Tammy Leonard

Neighborhood-level socioeconomic deprivation predicts weight gain in a multi-ethnic population: Longitudinal data from the Dallas Heart Study

OBJECTIVE The aim of this study is to examine a relationship between neighborhood-level socioeconomic deprivation and weight change in a multi-ethnic cohort from Dallas County, Texas and whether behavioral/psychosocial factors attenuate the relationship. METHODS Non-movers (those in the same neighborhood throughout the study period) aged 18-65 (N=939) in Dallas Heart Study (DHS) underwent weight measurements between 2000 and 2009 (median 7-year follow-up). Geocoded home addresses defined block groups; a neighborhood deprivation index (NDI) was created (higher NDI=greater deprivation). Multi-level modeling determined weight change relative to NDI. Model fit improvement was examined with adding physical activity and neighborhood environment perceptions (higher score=more unfavorable perceptions) as covariates. A significant interaction between residence length and NDI was found (p-interaction=0.04); results were stratified by median residence length (11 years). RESULTS Adjusting for age, sex, race/ethnicity, smoking, and education/income, those who lived in neighborhood >11 years gained 1.0 kg per one-unit increment of NDI (p=0.03), or 6 kg for those in highest NDI tertile compared with those in the lowest tertile. Physical activity improved model fit; NDI remained associated with weight gain after adjustment for physical activity and neighborhood environment perceptions. There was no significant relationship between NDI and weight change for those in their neighborhood ≤11 years. CONCLUSIONS Living in more socioeconomically deprived neighborhoods over a longer time period was associated with weight gain in DHS.

Change in Neighborhood Socioeconomic Status and Weight Gain: Dallas Heart Study

INTRODUCTION Despite a proposed connection between neighborhood environment and obesity, few longitudinal studies have examined the relationship between change in neighborhood socioeconomic deprivation, as defined by moving between neighborhoods, and change in body weight. The purpose of this study is to examine the longitudinal relationship between moving to more socioeconomically deprived neighborhoods and weight gain as a cardiovascular risk factor. METHODS Weight (kilograms) was measured in the Dallas Heart Study (DHS), a multiethnic cohort aged 18-65 years, at baseline (2000-2002) and 7-year follow-up (2007-2009, N=1,835). Data were analyzed in 2013-2014. Geocoded addresses were linked to Dallas County, TX, census block groups. A block group-level neighborhood deprivation index (NDI) was created. Multilevel difference-in-difference models with random effects and a Heckman correction factor (HCF) determined weight change relative to NDI change. RESULTS Forty-nine percent of the DHS population moved (263 to higher NDI, 586 to lower NDI, 47 within same NDI), with blacks more likely to move than whites or Hispanics (p<0.01), but similar baseline BMI and waist circumference were observed in movers versus non-movers (p>0.05). Adjusting for HCF, sex, race, and time-varying covariates, those who moved to areas of higher NDI gained more weight compared to those remaining in the same or moving to a lower NDI (0.64 kg per 1-unit NDI increase, 95% CI=0.09, 1.19). Impact of NDI change on weight gain increased with time (p=0.03). CONCLUSIONS Moving to more-socioeconomically deprived neighborhoods was associated with weight gain among DHS participants.

Systematic neighborhood observations at high spatial resolution: Methodology and assessment of potential benefits

There is a growing body of public health research documenting how characteristics of neighborhoods are associated with differences in the health status of residents. However, little is known about how the spatial resolution of neighborhood observational data or community audits affects the identification of neighborhood differences in health. We developed a systematic neighborhood observation instrument for collecting data at very high spatial resolution (we observe each parcel independently) and used it to collect data in a low-income minority neighborhood in Dallas, TX. In addition, we collected data on the health status of individuals residing in this neighborhood. We then assessed the inter-rater reliability of the instrument and compared the costs and benefits of using data at this high spatial resolution. Our instrument provides a reliable and cost-effect method for collecting neighborhood observational data at high spatial resolution, which then allows researchers to explore the impact of varying geographic aggregations. Furthermore, these data facilitate a demonstration of the predictive accuracy of self-reported health status. We find that ordered logit models of health status using observational data at different spatial resolution produce different results. This implies a need to analyze the variation in correlative relationships at different geographic resolutions when there is no solid theoretical rational for choosing a particular resolution. We argue that neighborhood data at high spatial resolution greatly facilitates the evaluation of alternative geographic specifications in studies of neighborhood and health.

