Urban Form Lab Archives - Page 10 of 10

GPS-Based Exposure to Greenness and Walkability and Accelerometry-Based Physical Activity

James, Peter; Hart, Jaime E.; Hipp, J. Aaron; Mitchell, Jonathan A.; Kerr, Jacqueline; Hurvitz, Philip M.; Glanz, Karen; Laden, Francine. (2017). GPS-Based Exposure to Greenness and Walkability and Accelerometry-Based Physical Activity. Cancer Epidemiology Biomarkers & Prevention, 26(4), 525 – 532.

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Abstract

Background: Physical inactivity is a risk factor for cancer that may be influenced by environmental factors. Indeed, dense and well-connected built environments and environments with natural vegetation may create opportunities for higher routine physical activity. However, studies have focused primarily on residential environments to define exposure and self-reported methods to estimate physical activity. This study explores the momentary association between minute-level global positioning systems (GPS)-based greenness exposure and time-matched objectively measured physical activity. Methods: Adult women were recruited from sites across the United States. Participants wore a GPS device and accelerometer on the hip for 7 days to assess location and physical activity at minutelevel epochs. GPS records were linked to 250mresolution satellitebased vegetation data and Census Block Group-level U.S. Environmental Protection Agency (EPA) Smart Location Database walkability data. Minute-level generalized additive mixed models were conducted to test for associations between GPS measures and accelerometer count data, accounting for repeated measures within participant and allowing for deviations fromlinearity using splines. Results: Among 360 adult women (mean age of 55.3 +/- 10.2 years), we observed positive nonlinear relationships between physical activity and both greenness and walkability. In exploratory analyses, the relationships between environmental factors and physical activity were strongest among those who were white, had higher incomes, and who were middle-aged. Conclusions: Our results indicate that higher levels of physical activity occurred in areas with higher greenness and higher walkability. Impact: Findings suggest that planning and design policies should focus on these environments to optimize opportunities for physical activity. (C) 2017 AACR.

Keywords

Built Environments; Health Research; Breast-cancer; Obesity; Neighborhood; Validation; Validity; Walking; Risk; Energetics

Higher Residential and Employment Densities Are Associated with More Objectively Measured Walking in the Home Neighborhood

Huang, Ruizhu; Moudon, Anne, V; Zhou, Chuan; Saelens, Brian E. (2019). Higher Residential and Employment Densities Are Associated with More Objectively Measured Walking in the Home Neighborhood. Journal Of Transport & Health, 12, 142 – 151.

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Abstract

Introduction: Understanding where people walk and how the built environment influences walking is a priority in active living research. Most previous studies were limited by self-reported data on walking. In the present study, walking bouts were determined by integrating one week of accelerometry, GPS, and a travel log data among 675 adult participants in the baseline sample of the Travel Assessment and Community study at Seattle, Washington in the United State. Methods: Home neighborhood was defined as being within 0.5 mile of each participants' residence (a 10-min walk), with home neighborhood walking defined as walking bout lines with at least one GPS point within the home neighborhood. Home neighborhood walkability was constructed with seven built environment variables derived from spatially continuous objective values (SmartMaps). Collinearity among neighborhood environment variables was analyzed and variables that were strongly correlated with residential density were excluded in the regression analysis to avoid erroneous estimates. A Zero Inflated Negative Binomial (ZINB) served to estimate associations between home neighborhood environment characteristics and home neighborhood walking frequency. Results: The study found that more than half of participants' walking bouts occurred in their own home neighborhood. Higher residential density and job density were the two neighborhood walkability measures related to higher likelihood and more time walking in the home neighborhood, highest tertile residential density (22.4-62.6 unit/ha) (coefficient= 1.43; 95% CI 1.00-2.05) and highest tertile job density (12.4-272.3 jobs/acre) (coefficient= 1.62; 1.10-2.37). Conclusions: The large proportion of walking that takes place in the home neighborhood highlights the importance of continuing to examine the impact of the home neighborhood environment on walking. Potential interventions to increase walking behavior may benefit from increasing residential and employment density within residential areas.

Keywords

Body-mass Index; Built Environment; Physical-activity; Land Uses; Epidemiology; Selection; Location; Obesity; Travel Assessment And Community; Smartmaps; Neighborhood Environment; Physical Activity; Walking

Differential Associations of the Built Environment on Weight Gain by Sex and Race/Ethnicity but Not Age

Buszkiewicz, James H.; Bobb, Jennifer F.; Kapos, Flavia; Hurvitz, Philip M.; Arterburn, David; Moudon, Anne Vernez; Cook, Andrea; Mooney, Stephen J.; Cruz, Maricela; Gupta, Shilpi; Lozano, Paula; Rosenberg, Dori E.; Theis, Mary Kay; Anau, Jane; Drewnowski, Adam. (2021). Differential Associations of the Built Environment on Weight Gain by Sex and Race/Ethnicity but Not Age. International Journal Of Obesity, 45(12), 2648 – 2656.

