Food insecurity vulnerability among domestic migrants across Cambodian provinces: a multilevel analysis

Food insecurity affects over half of Cambodia's population, yet despite national efforts to improve equitable access to food, little is known about how migration patterns and provincial contexts shape this vulnerability. This study examines provincial variation in food insecurity in Cambodia, its association with domestic migration patterns, modification by household-head gender and the role of provincial-level contextual factors.

This cross-sectional study used data from 5166 adults aged 18 and older from the 2023 World Health Survey Plus Cambodia, linked with provincial-level data across 25 provinces. A two-level multilevel model examined the association between nine domestic migration patterns and food insecurity-defined as eating less or going hungry in the last 12 months due to lack of food or inability to afford food. The model included individual-level covariates (age, gender, wealth, education, urbanisation, household size, ethnicity and marital status), province-level factors (flooding, wealth, socio-geographic zones and special economic zones) and an interaction term between household-head gender and migration patterns.

Two groups of domestic migrants had higher odds of experiencing food insecurity than those who never moved: rural-to-rural migrants who moved either intra-provincially (OR 1.65, 95% CI 1.15 to 2.37) or inter-provincially (OR 1.59, 95% CI 1.15 to 2.19). Household-head gender modified the association between migration and food insecurity. Food insecurity prevalence varied across provinces, and only 1.1% of this variation was attributable to province-level characteristics, with half (0.5%) explained by flooding, provincial wealth, special economic zones and socio-geographic zones. Larger group-level variation (12.0% and 9.1%) was observed at the sub-provincial district level.

Domestic migrants moving between rural areas in Cambodia face higher risks of food insecurity. Policy-makers are encouraged to strengthen labour laws and social protection programmes, implement targeted interventions that account for migration and gendered effects and enhance data systems, especially at sub-provincial levels, to enable further research.