can be utilized to estimate the population causes of child death.

Wealth-related inequalities in the coverage of reproductive, maternal, newborn and child health interventions in 36 countries in the African Region.

OBJECTIVE: To investigate whether sub-Saharan African countries have succeeded in reducing wealth-related inequalities in the coverage of reproductive, maternal, newborn and child health interventions. METHODS: We analysed survey data from 36 countries, grouped into Central, East, Southern and West Africa subregions, in which at least two surveys had been conducted since 1995. We calculated the composite coverage index, a function of essential maternal and child health intervention parameters. We adopted the wealth index, divided into quintiles from poorest to wealthiest, to investigate wealth-related inequalities in coverage. We quantified trends with time by calculating average annual change in index using a least-squares weighted regression. We calculated population attributable risk to measure the contribution of wealth to the coverage index. FINDINGS: We noted large differences between the four regions, with a median composite coverage index ranging from 50.8% for West Africa to 75.3% for Southern Africa. Wealth-related inequalities were prevalent in all subregions, and were highest for West Africa and lowest for Southern Africa. Absolute income was not a predictor of coverage, as we observed a higher coverage in Southern (around 70%) compared with Central and West (around 40%) subregions for the same income. Wealth-related inequalities in coverage were reduced by the greatest amount in Southern Africa, and we found no evidence of inequality reduction in Central Africa. CONCLUSION: Our data show that most countries in sub-Saharan Africa have succeeded in reducing wealth-related inequalities in the coverage of essential health services, even in the presence of conflict, economic hardship or political instability.

Prevalence of institutional delivery and its correlates amongst women of reproductive age in Mozambique: a cross-sectional analysis.

BACKGROUND: The healthcare system in Mozambique is striving to reduce the high maternal and child mortality rates and stay on par with the Sustainable Development Goals (SDG 3.1). A key strategy to curb maternal and child mortality is to promote the use of professional childbirth services proven to be highly effective in averting maternal deaths. Currently, little is known about the use of childbirth services in Mozambique. The present study investigated the prevalence of professional healthcare delivery services and identified their sociodemographic correlates. METHODS: This study used cross-sectional data on 7080 women aged 15-49 years who reported having a child during the past 5 years. The data were collected from the 2011Mozambique Demographic and Health Survey. The outcome variables were the choice of childbirth services that included 1) place of delivery (respondent's home versus health facility), and mode of delivery (caesarean section versus vaginal birth). Data were analyzed using descriptive and multivariate regression methods. RESULTS: The prevalence of health facility and C-section delivery was 70.7 and 5.6%, respectively. There was a difference in the use of professional birthing services between urban and rural areas. Having better educational status and living in households of higher wealth quintiles showed a positive association with the use of facility delivery services among both urban and rural residents. Regarding ethnicity, women of Portugais [2.688,1.540,4.692], Cindau [1.876,1.423,2.474] and Xichangana [1.557,1.215,1.996] had relatively higher odds of using facility delivery services than others. Antenatal care (ANC) visits were a significant predictor of facility delivery services both in urban [OR = 1.655, 95%CI = 1.235,2.218] and rural [OR = 1.265, 95%CI = 1.108,1.445] areas. Among rural women, ANC visit was a significant predictor of C-section delivery [1.570,1.042,2.365]. CONCLUSION: More than a quarter of the women in Mozambique were not using health facility delivery services, with the prevalence being noticeably lower in the rural areas.

Socioeconomic factors contributing to under-five mortality in sub-Saharan Africa: a decomposition analysis.

BACKGROUND: In sub-Saharan Africa, socioeconomic factors such as place of residence, mother's educational level, or household wealth, are strongly associated with risk factors of under-five mortality (U5M) such as health behavior or exposure to diseases and injuries. The aim of the study was to assess the relative contribution of four known socioeconomic factors to the variability in U5M in sub-Saharan countries. METHODS: The study was based on birth histories from the Demographic and Health Surveys conducted in 32 sub-Saharan countries in 2010-2016. The relative contribution of sex of the child, place of residence, mother's educational level, and household wealth to the variability in U5M was assessed using a regression-based decomposition of a Gini-type index. RESULTS: The Gini index - measuring the variability in U5M related to the four socioeconomic factors - varied from 0.006 (95%CI: 0.001-0.010) in Liberia 2013 to 0.034 (95%CI: 0.029-0.039) in Côte d'Ivoire 2011/12. The main contributors to the Gini index (with a relative contribution higher than 25%) were different across countries: mother's educational level in 13 countries, sex of the child in 12 countries, household wealth in 11 countries, and place of residence in 8 countries (in some countries, more than one main contributor was identified). CONCLUSIONS: Factors related to socioeconomic status exert varied effects on the variability in U5M in sub-Saharan African countries. The findings provide evidence in support of prioritizing intersectoral interventions aiming at improving child survival in all subgroups of a population.

