Dataset Information

Fast food price, diet behavior, and cardiometabolic health: Differential associations by neighborhood SES and neighborhood fast food restaurant availability in the CARDIA study.

ABSTRACT: Little research has addressed whether neighborhood context influences associations between fast food price, diet, and cardiometabolic health. We investigated these associations using 25 years of Coronary Artery Risk Development in Young Adults (CARDIA) study data (n=4,469, observations=21,134). We found a negative association between fast food price and consumption, with stronger inverse associations in more (vs. less) deprived neighborhoods [3rd tertile: ?=-0.68 (95% CI: (-0.85, -0.51); 1st tertile: ?=-0.22 (95% CI: -0.42, -0.02); p-interaction-0.002], and a similar association for BMI [3rd tertile: ?=-1.34 (95% CI: -1.54, -1.14); 1st tertile: ?=-0.45 (95% CI: -0.66, -0.25); p-interaction<0.001], but not insulin resistance [3rd tertile: ?=-0.07 (95% CI: -0.24, 0.09); 1st tertile: ?=0.09 (95% CI: -0.08, 0.26); p-interaction=0.40]. We observed no modification of fast food price by fast food availability. Future research on obesity disparities should consider potential differences in the association between fast food prices and health outcomes across neighborhood socioeconomic levels.

SUBMITTER: Rummo PE

PROVIDER: S-EPMC4637179 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Fast food price, diet behavior, and cardiometabolic health: Differential associations by neighborhood SES and neighborhood fast food restaurant availability in the CARDIA study.

Rummo Pasquale E PE Meyer Katie A KA Green Howard Annie A Shikany James M JM Guilkey David K DK Gordon-Larsen Penny P

Health & place 20150915

Little research has addressed whether neighborhood context influences associations between fast food price, diet, and cardiometabolic health. We investigated these associations using 25 years of Coronary Artery Risk Development in Young Adults (CARDIA) study data (n=4,469, observations=21,134). We found a negative association between fast food price and consumption, with stronger inverse associations in more (vs. less) deprived neighborhoods [3rd tertile: β=-0.68 (95% CI: (-0.85, -0.51); 1st ter ...[more]

PMID: 26319447

Similar Datasets

Project description:Fiscal food policies (eg, taxation) are increasingly proposed to improve population-level health, but their impact on health disparities is unknown.To estimate subgroup-specific effects of fast food price changes on fast food consumption and cardiometabolic outcomes.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.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.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]).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.

Project description:BackgroundRecent obesity prevention initiatives focus on healthy neighborhood design, but most research examines neighborhood food retail and physical activity (PA) environments in isolation. We estimated joint, interactive, and cumulative impacts of neighborhood food retail and PA environment characteristics on body mass index (BMI) throughout early adulthood.Methods and findingsWe used cohort data from the Coronary Artery Risk Development in Young Adults (CARDIA) Study [n=4,092; Year 7 (24-42 years, 1992-1993) followed over 5 exams through Year 25 (2010-2011); 12,921 person-exam observations], with linked time-varying geographic information system-derived neighborhood environment measures. Using regression with fixed effects for individuals, we modeled time-lagged BMI as a function of food and PA resource density (counts per population) and neighborhood development intensity (a composite density score). We controlled for neighborhood poverty, individual-level sociodemographics, and BMI in the prior exam; and included significant interactions between neighborhood measures and by sex. Using model coefficients, we simulated BMI reductions in response to single and combined neighborhood improvements. Simulated increase in supermarket density (from 25(th) to 75(th) percentile) predicted inter-exam reduction in BMI of 0.09 kg/m(2) [estimate (95% CI): -0.09 (-0.16, -0.02)]. Increasing commercial PA facility density predicted BMI reductions up to 0.22 kg/m(2) in men, with variation across other neighborhood features [estimate (95% CI) range: -0.14 (-0.29, 0.01) to -0.22 (-0.37, -0.08)]. Simultaneous increases in supermarket and commercial PA facility density predicted inter-exam BMI reductions up to 0.31 kg/m(2) in men [estimate (95% CI) range: -0.23 (-0.39, -0.06) to -0.31 (-0.47, -0.15)] but not women. Reduced fast food restaurant and convenience store density and increased public PA facility density and neighborhood development intensity did not predict reductions in BMI.ConclusionsFindings suggest that improvements in neighborhood food retail or PA environments may accumulate to reduce BMI, but some neighborhood changes may be less beneficial to women.

Project description:BACKGROUND:Food consumed outside of the home is often high in energy and population level interventions that reduce energy intake of people from both lower and higher socioeconomic position (SEP) are needed. There is a lack of evidence on the effectiveness and SEP equity of structural-based (e.g. increasing availability of lower energy options) and information provision (e.g. menu energy labelling) interventions on food choice. METHODS:Across two online experiments, participants of lower and higher SEP made meal choices in a novel virtual fast-food restaurant. To be eligible to take part, participants were required to be UK residents, aged 18 or above, fluent in English, have access to a computer with an internet connection and have no dietary restrictions. Participants were randomized to one of four conditions in a 2 × 2 between-subjects design: menu energy labelling present vs. absent and increased availability of lower energy options (75% of menu options lower energy) vs. baseline availability (25% of menu options lower energy). Participants also completed measures of executive function and food choice motives. RESULTS:The analysis of pooled data from both studies (n = 1743) showed that increasing the availability of lower energy options resulted in participants ordering meals with significantly less energy on average (- 71 kcal, p < 0.001, partial η2 = 0.024) and this effect was observed irrespective of participant SEP. Menu labelling had no significant effect on energy ordered (- 18 kcal, p = 0.116, partial η2 = 0.001) in participants from both higher and lower SEP. Furthermore, we found no evidence that executive function or food choice motives moderated the effect of increasing lower energy menu options or energy labelling on total energy ordered. CONCLUSIONS:In a virtual fast-food environment, energy labelling was ineffective in reducing total energy ordered for both higher and lower SEP participants. Increasing the availability of lower energy options had an equitable effect, reducing total energy ordered in participants from higher and lower SEP. TRIAL REGISTRATION:Study protocols and analysis plans were pre-registered on the Open Science Framework (https://osf.io/ajcr6/).

Dataset Information

Fast food price, diet behavior, and cardiometabolic health: Differential associations by neighborhood SES and neighborhood fast food restaurant availability in the CARDIA study.

Publications

Fast food price, diet behavior, and cardiometabolic health: Differential associations by neighborhood SES and neighborhood fast food restaurant availability in the CARDIA study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets