Inequalities in child mortality in ten major African cities

Amenable Mortality in Children under 5: An Indicator for Identifying Inequalities in Healthcare Delivery: A Review

Universal health coverage has been proposed as a strategy to improve health in low- and middle-income countries, but this depends on a good provision of health services. Under-5 mortality (U5M) reflects the quality of health services, and its reduction has been a milestone in modern society, reducing global mortality rates by more than two-thirds between 1990 and 2020. However, despite these impressive achievements, they are still insufficient, and most deaths in children under 5 can be prevented with the provision of timely and high-quality health services. The aim of this paper is to conduct a literature review on amenable (treatable) mortality in children under 5. This indicator is based on the concept that deaths from certain causes should not occur in the presence of timely and effective medical care. A systematic and exhaustive review of available literature on amenable mortality in children under 5 was conducted using MEDLINE/PubMed, Cochrane CENTRAL, OVID medline, Scielo, Epistemonikos, ScienceDirect, and Google Scholar in both English and Spanish. Both primary sources, such as scientific articles, and secondary sources, such as bibliographic indices, websites, and databases, were used. Results: The main cause of amenable mortality in children under 5 was respiratory disease, and the highest proportion of deaths occurred in the perinatal period. Approximately 65% of avoidable deaths in children under 5 were due to amenable mortality, that is, due to insufficient quality in the provision of health services. Most deaths in all countries and around the world are preventable, primarily through effective and timely access to healthcare (amenable mortality) and the management of public health programs focused on mothers and children (preventable mortality).

Mortality in rural coastal Kenya measured using the Kilifi Health and Demographic Surveillance System: a 16-year descriptive analysis

Background: The Kilifi Health and Demographic Surveillance System (KHDSS) was established in 2000 to define the incidence and prevalence of local diseases and evaluate the impact of community-based interventions. KHDSS morbidity data have been reported comprehensively but mortality has not been described. This analysis describes mortality in the KHDSS over 16 years. Methods: We calculated mortality rates from 2003-2018 in four intervals of equal duration and assessed differences in mortality across these intervals by age and sex. We calculated the period survival function and median survival using the Kaplan-Meier method and mean life expectancies using abridged life tables. We estimated trend and seasonality by decomposing a time series of monthly mortality rates. We used choropleth maps and random-effects Poisson regression to investigate geographical heterogeneity. Results: Mortality declined by 36% overall between 2003-2018 and by 59% in children aged <5 years. Most of the decline occurred between 2003 and 2006. Among adults, the greatest decline (49%) was observed in those aged 15-54 years. Life expectancy at birth increased by 12 years. Females outlived males by 6 years. Seasonality was only evident in the 1-4 year age group in the first four years. Geographical variation in mortality was ±10% of the median value and did not change over time. Conclusions: Between 2003 and 2018, mortality among children and young adults has improved substantially. The steep decline in 2003-2006 followed by a much slower reduction thereafter suggests improvements in health and wellbeing have plateaued in the last 12 years. However, there is substantial inequality in mortality experience by geographical location.

[Social inequalities in under-five mortality: a systematic review]

OBJECTIVE

To identify the characteristics of the published studies on social inequalities in under-five mortality, their theoretical perspectives, axes of inequality, methods and results.

METHOD

We carried out a systematic literature review. We consulted four electronic databases and Google Scholar, for studies published between 2010 and 2018.

RESULTS

We analyzed 126 articles. In 62.7%, territory was studied as the axis of inequality, followed by socioeconomic determinants (27.8%). Neonatal, infant and under-five mortality was analyzed as an output in health in 19.0%, 49.2% and 32.3%, respectively. It predominated ecological (62.7%) and longitudinal (50.0%) studies. Significant reductions in mortality rates were found, however, the decline was not homogeneous among subpopulations.

CONCLUSIONS

The literature reports a marked decrease in under-five mortality; however, the gaps between different axes of inequality continue and in some cases they have increased. Gaps varied according to time, place, axis of inequality and type of mortality analyzed.

Factors contributing to household wealth inequality in under-five deaths in low- and middle-income countries: decomposition analysis

BACKGROUND

The burden of under-5 deaths is disproportionately high among poor households relative to economically viable ones in developing countries. Despite this, the factors driving this inequality has not been well explored. This study decomposed the contributions of the factors associated with wealth inequalities in under-5 deaths in low- and middle-income countries (LMICs).