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Abstract

Objective To explore the built environment (BE) and weight change relationship by age, sex, and racial/ethnic subgroups in adults. Methods Weight trajectories were estimated using electronic health records for 115,260 insured Kaiser Permanente Washington members age 18-64 years. Member home addresses were geocoded using ArcGIS. Population, residential, and road intersection densities and counts of area supermarkets and fast food restaurants were measured with SmartMaps (800 and 5000-meter buffers) and categorized into tertiles. Linear mixed-effect models tested whether associations between BE features and weight gain at 1, 3, and 5 years differed by age, sex, and race/ethnicity, adjusting for demographics, baseline weight, and residential property values. Results Denser urban form and greater availability of supermarkets and fast food restaurants were associated with differential weight change across sex and race/ethnicity. At 5 years, the mean difference in weight change comparing the 3rd versus 1st tertile of residential density was significantly different between males (-0.49 kg, 95% CI: -0.68, -0.30) and females (-0.17 kg, 95% CI: -0.33, -0.01) (P-value for interaction = 0.011). Across race/ethnicity, the mean difference in weight change at 5 years for residential density was significantly different among non-Hispanic (NH) Whites (-0.47 kg, 95% CI: -0.61, -0.32), NH Blacks (-0.86 kg, 95% CI: -1.37, -0.36), Hispanics (0.10 kg, 95% CI: -0.46, 0.65), and NH Asians (0.44 kg, 95% CI: 0.10, 0.78) (P-value for interaction <0.001). These findings were consistent for other BE measures. Conclusion The relationship between the built environment and weight change differs across demographic groups. Careful consideration of demographic differences in associations of BE and weight trajectories is warranted for investigating etiological mechanisms and guiding intervention development.

Keywords

Body-mass Index; Socioeconomic-status; Food Environment; Obesity; Health; Outcomes; Scale; Risk; Minority & Ethnic Groups; Urban Environments; Etiology; Demographics; Sex; Residential Density; Supermarkets; Age; Race; Ethnicity; Property Values; Body Weight Gain; Electronic Medical Records; Fast Food; Electronic Health Records; Real Estate; Subgroups; Demography; Trajectory Analysis; Weight

Urban Form Lab

The Urban Form Lab (UFL) research aims to affect policy and to support approaches to the design and planning of more livable environments. The UFL specializes in geospatial analyses of the built environment using multiple micro-scale data in Geographic Information Systems (GIS). Current research includes the development of novel GIS routines for performing spatial inventories and analyses of the built environment, and of spatially explicit sampling techniques. Projects address such topics as land monitoring, neighborhood and street design, active transportation, non-motorized transportation safety, physical activity, and access to food environments.

Research at the UFL has been supported by the U.S. and Washington State Departments of Transportation, the Centers for Disease Control and Prevention, the Robert Wood Johnson Foundation, the National Institutes of Health, and local agencies.

The Urban Form Lab is directed by Anne Vernez Moudon, Dr es Sc, a leading researcher and educator in quantifying the properties of the built environment as related to health and transportation behaviors. Philip M. Hurvitz, PhD, a veteran of geographic information science and data processing, leads data management and GIS work.

Urban@UW helps BE labs collaborate

The Urban@UW initiative brings together labs that study urban issues from across the University of Washington. Urban@UW works with scholars, policymakers, and community stakeholders in order to strengthen the connection between research and solutions to urban issues through cross-disciplinary and cross-sector collaborative research. Key functions of Urban@UW include amplifying public awareness of ongoing projects, connecting researchers with outside constituencies, providing staff and administrative support services, and providing pilot funding and fundraising assistance. Multiple BE labs are involved, including the Northwest…

New UW Data Collaborative connects BE researchers with restricted data

The University of Washington Data Collaborative (UWDC) is now offering services to researchers across campus, including BE researchers Gregg Colburn at the Runstad Department of Real Estate and the Urban Form Lab. Housed at the Center for Studies in Demography & Ecology, UWDC provides infrastructure to access restricted data in a secure and sophisticated computing environment. Data sets available to researchers cover health records, polling data, business and consumer data, and real estate data. Researchers interested in accessing these data…