Using geographical analysis to identify child health inequality in sub-Saharan Africa

Abstract

One challenge to achieving Millennium Development Goals was inequitable access to quality health services. In order to achieve the Sustainable Development Goals, interventions need to reach underserved populations. Analyzing health indicators in small geographic units aids the identification of hotspots where coverage lags behind neighboring areas. The purpose of these analyses is to identify areas of low coverage or high need in order to inform effective resource allocation to reduce child health inequity between and within countries. Using data from The Demographic and Health Survey Program surveys conducted in 27 selected African countries between 2010 and 2014, we computed estimates for six child health indicators for subnational regions. We calculated Global Moran’s I statistics and used Local Indicator of Spatial Association analysis to produce a spatial layer showing spatial associations. We created maps to visualize sub-national autocorrelation and spatial clusters. The Global Moran’s I statistic was positive for each indicator (range: 0.41 to 0.68), and statistically significant (p <0.05), suggesting spatial autocorrelation across national borders, and highlighting the need to examine health indicators both across countries and within them. Patterns of substantial differences among contiguous subareas were apparent; the average intra-country difference for each indicator exceeded 20 percentage points. Clusters of cross-border associations were also apparent, facilitating the identification of hotspots and informing the allocation of resources to reduce child health inequity between and within countries. This study exposes differences in health indicators in contiguous geographic areas, indicating that specific regional and subnational, in addition to national, strategies to improve health and reduce health inequalities are warranted.

Geographical disparities and determinants of childhood diarrheal illness in Ethiopia: Further Analysis of 2016 Ethiopian Demographic and Health Survey

“…This disparity might be due to study sample size, study period, coverage of latrine and utilization, access to safe water for drinking. However, this nding is consistent with the ndings in other sub-Saharan and South Asian countries, a study in Tanzania and India [8,[33][34][35]. The results signify that the strategic approach of the government is fruitful and the sweats of focusing on low performing states are paying off.…”

“…For example, according to the Global Burden of Disease study in 2016, 9.4% of all the severe cases of diarrhea in 2015 occurred in two countries: Ethiopia and the Democratic Republic of the Congo. In the Central African Republic, Gabon, Ivory Coast, Nigeria, and Zimbabwe saw disease increases over the 15 years [1,8,9].…”

Geographical disparities and determinants of childhood diarrheal illness in Ethiopia: further analysis of 2016 Ethiopian Demographic and Health Survey

“…For example, according to the Global Burden of Disease study in 2016, 9.4% of all severe cases of diarrhea in 2015 occurred in two countries, Ethiopia and the Democratic Republic of Congo. Also, diseases rise over 15 years have been seen in Central Africa, Gabon, Ivory Coast, Nigeria, and Zimbabwe [ 12 , 20 , 21 ].…”

Healthcare providers and Caregivers’ perspectives on factors underlying the persistent malnutrition of Children aged 0-59 months in Buhweju district, southwestern Uganda

“…In addition, access to markets, healthcare facilities, communal education especially of women and young people is essential to improve nutritional levels in rural regions, generally improving access and social services would positively impact nutrition of children. Yourkavitch and colleagues found differences in health indicators in different geographic areas, and suggested that in order to improve health, these access differences needed to be addressed to reduce health inequalities (14). Others have also noted that an equity focused approach leading to improvement in effective intervention coverage results in sharp decreases in child mortality and stunting and higher cost-effectiveness (15).…”