Investigating the prevalence and predictors of food insecurity: a comparison of HFSSM and EU-SILC indicators

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Purpose: Data from the Northern Ireland (NI) Health Survey 2014/15 (n = 2,231) were statistically analysed to examine the prevalence of food insecurity according to both indicators. Pearson's X 2 test for association and logistic regressions were used to examine associations between food security status and predictor variables. Design/methodology/approach: Household food insecurity has been identified as a significant societal issue in both developed and developing nations, but there exists no universal indicator to approximate its prevalence. In NI, two indicators (United States Household Food Security Survey Module [HFSSM] and the European Union Statistics on Income and Living Conditions [EU-SILC] food deprivation questions) have been used. This study examines how both indicators differ in their classification of food insecurity prevalence in a population sample and also examines the relationship between various demographic and household factors and food security status. Findings: According to the EU-SILC food deprivation questions, 8.3% (n = 185) were indicated to be food insecure, while according to the HFSSM, 6.5% (n = 146) were indicated to be food insecure. The HFSSM and EU-SILC regression models differed in the underlying variables they identified as significant predictors of food insecurity. Significant variables common to both modules were tenure, employment status, health status, anxiety/depression and receipt of benefits. Originality/value: Findings can inform policy action with regards to targeting the key contributors and can inform policy decisions in NI and elsewhere with regards to choosing the most appropriate food insecurity indicator.

Original languageEnglish
JournalBritish Food Journal
Early online date15 Oct 2021
Publication statusPublished online - 15 Oct 2021

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© 2021, Emerald Publishing Limited.


  • food insecurity
  • food poverty
  • deprivation
  • measurement
  • logistic regression


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