METHODS

We analysed data of 856,987 children from 66,495 neighbourhoods across 59 LMICs spanning recent Demographic and Health Surveys (2010-2018). Under-5 mortality was described as deaths among live births within 0 to 59 months of birth and it was treated as a dichotomous variable (dead or alive). The prevalence of under-five deaths was stratified using household wealth status. A Fairlie decomposition analysis was utilized to investigate the relative contribution of the factors associated with household wealth inequality in under-5 deaths at p<0.05. The WHO health equity assessment toolkit Plus was used to assess the differences (D) ratios (R), population attributable risk (PAR), and population attributable fraction (PAF) in household wealth inequalities across the countries.

RESULTS

The proportion of children from poor households was 45%. The prevalence of under-5 deaths in all samples was 51 per 1000 children, with 60 per 1000 and 44 per 1000 among children from poor and non-poor households (p<0.001). The prevalence of under-5 deaths was higher among children from poor households than those from non-poor households in all countries except in Ethiopia, Tanzania, Zambia, Lesotho, Gambia and Sierra Leone, and in the Maldives. Thirty-four of the 59 countries showed significantly higher under-5 deaths in poor households than in non-poor households (pro-non-poor inequality) and no significant pro-poor inequality. Rural-urban contexts, maternal education, neighborhood socioeconomic status, sex of the child, toilet kinds, birth weight and preceding birth intervals, and sources of drinking water are the most significant drivers of pro-poor inequities in under-5 deaths in these countries.

CONCLUSIONS

Individual-level and neighbourhood-level factors were associated with a high prevalence of under-5 deaths among poor households in LMICs. Interventions in countries should focus on reducing the gap between the poor and the rich as well as improve the education and livelihood of disadvantaged people.

Mortality in rural coastal Kenya measured using the Kilifi Health and Demographic Surveillance System: a 16-year descriptive analysis

Background: The Kilifi Health and Demographic Surveillance System (KHDSS) was established in 2000 to define the incidence and prevalence of local diseases and evaluate the impact of community-based interventions. KHDSS morbidity data have been reported comprehensively but mortality has not been described. This analysis describes mortality in the KHDSS over 16 years. Methods: We calculated mortality rates from 2003–2018 in four intervals of equal duration and assessed differences in mortality across these intervals by age and sex. We calculated the period survival function and median survival using the Kaplan–Meier method and mean life expectancies using abridged life tables. We estimated trend and seasonality by decomposing a time series of monthly mortality rates. We used choropleth maps and random-effects Poisson regression to investigate geographical heterogeneity. Results: Mortality declined by 36% overall between 2003–2018 and by 59% in children aged <5 years. Most of the decline occurred between 2003 and 2006. Among adults, the greatest decline (49%) was observed in those aged 15–54 years. Life expectancy at birth increased by 12 years. Females outlived males by 6 years. Seasonality was only evident in the 1–4 year age group in the first four years. Geographical variation in mortality was ±10% of the median value and did not change over time. Conclusions: Between 2003 and 2018, mortality among children and young adults has improved substantially. The steep decline in 2003–2006 followed by a much slower reduction thereafter suggests improvements in health and wellbeing have plateaued in the last 12 years. However, there is substantial inequality in mortality experience by geographical location.

Dynamics of inequality in child under-nutrition in Ethiopia

INTRODUCTION

Although Ethiopia has already achieved a remarkable progress in reducing under-five mortality in the last decades, undernutrition among children is still a common problem in this country. Socioeconomic inequalities in health outcomes in Ethiopia have been thus of focus in academia and policy spheres for a while now. This study provides new evidence on child undernutrition inequalities in Ethiopia using longitudinal perspective.

METHOD

Using three round of household panel survey (from 2012 to 2016), we use concentration index (associated curve), different mobility index approaches for measuring inequalities and its dynamics, and decomposition method to identify contributing factors.

RESULTS

In all concentration index computing approaches and socioeconomic status ranking variables, the concentration indices are significant with negative value. This implies that in either of short-run or long-run inequality estimates, the burden of unequal distribution of undernutrition remains on the poor with significant difference across regions. While employing different SES ranking variables, the difference in the concentration indices is only found significant in case of Height-for-age Z-score. It signifies that relatively higher inequality is measured using consumption as ranking variable. Significant difference in inequality is also shown across regions. With respect to dynamics of inequalities, results on mobility indices computed based on Allanson et al. (Longitudinal analysis of income-related health inequality. Dundee Discussion Working Paper No. 214, 2010) approach show that inequality remain stable (persistent) in Height-for- age Z-score, and reduction of inequality in Weight-for- age Z-score while in case of Weight-for- height Z-score, there is no clear trend over subsequent waves. Results on decomposition of inequalities show that the major contributors are wealth index, consumption and mother's education.

