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Background <p>Food insecurity is a critical challenge in Somalia, hindering SDG 2 progress. Exacerbated by conflict and climate change, understanding its complex drivers at multiple levels is vital for effective interventions. This study investigates the spatial variations and multilevel determinants (individual and community) of household food insecurity nationwide.</p> Methods <p>Using weighted 2020 Somalia Demographic and Health Survey data (<i>N</i> = 15,826), this cross-sectional study assessed household food insecurity (“lack of food”). Multilevel logistic regression examined individual (e.g., wealth, household head characteristics, assets) and community (region, residence) factors, accounting for data hierarchy. Spatial autocorrelation analyses (Global Moran’s I, Local Moran’s I, Getis-Ord Gi*) identified geographic clustering and hotspots/cold spots.</p> Results <p>High prevalence (70%) of household food insecurity was observed. Multilevel analysis showed richer wealth status (AOR = 0.21, 95% CI = 0.19–0.25 vs. poor), female household headship (AOR = 0.82, 95% CI = 0.76–0.90), older head age (&gt; 50 years: AOR = 0.85, 95% CI = 0.77–0.93), larger household size (&gt; 7 members: AOR = 0.83, 95% CI = 0.77–0.91), and school attendance by the head (AOR = 0.87, 95% CI = 0.80–0.95) were significantly associated with lower odds of food insecurity. Nomadic residence significantly increased odds compared to urban settings (AOR = 1.99, 95% CI = 1.59–2.51). Significant regional variations persisted. Spatial analyses revealed statistically significant positive spatial autocorrelation (Moran’s I = 0.64, <i>p</i> &lt; .001), indicating non-random clustering, with significant hotspots identified, particularly in Sool, Sanaag, and Bari regions.</p> Conclusion <p>Household food insecurity in Somalia is widespread, spatially clustered, and influenced by complex individual socioeconomic characteristics and community-level geographic factors. Wealth is a key protective factor. Findings necessitate spatially targeted, context-specific interventions alongside broader poverty alleviation strategies, particularly in identified hotspot regions, to effectively address food insecurity.</p>

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Spatial variation and determinants of household food insecurity in Somalia using spatial and multilevel analysis of nationwide data

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月2日

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  • Khadar Jama Osman,
  • Dahir Isaq Jibril,
  • Mohamed Mohamoud Abdilleh,
  • Abdirashid M. Yousuf,
  • Abdisalam Hassan Muse

摘要

Background

Food insecurity is a critical challenge in Somalia, hindering SDG 2 progress. Exacerbated by conflict and climate change, understanding its complex drivers at multiple levels is vital for effective interventions. This study investigates the spatial variations and multilevel determinants (individual and community) of household food insecurity nationwide.

Methods

Using weighted 2020 Somalia Demographic and Health Survey data (N = 15,826), this cross-sectional study assessed household food insecurity (“lack of food”). Multilevel logistic regression examined individual (e.g., wealth, household head characteristics, assets) and community (region, residence) factors, accounting for data hierarchy. Spatial autocorrelation analyses (Global Moran’s I, Local Moran’s I, Getis-Ord Gi*) identified geographic clustering and hotspots/cold spots.

Results

High prevalence (70%) of household food insecurity was observed. Multilevel analysis showed richer wealth status (AOR = 0.21, 95% CI = 0.19–0.25 vs. poor), female household headship (AOR = 0.82, 95% CI = 0.76–0.90), older head age (> 50 years: AOR = 0.85, 95% CI = 0.77–0.93), larger household size (> 7 members: AOR = 0.83, 95% CI = 0.77–0.91), and school attendance by the head (AOR = 0.87, 95% CI = 0.80–0.95) were significantly associated with lower odds of food insecurity. Nomadic residence significantly increased odds compared to urban settings (AOR = 1.99, 95% CI = 1.59–2.51). Significant regional variations persisted. Spatial analyses revealed statistically significant positive spatial autocorrelation (Moran’s I = 0.64, p < .001), indicating non-random clustering, with significant hotspots identified, particularly in Sool, Sanaag, and Bari regions.

Conclusion

Household food insecurity in Somalia is widespread, spatially clustered, and influenced by complex individual socioeconomic characteristics and community-level geographic factors. Wealth is a key protective factor. Findings necessitate spatially targeted, context-specific interventions alongside broader poverty alleviation strategies, particularly in identified hotspot regions, to effectively address food insecurity.