Impediments and Facilitators to Physical Activity and Perceptions of Sedentary Behavior Among Urban Community Residents: The Fair Park Study

Introduction Insufficient physical activity is an established risk factor for numerous chronic diseases and for premature death. Accumulating evidence reveals that prolonged sedentary time is detrimental, independent of the protective effects of physical activity. Although studies have explored correlates of physical activity among ethnic minority populations, few have examined factors related to sedentary behavior. Therefore, we conducted a preliminary investigation into urban adults’ perceptions of sedentary behavior alongside perceived barriers and enablers to physical activity. Methods In-depth semi-structured interviews were used to evaluate perceptions of physical activity and sedentary behavior in a sample of low-income, ethnic minority adults. The framework approach guided researchers in analyzing the qualitative data. Results Participants were well aware of the positive health benefits of physical activity. However, most admitted not regularly engaging in physical activity and cited numerous barriers to activity, such as lack of time, insufficient finances, and neighborhood crime. Enablers included weight loss, the presence of social support, and the availability of safe parks conducive to exercise. In comparison, participants were primarily unfamiliar with the term “sedentary behavior” and did not perceive a relationship between sedentary behavior and health outcomes. Conclusion Our findings illustrate the need to increase the awareness of negative health implications of prolonged sedentary time while continuing to address the multiple impediments to physical activity as a way to combat chronic disease.

Health behavior and behavioral economics: economic preferences and physical activity stages of change in a low-income African-American community.

Purpose. To examine the relationship between physical activity stages of change and preferences for financial risk and time. Design. A cross-sectional, community-based study. Setting. A low-income, urban, African-American neighborhood. Subjects. One hundred sixty-nine adults. Measures. Self-reported physical activity stages of change—precontemplation to maintenance, objectively measured body mass index and waist circumference, and economic preferences for time and risk measured via incentivized economic experiments. Analysis. Multivariable ordered logistic regression models were used to examine the association between physical activity stages of change and economic preferences while controlling for demographic characteristics of the individuals. Results. Individuals who are more tolerant of financial risks (odds ratio [OR] = 1.31, p < .05) and whose time preferences indicate more patience (OR = 1.68, p < .01) are more likely to be in a more advanced physical activity stage (e.g., from preparation to action). The likelihood of being in the maintenance stage increases by 5.6 and 10.9 percentage points for each one-unit increase in financial risk tolerance or one-unit increase in the time preference measure, respectively. Conclusion. Greater tolerance of financial risk and more patient time preferences among this low-income ethnic minority population are associated with a more advanced physical activity stage. Further exploration is clearly warranted in larger and more representative samples.

TV viewing and BMI by race/ethnicity and socio-economic status.

Objective To assess the association between TV viewing and obesity by race/ethnicity and socio-economic status. Design Cross-sectional analysis of 5,087 respondents to the Health Information National Trends Survey (HINTS), a nationally representative sample of US adults. Multivariate regression models were computed to assess the association between quartiles of TV viewing and BMI, stratified by race/ethnicity, educational attainment, employment and health insurance status. Results Findings indicate that increased TV viewing was associated with higher odds for being overweight/obese in the entire sample, while adjusting for physical activity and other confounders. After stratification by race/ethnicity, increased odds for overweight/obesity in the 3rd and 4th quartiles of TV viewing (e.g., 3rd quartile- cumulative OR = 1.43, 95%CI 1.07–1.92) was observed in non-Hispanic whites, with statistical significance. In non-Hispanic blacks and Hispanics, the odds were similar to whites, but did not reach statistical significance. Significant relations between greater TV viewing and increased BMI were observed in college graduates and non-graduates, those with health insurance and the employed. Conclusions This study extends previous research by examining potential inconsistencies in this association between various racial/ethnic groups and some socio-economic variables, which primarily were not found.

Who is Food Insecure? Implications for Targeted Recruitment and Outreach, National health and Nutrition Examination Survey, 2005-2010

Introduction Food insecurity is negatively associated with health; however, health needs may differ among people participating in food assistance programs. Our objectives were to characterize differences in health among people receiving different types of food assistance and summarize strategies for targeted recruitment and outreach of various food insecure populations. Methods We examined health status, behaviors, and health care access associated with food insecurity and receipt of food assistance among US adults aged 20 years or older using data from participants (N = 16,934) of the National Health and Nutrition Examination Survey from 2005 through 2010. Results Food insecurity affected 19.3% of US adults (95% confidence interval, 17.9%–20.7%). People who were food insecure reported poorer health and less health care access than those who were food secure (P < .001 for all). Among those who were food insecure, 58.0% received no assistance, 20.3% received only Supplemental Nutrition Assistance Program (SNAP) benefits, 9.7% received only food bank assistance, and 12.0% received both SNAP and food bank assistance. We observed an inverse relationship between receipt of food assistance and health and health behaviors among the food insecure. Receipt of both (SNAP and food bank assistance) was associated with the poorest health; receiving no assistance was associated with the best health. For example, functional limitations were twice as prevalent among people receiving both types of food assistance than among those receiving none. Conclusion Receipt of food assistance is an overlooked factor associated with health and has the potential to shape future chronic disease prevention efforts among the food insecure.

