scholarly journals Google Street View Derived Built Environment Indicators and Associations with State-Level Obesity, Physical Activity, and Chronic Disease Mortality in the United States

2020 ◽  
Vol 17 (10) ◽  
pp. 3659
Author(s):  
Lynn Phan ◽  
Weijun Yu ◽  
Jessica M. Keralis ◽  
Krishay Mukhija ◽  
Pallavi Dwivedi ◽  
...  
Keyword(s):  
Physical Activity ◽  
Built Environment ◽  
Health Outcomes ◽  
State Level ◽  
Premature Mortality ◽  
The United States ◽  
Single Family ◽  
Google Street View ◽  
Street View ◽  
Neighborhood Built Environment

Previous studies have demonstrated that there is a high possibility that the presence of certain built environment characteristics can influence health outcomes, especially those related to obesity and physical activity. We examined the associations between select neighborhood built environment indicators (crosswalks, non-single family home buildings, single-lane roads, and visible wires), and health outcomes, including obesity, diabetes, cardiovascular disease, and premature mortality, at the state level. We utilized 31,247,167 images collected from Google Street View to create indicators for neighborhood built environment characteristics using deep learning techniques. Adjusted linear regression models were used to estimate the associations between aggregated built environment indicators and state-level health outcomes. Our results indicated that the presence of a crosswalk was associated with reductions in obesity and premature mortality. Visible wires were associated with increased obesity, decreased physical activity, and increases in premature mortality, diabetes mortality, and cardiovascular mortality (however, these results were not significant). Non-single family homes were associated with decreased diabetes and premature mortality, as well as increased physical activity and park and recreational access. Single-lane roads were associated with increased obesity and decreased park access. The findings of our study demonstrated that built environment features may be associated with a variety of adverse health outcomes.

scholarly journals Using 164 Million Google Street View Images to Derive Built Environment Predictors of COVID-19 Cases

2020 ◽  
Vol 17 (17) ◽  
pp. 6359 ◽  
Author(s):  
Quynh C. Nguyen ◽  
Yuru Huang ◽  
Abhinav Kumar ◽  
Haoshu Duan ◽  
Jessica M. Keralis ◽  
...  
Keyword(s):  
Computer Vision ◽  
Built Environment ◽  
Local Area ◽  
Physical Disorder ◽  
Single Family ◽  
Google Street View ◽  
Environment Effects ◽  
Street View ◽  
Sociodemographic Disparities ◽  
Family Home

The spread of COVID-19 is not evenly distributed. Neighborhood environments may structure risks and resources that produce COVID-19 disparities. Neighborhood built environments that allow greater flow of people into an area or impede social distancing practices may increase residents’ risk for contracting the virus. We leveraged Google Street View (GSV) images and computer vision to detect built environment features (presence of a crosswalk, non-single family home, single-lane roads, dilapidated building and visible wires). We utilized Poisson regression models to determine associations of built environment characteristics with COVID-19 cases. Indicators of mixed land use (non-single family home), walkability (sidewalks), and physical disorder (dilapidated buildings and visible wires) were connected with higher COVID-19 cases. Indicators of lower urban development (single lane roads and green streets) were connected with fewer COVID-19 cases. Percent black and percent with less than a high school education were associated with more COVID-19 cases. Our findings suggest that built environment characteristics can help characterize community-level COVID-19 risk. Sociodemographic disparities also highlight differential COVID-19 risk across groups of people. Computer vision and big data image sources make national studies of built environment effects on COVID-19 risk possible, to inform local area decision-making.

scholarly journals Using Google Street View to examine associations between built environment characteristics and U.S. health outcomes

2019 ◽  
Vol 14 ◽  
pp. 100859 ◽  
Author(s):  
Quynh C. Nguyen ◽  
Sahil Khanna ◽  
Pallavi Dwivedi ◽  
Dina Huang ◽  
Yuru Huang ◽  
...  
Keyword(s):  
Built Environment ◽  
Health Outcomes ◽  
Google Street View ◽  
Street View

Investigating associations between physical activity-related neighborhood built environment features and child weight status to inform local practice

2021 ◽  
Vol 270 ◽  
pp. 113694
Author(s):  
Jordan A. Carlson ◽  
Robin P. Shook ◽  
Ann M. Davis ◽  
Amy Papa ◽  
Chelsea Steel ◽  
...  
Keyword(s):  
Physical Activity ◽  
Built Environment ◽  
Weight Status ◽  
Local Practice ◽  
Child Weight ◽  
Neighborhood Built Environment

