Inadequate food and nutrition affect human well-being, particularly for many poor subpopulations living in rural areas. The purpose of this research was to analyze the factors that determine the Household Dietary Diversity Score (HDDS) in the rural area of the Paute River Basin, Azuay Province, Ecuador. The sample size of 383 surveys was determined by a stratified random sampling method with proportional affixation. Dietary diversity was measured through the HDDS, with 12 food groups (cereals; roots and tubers; fruits; sugar/honey; meat and eggs; legumes or grains; vegetables; oils/fats; milk and dairy products; meats; miscellaneous; fish and shellfish) over a recall period of 7 days. A Poisson regression model was used to determine the relationship between the HDDS and sociodemographic variables. The results show that the average HDDS of food consumption is 10.89 foods. Of the analyzed food groups, the most consumed are cereals; roots and tubers; fruits; sugar/honey. In addition, the determinants that best explain the HDDS in the predictive model were housing size, household size, per capita food expenditure, area of cultivated land, level of education, and marital status of the head of household. The tools used in this research can be used to analyze food and nutrition security interventions. Furthermore, the results allow policymakers to identify applicable public policies in the fight against hunger.

Eliminating food insecurity is one of humanity’s greatest global challenges. Thus, the purpose of this research was to analyze the factors that determine food insecurity in households in the rural area of the Paute River Basin, Azuay Province, Ecuador. Stratified sampling was used as the sampling method, with proportional affixation. Moreover, we employed the Latin American and Caribbean Household Food Security Measurement Scale (ELCSA). We estimated the main determinants of household food insecurity using two binomial logit models and one ordered logit model. For the analysis of the data, the respective statistical and econometric tests were employed. The results show that housing size and access to food security information are the most important determinants of food insecurity in the three predictive models applied in this research. This research contributes to the existing literature on food insecurity and provides important information for policymakers, especially regarding food insecurity in rural areas, which has profound economic and social implications.