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<p>Food insecurity remains a major public health and socio-economic issue in many low-resource settings, including Somaliland. Despite national and international efforts, household-level determinants of food insecurity are not well understood, particularly in regional contexts. This study aimed to identify both individual- and community-level predictors of household food security in MaroodiJeex Region using a multilevel modeling approach. A community-based cross-sectional study was conducted from January to May 2025 among 411 households in Hargeisa, Somaliland. A two-stage sampling technique was employed, and data were collected using the standardized Household Food Insecurity Access Scale (HFIAS) questionnaire developed by FAO. The outcome variable was food security status, categorized as secure or insecure. Explanatory variables included socio-demographic, economic, and environmental factors. Multilevel logistic regression analysis (Models 0 to III) was performed using STATA v17, and model fit was assessed using AIC, BIC, and ICC. The prevalence of food insecurity was high, Household food insecurity affected 51.4% of surveyed households in MaroodiJeex Region. In the multilevel regression models, key individual-level factors included gender, employment status, and education. Female respondents had higher odds of living in food-insecure households (AOR = 1.38, 95% CI: 1.04–1.82) compared to males. Unemployment was associated with increased insecurity (AOR = 1.59, 95% CI: 1.16–2.17), while higher education (AOR = 1.80, 95% CI: 1.05–3.09) was significantly associated with improved food security. Food insecurity in MaroodiJeex remains a critical issue influenced by both household-level and community-level variables. Interventions targeting employment, education, and community food systems should be prioritized.</p> Graphical Abstract <p></p> <p>This visual summary provides a concise overview of a community-based cross-sectional study assessing the determinants of household food insecurity in the MaroodiJeex Region of Somaliland. <b>Data</b> were derived from 411 households using a two-stage stratified cluster sampling technique, utilizing the standardized FAO Household Food Insecurity Access Scale (HFIAS). <b>Analyses</b> involved rigorous descriptive statistics and multilevel binary logistic regression to account for hierarchical data structures. The <b>Model</b> framework progressed from an empty null model to a combined model (Model III), integrating individual-level factors (gender, education, employment) and community-level factors (income aggregation, food sources). <b>Results</b> depicted in the visual highlight a critical prevalence of food insecurity (over 60%), with significant disparities driven by gender, employment status, and education. Notably, the visual emphasizes that female respondents and the unemployed face significantly higher odds of insecurity, while community reliance on food aid negatively correlates with food security. The <b>Conclusion</b> presented underscores that food insecurity in arid Somaliland is not solely environmental but deeply rooted in socio-economic constraints. The study establishes that community-level variations account for over 25% of the disparity, advocating for multisectoral interventions that prioritize employment generation, educational empowerment, and the strengthening of local food systems over temporary aid dependency. This graphical representation serves as a rapid entry point for readers to grasp the study’s methodological rigor and policy-relevant outcomes.</p>

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Beyond Climate: Socio-Economic Determinants Dominating Household Food Insecurity in Somaliland

  • 期刊论文

  • 发表日期：

    2026年6月18日

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  • Yahye Hassan Muse,
  • Abdisalam Hassan Muse,
  • Mohamed Abdi Abdulahi,
  • Mukhtar Abdi Hassan,
  • Saralees Nadarajah

摘要

Food insecurity remains a major public health and socio-economic issue in many low-resource settings, including Somaliland. Despite national and international efforts, household-level determinants of food insecurity are not well understood, particularly in regional contexts. This study aimed to identify both individual- and community-level predictors of household food security in MaroodiJeex Region using a multilevel modeling approach. A community-based cross-sectional study was conducted from January to May 2025 among 411 households in Hargeisa, Somaliland. A two-stage sampling technique was employed, and data were collected using the standardized Household Food Insecurity Access Scale (HFIAS) questionnaire developed by FAO. The outcome variable was food security status, categorized as secure or insecure. Explanatory variables included socio-demographic, economic, and environmental factors. Multilevel logistic regression analysis (Models 0 to III) was performed using STATA v17, and model fit was assessed using AIC, BIC, and ICC. The prevalence of food insecurity was high, Household food insecurity affected 51.4% of surveyed households in MaroodiJeex Region. In the multilevel regression models, key individual-level factors included gender, employment status, and education. Female respondents had higher odds of living in food-insecure households (AOR = 1.38, 95% CI: 1.04–1.82) compared to males. Unemployment was associated with increased insecurity (AOR = 1.59, 95% CI: 1.16–2.17), while higher education (AOR = 1.80, 95% CI: 1.05–3.09) was significantly associated with improved food security. Food insecurity in MaroodiJeex remains a critical issue influenced by both household-level and community-level variables. Interventions targeting employment, education, and community food systems should be prioritized.

Graphical Abstract

This visual summary provides a concise overview of a community-based cross-sectional study assessing the determinants of household food insecurity in the MaroodiJeex Region of Somaliland. Data were derived from 411 households using a two-stage stratified cluster sampling technique, utilizing the standardized FAO Household Food Insecurity Access Scale (HFIAS). Analyses involved rigorous descriptive statistics and multilevel binary logistic regression to account for hierarchical data structures. The Model framework progressed from an empty null model to a combined model (Model III), integrating individual-level factors (gender, education, employment) and community-level factors (income aggregation, food sources). Results depicted in the visual highlight a critical prevalence of food insecurity (over 60%), with significant disparities driven by gender, employment status, and education. Notably, the visual emphasizes that female respondents and the unemployed face significantly higher odds of insecurity, while community reliance on food aid negatively correlates with food security. The Conclusion presented underscores that food insecurity in arid Somaliland is not solely environmental but deeply rooted in socio-economic constraints. The study establishes that community-level variations account for over 25% of the disparity, advocating for multisectoral interventions that prioritize employment generation, educational empowerment, and the strengthening of local food systems over temporary aid dependency. This graphical representation serves as a rapid entry point for readers to grasp the study’s methodological rigor and policy-relevant outcomes.