Subnational inequalities have received limited attention in the monitoring of progress towards national and global health targets during the past two decades. Yet, such data are often a critical basis for health planning and monitoring in countries, in support of efforts to reach all with essential interventions. Household surveys provide a rich basis for interventions coverage indicators on reproductive, maternal, newborn and child health (RMNCH) at the country first administrative level (regions or provinces). In this paper, we show the large subnational inequalities that exist in RMNCH coverage within 39 countries in sub-Saharan Africa, using a composite coverage index which has been used extensively by Countdown to 2030 for Women's, Children's and Adolescent's Health. The analyses show the wide range of subnational inequality patterns such as low overall national coverage with very large top inequality involving the capital city, intermediate national coverage with bottom inequality in disadvantaged regions, and high coverage in all regions with little inequality. Even though nearly half of the 34 countries with surveys around 2004 and again around 2015 appear to have been successful in reducing subnational inequalities in RMNCH coverage, the general picture shows persistence of large inequalities between subnational units within many countries. Poor governance and conflict settings were identified as potential contributing factors. Major efforts to reduce within-country inequalities are required to reach all women and children with essential interventions. © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.Adolescent sexual and reproductive health (ASRH) continues to be a major public health challenge in sub-Saharan Africa where child marriage, adolescent childbearing, HIV transmission and low coverage of modern contraceptives are common in many countries. The evidence is still limited on inequalities in ASRH by gender, education, urban-rural residence and household wealth for many critical areas of sexual initiation, fertility, marriage, HIV, condom use and use of modern contraceptives for family planning. We conducted a review of published literature, a synthesis of national representative Demographic and Health Surveys data for 33 countries in sub-Saharan Africa, and analyses of recent trends of 10 countries with surveys in around 2004, 2010 and 2015. Our analysis demonstrates major inequalities and uneven progress in many key ASRH indicators within sub-Saharan Africa. Gender gaps are large with little evidence of change in gaps in age at sexual debut and first marriage, resulting in adolescent girls remaining particularly vulnerable to poor sexual health outcomes. There are also major and persistent inequalities in ASRH indicators by education, urban-rural residence and economic status of the household which need to be addressed to make progress towards the goal of equity as part of the sustainable development goals and universal health coverage. These persistent inequalities suggest the need for multisectoral approaches, which address the structural issues underlying poor ASRH, such as education, poverty, gender-based violence and lack of economic opportunity. © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.Introduction Universal Health Coverage (UHC) is a critical goal under the Sustainable Development Goals (SDGs) for health. Achieving this goal for reproductive, maternal, newborn and child health (RMNCH) service coverage will require an understanding of national progress and how socioeconomic and demographic subgroups of women and children are being reached by health interventions. Methods We accessed coverage databases produced by the International Centre for Equity in Health, which were based on reanalysis of Demographic and Health Surveys, Multiple Indicator Cluster Surveys and Reproductive and Health Surveys. We limited the data to 58 countries with at least two surveys since 2008. We fitted multilevel linear regressions of coverage of RMNCH, divided into four main components-reproductive health, maternal health, child immunisation and child illness treatment-to estimate the average annual percentage point change (AAPPC) in coverage for the period 2008-2017 across these countries and for subgroups definedat are well off. The latter groups however continue to maintain substantially higher coverage levels over the former. No acceleration in RMNCH coverage was observed when the periods 2000-2008 and 2008-2017 were compared. Conclusion At the dawn of the SDGs, progress in coverage in RMNCH remains insufficient at the national level and across equity dimensions to accelerate towards UHC by 2030. https://www.selleckchem.com/products/epz015666.html Greater attention must be paid to child immunisation to sustain the past gains and to child illness treatment to substantially raise its coverage across all groups. © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.Introduction Wealth-related inequalities in reproductive, maternal, neonatal and child health have been widely studied by dividing the population into quintiles. We present a comprehensive analysis of wealth inequalities for the composite coverage index (CCI) using national health surveys carried out since 2010, using wealth deciles and absolute income estimates as stratification variables, and show how these new approaches expand on traditional equity analyses. Methods 83 low-income and middle-income countries were studied. The CCI is a combined measure of coverage with eight key reproductive, maternal, newborn and child health interventions. It was disaggregated by wealth deciles for visual inspection of inequalities, and the slope index of inequality (SII) was estimated. The correlation between coverage in the extreme deciles and SII was assessed. Finally, we used multilevel models to examine how the CCI varies according to the estimated absolute income for each wealth quintile in the surveys. Results The analyses of coverage by wealth deciles and by absolute income show that inequality is mostly driven by coverage among the poor, which is much more variable than coverage among the rich across countries.