Associations of the Neighborhood Built Environment With Physical Activity Across Pregnancy

2021 ◽  
pp. 1-7
Author(s):  
Kiarri N. Kershaw ◽  
Derek J. Marsh ◽  
Emma G. Crenshaw ◽  
Rebecca B. McNeil ◽  
Victoria L. Pemberton ◽  
...  
Keyword(s):  
Physical Activity ◽  
Built Environment ◽  
Confidence Interval ◽  
Leisure Time ◽  
Leisure Time Physical Activity ◽  
Cross Sectional ◽  
Relative Risks ◽  
Recreation Areas ◽  
General Populations ◽  
Neighborhood Built Environment

Background: Several features of the neighborhood built environment have been shown to promote leisure-time physical activity (PA) in the general population, but few studies have examined its impact on PA during pregnancy. Methods: Data were extracted from 8362 Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be cohort participants (2010–2013). Residential address information was linked to 3 built environment characteristics: number of gyms and recreation areas within a 3-km radius of residence and census block level walkability. Self-reported leisure-time PA was measured in each trimester and dichotomized as meeting PA guidelines or not. Relative risks for cross-sectional associations between neighborhood characteristics and meeting PA guidelines were estimated using Poisson regression. Results: More gyms and recreation areas were each associated with a greater chance of meeting PA guidelines in models adjusted for sociodemographic characteristics and preexisting conditions. Associations were strongest in the third trimester where each doubling in counts of gyms and recreation areas was associated with 10% (95% confidence interval, 1.07–1.13) and 8% (95% confidence interval, 1.03–1.12), respectively, greater likelihood of meeting PA guidelines. Associations were similar though weaker for walkability. Conclusions: Results from a large, multisite cohort suggest that these built environment characteristics have similar PA-promoting benefits in pregnant women as seen in more general populations.

The Built Environment, Physical Activity, and Aging in the United States: A State of the Science Review

2015 ◽  
Vol 23 (2) ◽  
pp. 323-329 ◽  
Author(s):  
Elizabeth M. Haselwandter ◽  
Michael P. Corcoran ◽  
Sara C. Folta ◽  
Raymond Hyatt ◽  
Mark Fenton ◽  
...  
Keyword(s):  
Physical Activity ◽  
United States ◽  
Built Environment ◽  
The United States ◽  
Science Review ◽  
State Of The Science

scholarly journals Neighborhood built environment impacts park use of diverse, low-income mothers and their children

2021 ◽  
Vol 1 (3) ◽  
pp. 98-110
Author(s):  
Lauren Mullenbach ◽  
Lincoln Larson ◽  
Myron Floyd ◽  
Oriol Marquet ◽  
Jing-Huei Huang ◽  
...  
Keyword(s):  
Built Environment ◽  
Low Income ◽  
The United States ◽  
Racially Diverse ◽  
Perceived Safety ◽  
Neighborhood Walkability ◽  
Park Use ◽  
Physical Health Outcomes ◽  
Low Income Mothers ◽  
Neighborhood Built Environment

Built environment features, including parks, often exacerbate health disparities. We examined built environment perceptions and park use among a population at high risk for physical health outcomes: racially diverse, low-income mothers across the United States. Perceived safety from crime and living near a park were associated with more frequent park use for mothers and their children, and neighborhood walkability was linked to longer park visits. However, only 40% of mothers lived within a ten-minute walk from a park, and perceptions of walkability and safety from crime were low. To enhance physical activity and health of low-income mothers and their children, investments are needed to close disparities in park access and improve neighborhood safety.

Spatial Analyses of Obesity and Poverty

2012 ◽  
Author(s):  
Adam Drewnowski
Keyword(s):  
Health Outcomes ◽  
State Level ◽  
The United States ◽  
Healthy Foods ◽  
Distribution Of Wealth ◽  
Dietary Behaviours ◽  
Political District ◽  
The Impact ◽  
System Methodology ◽  
Zip Code

Obesity in the United States is a socio-economic issue. Recent advances in geographic information system methodology can provide a better understanding of the impact of neighbourhood deprivation on access to healthy foods, diet quality and selected health outcomes. Whereas state-level Centers for Disease Control maps are still best known, newer approaches have mapped obesity at different levels of geographic aggregation: county, political district, zip code or census tract. This chapter examines data from the new Seattle Obesity Study, which permits the mapping of dietary behaviours and health outcomes at the property parcel tax level – the finest level of geographic resolution possible. Analysis suggests that food-consumption patterns also show a spatial distribution, broadly following the geographic distribution of wealth and social class.

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