Examining disparities in diet quality between SNAP participants and non-participants using Oaxaca-Blinder decomposition analysis

Chelsea R Singleton; Sabrina K Young; Nicollette Kessee; Sparkle E Springfield; Bisakha P Sen

doi:10.1016/j.pmedr.2020.101134

Examining disparities in diet quality between SNAP participants and non-participants using Oaxaca-Blinder decomposition analysis

Prev Med Rep. 2020 May 28:19:101134. doi: 10.1016/j.pmedr.2020.101134. eCollection 2020 Sep.

Authors

Chelsea R Singleton¹, Sabrina K Young², Nicollette Kessee³, Sparkle E Springfield⁴, Bisakha P Sen⁵

Affiliations

¹ Department of Kinesiology and Community Health, College of Applied Health Sciences, University of Illinois at Urbana-Champaign, 1206 S Fourth St., Champaign, IL 61820, USA.
² Division of Health Policy and Administration, University of Illinois at Chicago, 1603 W Taylor Street, Chicago, IL 60612, USA.
³ Department of Kinesiology and Nutrition, University of Illinois at Chicago, 1919 W Taylor St., Chicago, IL 60612, USA.
⁴ Stanford Prevention Research Center, Stanford University, 3300 Hillview Avenue, Palo Alto, CA 94304, USA.
⁵ Department of Health Care Organization and Policy, University of Alabama at Birmingham, 1665 University Boulevard, Birmingham, AL 35294, USA.

Abstract

Recent studies have reported that SNAP participants have poorer diet quality than non-participants. This study aimed to examine how differences in socio-demographic, household, and health-related measures explain disparities in diet quality between SNAP participants and non-participants using Oaxaca-Blinder decomposition analysis. We analyzed cross-sectional data on 14,331 adult respondents of the National Health and Nutrition Examination Survey (NHANES) 2009 - 2014. To measure diet quality, we applied the Healthy Eating Index (HEI)-2015 to respondents' 24-hour dietary recall data (scale: 0-100 points). We used Oaxaca-Blinder decomposition analysis to determine how much of the disparity in HEI-2015 total score between SNAP participants and non-participants was explained by socio-demographic (e.g., age, race/ethnicity, educational), household (e.g., household size, food security status), and health-related measures (e.g., BMI, smoking status). Analyses performed revealed significant differences in HEI-2015 total score by SNAP participation status (p < 0.001). We found that the total gap in HEI-2015 total score between SNAP participants and income-ineligible non-participants was 6.30 points. Socio-demographic measures alone explained 72.40% of the disparity. All measures together explained 86.31% of the disparity. The total gap between SNAP participants and income-eligible non-participants was 3.24 points. Socio-demographic measures alone explained 35.51% of this disparity while all measures together explained 56.86%. We observed disparities in diet quality between SNAP participants and non-participants. Socio-demographic, household, and health-related measures explained a significant amount of the disparity that existed between SNAP participants and income-ineligible non-participants; they explained less of the disparity between SNAP participants and income-eligible non-participants.

Keywords: BMI, Body Mass Index; CDC, Centers for Disease Control and Prevention; DGAs, Dietary Guidelines for Americans; Diet; Food assistance; HEI, Healthy Eating Index; IPR, Income-to-Poverty Ratio; NHANES, National Health and Nutrition Examination Survey; Nutrition surveys; Poverty; SNAP, Supplemental Nutrition Assistance Program.

Abstract

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