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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.

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Background: Despite the proliferation of studies on the impact of the coronavirus disease 2019 (COVID-19) pandemic, there is less evidence on the indirect death toll compared to the health system and service provision disruptions. We assessed the impact of the COVID-19 pandemic on national and regional trends and differences in stillbirths, under-5 and maternal deaths in Brazil. Methods: We used the nationwide routine health information system data from January 2017 to December 2021, to which we applied descriptive and advanced mixed effects ordinary least squared regression models to measure the percent change in mortality levels during the COVID-19 pandemic (March 2020 to December 2021). We carried out counterfactual analyses comparing the observed and expected mortality levels for each type of mortality at national and regional levels. Results: Stillbirths increased 4.8% (3.1% in 2020 and 6.2% in 2021) and most noticeably maternal deaths increased 71.6% (35.3% in 2020 and 103.3% in 2021) over the COVID-19 period. An opposite pattern was observed in under-5 mortality, which dropped -10.2% (-12.5% in 2020 and -8.1% in 2021). We identified regional disparities, with a higher percent increase in stillbirths observed in the Central-West region and in maternal deaths in the South region. Discussion: Based on pre-pandemic trends and expected number of deaths in the absence of the COVID-19, we observed increases in stillbirths and maternal deaths and reductions in under-5 deaths during the pandemic. The months with the highest number of deaths (stillbirths and maternal deaths) coincided with the months with the highest mortality from COVID-19. The increase in deaths may also have resulted from indirect effects of the pandemic, such as unavailability of health services or even reluctance to go to the hospital when necessary due to fear of contagion. Conclusions: In Brazil, the COVID-19 outbreak and subsequent restrictions had a detrimental impact on stillbirths and maternal deaths. Even before the pandemic, mortality trends highlighted pre-existing regional inequalities in the country's health care system. Although there were some variations, increases were observed in all regions, indicating potential weaknesses in the health system and inadequate management during the pandemic, particularly concerning pregnant and postpartum women.

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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.

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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.

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BACKGROUND: Antenatal care (ANC) is critical for improving maternal and newborn health. WHO recommends that pregnant women complete at least four ANC visits. Countdown and other global monitoring efforts track the proportions of women who receive one or more visits by a skilled provider (ANC1+) and four or more visits by any provider (ANC4+). This study investigates patterns of drop-off in use between ANC1+ and ANC4+, and explores inequalities in women's use of ANC services. It also identifies determinants of utilization and describes countries' ANC-related policies, and programs. METHODS: We performed secondary analyses using Demographic Health Survey (DHS) data from seven Countdown countries: Bangladesh, Cambodia, Cameroon, Nepal, Peru, Senegal and Uganda. The descriptive analysis illustrates country variations in the frequency of visits by provider type, content, and by household wealth, women's education and type of residence. We conducted a multivariable analysis using a conceptual framework to identify determinants of ANC utilization. We collected contextual information from countries through a standard questionnaire completed by country-based informants. RESULTS: Each country had a unique pattern of ANC utilization in terms of coverage, inequality and the extent to which predictors affected the frequency of visits. Nevertheless, common patterns arise. Women having four or more visits usually saw a skilled provider at least once, and received more evidence-based content interventions than women reporting fewer than four visits. A considerable proportion of women reporting four or more visits did not report receiving the essential interventions. Large disparities exist in ANC use by household wealth, women's education and residence area; and are wider for a larger number of visits. The multivariable analyses of two models in each country showed that determinants had different effects on the dependent variable in each model. Overall, strong predictors of ANC initiation and having a higher frequency (4+) of visits were woman's education and household wealth. Gestational age at first visit, birth rank and preceding birth interval were generally negatively associated with initiating visits and with having four or more visits. Information on country policies and programs were somewhat informative in understanding the utilization patterns across the countries, although timing of adoption and actual implementation make direct linkages impossible to verify. CONCLUSION: Secondary analyses provided a more detailed picture of ANC utilization patterns in the seven countries. While coverage levels differ by country and sub-groups, all countries can benefit from specific in-country assessments to properly identify the underserved women and the reasons behind low coverage and missed interventions. Overall, emphasis needs to be put on assessing the quality of care offered and identifying women's perception to the care as well as the barriers hindering utilization. Country policies and programs need to be reviewed, evaluated and/or implemented properly to ensure that women receive the recommended number of ANC visits with appropriate content, especially, poor and less educated women residing in rural areas.

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