Factorial effects contributing to food security in Mexico during COVID-19 context

Abstract

The COVID-19 pandemic has altered the social, economic and environmental order of the world, and it wreaked havoc in many aspects of the life of societies, including the food insecurity (FI) rates in the regions. Due to the multifaceted nature of this phenomenon, it is required a better understanding of the associated variables that contribute to food security (FS), such as the socioeconomic and demographic variables for designing effective and efficient policy interventions. In this sense, this study describes an innovative way of interpreting the causal influence of the interaction effects between the socioeconomic and demographic variables on the level of FS experienced by Mexican households during the pandemic crisis. The period from March to May of 2021, a digital survey was applied to 630 households to analyze the harmonized version of the Latin American and Caribbean Food Security Scale (ELCSA). For this, a factorial regression model was used to estimate the factorial effects contribution of the mentioned variables under study, obtaining important results on the level of FS in two Mexican states: Nayarit and the State of Mexico. The obtained model shows the contribution factors, involved on the level of FS, are the following: mother's job, household incomes, the portion of income destined for food, the interaction between the family members with the place of residence, the interaction of the gender of the household head with the place of residence, the interaction of the mother's job with the father's schooling, and the interaction of the father's schooling with the portion of income spent on food. These findings offer essential insights for identifying vulnerable groups susceptible to experiencing food insecurity, in order to facilitate effective intervention in the multiple areas that require improvement, thus enhancing food security in the regions and contributing to the achievement of the SDG.

Keywords

• Factorial linear regression
• Food security
• Mexico
• ELCSA