Penny Gordon-Larsen

CONTEXT. Environmental factors are suggested to play a major role in physical activity (PA) and other obesity-related behaviors, yet there is no national research on the relationship between disparity in access to recreational facilities and additional impact on PA and overweight patterns in US adolescents. OBJECTIVE. In a nationally representative cohort, we sought to assess the geographic and social distribution of PA facilities and how disparity in access might underlie population-level PA and overweight patterns. DESIGN, SETTING, AND PARTICIPANTS. Residential locations of US adolescents in wave I (1994–1995) of the National Longitudinal Study of Adolescent Health (N = 20745) were geocoded, and a 8.05-km buffer around each residence was drawn (N = 42857 census-block groups [19% of US block groups]). PA facilities, measured by national databases and satellite data, were linked with Geographic Information Systems technology to each respondent. Logistic-regression analyses tested th...

2 Supported by the National Institutes of Health (R01-CA109831, R01-CA121152, and K01-HD044263). Additionally supported by NIH (R01-AA12162), the UNC-CH Center for Environmental Health and Susceptibility (NIH P30-ES10126), the UNC-CH Clinic Nutrition Research ...

Engagement in healthy lifestyle behaviors likely reflects access to a diverse and synergistic set of food and physical activity resources, yet most research examines discrete characteristics. We characterized neighborhoods with respect to their composition of features, and quantified associations with diet, physical activity (PA), body mass index (BMI), and insulin resistance (IR) in a longitudinal biracial cohort (n=4143; aged 25-37; 1992-2006). We used latent class analysis to derive population-density-specific (<vs.≥1750 people per sq km) clusters of neighborhood indicators: road connectivity, parks and PA facilities, and food stores/restaurants. In lower population density areas, a latent class with higher food and PA resource diversity (relative to other clusters) was significantly associated with higher diet quality. In higher population density areas, a cluster with relatively more natural food/specialty stores; fewer convenience stores; and more PA resources was associate...

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.

We examine the associations between overall urbanicity and specific physical and social components of community-level urbanization with C-reactive protein (CRP) in adults participating in the China Health and Nutrition Study. Higher overall urbanicity and environment-related urbanicity component scores, including education, housing quality, and access to markets, were associated with elevated CRP in multilevel models controlling for clustering by community. These associations differed by age and gender and persisted after controlling for individual-level anthropometric, diet, and pathogenic risk factors. These results highlight the importance of place in relation to inflammation across the spectrum of rural and urban environments.

Interest in urban neighborhood form is strong among scholars trained in multiple disciplines. The increasing popularity of this field calls for a set of metrics that can be used to describe meaningful patterns of built features in neighborhood environments. This study employs national-level datasets from Add Health, the National Land Cover Dataset (NLCD) 2001, the U.S. Census TIGER, and the U.S. Geological Survey to construct neighborhood form metrics for 20,467 residents, whose residential environments cover a wide array of geographic areas representative of comprehensive neighborhood types across the United States. Buffers of different sizes (1 km, 3 km, 5 km, and 8 km, respectively) are drawn around each resident's location as the unit of analysis. For the four sets of 20,467 neighborhood environments, 27 neighborhood form metrics are selected, computed, and further reduced through factor analysis. The results suggest that the derived subsets of univariate metrics can be applied across neighborhood types to characterize diverse neighborhood environments.

With the emergence of obesity as a global health issue an increasing number of major demographic surveys are collecting measured anthropometric data. Yet little is known about the characteristics and reliability of these data. We evaluate the accuracy and reliability of anthropometric data collected in the home during Wave IV of the National Longitudinal Study of Adolescent to Adult Health (Add Health), compare our estimates to national standard, clinic-based estimates from the National Health and Nutrition Examination Survey (NHANES) and, using both sources, provide a detailed anthropometric description of young adults in the United States. The reliability of Add Health in-home anthropometric measures was estimated from repeat examinations of a random subsample of study participants. A digit preference analysis evaluated the quality of anthropometric data recorded by field interviewers. The adjusted odds of obesity and central obesity in Add Health vs. NHANES were estimated with logistic regression. Short-term reliabilities of in-home measures of height, weight, waist and arm circumference-as well as derived body mass index (BMI, kg/m(2))-were excellent. Prevalence of obesity (37% vs. 29%) and central obesity (47% vs. 38%) was higher in Add Health than in NHANES while socio-demographic patterns of obesity and central obesity were comparable in the two studies. Properly trained non-medical field interviewers can collect reliable anthropometric data in a nationwide, home visit study. This national cohort of young adults in the United States faces a high risk of early-onset chronic disease and premature mortality.

