Spatial distribution and predictors of intimate partner violence among women in Nigeria

Background: Globally, intimate partner violence is one of the major health problems women face every day. Its consequences are enormous. However, our search of the available literature revealed that no study had examined the spatial distribution of intimate partner violence and the predictors of intimate partner violence among women in Nigeria using current nationally representative data. This study, therefore, sought to examine the spatial distribution of intimate partner violence and its predictors among women in Nigeria. Method: We sourced data from the 2018 Nigeria Demographic and Health Survey for this study. A sample size of 8,968 women was considered for this study. We employed both multilevel and spatial analyses to ascertain the factors associated with intimate partner violence and its spatial clustering. Results: The hot spot areas for intimate partner violence in Nigeria were Gombe, Bauchi, Adamawa, Plateau, Kogi, Edo, Ebonyi, and Rivers. The likelihood of experiencing intimate partner violence among women in Nigeria was high among women with primary education, those that were previously married, women currently working, women who were Yoruba, women with parity of four and above and women who were exposed to mass media while low odds of intimate partner violence was reported among women who were Muslims. Women who resided in the North East region and those who lived in communities with medium socioeconomic status were more likely to experience intimate partner violence, while women who were within the richest wealth index and those residing in the South West region were less likely to experience intimate partner violence. Conclusion: The study found regional variations in the prevalence of intimate partner violence among women in Nigeria. Therefore, policymakers should focus their attention on the hotspots for intimate partner violence in the country. There is also the need to consider the factors identified in this study to reduce intimate partner violence among women in Nigeria. Empowering women would yield a significant improvement in the fight against gender-based violence

Multi-Level Analysis and Spatial Interpolation of Distributions and Predictors of Childhood Diarrhea in Nigeria

Background: Diarrhea is one of the health problems contributing to Nigeria’s under-5 mortality rate, ranked as the eighth highest globally. As our search is concerned, there is limited evidence on the spatial distribution of childhood diarrhea in Nigeria. Therefore, this study aimed to examine the spatial distribution and predictors of diarrhea among under-5 children in Nigeria. Materials and Methods: Using data from the child’s recode file of the 2018 Nigeria Demographic and Health Survey, a sample of 28 583 children of women of reproductive age was considered as the sample size for this study. The outcome variable used in this study was childhood diarrhea. We employed both multilevel and spatial analyses to ascertain the factors associated with childhood diarrhea as well as its spatial clustering. Results: The regional distribution of the prevalence of diarrhea among children in Nigeria ranged from 0% to 62%. The hotspots for childhood diarrhea were in Yobe, Bauchi, Gombe, Kano, Sokoto, Imo, and Taraba. The likelihood of a child having diarrhea in Nigeria was higher among women whose partners have secondary education and above [aOR = 1.18; 95%CI = 1.05-1.33], women currently working [aOR = 1.24; 95%CI = 1.13-1.35], women practicing Islam [aOR = 1.24; 95%CI = 1.04-1.46], and women who were exposed to mass media [aOR = 1.29; 95%CI = 1.18-1.42], compared to women whose partners had no formal education, women not currently working, women practicing Christianity, and those who were not exposed to mass media. Children born to mothers who reside in North East [aOR = 2.55; 95%CI = 2.10-3.10], and communities with medium socioeconomic status [aOR = 1.44; 95%CI = 1.09-1.91] were more likely to experience diarrhea compared to those born to mothers residing in the North Central and in communities with low socioeconomic status. Conclusion: High proportions of childhood diarrhea among under-5 children in Nigeria were located in Yobe, Bauchi, Gombe, Kano, Sokoto, Imo, and Taraba. Policies and interventions that seek to reduce or eliminate diarrhea diseases among under-5 children in Nigeria should take a keen interest in the factors identified as predictors of childhood diarrhea in this study as this will help in achieving the aims of WASH, ORT corners, and SDG 3 by the year 2030

Spatial distribution and factors associated with modern contraceptive use among women of reproductive age in Nigeria: a multilevel analysis

Background: Evidence suggests that in countries with high fertility and fecundity rates, such as Nigeria, the promotion of modern contraceptive use prevents approximately 32% and 10% of maternal and child mortality, respectively. Therefore, this study aimed to assess the spatial distribution of modern contraceptive use and its predictors among women of reproductive age in Nigeria. Methods: The study employed a cross-sectional analysis of population-based data involving 24,281 women of reproductive age in Nigeria. The study adopted both multilevel and spatial analyses to identify the predictors of modern contraceptive use and its spatial clustering among women in Nigeria. Results: Modern contraceptive use among the study population in Nigeria ranged from 0% to 75%, with regional variations. The spatial analysis showed that areas with a low proportion of modern contraceptive use were Sokoto, Yobe, Borno, Katsina, Zamfara, Kebbi, Niger, Taraba and Delta. Areas with a high proportion of modern contraceptive use were Lagos, Oyo, Osun, Ekiti, Federal capital territory, Plateau, Adamawa, Imo, and Bayelsa. The multilevel analysis revealed that at the individual level, women with secondary/higher education, women from the Yoruba ethnic group, those who had four children and above, and those exposed to mass media had higher odds of using modern contraceptives. On the other hand, women who were 35 years and above, those who were married, and women who were practicing Islam were less likely to use modern contraceptives. At the household/community level, women from the richest households, those residing in communities with medium knowledge of modern contraceptive methods, and women residing in communities with a high literacy level were more likely to use modern contraceptives. Conclusion: There were major variations in the use of modern contraception across various regions in Nigeria. As a result, areas with low contraceptive rates should be given the most deserving attention by promoting contraceptive education and use as well as considering significant factors at the individual and household/community levels

