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Sociodemographic differences in fast food price sensitivity. | LitMetric

Sociodemographic differences in fast food price sensitivity.

JAMA Intern Med

Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill3Carolina Population Center, University of North Carolina, Chapel Hill.

Published: March 2014

AI Article Synopsis

  • Fiscal food policies aim to improve health at the population level, but their effects on health disparities remain unclear.
  • The study analyzes how changes in fast food prices affect consumption and health outcomes among different demographic groups over 20 years, using data from a diverse US cohort.
  • Results show that higher fast food prices reduce consumption, with significant differences based on race, income, and education, highlighting that these fiscal policies may differentially impact health outcomes based on socioeconomic factors.

Article Abstract

Importance: Fiscal food policies (eg, taxation) are increasingly proposed to improve population-level health, but their impact on health disparities is unknown.

Objective: To estimate subgroup-specific effects of fast food price changes on fast food consumption and cardiometabolic outcomes.

Design, Setting, And Participants: Twenty-year follow-up (5 examinations) in a biracial US prospective cohort: Coronary Artery Risk Development in Young Adults (CARDIA) (1985/1986-2005/2006, baseline N = 5115). Participants were aged 18 to 30 years at baseline; design indicated equal recruitment by race (black vs white), educational attainment, age, and sex. Community-level price data from the Council for Community and Economic Research were temporally and geographically linked to study participants' home address at each examination.

Main Outcomes And Measures: Participant-reported number of fast food eating occasions per week, body mass index (BMI), and homeostasis model assessment insulin resistance (HOMA-IR) from fasting glucose and insulin concentrations. Covariates included individual-level and community-level social and demographic factors.

Results: In repeated measures regression analysis, multivariable-adjusted associations between fast food price and consumption were nonlinear (quadratic, P < .001), with significant inverse estimated effects on consumption at higher prices; estimates varied according to race (interaction P = .04), income (P = .07), and education (P = .03). At the 10th percentile of price ($1.25/serving), blacks and whites had mean fast food consumption frequency of 2.20 (95% CI, 2.07-2.33) and 1.55 (1.45-1.65) times/wk, respectively, whereas at the 90th percentile of price ($1.53/serving), respective mean consumption estimates were 1.86 (1.75-1.97) and 1.50 (1.41-1.59) times/wk. We observed differential price effects on HOMA-IR (inverse for lower educational status only [interaction P = .005] and at middle income only [interaction P = .02]) and BMI (inverse for blacks, less education, and middle income; positive for whites, more education, and high income [all interaction P < .001]).

Conclusions And Relevance: We found greater fast food price sensitivity on fast food consumption and insulin resistance among sociodemographic groups that have a disproportionate burden of chronic disease. Our findings have implications for fiscal policy, particularly with respect to possible effects of fast food taxes among populations with diet-related health disparities.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3963142PMC
http://dx.doi.org/10.1001/jamainternmed.2013.13922DOI Listing

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