CONCLUSION

The argument of the choice of welfare indicator can have a large and significant impact on measured socioeconomic inequalities in a health variable which it depends on the variable examined. Employing longitudinal perspective rather than weighted average of cross-sectional data is justifiable to see the dynamic of inequality in child malnutrition. In both socioeconomic status ranking variables, the bulk of inequality in malnutrition is caused by inequality in socioeconomic status in which it disfavours the poor in both cases. This calls for enhancing the policy measures that narrow socioeconomic gaps between groups in the population and targeting on early childhood intervention and nutrition sensitive.

Neighbourhood-level housing quality indices for health assessment in Dakar, Senegal

In sub-Saharan African cities, the dearth of accurate and detailed data is a major problem in the study of health and socioeconomic changes driven by rapid urbanization. Data on both health determinants and health outcomes are often lacking or are of poor quality. Proxies associated with socioeconomic differences are needed to compensate the lack of data. One of the most straightforward proxies is housing quality, which is a multidimensional concept including characteristics of both the built and natural environments. In this work, we combined the 2013 census data with remotely sensed land cover and land use data at a very high resolution in order to develop an integrated housing quality-based typology of the neighbourhoods in Dakar, Senegal. Principal component analysis and hierarchical classification were used to derive neighbourhood housing quality indices and four neighbourhood profiles. Paired tests revealed significant variations in the censusderived mortality rates between profile 1, associated with the lowest housing quality, and the three other profiles. These findings demonstrate the importance of housing quality as an important health risk factor. From a public health perspective, it should be a useful contribution for geographically targeted planning health policies, at the neighbourhood spatial level, which is the most appropriate administrative level for interventions.

Health Inequalities in Under-Five Mortality: An Assessment of Empowered Action Group (EAG) States of India

Background: The effect of childhood well-being programs is commonly interconnected with a change in mortality trends. The proportion of disparity shows that inequality in child mortality is more collective in the similarly evolved states than the poorer states in India. Objective: To estimate and compare the health inequality of under-five mortality in Empowered Action groups (EAG) states of India. Methods: Data from the National Family Health Survey (NFHS-4) was used only for the EAG States of India. Under-five mortality rates (U5MR) were calculated for associated background characteristics by using the life table method. Wealth inequality was assessed separately for all EAG states by calculating measures of concentration index (CI). Concentration curves (CC) were also plotted to see the difference in inequality. Results: Higher U5MR was observed in all EAG states compared with estimates for overall India. On comparing estimates of inequality, CI values show the substantial burden of U5MR among EAG states of India. The CC shows the lowest inequality in EAG states of India. Conclusion: The results suggested the need to receive various health strategy intercessions in agreement with the instance of ever-changing commitments of economic components to child health disparities in EAG states. Measuring the impact of determinants to wealth-related inequality in U5MR helps in lining up the interventions targeted at improving child survival.

Sexual and Gender-Based Violence Among Refugees and Internally Displaced Persons in the Democratic Republic of the Congo: Post-Conflict Scenario

The ongoing humanitarian crisis in the Democratic Republic of the Congo has triggered sexual and gender-based violence, including rape, sexual slavery, trafficking, intimate partner violence, and sexual exploitation. Gender inequalities and abuse of power experienced by women and young girls at refugee settings further exacerbate their vulnerability to different forms of violence. This study aimed to offer an evidence-based approach to developing strategies in tackling the complex problem of sexual and gender-based violence among refugees and internally displaced persons in the Congo. We conducted a narrative review of all the relevant papers known to the authors to explore the origins of the problem, its implications on public health, and its impact on equity. The study revealed that sexual assault survivors face physical and psychological sufferings, excruciating emotions, and profound disruption of their social well-being since they are often stigmatized and ostracized by society. The analysis of current government policies revealed a lack of programs to address survivors' specific concerns and policy enforcement problems. This study suggested strategic objectives and policy implementation steps. The proposed strategies address women empowerment and gender stigma, provision of effective health services, and adequate response action.

Characterising variability and predictors of infant mortality in urban settings: findings from 286 Latin American cities

Background

Urbanisation in Latin America (LA) is heterogeneous and could have varying implications for infant mortality (IM). Identifying city factors related to IM can help design policies that promote infant health in cities.

Methods

We quantified variability in infant mortality rates (IMR) across cities and examined associations between urban characteristics and IMR in a cross-sectional design. We estimated IMR for the period 2014–2016 using vital registration for 286 cities above 100 000 people in eight countries. Using national censuses, we calculated population size, growth and three socioeconomic scores reflecting living conditions, service provision and population educational attainment. We included mass transit availability of bus rapid transit and subway. Using Poisson multilevel regression, we estimated the per cent difference in IMR for a one SD (1SD) difference in city-level predictors.