Socioeconomic Inequalities Persist Despite Declining Stunting Prevalence in Low- and Middle-Income Countries.

Background: Global stunting prevalence has been nearly halved between 1990 and 2016, but it remains unclear whether this decline has benefited poor and rural populations within low- and middle-income countries (LMICs). Objective: We assessed time trends in stunting among children <5 y of age (under-5) according to household wealth and place of residence in 67 LMICs. Methods: Stunting prevalence was analyzed in 217 nationally representative Demographic and Health Surveys and Multiple Indicator Cluster Surveys from 67 countries with ≥2 surveys between 1993 and 2014. National estimates were stratified by wealth and area of residence, comparing the poorest 40% with the wealthiest 60%, and those residing in urban and rural areas. Time trends were calculated for LMICs by using multilevel regression models weighted by under-5 population, with stratification by wealth and by residence. Trends in absolute (slope index of inequality; SII) and relative (concentration index; CIX) inequalities were calculated. Results: Mean prevalences in 1993 were 53.7% in low-income and 48.2% in middle-income countries, with annual average linear declines of 0.76 and 0.72 percentage points (pp), respectively. Although similar slopes of declines were observed for the poorest 40% and wealthiest 60% groups in all countries (0.78 and 0.74 pp, respectively), absolute and relative inequalities increased over time in low-income countries (SII increased from -19.3% in 1993 to -23.7% in 2014 and CIX increased from -6.2% to -10.8% in the same period). In middle-income countries, socioeconomic inequalities remained stable. Overall, stunting prevalence decreased more rapidly among rural than for urban children (0.78 and 0.55 pp, respectively). Conclusions: The prevalence of stunting is decreasing. Poor-rich gaps are stable in middle-income countries and slightly increasing in low-income countries. Rural-urban inequalities are decreasing over time.

Inequalities in maternal health care utilization in Benin: a population based cross-sectional study.

BACKGROUND: Ensuring equitable access to maternal health care including antenatal, delivery, postnatal services and fertility control methods, is one of the most critical challenges for public health sector. There are significant disparities in maternal health care indicators across many geographical locations, maternal, economic, socio-demographic factors in many countries in sub-Sahara Africa. In this study, we comparatively explored the utilization level of maternal health care, and examined disparities in the determinants of major maternal health outcomes. METHODS: This paper used data from two rounds of Benin Demographic and Health Survey (BDHS) to examine the utilization and disparities in factors of maternal health care indicators using logistic regression models. Participants were 17,794 and 16,599 women aged between15-49 years in 2006 and 2012 respectively. Women's characteristics were reported in percentage, mean and standard deviation. RESULTS: Mean (±SD) age of the participants was 29.0 (±9.0) in both surveys. The percentage of at least 4 ANC visits was approximately 61% without any change between the two rounds of surveys, facility based delivery was 93.5% in 2012, with 4.9% increase from 2006; postnatal care was currently 18.4% and contraceptive use was estimated below one-fifth. The results of multivariable logistic regression models showed disparities in maternal health care service utilization, including antenatal care, facility-based delivery, postnatal care and contraceptive use across selected maternal factors. The current BHDS showed age, region, religion were significantly associated with maternal health care services. Educated women, those from households of high wealth index and women currently working were more likely to utilize maternal health care services, compared to women with no formal education, from poorest households or not currently employed. Women who watch television (TV) were 1.31 (OR = 1.31; 95% CI = 1.13-1.52), 1.69 (OR = 1.69; 95% CI = 1.20-2.37) and 1.38 (OR = 1.38; 95% CI = 1.16-1.65) times as likely to utilize maternal health care services after adjusting for other covariates. CONCLUSION: The findings would guide stakeholders to address inequalities in maternal health care services. More so, health care programmes and policies should be strengthened to enhance accessibility as well as improve the utilization of maternal care services, especially for the disadvantaged, uneducated and those who live in hard-to-reach rural areas in Benin. The Benin government needs to create strategies that cover both the supply and demand side factors at attain the universal health coverage.

Stillbirths: rates, risk factors, and acceleration towards 2030.

