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Race, Gender, and Obesity: How the Social Environment Constrains or Enables Physical Activity
Faculty associate Rashawn Ray investigates the social and environmental changes needed in order to remove neighborhood barriers to regular physical exercise
Located in Research / Selected Research
School of Public Health - Epidemiology Seminar Announcement: Michael Long
Leveraging Epidemiologic Data with Simulation Models to Inform Obesity Prevention Policy
Located in Coming Up
Article Reference Troff document (with manpage macros)Use of social media, search queries, and demographic data to assess obesity prevalence in the United States
Obesity is a global epidemic affecting millions. Implementation of interventions to curb obesity rates requires timely surveillance. In this study, we estimated sex-specific obesity prevalence using social media, search queries, demographics and built environment variables. We collected 3,817,125 and 1,382,284 geolocated tweets on food and exercise respectively, from Twitter’s streaming API from April 2015 to March 2016. We also obtained searches related to physical activity and diet from Google Search Trends for the same time period. Next, we inferred the gender of Twitter users using machine learning methods and applied mixed-effects state-level linear regression models to estimate obesity prevalence. We observed differences in discussions of physical activity and foods, with males reporting higher intensity physical activities and lower caloric foods across 40 and 48 states, respectively. In addition, counties with the highest percentage of exercise and food tweets had lower male and female obesity prevalence. Lastly, our models separately captured overall male and female spatial trends in obesity prevalence. The average correlation between actual and estimated obesity prevalence was 0.797(95% CI, 0.796, 0.798) and 0.830 (95% CI, 0.830, 0.831) for males and females, respectively. Social media can provide timely community-level data on health information seeking and changes in behaviors, sentiments and norms. Social media data can also be combined with other data types such as, demographics, built environment variables, diet and physical activity indicators from other digital sources (e.g., mobile applications and wearables) to monitor health behaviors at different geographic scales, and to supplement delayed estimates from traditional surveillance systems.
Located in MPRC People / Quynh Nguyen, Ph.D., M.S.P.H. / Quynh Nguyen Publications
Article Reference Troff document (with manpage macros)Income and Marital Status Interact on Obesity Among Black and White Men
Racial disparities in obesity among men are accompanied by positive associations between income and obesity among Black men only. Race also moderates the positive association between marital status and obesity. This study sought to determine how race, income, and marital status interact on obesity among men. Using data from the 2007 to 2014 National Health and Nutrition Examination Survey, obesity was measured as body mass index ≥30 kg/m 2  among 6,145 Black and White men. Income was measured by percentage of the federal poverty line and marital status was categorized as currently, formerly, or never married. Using logistic regression and interaction terms, the associations between income and obesity were assessed by race and marital status categories adjusted for covariates. Black compared to White (OR = 1.19, 95% CI [1.03, 1.38]), currently married compared to never married (OR = 1.45, 95% CI [1.24, 1.69]), and high-income men compared to low income men (OR = 1.26, 95% CI [1.06, 1.50]) had higher odds of obesity. A three-way interaction was significant and analyses identified that income was positively associated with obesity among currently married Black men and never married White men with the highest and lowest probabilities of obesity, respectively. High-income, currently married Black men had higher obesity rates and may be at increased risk for obesity-related morbidities.
Located in Retired Persons / Caryn Bell, Ph.D. / Caryn Bell Publications
Article ReferencePsychosocial Stress and Overweight and Obesity: Findings From the Chicago Community Adult Health Study
  Background Psychosocial stress has been implicated as a risk factor for overweight and obesity. However, research on psychosocial stressors and overweight and obesity has typically focused on single stressors in isolation, which may overestimate the impact of a specific stressor and fail to describe the role of cumulative stress on overweight and obesity risk. Purpose This study explores the association between overweight/obesity and cumulative exposure to a wide range of psychosocial stressors, among a multiracial/ethnic sample of adults. Methods Using secondary data from the Chicago Community Adult Health Study (n = 2,983), we conducted multinomial logistic regression analyses to quantify associations between eight psychosocial stressors, individually and in combination, and measured overweight and obesity, adjusted for sociodemographic factors, alcohol use and smoking. Results In separated covariate-adjusted models, childhood adversities (odds ratio [OR] = 1.16; confidence interval [CI] = [1.03, 1.30]), acute life events (OR = 1.18; CI = [1.04, 1.34]), financial strain (OR = 1.30; CI = [1.15, 1.47]), and relationship stressors (OR = 1.18; CI = [1.04, 1.35]) were associated with increased odds of obesity. In a model adjusted for all stressors simultaneously, financial strain was the only stressor independently associated with overweight (OR = 1.17; CI = [1.00, 1.36]) and obesity (OR = 1.21; CI = [1.05, 1.39]). Participants with stress exposure in the highest quintile across 2, 3, or ≥4 (compared to no) types of stressors had significantly higher odds of obesity. Conclusions Multiple types of stressors may be risk factors for obesity, and cumulative exposure to these stressors may increase the odds of obesity. Reducing exposure to stressors at the population level may have the potential to contribute to reducing the burden of obesity.  
Located in Retired Persons / Natalie Slopen, Sc.D. / Natalie Slopen Publications
Article ReferenceAssessing the Role of Health Behaviors, Socioeconomic Status, and Cumulative Stress for Racial/Ethnic Disparities in Obesity
Objective: This study aimed to examine the explanatory role of health behaviors, socioeconomic position (SEP), and psychosocial stressors on racial/ethnic obesity disparities in a multiethnic and multiracial sample of adults. Methods: Using data from the Chicago Community Adult Health Study (2001-2003), Oaxaca-Blinder decomposition analysis was conducted to quantify the extent to which health behaviors (fruit and vegetable consumption and physical activity), SEP, and cumulative stressors (e.g., perceived discrimination, financial strain) each explained differences in obesity prevalence in Black, US-born Hispanic, and non-US-born Hispanic compared with non-Hispanic White participants. Results: SEP and health behaviors did not explain obesity differences between racial/ethnic minorities and White individuals. Having high levels of stress in four or more domains explained 4.46% of the differences between Black and White individuals, whereas having high levels of stress in three domains significantly explained 14.13% of differences between US-born Hispanic and White. Together, the predictors explained less than 20% of differences between any racial/ethnic minority group and White individuals. Conclusions: Exposure to stressors may play a role in obesity disparities, particularly among Black and US-born Hispanic individuals. Other obesity-related risk factors need to be examined to understand the underlying mechanisms explaining obesity disparities.
Located in Retired Persons / Natalie Slopen, Sc.D. / Natalie Slopen Publications