Results

Of the 286 cities, 130 had <250 000 inhabitants and 5 had >5 million. Overall IMR was 11.2 deaths/1000 live births. 57% of the total IMR variability across cities was within countries. Higher population growth, better living conditions, better service provision and mass transit availability were associated with 6.0% (95% CI −8.3 to 3.7%), 14.1% (95% CI −18.6 to −9.2), 11.4% (95% CI −16.1 to −6.4) and 6.6% (95% CI −9.2 to −3.9) lower IMR, respectively. Greater population size was associated with higher IMR. No association was observed for population-level educational attainment in the overall sample.

Conclusion

Improving living conditions, service provision and public transportation in cities may have a positive impact on reducing IMR in LA cities.

Women, children and adolescents in conflict countries: an assessment of inequalities in intervention coverage and survival

Introduction

Conflict adversely impacts health and health systems, yet its effect on health inequalities, particularly for women and children, has not been systematically studied. We examined wealth, education and urban/rural residence inequalities for child mortality and essential reproductive, maternal, newborn and child health interventions between conflict and non-conflict low-income and middle-income countries (LMICs).

Methods

We carried out a time-series multicountry ecological study using data for 137 LMICs between 1990 and 2017, as defined by the 2019 World Bank classification. The data set covers approximately 3.8 million surveyed mothers (15-49 years) and 1.1 million children under 5 years including newborns (<1 month), young children (1-59 months) and school-aged children and adolescents (5-14 years). Outcomes include annual maternal and child mortality rates and coverage (%) of family planning services, 1+antenatal care visit, skilled attendant at birth (SBA), exclusive breast feeding (0-5 months), early initiation of breast feeding (within 1 hour), neonatal protection against tetanus, newborn postnatal care within 2 days, 3 doses of diphtheria, pertussis and tetanus vaccine, measles vaccination, and careseeking for pneumonia and diarrhoea.

Results

Conflict countries had consistently higher maternal and child mortality rates than non-conflict countries since 1990 and these gaps persist despite rates continually declining for both groups. Access to essential reproductive and maternal health services for poorer, less educated and rural-based families was several folds worse in conflict versus non-conflict countries.

Conclusions

Inequalities in coverage of reproductive/maternal health and child vaccine interventions are significantly worse in conflict-affected countries. Efforts to protect maternal and child health interventions in conflict settings should target the most disadvantaged families including the poorest, least educated and those living in rural areas.

Sub national variation and inequalities in under-five mortality in Kenya since 1965

Background

Despite significant declines in under five mortality (U5M) over the last 3 decades, Kenya did not achieve Millennium Development Goal 4 (MDG 4) by 2015. To better understand trends and inequalities in child mortality, analysis of U5M variation at subnational decision making units is required. Here the comprehensive compilation and analysis of birth history data was used to understand spatio-temporal variation, inequalities and progress towards achieving the reductions targets of U5M between 1965 and 2013 and projected to 2015 at decentralized health planning units (counties) in Kenya.

Methods

Ten household surveys and three censuses with data on birth histories undertaken between 1989 and 2014 were assembled. The birth histories were allocated to the respective counties and demographic methods applied to estimate U5M per county by survey. To generate a single U5M estimate for year and county, a Bayesian spatio-temporal Gaussian process regression was fitted accounting for variation in sample size, surveys and demographic methods. Inequalities and the progress in meeting the goals set to reduce U5M were evaluated subnationally.

Results

Nationally, U5M reduced by 61·6%, from 141·7 (121·6–164·0) in 1965 to 54·5 (44·6–65·5) in 2013. The declining U5M was uneven ranging between 19 and 80% across the counties with some years when rates increased. By 2000, 25 counties had achieved the World Summit for Children goals. However, as of 2015, no county had achieved MDG 4. There was a striking decline in the levels of inequality between counties over time, however, disparities persist. By 2013 there persists a 3·8 times difference between predicted U5M rates when comparing counties with the highest U5M rates against those with the lowest U5M rates.

Conclusion

Kenya has made huge progress in child survival since independence. However, U5M remains high and heterogeneous with substantial differences between counties. Better use of the current resources through focused allocation is required to achieve further reductions, reduce inequalities and increase the likelihood of achieving Sustainable Development Goal 3·2 on U5M by 2030.

Electronic supplementary material

The online version of this article (10.1186/s12889-019-6474-1) contains supplementary material, which is available to authorized users.

