Very Low Food Security in US Households Is Predicted by Complex Patterns of Health, Economics, and Service Participation1

• Published in: The Journal of nutrition Vol. 147; no. 10; pp. 1992 - 2000
• Main Authors: Choi, Seul Ki, Fram, Maryah S, Frongillo, Edward A
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.10.2017
• Subjects: classification and regression tree; decision tree; food assistance program; household composition; medical needs; very low food security; NHIS; FPL; very low food security; CPS; VLFS; SNAP; AUC; classification and regression tree; decision tree; medical needs; household composition; food assistance program; CART
• ISSN: 0022-3166; 1541-6100
• DOI: 10.3945/jn.117.253179

Very low food security (VLFS) happens at the intersection of nuanced and complex patterns of risk characteristics across multiple domains. Little is known about the idiosyncratic situations that lead households to experience VLFS. We used classification and regression tree (CART) analysis, which can handle complex combinations of predictors, to identify patterns of characteristics that distinguish VLFS households in the United States from other households. Data came from 3 surveys, the 2011–2014 National Health Interview Survey (NHIS), the 2005–2012 NHANES, and the 2002–2012 Current Population Survey (CPS), with sample participants aged ≥18 y and households with income <300% of the federal poverty line. Survey participants were stratified into households with children, adult-only households, and older-adult households (NHIS, CPS) or individuals aged 18–64 y and individuals aged ≥65 y (NHANES). Household food security was measured with the use of the 10-item US Adult Food Security Scale. Variables from multiple domains, including sociodemographic characteristics, health, health care, and participation in social welfare and food assistance programs, were considered as predictors. The 3 data sources were analyzed separately with the use of CART analysis. Household experiences of VLFS were associated with different predictors for different types of households and often occurred at the intersection of multiple characteristics spanning unmet medical needs, poor health, disability, limitation, depressive symptoms, low income, and food assistance program participation. These predictors built complex trees with various combinations in different types of households. This study showed that multiple characteristics across multiple domains distinguished VLFS households. Flexible and nonlinear methods focusing on a wide range of risk characteristics should be used to identify VLFS households and to inform policies and programs that can address VLFS households’ various needs.