An estimated 2.6 million third trimester stillbirths occurred in 2015 (uncertainty range 2.4-3.0 million). The number of stillbirths has reduced more slowly than has maternal mortality or mortality in children younger than 5 years, which were explicitly targeted in the Millennium Development Goals. The Every Newborn Action Plan has the target of 12 or fewer stillbirths per 1000 births in every country by 2030. 94 mainly high-income countries and upper middle-income countries have already met this target, although with noticeable disparities. At least 56 countries, particularly in Africa and in areas affected by conflict, will have to more than double present progress to reach this target. Most (98%) stillbirths are in low-income and middle-income countries. Improved care at birth is essential to prevent 1.3 million (uncertainty range 1.2-1.6 million) intrapartum stillbirths, end preventable maternal and neonatal deaths, and improve child development. Estimates for stillbirth causation are impeded by various classification systems, but for 18 countries with reliable data, congenital abnormalities account for a median of only 7.4% of stillbirths. Many disorders associated with stillbirths are potentially modifiable and often coexist, such as maternal infections (population attributable fraction: malaria 8.0% and syphilis 7.7%), non-communicable diseases, nutrition and lifestyle factors (each about 10%), and maternal age older than 35 years (6.7%). Prolonged pregnancies contribute to 14.0% of stillbirths. Causal pathways for stillbirth frequently involve impaired placental function, either with fetal growth restriction or preterm labour, or both. Two-thirds of newborns have their births registered. However, less than 5% of neonatal deaths and even fewer stillbirths have death registration. Records and registrations of all births, stillbirths, neonatal, and maternal deaths in a health facility would substantially increase data availability. Improved data alone will not save lives but provide a way to target interventions to reach more than 7000 women every day worldwide who experience the reality of stillbirth.

Predicting high risk births with contraceptive prevalence and contraceptive method-mix in an ecologic analysis.

BACKGROUND: Increased contraceptive use has been associated with a decrease in high parity births, births that occur close together in time, and births to very young or to older women. These types of births are also associated with high risk of under-five mortality. Previous studies have looked at the change in the level of contraception use and the average change in these types of high-risk births. We aim to predict the distribution of births in a specific country when there is a change in the level and method of modern contraception. METHODS: We used data from full birth histories and modern contraceptive use from 207 nationally representative Demographic and Health Surveys covering 71 countries to describe the distribution of births in each survey based on birth order, preceding birth space, and mother's age at birth. We estimated the ecologic associations between the prevalence and method-mix of modern contraceptives and the proportion of births in each category. Hierarchical modelling was applied to these aggregated cross sectional proportions, so that random effects were estimated for countries with multiple surveys. We use these results to predict the change in type of births associated with scaling up modern contraception in three different scenarios. RESULTS: We observed marked differences between regions, in the absolute rates of contraception, the types of contraceptives in use, and in the distribution of type of birth. Contraceptive method-mix was a significant determinant of proportion of high-risk births, especially for birth spacing, but also for mother's age and parity. Increased use of modern contraceptives is especially predictive of reduced parity and more births with longer preceding space. However, increased contraception alone is not associated with fewer births to women younger than 18 years or a decrease in short-spaced births. CONCLUSIONS: Both the level and the type of contraception are important factors in determining the effects of family planning on changes in distribution of high-risk births. The best predictions for how birth risk changes with increased modern contraception and for different contraception methods allow for more nuanced predictions specific to each country and can aid better planning for the scaling up of modern contraception.

A qualitative exploration of care-seeking pathways for sick children in the rural Oromia region of Ethiopia.

BACKGROUND: Ethiopia has experienced rapid improvements in its healthcare infrastructure, such as through the recent scale up of integrated community case management (iCCM) delivered by community-based health extension workers (HEWs) targeting children under the age of five. Despite notable improvements in child outcomes, the use of HEWs delivering iCCM remains very low. The aim of our study was to explain this phenomenon by examining care-seeking practices and treatment for sick children in two rural districts in the Oromia Region of Ethiopia. METHODS: Using qualitative methods, we explored perceptions of child illness, influences on decision-making processes occurring over the course of a child's illness and caregiver perceptions of available community-based sources of child illness care. Sixteen focus group discussions (FGDs) and 40 in-depth interviews (IDIs) were held with mothers of children under age five. For additional perspective, 16 IDIs were conducted fathers and 22 IDIs with health extension workers and community health volunteers. RESULTS: Caregivers often described the act of care-seeking for a sick child as a time of considerable uncertainty. In particular, mothers of sick children described the cultural, social and community-based resources available to minimize this uncertainty as well as constraints and strategies for accessing these resources in order to receive treatment for a sick child. The level of trust and familiarity were the most common dynamics noted as influencing care-seeking strategies; trust in biomedical and government providers was often low. CONCLUSIONS: Overall, our research highlights the multiple and dynamic influences on care-seeking for sick children in rural Ethiopia. An understanding of these influences is critical for the success of existing and future health interventions and continued improvement of child health in Ethiopia.

