ArticlePublic health nutrition2018
Post-conflict household structures and underweight: a multilevel analysis of a community-based study in northern Uganda.
Article in Public health nutrition, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors at 3 institutions in 3 countries.
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Abstract
objectiveTo examine associations between household-level characteristics and underweight in a post-conflict population.
designNutritional status of residents in the Gulu Health and Demographic Surveillance Site was obtained during a community-based cross-sectional study, ~6 years after the civil war. Household-level factors included headship, polygamy, household size, child-to-adult ratio, child crowding, living with a stunted or overweight person, deprived area, distance to health centre and socio-economic status. Multilevel logistic regression models examined associations of household and community factors with underweight, calculating OR, corresponding 95 % CI and intraclass correlation coefficients. Effect modification by gender and age was examined by interaction terms and stratified analyses.
settingRural post-conflict area in northern Uganda. SUBJECTS: In total, 2799 households and 11 312 individuals were included, representing all age groups.
resultsLiving in a female-headed v. male-headed household was associated (OR; 95 % CI) with higher odds for underweight among adult men (2·18; 1·11, 4·27) and girls <5 years (1·51; 0·97, 2·34), but lower odds among adolescent women aged 13-19 years (0·46; 0·22, 0·97). Higher odds was seen for residents living in deprived areas (1·37; 0·97, 1·94), with increasing distance to health services (P-trend <0·05) and among adult men living alone v. living in an average-sized household of seven members (3·23; 1·22, 8·59). Residents living in polygamous households had lower odds for underweight (0·79; 0·65, 0·97).
conclusionsThe gender- and age-specific associations between household-level factors and underweight are likely to reflect local social capital structures. Adapting to these is crucial before implementing health and nutrition interventions.
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