The purpose of this study was to examine the association of intergenerational education and country of birth with waist circumference, metabolic syndrome, and type 2 diabetes among older adult Latinos in the United States. We used cross-sectional data from the Sacramento Area Latino Study on Aging, a cohort of older adult Mexican-American Latinos (mean age = 70 years). At baseline, we measured waist circumference and assessed metabolic syndrome and diabetes according to established guidelines (N = 1,789). Participants were classified as US-born or foreign-born based on self-reported birth country. Participants reported their parents' education level (≥6 years vs. <6) and their own educational attainment (≥12 years vs. <12). US-born participants who achieved high adult education, regardless of their parents' education, had 37% lower odds of type 2 diabetes compared to US-born participants with both low parental and personal education levels [e.g., multivariable-adjusted OR (parental low/adult high) = 0.63; 95%CI = 0.40, 0.99]. Among the foreign-born, only those with both high parental and high personal education levels had 55% lower odds of large waist circumference (OR = 0.45; 95% CI = 0.23, 0.88) compared to foreign-born participants with both low parental and personal education levels. Intergenerational exposure to low education levels may increase central obesity and type 2 diabetes differentially among US-born and foreign-born Latinos.

Away-from-home food consumption has rapidly increased, though little is known about the independent associations of restaurant food and fast food intake with body mass index (BMI) and BMI change. The aim was to compare the associations of restaurant food and fast food consumption with current and 3-y changes in BMI. Multivariate linear regression models, with control for demographic and lifestyle factors, were used to examine cross-sectional and longitudinal associations of away-from-home eating with BMI by using data from subjects of the Coronary Artery Risk Development in Young Adults Study (n = 3394) obtained at exam years 7 (1992-1993) and 10 (1995-1996). Forty percent of the sample increased their weekly consumption of restaurant or fast food, though mean (+/-SD) changes were -0.16 +/- 2.39 times/wk (P = 0.0001) and -0.56 +/- 3.04 times/wk (P < 0.0001), respectively. Cross-sectionally, fast food, but not restaurant food, consumption was positively associated with BMI. Simila...

In this paper, the environment is defined as the macro- and community-level factors, including physical, legal and policy factors, that influence household and individual decisions. Thus, environment is conceived as the external context in which household and individual decisions are made. This paper reviews the literature on the ways the environment affects diet, physical activity, and obesity. Other key environmental factors discussed include economic, legal, and policy factors. Behind the major changes in diet and physical activity in the US and globally lie large shifts in food production, processing, and distribution systems as well as food shopping and eating options, resulting in the increase in availability of energy-dense foods. Similarly, the ways we move at home, work, leisure, and travel have shifted markedly, resulting in substantial reductions in energy expenditure. Many small area studies have linked environmental shifts with diet and activity changes. This paper begi...

This paper explores the major changes in diet and physical activity patterns around the world and focuses on shifts in obesity. Review of results focusing on large-scale surveys and nationally representative studies of diet, activity, and obesity among adults and children. Youth and adults from a range of countries around the world. The International Obesity Task Force guidelines for defining overweight and obesity are used for youth and the body mass index > or =25 kg/m(2) and 30 cutoffs are used, respectively, for adults. The nutrition transition patterns are examined from the time period termed the receding famine pattern to one dominated by nutrition-related noncommunicable diseases (NR-NCDs). The speed of dietary and activity pattern shifts is great, particularly in the developing world, resulting in major shifts in obesity on a worldwide basis. Data limitations force us to examine data on obesity trends in adults to provide a broader sense of changes in obesity over time, a...

No nationally representative longitudinal data have been analyzed to evaluate the incidence of obesity in the transition between adolescence and adulthood. The objective was to examine dynamic patterns of change in obesity among white, black, Hispanic, and Asian US teens as they transitioned to young adulthood. We used nationally representative, longitudinally measured height and weight data collected from US adolescents enrolled in wave II (1996; ages 13-20 y) and wave III (2001; 19-26 y) of the National Longitudinal Study of Adolescent Health (n = 9795). Obesity incidence was defined on the basis of International Obesity Task Force (IOTF) cutoffs (wave II), which link childhood body mass index (BMI) centiles to adult cutoffs (BMI > or = 30; wave III), for comparability between adolescence and adulthood. In addition, the more commonly used cutoff of BMI > or = 95th percentile for age- and sex-specific cutoffs from the 2000 Centers for Disease Control and Prevention growth cha...

