Affiliation:
1. Faculty of Agricultural and Environmental Sciences, School of Human Nutrition McGill University Montreal Québec Canada
2. College of Humanities and Social Sciences, School of Women and Gender Studies Makerere University Kampala Uganda
3. Faculty of Agricultural and Environmental Sciences, Margaret A. Gilliam Institute for Global Food Security McGill University Montreal Québec Canada
Abstract
AbstractPrior research in health equity, including food security, indicates that disadvantaged groups, such as women with limited resources, face many obstacles in achieving food security. One of the first of its kind to draw on intersectionality and the social determinants of health frameworks, this study identified and tested gender differences in experiencing food security inequities using nationally representative data from the Gallup World Poll, Uganda 2019 (N = 951). Binary logit models disaggregated by gender were estimated to identify gender differences in food security. Three points of intersection were categorized: individual characteristics (gender, age, region, marital status, household number of children and adults); available resources (education, income, employment, shelter, social support); and the socio‐political context (community infrastructures, corruption within the business). Testing the moderation effect of gender with each variable (difference‐in‐difference) showed that although most variables correlated with a difference in experiencing food security by gender, only two—marital status, and social support—presented a statistically significant difference. Accounting for this moderation effect, the final model showed that lacking shelter and residing in Eastern Uganda decreased food security. More adults in the household, higher education, higher income, available social support, and satisfaction with community infrastructures enhanced the odds of food security. Results suggest that (a) conventional food security quantitative approaches may not suffice to model inequities when gender is a control variable rather than a foundation to explain inequities; and (b) gendered‐centered analysis helps better identify disadvantaged groups and inform policies that target associated inequities.