Revealing and Responding to Multiple Health Risks in Informal Settlements in Sub-Saharan African Cities

This paper underscores the need for detailed data on health and disaster risks for sub-Saharan African cities, particularly for their informal settlements. Systems that should contribute to the information base on health and health risks in each locality are rarely functional. In most cities, there is a lack of data on health risks, health outcomes, and health determinants; where data are available, they are usually too aggregated to be useful to urban governments. Such data shortfalls likely hide the scale of premature death, serious illness, and injury in informal settlements; limited data can also curtail the identification of particularly vulnerable urban residents. After outlining data shortfalls, this paper considers two sources of data that can help fill data gaps on health and health determinants. The first is from city case studies undertaken within a research programme called Urban Africa: Risk Knowledge (Urban-ARK). Urban-ARK's findings reveal the large spectrum of health risks in informal settlements, ranging from 'everyday' risks (e.g. infectious and parasitic diseases) to small- and larger-scale disasters. The second is from data collected by slum/shack dweller federations, which offer qualitative and quantitative findings on health, disasters, and other health determinants in informal settlements. Our conclusion reflects upon the need for additional data on multiple risks to advance urban health and well-being and support the 2030 Agenda for Sustainable Development. It also highlights the need to strengthen accountable urban governance in sub-Saharan Africa.

Inequalities in early childhood mortality in Myanmar - Association between parents' socioeconomic status and early childhood mortality

BACKGROUND

Despite global achievements in reducing early childhood mortality, disparities remain. There have been empirical studies of inequalities conducted in low- and middle-income countries. However, there have been no epidemiological studies on socioeconomic inequalities and early childhood survival in Myanmar.

OBJECTIVE

To estimate associations between two measures of parental socioeconomic status - household wealth and education - and age-specific early childhood mortality in Myanmar.

METHODS

Using cross-sectional data obtained from the Myanmar Demographic Health Survey (2015-2016), univariate and multiple logistic regressions were performed to investigate associations between household wealth and highest attained parental education, and under-5, neonatal, post-neonatal and child mortality. Data for 10,081 children born to 5,932 married women (aged 15-49 years) 10 years prior to the survey, were analysed.

RESULTS

Mortality during the first five years was associated with household wealth. In multiple logistic models, wealth was protective for post-neonatal mortality. After adjusting for individual proximate determinants, the odds of post-neonatal mortality in the richest households were 85% lower (95% CI: 50-96%) than in the poorest households. However, significant association was not found between wealth and neonatal mortality. Parental education was important for early childhood mortality; the highest benefit from parental education was for child mortality in the one- to five-year age bracket. After adjusting for proximate determinants, children with a higher educated parent had 95% (95% CI 77-99%) lower odds of death in this age group compared with children whose parents' highest educational attainment was at primary level. The association between parental education and neonatal mortality was not significant.

CONCLUSIONS

In Myanmar, household wealth and parental education are important for childhood survival before five years of age. This study identified nuanced age-related differences in associations. Health policy must take socioeconomic determinants into account in order to address unfair inequalities in early childhood mortality.

Trends in Socioeconomic Inequalities and Prevalence of Anemia Among Children and Nonpregnant Women in Low- and Middle-Income Countries

IMPORTANCE

Anemia remains a major challenge for women's and children's health in low- and middle-income countries (LMICs).

OBJECTIVE

To assess the socioeconomic inequalities and prevalence of anemia among children and nonpregnant girls and women in LMICs over time.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional and repeated cross-sectional analysis used data from the Demographic and Health Surveys collected from January 1, 2000, through December 31, 2014. Initial cross-sectional data sets constructed from the most recent surveys included 163 419 children aged 6 to 59 months and 304 202 nonpregnant girls and women aged 15 to 49 years (hereinafter referred to as nonpregnant women) from 45 LMICs. Repeated cross-sectional data sets from the most recent and the earliest surveys consisted of 322 088 nonpregnant women from 25 LMICs and 182 273 children from 24 LMICs. Analyses were conducted from June 1, 2016, through July 3, 2018.

MAIN OUTCOMES AND MEASURES

Total and severe anemia for children aged 6 to 59 months (hemoglobin level, <11 and <7 g/dL, respectively) and nonpregnant women aged 15 to 49 years (<12 and <8 g/dL, respectively) were defined according to the World Health Organization hemoglobin cutoff levels. The slope index of inequality (SII) and the relative index of inequality (RII) were calculated to determine anemia inequalities.

