Nutritional inequalities among under-five children: a geospatial analysis of hotspots and cold spots in 73 low- and middle-income countries

Abstract

Background Child undernutrition is a severe health problem in the developing world, which affects children’s development in the long term. This study analyses the extent and patterns of under-five child undernutrition using Demographic and Health Surveys (DHS) for 73 low- and middle-income countries (LMICs). Methods First, we mapped the prevalence of undernutrition in the developing world. Second, using the LISA (a local indicator of spatial association) technique, we analyzed the geographical patterns in undernutrition to highlight the localized hotspots (regions with high undernutrition prevalence surrounded by similar other regions), cold spots (regions with low undernutrition prevalence surrounded by similar other regions), and outliers (regions with high undernutrition surrounded by low undernutrition and vice versa). Third, we used Moran’s I to find global patterns in child undernutrition. Results We find that South Asia has the highest under-five child undernutrition rates. The intra-country nutritional inequalities are highest in Burundi (stunting), Kenya (wasting), and Madagascar (underweight). The local indicator of spatial association (LISA) analysis suggests that South Asia, Middle East and North Africa (MENA) region, and Sub-Saharan Africa are undernutrition hotspots and Europe and Central Asia and Latin America, and the Caribbean are undernutrition cold spots (regions with low undernutrition surrounded by similar other regions). Getis Ord-Gi* estimates generally support LISA analysis. Moran’s I and Geary’s C gave similar results about the global patterns of undernutrition. Geographically weighted regressions suggest that several socioeconomic indicators significantly explain child undernutrition. Conclusions We found a significant within and across country variation in stunting, wasting and underweight rates among the under-five children’s population. The geospatial analysis also suggested that stunting, wasting, and underweight patterns exhibit clear regional patterns, underscoring the need for coordinated interventions at the regional level.

A Scoping Review on Influence of Socioeconomic Status on Antenatal Care Utilization and Pregnancy Outcomes in Sub-Saharan Africa

“…Even though studies on the effect of occupation on ANC utilization and pregnancy outcome are limited. The review reveals that women's occupation in countries with high mortality cases is burdening [78,79]. Even housewives who are believed or expected to be less busy, are more engaged physically and emotionally and are mostly health-challenged [59,80].…”

How do household living conditions and gender-related decision-making influence child stunting in Rwanda? A population-based study

“…19.23294315 doi: medRxiv preprint Rwanda, like other LMICs, has implemented various programs to combat malnutrition, including providing each family with one cow, offering micro-nutrients to vulnerable children, as well as providing school feeding programs across the country [15]. Despite equal distribution of resources and initiatives, stunting remains a significant problem mainly in the Western and Northern Provinces of Rwanda, where 40% and 41%, respectively, of children <5 years are stunted compared with the city of Kigali, and the Eastern and Southern Provinces, where the rates are 21%, 29%, and 33%, respectively [11]. According to the Rwanda DHS reports of 2014/2015 and 2019/2020, stunting rates in other provinces have decreased, whereas the prevalence of stunting in the Northern Province has increased slightly [14,17].…”

How do household living conditions and gender-related decision-making influence child stunting in Rwanda? A population-based study

“…However, there is an imbalance between the desired level of improvement in undernutrition and the nutritional interventions actually implemented [ 10 ]. Studies undertaken in sub-Saharan Africa demonstrate that the decrease in undernutrition is slow, and improvements are distributed unequally in different areas within the same country [ 11 ]. For example, families living in the northern region of Ghana had higher rates of underweight children compared with other regions due to poor socioeconomic conditions [ 12 ].…”

“…Rwanda, like other LMICs, has implemented various programs to combat malnutrition, including providing each family with one cow, offering micro-nutrients to vulnerable children, as well as providing school feeding programs across the country [ 15 ]. Despite equal distribution of resources and initiatives, stunting remains a significant problem mainly in the Western and Northern Provinces of Rwanda, where 40% and 41%, respectively, of children <5 years are stunted compared with the city of Kigali, and the Eastern and Southern Provinces, where the rates are 21%, 29%, and 33%, respectively [ 11 ]. According to the Rwanda DHS reports of 2014/2015 and 2019/2020, stunting rates in other provinces have decreased, whereas the prevalence of stunting in the Northern Province has increased slightly [ 14 , 17 ].…”