Overview

Abstract (English)

Background: Many analyses examining health and socio-demographic correlates of household food insecurity use a binary variable (i.e. food security vs food insecurity). This dichotomy implies that food insecure households represent a homogenous group; however, recent evidence suggests that the severity of the experience of food insecurity is an important marker of increased vulnerability. Objective: To examine an alternative analytic approach that considers the severity of food insecurity. Methods: The aggregate number of affirmative responses to the 18-item Household Food Security Survey Module can be used to create the food insecurity raw score (FIRS), ranging from 0 to 10 for households without children and 0 to 18 for households with children. Considering that the true degree of food security and insecurity is unknown for households at the extreme ends of the range, the Tobit model is used to account for the censoring of the dependent variable. The model estimates coefficients providing the linear effect of the predictors on the predicted value of FIRS. In this presentation, we will contrast the insights gained from an application of the Tobit model with the results of conventional analyses of food insecurity using a simple binary variable. Implication: The correlates of food insecurity have been extensively documented, but there are few studies exploring the full range of households’ experiences of food insecurity. A better understanding of the characteristics related to the severity of food insecurity is essential to identify policy interventions targeting some of the most vulnerable households in Canada.

Abstract (French)

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