10.1371/journal.pmed.0020297

Vollständiger Abstract

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Child malnutrition remains a global crisis, exacerbated in border regions by Myanmar's post-2021 conflict. This study utilized Structural Equation Modeling (SEM) to examine the pathways linking household food insecurity (HFI) to undernutrition among migrant children along the Thailand-Myanmar border. A cross-sectional survey was conducted among 384 mothers in Tak and Mae Hong Son provinces with children aged 6-59 months. Data were collected via multistage sampling, face-to-face interviews, and anthropometric assessments. HFI was measured using the HFIAS scale. Undernutrition affected 37.0% of children, with specific prevalence for stunting (18.0%), wasting (19.8%), and underweight (18.5%). HFI was prevalent in 63.8% of households and served as a central structural mediator; notably, nearly 40% of stunted children resided in severely food-insecure households. SEM results indicated that higher socio-economic status (SES) consistently improved HAZ (β = 0.230, p < .001) and WAZ (β = 0.294, p < .001). Improved water availability, safe sanitation, and higher SES were strong predictors of better HFI status across all models (β ranging from 0.127 to 0.318, p < .023). Conversely, a higher number of children under five in the household negatively impacted food security (β ranging from -0.155 to -0.159, p < .003). This improved HFI status directly enhanced dietary diversity (β = 0.183, p = .001) and HAZ (β = 0.113, p = .033). Regarding acute outcomes, fever (β = -0.147, p = .008) and diarrhea (β = -0.131, p = .049) significantly reduced WHZ, while respiratory infections (β = -0.144, p = .014) negatively influenced WAZ. Addressing undernutrition in this migrant population requires integrated multi-sectoral interventions. Strategies must prioritize economic stability and HFI mitigation to address chronic growth failure, alongside WASH infrastructure and rapid illness response to mitigate acute and composite nutritional deficits through a synergistic, cross-sectoral approach.

Abstract: PubMed · Datensatz