title: Sociodemographic differences in fast food price sensitivity.
abstract: OBJECTIVE
  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.
  
  
  METHODS
  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.
  
  
  METHODS
  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
  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.
authors.affiliation: Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill.
authors.forename: Katie A
authors.initials: KA
authors.lastname: Meyer
authors.affiliation: Department of Economics, University of North Carolina, Chapel Hill3Carolina Population Center, University of North Carolina, Chapel Hill.
authors.forename: David K
authors.initials: DK
authors.lastname: Guilkey
authors.affiliation: Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill3Carolina Population Center, University of North Carolina, Chapel Hill.
authors.forename: Shu Wen
authors.initials: SW
authors.lastname: Ng
authors.affiliation: Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill4Department of Human Nutrition, Foods, and Exercise, Virginia Polytechnic Institute and State University, Blacksburg.
authors.forename: Kiyah J
authors.initials: KJ
authors.lastname: Duffey
authors.affiliation: Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill3Carolina Population Center, University of North Carolina, Chapel Hill.
authors.forename: Barry M
authors.initials: BM
authors.lastname: Popkin
authors.affiliation: Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester.
authors.forename: Catarina I
authors.initials: CI
authors.lastname: Kiefe
authors.affiliation: Division of Epidemiology and Community Health, University of Minnesota, Minneapolis.
authors.forename: Lyn M
authors.initials: LM
authors.lastname: Steffen
authors.affiliation: Division of Preventive Medicine, University of Alabama at Birmingham, Birmingham.
authors.forename: James M
authors.initials: JM
authors.lastname: Shikany
authors.affiliation: Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill3Carolina Population Center, University of North Carolina, Chapel Hill.
authors.forename: Penny
authors.initials: P
authors.lastname: Gordon-Larsen
mesh_terms: D000293:Adolescent; D000328:Adult; D001741:Black or African American; D003132:Commerce / Q000191:economics*; D004032:Diet / Q000191:economics*; D057140:Fast Foods / Q000191:economics*; D005247:Feeding Behavior; D005260:Female; D054625:Healthcare Disparities / Q000191:economics*; D006801:Humans; D007182:Income; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D011446:Prospective Studies; D012307:Risk Factors; D012959:Socioeconomic Factors; D044465:White People