Prevalence of food security in the UK measured by the Food Insecurity Experience Scale

Abstract

Background Measurement of UK food insecurity has historically been inconsistent, making it difficult to understand trends. This study contributes by reporting and analysing data from a national survey conducted in line with UN Food and Agriculture Organization (FAO) recommendations and standard methods, providing an internationally comparable pre-coronavirus disease 2019 (COVID-19) snapshot of food insecurity. Methods Data came from a nationally representative 2019 UK sample (N = 2000) surveyed by Ipsos-Mori. Prevalence of food insecurity was assessed using the UN FAO Food Insecurity Experience Scale. Logistic regression was used to model food insecurity in relation to geographic and socio-demographic variables. Results Severe food insecurity was reported by 3% of the sample, an increase of 66.7% over the last directly comparable UK analysis (Gallup World Poll data from 2016 to 2018). Indication of some degree of food insecurity was reported by 14.2% of the sample and tended to be higher amongst younger age groups, those on lower incomes, and home renters (as opposed to owners). No geographic variables were significantly associated with food insecurity prevalence. Conclusions The finding that prevalence of severe food insecurity was already increasing before the COVID-19 pandemic, across all areas of the UK, is cause for concern. Our results provide an important benchmark for assessing the impact of COVID-19 on food insecurity.

Exploring the nexus between natural disasters and food (in)security: Evidence from rural Bangladesh

“…For example, Faridi and Wadood (2010) employed a logistic model to investigate the determinants of food security in Bangladesh, while Islam and Ahmed (2017), Uddin (2012), Stevens et al (2017), and Alam et al (2020) relied mainly on descriptive statistics as well as the non‐parametric tests to analyse food security. Based on the FIES, Smith et al (2017) analysed the determinants of food insecurity with the help of a linear probability model, while Pool and Dooris (2021) investigated the prevalence of food security in the United Kingdom using the logistic regression technique.…”

Prevalence and Risk Factors of Food Insecurity among Mexican University Students’ Households

“…Low income is one of the main risk factors for FI. In other contexts, lower income was positively associated with FI in UK adults [5], Australian adults [35], and in US college students [36]. In the Mexican population, any income level in comparison to very low income was positively associated with food security and negatively with FI [4].…”

“…4 Data is presented as frequency (percentage). 5 A person who considers himself/herself as indigenous, according to his/her culture. 6 Others: One-person household, extended household, composite household, co-resident household.…”

“…However, these rates are expected to rise due to the coronavirus disease (COVID-19) pandemic [2]. Some risk factors associated with FI in the general Mexican population [4] and other contexts [5,6] are the following: woman household head, household with a family member that is disabled, a household head with no formal education, native language, having two or more children at home, living in a rural area [4], younger age [4][5][6], renting their home [5,6], being unmarried with or without children [6], and low-income household [4,6].…”

“…Data is presented as mean ± standard deviation 4. Data is presented as frequency (percentage) 5. A person who considers himself/herself as indigenous, according to his/her culture 6.…”