RESULTS

Among the 163 419 children aged 6 to 59 months and the 304 202 nonpregnant women aged 15 to 49 years in the initial cross-sectional data sets, 34 of 45 countries had anemia prevalence levels for children greater than 40% and 37 of 45 had anemia prevalence levels greater than 20% for nonpregnant women. Among the 182 273 children from 24 LMICs and 322 088 nonpregnant women from 25 LMICs in the repeated cross-sectional data sets, the annualized absolute decreases in the prevalence of anemia ranged from 0.67 to 3.98 percentage points in 16 of the 24 LMICs; for cases of severe anemia, the decrease was 0.03 to 0.82 percentage points in 15 LMICs. Among 322 088 nonpregnant women from 25 LMICs in the repeated cross-sectional data sets, the annualized absolute decreases in the prevalence of anemia ranged from 0.49 to 2.59 percentage points in 17 of 25 LMICs; for severe anemia, the decrease was 0.03 to 0.29 percentage points in 15 LMICs. The SII was significantly negative and the RII was significantly less than 1 in 37 of the 45 LMICs among children and in 26 of the 45 LMICs for nonpregnant women. The annualized changes in the SII approached 0 in 16 of the 24 LMICs among children and in 11 of 25 LMICs among nonpregnant women.

CONCLUSIONS AND RELEVANCE

Most LMICs continue to exhibit a high prevalence of anemia among children and nonpregnant women, although the prevalence of total and severe anemia have decreased in many LMICs. Anemia inequalities among children and nonpregnant women persist in most LMICs.

National and regional under-5 mortality rate by economic status for low-income and middle-income countries: a systematic assessment

Background

The progress to achieve the fourth Millennium Development Goal in reducing mortality rate in children younger than 5 years since 1990 has been remarkable. However, work remains to be done in the Sustainable Development Goal era. Estimates of under-5 mortality rates at the national level can hide disparities within countries. We assessed disparities in under-5 mortality rates by household economic status in low-income and middle-income countries (LMICs).

Method

We estimated country-year-specific under-5 mortality rates by wealth quintile on the basis of household wealth indices for 137 LMICs from 1990 to 2016, using a Bayesian statistical model. We estimated the association between quintile-specific and national-level under-5 mortality rates. We assessed the levels and trends of absolute and relative disparity in under-5 mortality rate between the poorest and richest quintiles, and among all quintiles.

Findings

In 2016, for all LMICs (excluding China), the aggregated under-5 mortality rate was 64·6 (90% uncertainty interval [UI] 61·1–70·1) deaths per 1000 livebirths in the poorest households (first quintile), 31·3 (29·5–34·2) deaths per 1000 livebirths in the richest households (fifth quintile), and in between those outcomes for the middle quintiles. Between 1990 and 2016, the largest absolute decline in under-5 mortality rate occurred in the two poorest quintiles: 77·6 (90% UI 71·2–82·6) deaths per 1000 livebirths in the poorest quintile and 77·9 (72·0–82·2) deaths per 1000 livebirths in the second poorest quintile. The difference in under-5 mortality rate between the poorest and richest quintiles decreased significantly by 38·8 (90% UI 32·9–43·8) deaths per 1000 livebirths between 1990 and 2016. The poorest to richest under-5 mortality rate ratio, however, remained similar (2·03 [90% UI 1·94–2·11] in 1990, 1·99 [1·91–2·08] in 2000, and 2·06 [1·92–2·20] in 2016). During 1990–2016, around half of the total under-5 deaths occurred in the poorest two quintiles (48·5% in 1990 and 2000, 49·5% in 2016) and less than a third were in the richest two quintiles (30·4% in 1990, 30·5% in 2000, 29·9% in 2016). For all regions, differences in the under-5 mortality rate between the first and fifth quintiles decreased significantly, ranging from 20·6 (90% UI 15·9–25·1) deaths per 1000 livebirths in eastern Europe and central Asia to 59·5 (48·5–70·4) deaths per 1000 livebirths in south Asia. In 2016, the ratios of under-5 mortality rate in the first quintile to under-5 mortality rate in the fifth quintile were significantly above 2·00 in two regions, with 2·49 (90% UI 2·15–2·87) in east Asia and Pacific (excluding China) and 2·41 (2·05–2·80) in south Asia. Eastern and southern Africa had the smallest ratio in 2016 at 1·62 (90% UI 1·48–1·76). Our model suggested that the expected ratio of under-5 mortality rate in the first quintile to under-5 mortality rate in the fifth quintile increases as national-level under-5 mortality rate decreases.

Interpretation

For all LMICs (excluding China) combined, the absolute disparities in under-5 mortality rate between the poorest and richest households have narrowed significantly since 1990, whereas the relative differences have remained stable. To further narrow the rich-and-poor gap in under-5 mortality rate on the relative scale, targeted interventions that focus on the poorest populations are needed.

