Identifying predictors for food insecurity in England: a cross-sectional database analysis

Abstract

Background: Nutrition plays a significant role in non-communicable disease worldwide and is a modifiable risk factor. Food security is defined as the ability of a household or individual to afford and access sufficient healthy and nutritious food. Food insecurity rates in the UK are among the worst in Europe and rising food prices have disproportionately affected lower income households. We aimed to identify predictors for food insecurity in England using nationally representative data. Methods: We conducted a database analysis on data collected in the ‘Food and You 2: Wave 6’ public cross-sectional dataset. Data were analysed from a mixed survey, collating 3,033 responses to the United Stated Department of Agriculture Household Food Security Survey Module, which defined food security status. We calculated risk ratios (RR) for food insecurity in relation to each independent variable, including sex, respondent age group, household size, presence of children in household, income, employment status, urban/rural living status, ethnicity, chronic conditions and Index of Multiple Deprivation (IMD). Results: 72.3% (n = 2,194) were food secure, 23.4% (n = 710) were food-insecure. Variables associated with increased food insecurity risk included all respondent age groups below 65 year old, household size of 5 or more, presence of children under 16 years and under 6 years, household income less than £64,000 per annum, unemployed individuals, students, Asian / Asian British and African / African British ethnicities, presence of one or more chronic conditions and IMD of 1. Conclusions: In this analysis of nationally representative data, age, household size, presence of children, income, employment status, ethnicity and IMD were all associated with significantly increased risk for food insecurity. Further work is required to understand the relationship between these variables and food security in order to develop screening tools to identify those at highest risk of food insecurity in the population. This will help facilitate the effective provision of support to those who need it the most.