Engagement in healthy lifestyle behaviors likely reflects access to a diverse and synergistic set of food and physical activity resources, yet most research examines discrete characteristics. We characterized neighborhoods with respect to their composition of features, and quantified associations with diet, physical activity (PA), body mass index (BMI), and insulin resistance (IR) in a longitudinal biracial cohort (n=4143; aged 25-37; 1992-2006). We used latent class analysis to derive population-density-specific (<vs.≥1750 people per sq km) clusters of neighborhood indicators: road connectivity, parks and PA facilities, and food stores/restaurants. In lower population density areas, a latent class with higher food and PA resource diversity (relative to other clusters) was significantly associated with higher diet quality. In higher population density areas, a cluster with relatively more natural food/specialty stores; fewer convenience stores; and more PA resources was associate...

Over the past three decades, obesity-related diseases have increased tremendously in China, and are now the leading causes of morbidity and mortality. Patterns of weight change can be used to predict risk of obesity-related diseases, increase understanding of etiology of disease risk, identify groups at particularly high risk, and shape prevention strategies. Latent class trajectory modeling was used to compute weight change trajectories for adults aged 18 to 66 using the China Health and Nutrition Survey (CHNS) data (n = 12,611). Weight change trajectories were computed separately for males and females by age group at baseline due to differential age-related patterns of weight gain in China with urbanization. Generalized linear mixed effects models examined the association between weight change trajectories and baseline characteristics including urbanicity, BMI category, age, and year of study entry. Trajectory classes were identified for each of six age-sex subgroups corresponding to various degrees of weight loss, maintenance and weight gain. Baseline BMI status was a significant predictor of trajectory membership for all age-sex subgroups. Baseline overweight/obesity increased odds of following 'initial loss with maintenance' trajectories. We found no significant association between baseline urbanization and trajectory membership after controlling for other covariates. Trajectory analysis identified patterns of weight change for age by gender groups. Lack of association between baseline urbanization status and trajectory membership suggests that living in a rural environment at baseline was not protective. Analyses identified age-specific nuances in weight change patterns, pointing to the importance of subgroup analyses in future research.

To assess the relationship between dieting and subsequent weight change and whether the association varies by gender or race/ethnicity. Male (n = 4100) and female (n = 4302) participants in the National Longitudinal Study of Adolescent Health who provided information on weight and height at baseline and two follow-up assessments and were not missing information on weight control strategies or race were studied. Generalized estimating equations were used to assess whether dieting to lose or maintain weight at Wave I or II predicted BMI (kg/m(2)) change between adolescence and young adulthood (Wave II to III). Analyses were stratified by gender and took sampling weights and clustering into account. At Wave I, the mean age of the participants was 14.9 years. Approximately 29.3% of female participants and 9.8% of male participants reported dieting in Wave I or II. Fewer African Americans than whites (6.2% vs. 10.0% and 25.5% vs. 31.2%, p = 0.007 and p = 0.02, among males and females, respectively) reported dieting. Between Waves II and III, participants gained on average 3.3 kg/m(2). Independent of BMI gain during adolescence (Waves I to II), female participants who dieted to lose or maintain weight during adolescence made larger gains in BMI during the 5 years between Waves II and III (mean additional gain, 0.39 kg/m(2); 95% confidence interval, 0.08 to 0.71) than their nondieting peers. The association was not significant among the male participants. The association was largest among African-American female participants. The results suggest that not only is dieting to lose weight ineffective, it is actually associated with greater weight gain, particularly among female adolescents. Female African-American dieters made the largest BMI gains.

Results: Six robust neighborhood patterns were identified: (1) rural working class; (2) exurban; (3) newer suburban; (4) upper-middle class, older suburban; (5) mixed-race urban; and (6) low-socioeconomic-status (SES) inner-city areas. Compared to adolescents living in newer suburbs, those in rural working-class (adjusted RR(ARR)1.38, 95% confidence interval (CI)1.13-1.69), exurban (ARR1.30, CI1.04-1.64), and mixed-race urban (ARR1.31, CI1.05-1.64) neighborhoods were more likely to be overweight, independent of individual SES, age, and race/ethnicity. Adolescents living in older suburban areas were more likely to be physically active than residents of newer suburbs (ARR1.11, CI1.04-1.18). Those living in low-SES inner-city neighborhoods were more likely to be active, though not significantly so, compared to mixed-race urban residents (ARR1.09, CI1.00-1.18). Conclusions: These findings demonstrate disadvantageous associations between specific rural and urban environments and behavior...