Improving Environmental Measures In Obesity Research Using Innovative Technology
In this study, we seek to test the use of an innovative technology (GigaPan) for measuring the built environment. GigaPan is a robot system that automates obtaining numerous photos of an area using a basic camera housed within its apparatus. The resulting photos are then stitched together to form a single high-resolution photo that is highly navigable. Using GigaPan, we document and characterize features of the built environment on street segments and park/playgrounds. These measures will be compared to measures obtained via direct observation and web-based audits using Google Street View. GigaPan technology may be able to embody the benefits of direct observation while significantly reducing the time and cost burden. In addition, GigaPan may be more valid than measures obtained from Google Street View and better suited for studies of built environment change as GigaPan data are time sensitive. The study will capitalize on individual-level data from a population-based cohort of adults living in low-income minority communities that are experiencing significant built environment changes. We believe that this study will demonstrate GigaPan's promise as a relevant tool for future multi-regional and longitudinal studies examining the effect of built environment changes on health behavior and will serve as an important intermediate step in automating the process of coding built environment characteristics.
Built Environments on Stroke Risk and Stroke Disparities In A National Sample
Built and social environments (BSEs) are important factors that will further our understanding of the distribution of cardiovascular disease in the population. However, to date no studies have examined the effect of BSEs on stroke risk, or the large racial and geographic disparities in stroke rates. This study addresses these gaps by utilizing a unique assembled cohort, the Reasons for Geographic and Racial Differences in Stroke (REGARDS) cohort. The REGARDS cohort is a national sample of adults over age 45, with oversamples of African-American participants and persons in the stroke belt. This study expands on the REGARDS study by obtaining data on a broad range of characteristics of the REGARDS participants’ built environment (e.g., food availability, land use, and neighborhood physical environment) and participants' social environment (objective crime, neighborhood SES, and social cohesion). This research provides a cost-effective way to examine the importance of BSEs for stroke prevention across diverse community settings and racial groups, and will help inform future modifications of environments to improve population health.
Impact of Public Housing Assistance on Modifiable Cancer Risk
Despite improvements in cancer mortality in the past two decades, significant disparities persist among racial, ethnic, and socioeconomic status (SES) subpopulations. Housing has been identified as an important social determinant for health disparities in general and cancer-related disparities specifically. Public housing (PH) assistance aims to improve housing affordability and quality for the lowest-SES households. Thus, PH represents an intervention to improve housing as a social determinant of health. This study uses data collected from 1999-2013 in the Panel Study of Income Dynamics (PSID) to estimate the effect of living in PH on four leading modifiable risk factors for cancer (smoking, alcohol use, physical inactivity, and overweight/obesity) in adults <62 years of age. The PSID offers a unique opportunity to examine the effects of PH because it is a nationally representative, longitudinal survey with a wide range of demographic, household, housing, economic, employment, social, and health variables. Study results will be used to help clarify whether living in PH improves or worsens modifiable risk factors for cancer. Importantly, information obtained about pathways through which these effects occur can inform future housing and public health research, practice, and policy.
Environments and Activity: GPS-Based Collection of Real-Time Perception and Behavioral Data to Support Modeling.
Obesity levels have increased dramatically over the past three decades. The increased prevalence of obesity is likely due, in part, to changes in the built environment. Changes in the built environment have contributed to inadequate physical activity levels and poor diet. This study aims to examine the role of the built and social environment on physical activity behavior using novel data and methodology. In particular, this study will refine and test methodology to capture survey data on mobile phones where surveys are triggered based on a sensor (e.g., GPS, accelerometer data). Surveys will be automatically triggered under two conditions 1) when a respondent enters an area of interest, such as a park and 2) when the participant changes locations (data akin to a travel diary). The surveys will be designed to provide data that will be useful for agent-based models of walking behavior in both children and adults.