Bayesian joint spatial modeling of child malnutrition and household food insecurity among under-five children in Somaliland
Year: 2026
Type: article
Abstract: Malnutrition and household food insecurity are major public health concerns among under-five children in Somaliland, often sharing overlapping risk factors. Using data from the 2020 Somaliland Health and Demographic Survey (n = 3961), this study assessed their prevalence, spatial distribution, and shared determinants through descriptive statistics, spatial autocorrelation, and a multivariate Bayesian spatial model. The prevalence of malnutrition and food insecurity was 42.7% and 26.7%, respectively, with higher risk of malnutrition among children in food-insecure households (OR = 1.17). Both outcomes were most prevalent in eastern regions such as Sool and Sanaag, with significant clustering of food insecurity and their joint occurrence. Risk factors for food insecurity included large family size, lack of radio and agricultural land, and longer water-fetching time, while higher wealth, electricity access, and more sleeping rooms were protective. Malnutrition was associated with female sex, absence of cooling facilities, and longer water-fetching time. The joint burden was influenced by nomadic residence, household wealth, family size, sleeping rooms, and electricity. These findings highlight the geographic concentration and interconnectedness of malnutrition and food insecurity and underscore the need for multi-sectoral interventions targeting poverty reduction, water access, and infrastructure, with a particular focus on eastern regions. Strengthening nutrition-sensitive policies and integrated programs that address both household resources and structural barriers could reduce the overlapping burden of child malnutrition and food insecurity, providing critical evidence for policymakers and development partners in Somaliland and similar fragile contexts.
Source: Health & Place
Language: English
Subfield: Nutrition and Dietetics
Field: Nursing
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,380
OpenAlex ID: W7132848786