Funding

National University of Singapore, UN Children's Fund, United States Agency for International Development, and the Bill & Melinda Gates Foundation.

Wealth-related inequality in early uptake of HIV testing among pregnant women: an analysis of data from a national cross-sectional survey, South Africa

OBJECTIVES

Wealth-related inequality across the South African antenatal HIV care cascade has not been considered in detail as a potential hindrance to eliminating mother-to-child HIV transmission (EMTCT). We aimed to measure wealth-related inequality in early (before enrolling into antenatal care) uptake of HIV testing and identify the contributing determinants.

DESIGN

Cross-sectional survey.

SETTINGS

South African primary public health facilities in 2012.

PARTICIPANTS

A national-level sample of 8618 pregnant women.

OUTCOME MEASURES

Wealth-related inequality in early uptake of HIV testing was measured using the Erreygers concentration index (CI) further adjusted for inequality introduced by predicted healthcare need (ie, need-standardised). Determinants contributing to the observed inequality were identified using the Erreygers and Wagstaff decomposition methods.

RESULTS

Participants were aged 13 to 49 years. Antenatal HIV prevalence was 33.2%, of which 43.7% came from the lowest 40% wealth group. A pro-poor wealth-related inequality in early HIV testing was observed. The need-standardised concentration index was -0.030 (95% confidence interval -0.038 to -0.022). The proportion of early HIV testing was significantly better in the lower 40% wealth group compared with the higher 40% wealth group (p value=0.040). The largest contributions to the observed inequality were from underlying inequalities in province (contribution, 65.27%), age (-44.38%), wealth group (24.73%) and transport means (21.61%).

CONCLUSIONS

Our results on better early uptake of HIV testing among the poorer subpopulation compared with the richer highlights inequity in uptake of HIV testing in South Africa. This socioeconomic difference could contribute to fast-tracking EMTCT given the high HIV prevalence among the lower wealth group. The high contribution of provinces and age to inequality highlights the need to shift from reliance on national-level estimates alone but identify subregional-specific and age-specific bottlenecks. Future interventions need to be context specific and tailored for specific subpopulations and subregional settings.

Explaining changes in child health inequality in the run up to the 2015 Millennium Development Goals (MDGs): The case of Zambia

Background

Child health interventions were drastically scaled up in the period leading up to 2015 as countries aimed at meeting the 2015 target of the Millennium Development Goals (MDGs). MDGs were defined in terms of achieving improvements in average health. Significant improvements in average child health are documented, but evidence also points to rising inequality. It is important to investigate factors that drive the increasing disparities in order to inform the post-2015 development agenda of reducing inequality, as captured in the Sustainable Development Goals (SDGs). We investigated changes in socioeconomic inequality in stunting and fever in Zambia in 2007 and 2014. Unlike the huge literature that seeks to quantify the contribution of different determinants on the observed inequality at any given time, we quantify determinants of changes in inequality.

Methods

Data from the 2007 and 2014 waves of the Zambia Demographic and Health Survey (DHS) were utilized. Our sample consisted of children aged 0–5 years (n = 5,616 in 2007 and n = 12,714 in 2014). We employed multilevel models to assess the determinants of stunting and fever, which are two important child health indicators. The concentration index (CI) was used to measure the magnitude of inequality. Changes in inequality of stunting and fever were investigated using Oaxaca-type decomposition of the CI. In this approach, the change in the CI for stunting/fever is decomposed into changes in CI for each determinant and changes in the effect—measured as an elasticity—of each determinant on stunting/fever.

Results

While average rates of stunting reduced in 2014 socioeconomic inequality in stunting increased significantly. Inequality in fever incidence also increased significantly, but average rates of fever did not reduce.

The increase in the inequality (CI) of determinants accounted for the largest part (42.5%) of the increase in inequality of stunting, while the increase in the effect of determinants explained 35% of the increase. The determinants with the greatest total contribution (change in CI plus change in effect) to the increase in inequality of stunting were mother’s height and weight, wealth, birth order, facility delivery, duration of breastfeeding, and maternal education.

For fever, almost all (86%) the increase in inequality was accounted for by the increase in the effect of determinants of fever, while the distribution of determinants mattered less. The determinants with the greatest total contribution to the increase in inequality of fever were wealth, maternal education, birth order and breastfeeding duration.

In the multilevel model, we found that the likelihood of a child being stunted or experiencing fever depends on the community in which they live.