Diarrhea management in children under five in sub-Saharan Africa: does the source of care matter? A Countdown analysis.

BACKGROUND: Diarrhea remains a high burden disease, responsible for nine percent of deaths in children under five globally. We analyzed diarrhea management practices in young children and their association with the source of care. METHODS: We used Demographic and Health Survey data from 12 countries in sub-Saharan Africa with high burdens of childhood diarrhea. We classified the quality of diarrhea management practices as good, fair, or poor based on mothers' reports for children with diarrhea, using WHO/UNICEF recommendations for appropriate treatment. We described the prevalence of diarrhea management by type and assessed the association between good management and source of care, adjusting for potential confounders. RESULTS: Prevalence of good diarrhea management is low in 11 of the 12 analyzed surveys, varying from 17 % in Cote d'Ivoire to 38 % in Niger. The exception is Sierra Leone, where prevalence of good practice is 67 %. Prevalence of good management was low even among children taken to health facilities [median 52 %, range: 34-64 %]. Diarrhea careseeking from health facilities or community providers was associated with higher odds of good management than care from traditional/informal sources or no care. Careseeking from facilities did not result systematically in a higher likelihood of good diarrhea management than care from community providers. The odds of good diarrhea management were similar for community versus facility providers in six countries, higher in community than facility providers in two countries, and higher in facility than in community providers in four countries. CONCLUSION: Many children's lives can be saved with correct management of childhood diarrhea. Too many children are not receiving adequate care for diarrhea in high-burden sub-Saharan African countries, even among those seen in health facilities. Redoubling efforts to increase careseeking and improve quality of care for childhood diarrhea in both health facilities and at community level is an urgent priority.

Count every newborn; a measurement improvement roadmap for coverage data.

BACKGROUND: The Every Newborn Action Plan (ENAP), launched in 2014, aims to end preventable newborn deaths and stillbirths, with national targets of ≤12 neonatal deaths per 1000 live births and ≤12 stillbirths per 1000 total births by 2030. This requires ambitious improvement of the data on care at birth and of small and sick newborns, particularly to track coverage, quality and equity. METHODS: In a multistage process, a matrix of 70 indicators were assessed by the Every Newborn steering group. Indicators were graded based on their availability and importance to ENAP, resulting in 10 core and 10 additional indicators. A consultation process was undertaken to assess the status of each ENAP core indicator definition, data availability and measurement feasibility. Coverage indicators for the specific ENAP treatment interventions were assigned task teams and given priority as they were identified as requiring the most technical work. Consultations were held throughout. RESULTS: ENAP published 10 core indicators plus 10 additional indicators. Three core impact indicators (neonatal mortality rate, maternal mortality ratio, stillbirth rate) are well defined, with future efforts needed to focus on improving data quantity and quality. Three core indicators on coverage of care for all mothers and newborns (intrapartum/skilled birth attendance, early postnatal care, essential newborn care) have defined contact points, but gaps exist in measuring content and quality of the interventions. Four core (antenatal corticosteroids, neonatal resuscitation, treatment of serious neonatal infections, kangaroo mother care) and one additional coverage indicator for newborns at risk or with complications (chlorhexidine cord cleansing) lack indicator definitions or data, especially for denominators (population in need). To address these gaps, feasible coverage indicator definitions are presented for validity testing. Measurable process indicators to help monitor health service readiness are also presented. A major measurement gap exists to monitor care of small and sick babies, yet signal functions could be tracked similarly to emergency obstetric care. CONCLUSIONS: The ENAP Measurement Improvement Roadmap (2015-2020) outlines tools to be developed (e.g., improved birth and death registration, audit, and minimum perinatal dataset) and actions to test, validate and institutionalise proposed coverage indicators. The roadmap presents a unique opportunity to strengthen routine health information systems, crosslinking these data with civil registration and vital statistics and population-based surveys. Real measurement change requires intentional transfer of leadership to countries with the greatest disease burden and will be achieved by working with centres of excellence and existing networks.