Spatiotemporal analysis of the effect of global development indicators on child mortality

Abstract Background Child mortality continue to be a major public health issue in most developing countries; albeit there has been a decline in global under-five deaths. The differences in child mortality can best be explained by socioeconomic and environmental inequalities among countries. In this study, we explore the effect of country-level development indicators on under-five mortality rates. Specifically, we examine potential spatio-temporal heterogeneity in the association between major world development indicators on under-five mortality, as well as, visualize the global differential time trend of under-five mortality rates. Methods The data from 195 countries were curated from the World Bank’s World Development Indicators (WDI) spanning from 2000 to 2017 and national estimates for under-five mortality from the UN Inter-agency Group for Child Mortality Estimation (UN IGME).We built parametric and non-parametric Bayesian space-time interaction models to examine the effect of development indicators on under-five mortality rates. We also used employed Bayesian spatio-temporal varying coefficient models to assess the spatial and temporal variations in the effect of development indicators on under-five mortality rates. Results In both parametric and non-parametric models, the results show indicators of good socioeconomic development were associated with a reduction in under-five mortality rates while poor indicators were associated with an increase in under-five mortality rates. For instance, the parametric model shows that gross domestic product (GDP) (β = − 1.26, [CI − 1.51; − 1.01]), current healthcare expenditure (β = − 0.40, [CI − 0.55; − 0.26]) and access to basic sanitation (β = − 0.03, [CI − 0.05; − 0.01]) were associated with a reduction under-five mortality. An increase in the proportion practising open defecation (β = 0.14, [CI 0.08; 0.20]) an increase under-five mortality rate. The result of the spatial components spatial variation in the effect of the development indicators on under-five mortality rates. The spatial patterns of the effect also change over time for some indicators, such as PM2.5. Conclusion The findings show that the burden of under-five mortality rates was considerably higher among sub-Saharan African countries and some southern Asian countries. The findings also reveal the trend in reduction in the sub-Saharan African region has been slower than the global trend

The effect of sociodemographic factors on the risk of poor mental health in Akron (Ohio): a Bayesian hierarchical spatial analysis

We examined the association of sociodemographic factors on mental health risk within the city of Akron (Ohio). A Spatial Bayesian Hierarchical model was used in this study. We found that the risk of poor mental health was positively associated with the proportion of people lacking sufficient sleep (RR = 0.42, 95% CI:0.22-0.62), the percentage of people below poverty (RR = 0.12, 95% CI: 0.09, 0.16), and the percentage of married couples (RR = 0.02, 95% CI: -0.05, 0.08). On the contrary, the percentage of female population (RR = -0.06, 95% CI: -0.13, 0.01), the percentage of the black population (RR = -0.05, 95% CI: -0.08, -0.02), and the college-educated population (RR = -0.03, 95% CI: -0.09, 0.04) was negatively associated with the risk of poor mental health. We also found that the sociodemographic variables have spatially varying effects across different neighborhoods. Future studies will examine the joint spatial effect of poor mental health risk and suicide ideation in the study area

Examining spatial variability in the association between male partner alcohol misuse and intimate partner violence against women in Ghana: a GWR analysis

Globally, it is estimated that about 30% of ever-partnered women have experienced some form of intimate partner violence (IPV)—physical assault, sexual assault, or emotional abuse. The prevalence of IPV in sub-Saharan Africa is considerably higher than the global estimate. In Ghana, it is estimated that 24% of women have experienced physical and/or sexual IPV in their lifetime. Studies point to the association between alcohol misuse by intimate male partners and violence against women. However, there has been no consideration for potential spatial variation or heterogeneity in this association. Using estimates from the 2008 Ghana Demographic and Health Survey Data, we employed geographically weighted regression (GWR) analysis to examine spatial variations in the relationship between male partner’s alcohol misuse and IPV among women in Ghana. We fitted three models to assess the relationship using a step-wise approach. The first model has alcohol misuse as the only predictor, whereas the second model included other male partner characteristics, such as post-secondary education and employment status. The final introduced female characteristics as additional covariates. The result of the GWR analysis shows that the effect of alcohol misuse on IPV is elevated in the south-western part of Ghana. The findings suggest the potential influence of place-based or contextual factors on the association between alcohol misuse and women’s exposure to IPV