Sociodemographic differences in fast food price sensitivity

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.

Figure 1

Slopes¹ (95% CI) for the estimated effect of fast food price² (2 SD units³) on fast food consumption (frequency/week)⁴ according to sociodemographic subgroups: CARDIA 1985/86–2005/06. ^1. Slopes (marginal effects) from repeated measures negative binomial regression models adjusted for: exam year, study center, age, race, sex, maximum educational attainment, highest reported income, population density, cost of living, and neighborhood deprivation. Random effects were used to account for within-person clustering over exam periods. Interaction term p-values: race=0.04, income=0.07, education=0.03. P-values for trend (by group): <0.01 (black), 0.42 (whites), <0.01 (income<$40,000), 0.04 (income $40–75,000), 0.09 (income>$75,000), 0.01 (<16 years education), and 0.50 (≥16 years education). ^2.Fast food prices deflated to 1982–1984. Prices shown at decile cutpoints (10^th to 90^th percentiles: $1.25, 1.30, 1.32, 1.36, 1.38, 1.40, 1.47, 1.49, 1.53). ^3.2 SD units = $0.20. ^4.Fast food consumption mean (SD): 1.80 (2.34).

Figure 2

Slopes¹ (95% CI) for the estimated effect of fast food price² (2 SD units³) on ln-HOMA-IR⁴ according to sociodemographic subgroups: CARDIA 1985/86–2005/06. ^1. Slopes (marginal effects) from repeated measures linear regression models adjusted for: exam year, study center, age, race, sex, maximum educational attainment, highest reported income, population density, cost of living, and neighborhood deprivation. Random effects were used to account for within-person clustering over exam periods. Interaction term p-values: race=0.10, income=0.02, education<0.01. P-values for trend (by group): 0.06 (black), 0.86 (whites), 0.27 (income<$40,000), <0.01 (income $40–75,000), 0.95 (income>$75,000), 0.02 (<16 years education), and 0.69 (≥16 years education). ^2.Fast food prices deflated to 1982–1984. Prices shown at decile cutpoints (10^th to 90^th percentiles: $1.25, 1.30, 1.32, 1.36, 1.38, 1.40, 1.47, 1.49, 1.53). ^3.2 SD units = $0.20. ^4. Ln-HOMA-IR mean (SD): 1.31 (0.47).

Figure 3

Slopes¹ (95% CI) for the estimated effect of fast food price² (2 SD units³) on ln-BMI⁴ according to sociodemographic subgroups: CARDIA 1985/86–2005/06. ^1.Slopes (marginal effects) from repeated measures linear regression models adjusted for: exam year, study center, age, race, sex, maximum educational attainment, highest reported income, population density, cost of living, and neighborhood deprivation. Random effects were used to account for within-person clustering over exam periods. Interaction term p-values: race<0.01, income<0.01, education<0.01. P-values for trend (by group): <0.01 (blacks), <0.01 (whites), 0.98 (income<$40,000), <0.01 (income $40–75,000), 0.02 (income>$75,000), 0.05 (<16 years education), and 0.08 (≥16 years education). ^2.Fast food prices deflated to 1982–1984. Prices shown at decile cutpoints (10^th to 90^th percentiles: $1.25, 1.30, 1.32, 1.36, 1.38, 1.40, 1.47, 1.49, 1.53). ^3.2 SD units = $0.20. ^4. Ln-BMI mean (SD): 3.27 (0.22).