Geospatial and Contextual Approaches to Energy Balance and Health.

In the past 15 years, a major research enterprise has emerged that is aimed at understanding associations between geographic and contextual features of the environment (especially the built environment) and elements of human energy balance, including diet, weight and physical activity. Here we highlight aspects of this research area with a particular focus on research and opportunities in the United States as an example. We address four main areas: (1) the importance of valid and comparable data concerning behaviour across geographies; (2) the ongoing need to identify and explore new environmental variables; (3) the challenge of identifying the causally relevant context; and (4) the pressing need for stronger study designs and analytical methods. Additionally, we discuss existing sources of geo-referenced health data which might be exploited by interdisciplinary research teams, personnel challenges and some aspects of funding for geospatial research by the US National Institutes of Health in the past decade, including funding for international collaboration and training opportunities.

Physicians, Clinics, and Neighborhoods: Multiple Levels of Influence on Colorectal Cancer Screening

Background: We (i) described variability in colorectal cancer (CRC) test use across multiple levels, including physician, clinic, and neighborhood; and (ii) compared the performance of novel cross-classified models versus traditional hierarchical models. Methods: We examined multilevel variation in CRC test use among patients not up-to-date with screening in a large, urban safety net health system (2011–2012). Outcomes included: (i) fecal occult blood test (FOBT) or (ii) colonoscopy and were ascertained using claims data during a 1-year follow-up. We compared Bayesian (i) cross-classified four-level logistic models nesting patients within separate, nonoverlapping “levels” (physicians, clinics, and census tracts) versus (ii) three hierarchical two-level models using deviance information criterion. Models were adjusted for covariates (patient sociodemographic factors, driving time to clinic, and census tract poverty rate). Results: Of 3,195 patients, 157 (4.9%) completed FOBT and 292 (9.1%) completed colonoscopy during the study year. Patients attended 19 clinics, saw 177 physicians, and resided in 332 census tracts. Significant variability was observed across all levels in both hierarchical and cross-classified models that was unexplained by measured covariates. For colonoscopy, variance was similar across all levels. For FOBT, physicians, followed by clinics, demonstrated the largest variability. Model fit using cross-classified models was superior or similar to 2-level hierarchical models. Conclusions: Significant and substantial variability was observed across neighborhood, physician, and clinic levels in CRC test use, suggesting the importance of factors at each of these levels on CRC testing. Impact: Future multilevel research and intervention should consider the simultaneous influences of multiple levels, including clinic, physician, and neighborhood. Cancer Epidemiol Biomarkers Prev; 23(7); 1346–55. ©2014 AACR.

Defining Neighborhood Boundaries in Studies of Spatial Dependence in Child Behavior Problems

BackgroundThe purpose of this study was to extend the analysis of neighborhood effects on child behavioral outcomes in two ways: (1) by examining the geographic extent of the relationship between child behavior and neighborhood physical conditions independent of standard administrative boundaries such as census tracts or block groups and (2) by examining the relationship and geographic extent of geographic peers’ behavior and individual child behavior.MethodsThe study neighborhood was a low income, ethnic minority neighborhood of approximately 20,000 residents in a large city in the southwestern United States. Observational data were collected for 11,552 parcels and 1,778 face blocks in the neighborhood over a five week period. Data on child behavior problems were collected from the parents of 261 school-age children (81% African American, 14% Latino) living in the neighborhood. Spatial analysis methods were used to examine the spatial dependence of child behavior problems in relation to physical conditions in the neighborhood for areas surrounding the child’s home ranging from a radius of 50 meters to a radius of 1000 meters. Likewise, the spatial dependence of child behavior problems in relation to the behavior problems of neighborhood peers was examined for areas ranging from a radius 255 meters to a radius of 600 meters around the child’s home. Finally, we examined the joint influence of neighborhood physical conditions and geographic peers.ResultsPoor conditions of the physical environment of the neighborhood were related to more behavioral problems, and the geographic extent of the physical environment that mattered was an area with a radius between 400 and 800 meters surrounding the child’s home. In addition, the average level of behavior problems of neighborhood peers within 255 meters of the child’s home was also positively associated with child behavior problems. Furthermore, these effects were independent of one another.ConclusionsThese findings demonstrate that using flexible geographies in the study of neighborhood effects can provide important insights into spatial influences on health outcomes. With regards to child behavioral outcomes, specifically, these findings support the importance of addressing the physical and social environment when planning community-level interventions to reduce child behavior problems.