While a major focus of disparities research has been on understanding patterns of health determinants and outcomes by race-ethnic and SES subpopulations, there are major gaps in understanding how to use public policy to reduce these gaps. The proposed project examines food prices and food environment factors, two areas with great potential for policy change. We will use longitudinal data to understand the effects of changes in food prices, and availability and access to away-from-home food eateries and food shopping options on diet, and in turn, weight gain and metabolic risk factors. We will finalize a longitudinal data set that geographically and temporally links food price and food environment measures to residential locations of respondents of the Coronary Artery Risk Development in Young Adults (CARDIA) Study, a study of the antecedents and risk factors for cardiovascular disease in an ethnicity-, age-, and sex-balanced cohort of 5,115 black and white young adults aged 18-30 years at baseline (1985-86) and followed over 25 years into 2010-11. We capitalize upon neighborhood-level data linked to individual data using a multidisciplinary approach melding spatial analysis methodologies with traditional epidemiological and economic methods. We examine how food prices and neighborhood food and social environmental factors interact with individual-level household income and education to affect the adoption and maintenance of overall measures of beverage and diet quality. Furthermore, we will examine the effect of these behaviors on change in weight and metabolic risk factors (e.g., fasting glucose, waist circumference, systolic and diastolic blood pressure, triglycerides, and LDL and HDL cholesterol) over 25 years. We specifically examine how these relationships differ by individual-level race/ethnicity, income, and education. The proposed study builds on work we have done to create a CARDIA neighborhood-level dataset consisting of price and economic data for Exam Years 1-20 and a food environment dataset for years 1-15 (we currently do not have food environment data for year 20).
Specific aims i nclude: 1) Add identical food environment data for Year 20 (2005-06) when we will have the third wave of individual-level dietary data;2) Create and implement a full structural equations model with a specific focus on comparisons within race-ethnicity (black versus white), income (high versus low), education (high versus low) to jointly examine the temporal impact of economic and food environment factors on: (a) individual-level beverage intake and overall diet quality, (b) patterns of weight maintenance and gain, and (c) the incidence, persistence, and reversal on the above metabolic risk factors (controlling for residential choice, pregnancy and marriage status, physical activity and smoking). Using this full system we will be able to examine the full set of relationships between food prices and food environment factors with diet, weight and metabolic risk factors. Our overall impact is to identify economic and food environment factors that are associated with health and can be addressed as potential targets for intervention to reduce disparities in obesity and metabolic risk.
We will use longitudinal data to examine the full set of relationships between food prices and food environment factors with diet, weight and metabolic risk factors. Our overall impact is to identify economic and food environment factors that are associated with health and can be addressed as potential targets for intervention to reduce disparities in obesity and metabolic risk.
|Rummo, Pasquale E; Albrecht, Sandra S; Gordon-Larsen, Penny (2015) Field validation of food outlet databases: the Latino food environment in North Carolina, USA. Public Health Nutr 18:977-82|
|Richardson, Andrea S; Meyer, Katie A; Howard, Annie Green et al. (2014) Neighborhood socioeconomic status and food environment: a 20-year longitudinal latent class analysis among CARDIA participants. Health Place 30:145-53|
|Ng, Shu Wen; Slining, Meghan M; Popkin, Barry M (2014) Turning point for US diets? Recessionary effects or behavioral shifts in foods purchased and consumed. Am J Clin Nutr 99:609-16|
|Poti, Jennifer M; Slining, Meghan M; Popkin, Barry M (2014) Where are kids getting their empty calories? Stores, schools, and fast-food restaurants each played an important role in empty calorie intake among US children during 2009-2010. J Acad Nutr Diet 114:908-17|
|Meyer, Katie A; Guilkey, David K; Ng, Shu Wen et al. (2014) Sociodemographic differences in fast food price sensitivity. JAMA Intern Med 174:434-42|
|Gordon-Larsen, Penny (2014) Food availability/convenience and obesity. Adv Nutr 5:809-17|
|Poti, Jennifer M; Duffey, Kiyah J; Popkin, Barry M (2014) The association of fast food consumption with poor dietary outcomes and obesity among children: is it the fast food or the remainder of the diet? Am J Clin Nutr 99:162-71|
|Ford, Christopher N; Slining, Meghan M; Popkin, Barry M (2013) Trends in dietary intake among US 2- to 6-year-old children, 1989-2008. J Acad Nutr Diet 113:35-42|
|Poti, Jennifer M; Slining, Meghan M; Popkin, Barry M (2013) Solid fat and added sugar intake among U.S. children: The role of stores, schools, and fast food, 1994-2010. Am J Prev Med 45:551-9|
|Slining, M M; Popkin, B M (2013) Trends in intakes and sources of solid fats and added sugars among U.S. children and adolescents: 1994-2010. Pediatr Obes 8:307-24|
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