Conclusions

To curb the increase in inequality of stunting and fever, policy may focus on improving levels of, and reducing inequality in, access to facility deliveries, maternal nutrition (which may be related to maternal weight and height), complementary feeding (for breastfed children), wealth, maternal education, and child care (related to birth order effects). Improving overall levels of these determinants contribute to the persistence of inequality if these determinants are unequally concentrated on the well off to begin with.

Housing materials as predictors of under-five mortality in Nigeria: evidence from 2013 demographic and health survey

BACKGROUND

Nigeria is among countries with high Under-Five Mortality (U5M) rates worldwide. Both maternal and childhood factors have been linked to U5M in the country. However, despite the growing global recognition of the association between housing and quality of life, the role of housing materials as predictors of U5M remain largely unexplored in Nigeria. This study, therefore, investigated the relationship between housing materials and U5M in Nigeria.

METHODS

The study utilised the 2013 Nigeria Demographic and Health Survey data. A representative sample of 40,680 households was selected for the survey. The sample included 18,516 women of reproductive age who had given birth in the past 5 years prior the survey; with attention on the survival status of the index child (the most recent delivery). Data were analysed using descriptive statistics, Chi-square, Cox-proportional hazard and Brass 2-parameter models (α = 0.05).

RESULTS

The hazard ratio of U5M was 1.46 (C.I = 1.02-1.47, p < 0.001) and 1.23 (C.I = 1.24-1.71, p < 0.001) higher among children who lived in houses built with inadequate and moderate housing materials respectively than those in good housing materials. Under-five deaths show a downward trend (slope = -0.4871) relative to the housing materials assessment score. The refined U5M rate was 143.5, 127.0 and 90.8 per 1000 live birth among women who live in houses built with inadequate, moderate and adequate housing materials respectively. Other predictors of U5M were; the size of the child at birth, preceding birth interval, prenatal care provider, residence and education. Under-five death reduces with increasing maternal level of; education, wealth quintile, media exposure and housing material type and mostly experienced by Muslim women (6.0%), rural women (6.5%) and women residence in the North-West geopolitical zones (6.9%).

CONCLUSIONS

Living in houses built with poor housing materials promoted U5M in Nigeria. Provision of sustainable housing by the government and the maintenance of existing housing stock to healthful conditions will play a significant role in reducing the burden of U5M in Nigeria.

Place of Residence Moderates the Risk of Infant Death in Kenya: Evidence from the Most Recent Census 2009

Background

Substantial progress has been made in reducing childhood mortality worldwide from 1990–2015 (Millennium Development Goal, target 4). Achieving target goals on this however remains a challenge in Sub-Saharan Africa. Kenya’s infant mortality rates are higher than the global average and are more pronounced in urban areas as compared to rural areas. Only limited knowledge exists about the differences in individual level risk factors for infant death among rural, non-slum urban, and slum areas in Kenya. Therefore, this paper aims at 1) assess individual and socio-ecological risk factors for infant death in Kenya, and at 2) identify whether living in rural, non-slum urban, or slum areas moderated individual or socio-ecological risk factors for infant death in Kenya.

Methodology

We used a cross-sectional study design based on the most recent Kenya Population and Housing Census of 2009 and extracted the records of all females who had their last child born in 12 months preceding the survey (N = 1,120,960). Multivariable regression analyses were used to identify risk factors that accounted for the risk of dying before the age of one at the individual level in Kenya. Place of residence (rural, non-slum urban, slum) was used as an interaction term to account for moderating effects in individual and socio-ecological risk factors.

Results

Individual characteristics of mothers and children (older age, less previously born children that died, better education, girl infants) and household contexts (better structural quality of housing, improved water and sanitation, married household head) were associated with lower risk for infant death in Kenya. Living in non-slum urban areas was associated with significantly lower infant death as compared to living in rural or slum areas, when all predictors were held at their reference levels. Moreover, place of residence was significantly moderating individual level predictors: As compared to rural areas, living in urban areas was a protective factor for mothers who had previous born children who died, and who were better educated. However, living in urban areas also reduced the health promoting effects of better structural quality of housing (i.e. poor or good versus non-durable). Furthermore, durable housing quality in urban areas turned out to be a risk factor for infant death as compared to rural areas. Living in slum areas was also a protective factor for mothers with previous child death, however it also reduced the promoting effects of older ages in mothers.

Conclusions

While urbanization and slum development continues in Kenya, public health interventions should invest in healthy environments that ideally would include improvements to access to safe water and sanitation, better structural quality of housing, and to access to education, health care, and family planning services, especially in urban slums and rural areas. In non-slum urban areas however, health education programs that target healthy diets and promote physical exercise may be an important adjunct to these structural interventions.