Spatial distribution and multilevel analysis of factors associated with child marriage in Nigeria

Background: Child marriage among women has become a major threat to the rights of women, especially in low- and middle-income countries. The marriage of girls below age 18 y is a major public and global health challenge. Therefore, this study examined the spatial pattern and factors associated with child marriage in Nigeria. Methods: The data were sourced from the 2018 Nigeria Demographic and Health Survey. The study included a total of 4283 young women aged 20–24 y. The findings were provided in the form of spatial maps and adjusted ORs (aORs) with 95% confidence interval (CI). Results: Hotspot areas for child marriage in Nigeria were located in Sokoto, Kebbi, Katsina, Kano, Jigawa, Yobe, Bauchi, Niger, Borno, Gombe, and Adamawa. The prevalence of child marriage in Nigeria was 41.50%. The likelihood of child marriage in Nigeria was high among those currently working (aOR=1.31; 95% CI 1.11 to 1.55) compared with young women who were not working. On the other hand, young women whose partners had secondary education and above (aOR=0.57; 95% CI 0.45 to 0.73) were less likely to report child marriage in Nigeria compared with those whose partners had no education. Conclusions: The findings of the study indicate that there are several hotspots in Nigeria that need to be targeted when implementing interventions aimed at eliminating child marriage in the country

Spatial distribution and predictors of lifetime experience of intimate partner violence among women in South Africa

In recent times, intimate partner has gained significant attention. However, there is limited evidence on the spatial distribution and predictors of intimate partner violence. Therefore, this study examined the spatial distribution and predictors of intimate partner violence in South Africa. The dataset for this study was obtained from a cross-sectional survey of the 2016 South Africa Demographic and Health Survey. We adopted both spatial and multilevel analyses to show the distribution and predictors of intimate partner violence among 2,410 women of reproductive age who had ever experienced intimate partner violence in their lifetime in South Africa. The spatial distribution of intimate partner violence in South Africa ranged from 0 to 100 percent. Western Cape, Free State, and Eastern Cape were predicted areas that showed a high proportion of intimate partner violence in South Africa. The likelihood of experiencing intimate partner violence among women in South Africa was high among those who were cohabiting [aOR = 1.41; 95%(CI = 1.10–1.81)] and women who were previously married [aOR = 2.09; 95%(CI = 1.30–3.36)], compared to women who were currently married. Women who lived in households with middle [aOR = 0.67; 95%(CI = 0.48–0.95)] and richest wealth index [aOR = 0.57; 95%(CI = 0.34–0.97)] were less likely to experience lifetime intimate partner violence compared to those of the poorest wealth index. The study concludes that there is a regional variation in the distribution of intimate partner violence in South Africa. A high prevalence of intimate partner violence was found among women who live in the Western Cape, Free State, and Eastern Cape. Furthermore, predictors such as women within the poorest wealth index, women who were cohabiting and those who were previously married should be considered in the development and implementation of interventions against intimate partner violence in South Africa

Mapping child growth failure across low- and middle-income countries

Child growth failure (CGF), manifested as stunting, wasting, and underweight, is associated with high 5 mortality and increased risks of cognitive, physical, and metabolic impairments. Children in low- and middle-income countries (LMICs) face the highest levels of CGF globally. Here we illustrate national and subnational variation of under-5 CGF indicators across LMICs, providing 2000–2017 annual estimates mapped at a high spatial resolution and aggregated to policy-relevant administrative units and national levels. Despite remarkable declines over the study period, many LMICs remain far from the World Health 10 Organization’s ambitious Global Nutrition Targets to reduce stunting by 40% and wasting to less than 5% by 2025. Large disparities in prevalence and rates of progress exist across regions, countries, and within countries; our maps identify areas where high prevalence persists even within nations otherwise succeeding in reducing overall CGF prevalence. By highlighting where subnational disparities exist and the highest-need populations reside, these geospatial estimates can support policy-makers in planning locally 15 tailored interventions and efficient directing of resources to accelerate progress in reducing CGF and its health implications

Mapping 123 million neonatal, infant and child deaths between 2000 and 2017

Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2—to end preventable child deaths by 2030—we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000–2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations

Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019 : A systematic analysis for the Global Burden of Disease Study 2019

Background Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Methods Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0–100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Findings Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2–47·5) in 1990 to 60·3 (58·7–61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9–3·3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010–2019 relative to 1990–2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0·79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach $1398 pooled health spending per capita (US$ adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388·9 million (358·6–421·3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3·1 billion (3·0–3·2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968·1 million [903·5–1040·3]) residing in south Asia. Interpretation The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people—the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close—or how far—all populations are in benefiting from UHC

Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Methods Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0–100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Findings Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2–47·5) in 1990 to 60·3 (58·7–61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9–3·3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010–2019 relative to 1990–2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0·79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach $1398 pooled health spending per capita (US$ adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388·9 million (358·6–421·3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3·1 billion (3·0–3·2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968·1 million [903·5–1040·3]) residing in south Asia. Interpretation The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people—the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close—or how far—all populations are in benefiting from UHC

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens