Jiao, J.; Moudon, A. V.; Kim, S. Y.; Hurvitz, P. M.; Drewnowski, A. (2015). Health Implications of Adults’ Eating at and Living Near Fast Food or Quick Service Restaurants. Nutrition & Diabetes, 5.
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Abstract
BACKGROUND: This paper examined whether the reported health impacts of frequent eating at a fast food or quick service restaurant on health were related to having such a restaurant near home. METHODS: Logistic regressions estimated associations between frequent fast food or quick service restaurant use and health status, being overweight or obese, having a cardiovascular disease or diabetes, as binary health outcomes. In all, 2001 participants in the 2008-2009 Seattle Obesity Study survey were included in the analyses. RESULTS: Results showed eating >= 2 times a week at a fast food or quick service restaurant was associated with perceived poor health status, overweight and obese. However, living close to such restaurants was not related to negative health outcomes. CONCLUSIONS: Frequent eating at a fast food or quick service restaurant was associated with perceived poor health status and higher body mass index, but living close to such facilities was not.
Keywords
Body-mass Index; Socioeconomic-status; Built Environment; Obesity; Association; Consumption; Weight; Proximity; Outlets; Establishments
Drewnowski, A.; Arterburn, D.; Zane, J.; Aggarwal, A.; Gupta, S.; Hurvitz, P. M.; Moudon, A., V; Bobb, J.; Cook, A.; Lozano, P.; Rosenberg, D. (2019). The Moving to Health (M2H) Approach to Natural Experiment Research: A Paradigm Shift for Studies on Built Environment and Health. Ssm-population Health, 7.
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Abstract
Improving the built environment (BE) is viewed as one strategy to improve community diets and health. The present goal is to review the literature on the effects of BE on health, highlight its limitations, and explore the growing use of natural experiments in BE research, such as the advent of new supermarkets, revitalized parks, or new transportation systems. Based on recent studies on movers, a paradigm shift in built-environment health research may be imminent. Following the classic Moving to Opportunity study in the US, the present Moving to Health (M2H) strategy takes advantage of the fact that changing residential location can entail overnight changes in multiple BE variables. The necessary conditions for applying the M2H strategy to Geographic Information Systems (GIS) databases and to large longitudinal cohorts are outlined below. Also outlined are significant limitations of this approach, including the use of electronic medical records in lieu of survey data. The key research question is whether documented changes in BE exposure can be linked to changes in health outcomes in a causal manner. The use of geo-localized clinical information from regional health care systems should permit new insights into the social and environmental determinants of health.
Keywords
Body-mass Index; Neighborhood Food Environment; Residential Property-values; Cardiometabolic Risk-factors; New-york-city; Physical-activity; Obesity Rates; King County; Weight-gain; Land-use; Built Environment (be); Geographic Information Systems (gis); Electronic Medical Records; Natural Experiments; Obesity; Diabetes; Residential Mobility
Duncan, Glen E.; Hurvitz, Philip M.; Moudon, Anne Vernez; Avery, Ally R.; Tsang, Siny. (2021). Measurement of Neighborhood-Based Physical Activity Bouts. Health & Place, 70.
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Abstract
This study examined how buffer type (shape), size, and the allocation of activity bouts inside buffers that delineate the neighborhood spatially produce different estimates of neighborhood-based physical activity. A sample of 375 adults wore a global positioning system (GPS) data logger and accelerometer over 2 weeks under free-living conditions. Analytically, the amount of neighborhood physical activity measured objectively varies substantially, not only due to buffer shape and size, but by how GPS-based activity bouts are identified with respect to containment within neighborhood buffers. To move the neighborhood-effects literature forward, it is critical to delineate the spatial extent of the neighborhood, given how different ways of measuring GPS-based activity containment will result in different levels of physical activity across different buffer types and sizes.
Keywords
Built Environment; Walking; Home; Accelerometry; Geographic Information Systems; Gps; Neighborhood; Physical Activity
Bassok, Alon; Hurvitz, Phil M.; Bae, C-H. Christine; Larson, Timothy. (2010). Measuring Neighbourhood Air Pollution: The Case of Seattle’s International District. Journal Of Environmental Planning & Management, 53(1), 23 – 39.
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Abstract
Current US regulatory air quality monitoring networks measure ambient levels of pollutants and cannot capture the effects of mobile sources at the micro-scale. Despite the fact that overall air quality has been getting better, more vulnerable populations (children, the elderly, minorities and the poor) continue to suffer from traffic-related air pollution. As development intensifies in urban areas, more people are exposed to road-related air pollution. However, the only consideration given to air quality, if any, is based on ambient measures. This paper uses an inexpensive, portable Particle Soot Absorption Photometer (PSAP) to measure Black Carbon (BC) emissions, a surrogate for diesel fuels emissions, in Seattle's International District. With the aid of a GPS receiver, street-level BC data were geocoded in real space-time. It was found that pollution levels differed substantially across the study area. The results show the need for street-level air pollution monitoring, revisions in current land use and transportation policies, and air quality planning practice.
Keywords
Emission Standards; Air Pollution; Atmospheric Deposition; Social Groups; Waste Products; Sanitary Landfills; Black Carbon; Freeway Air Pollution Sheds (faps); Land Use; Mobile Monitoring; Neighbourhood Air Quality; Aerosol Light-absorption; Respiratory Health; Coefficient; Exposure; Symptoms; Children; Pollutants; Particles; Exhaust; Asthma
Kang, Bumjoon; Scully, Jason Y.; Stewart, Orion; Hurvitz, Philip M.; Moudon, Anne V. (2015). Split-Match-Aggregate (SMA) Algorithm: Integrating Sidewalk Data with Transportation Network Data in GIS. International Journal Of Geographical Information Science, 29(3), 440 – 453.
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Abstract
Sidewalk geodata are essential to understand walking behavior. However, such geodata are scarce, only available at the local jurisdiction and not at the regional level. If they exist, the data are stored in geometric representational formats without network characteristics such as sidewalk connectivity and completeness. This article presents the Split-Match-Aggregate (SMA) algorithm, which automatically conflates sidewalk information from secondary geometric sidewalk data to existing street network data. The algorithm uses three parameters to determine geometric relationships between sidewalk and street segments: the distance between streets and sidewalk segments; the angle between sidewalk and street segments; and the difference between the lengths of matched sidewalk and street segments. The SMA algorithm was applied in urban King County, WA, to 13 jurisdictions' secondary sidewalk geodata. Parameter values were determined based on agreement rates between results obtained from 72 pre-specified parameter combinations and those of a trained geographic information systems (GIS) analyst using a randomly selected 5% of the 79,928 street segments as a parameter-development sample. The algorithm performed best when the distances between sidewalk and street segments were 12m or less, their angles were 25 degrees or less, and the tolerance was set to 18m, showing an excellent agreement rate of 96.5%. The SMA algorithm was applied to classify sidewalks in the entire study area and it successfully updated sidewalk coverage information on the existing regional-level street network data. The algorithm can be applied for conflating attributes between associated, but geometrically misaligned line data sets in GIS.
Keywords
Geodatabases; Sidewalks; Algorithms; Pedestrians; Digital Mapping; Algorithm; Gis; Pedestrian Network Data; Polyline Conflation; Sidewalk; Built Environment; Physical-activity; Mode Choice; Urban Form; Land-use; Travel; Generation; Walking
Drewnowski, Adam; Aggarwal, Anju; Rose, Chelsea M.; Gupta, Shilpi; Delaney, Joseph A.; Hurvitz, Philip M. (2019). Activity Space Metrics Not Associated with Sociodemographic Variables, Diet or Health Outcomes in the Seattle Obesity Study II. Spatial And Spatio-temporal Epidemiology, 30.
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Abstract
Background: Activity spaces (AS), captured using GPS tracking devices, are measures of dynamic exposure to the built environment (BE). Methods: Seven days of Global Positioning Systems (GPS) tracking data were obtained for 433 adult participants in the Seattle Obesity Study (SOS II). Heights and weights were measured. Dietary intakes from a food frequency questionnaire were used to calculate Healthy Eating Index (HEI 2010) scores. Linear regression analyses examined associations between AS measures: daily route length, convex hull, and radius of gyration, and diet quality and health outcomes, adjusting for covariates. Results: AS measures did not vary by age, gender, race/ethnicity, or socioeconomic status. AS measures were not associated with diet quality or with self-reported obesity or diabetes. One AS measure, route length (in miles), was associated with being employed, living in the suburbs, and with distance and time commuting to work. Conclusion: Spatial mobility studies based on GPS tracking of environmental exposure need to demonstrate a link to relevant health outcomes. (C) 2019 The Authors. Published by Elsevier Ltd.
Keywords
Local Food Environment; Physical-activity; Gps Data; Exposure; Patterns; Quality; Women; Index; Built Environment (be); Activity Space; Route Length; Hei 2010; Bmi
Garg, Parveen K.; Platt, Jonathan M.; Hirsch, Jana A.; Hurvitz, Philip; Rundle, Andrew; Biggs, Mary Lou; Psaty, Bruce M.; Moore, Kari; Lovasi, Gina S. (2021). Association of Neighborhood Physical Activity Opportunities with Incident Cardiovascular Disease in the Cardiovascular Health Study. Health & Place, 70.
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Abstract
We determined associations of cumulative exposures to neighborhood physical activity opportunities with risk of incident cardiovascular disease (CVD). We included 3595 participants from the Cardiovascular Health Study recruited between 1989 and 1993 (mean age = 73; 60% women; 11% black). Neighborhood environment measures were calculated using Geographic Information Systems (GIS) and annual information from the National Establishment Time Series database, including the density of (1) walking destinations and (2) physical activity/ recreational facilities in a 1- and 5-km radius around the respondent's home. Incident CVD was defined as the development of myocardial infarction, stroke, or cardiovascular death and associations with time to incident CVD were estimated using Cox proportional hazards models. A total of 1986 incident CVD cases occurred over a median follow-up of 11.2 years. After adjusting for baseline and time-varying individual and neighborhood-level confounding, a one standard deviation increase in walking destinations and physical activity/recreational facilities within 5 km of home was associated with a respective 7% (95% confidence interval (CI) = 0.87-0.99) and 12% (95% CI = 0.73-1.0) decreased risk of incident CVD. No significant associations were noted within a 1-km radius. Efforts to improve the availability of physical activity resources in neighborhoods may be an important strategy for lowering CVD.
Keywords
Cardiovascular Diseases; Physical Activity; Proportional Hazards Models; Geographic Information Systems; Recreation Centers; Built Environment; Cardiovascular Disease; Coronary-heart-disease; Census Tract Data; Older-adults; Longitudinal Associations; Risk; Resources; Time; Atherosclerosis; Survival
Moudon, Anne Vernez; Cook, Andrea J.; Ulmer, Jared; Hurvitz, Philip M.; Drewnowski, Adam. (2011). A Neighborhood Wealth Metric for Use in Health Studies. American Journal Of Preventive Medicine, 41(1), 88 – 97.
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Abstract
Background: Measures of neighborhood deprivation used in health research are typically based on conventional area-based SES. Purpose: The aim of this study is to examine new data and measures of SES for use in health research. Specifically, assessed property values are introduced as a new individual-level metric of wealth and tested for their ability to substitute for conventional area-based SES as measures of neighborhood deprivation. Methods: The analysis was conducted in 2010 using data from 1922 participants in the 2008-2009 survey of the Seattle Obesity Study (SOS). It compared the relative strength of the association between the individual-level neighborhood wealth metric (assessed property values) and area-level SES measures (including education, income, and percentage above poverty as single variables, and as the composite Singh index) on the binary outcome fair/poor general health status. Analyses were adjusted for gender, categoric age, race, employment status, home ownership, and household income. Results: The neighborhood wealth measure was more predictive of fair/poor health status than area-level SES measures, calculated either as single variables or as indices (lower DIC measures for all models). The odds of having a fair/poor health status decreased by 0.85 (95% CI=0.77, 0.93) per $50,000 increase in neighborhood property values after adjusting for individual-level SES measures. Conclusions: The proposed individual-level metric of neighborhood wealth, if replicated in other areas, could replace area-based SES measures, thus simplifying analyses of contextual effects on health. (Am J Prev Med 2011; 41(1): 88-97) (C) 2011 American Journal of Preventive Medicine
Keywords
Health -- Social Aspects; Social Status; Public Health Research; Home Ownership; Income; Real Property; Deprivation (psychology); Health Education; Disparities Geocoding Project; Body-mass Index; Socioeconomic-status; Ecological Fallacy; Built Environment; Deprivation Indexes; Multilevel Analysis; Individual-level; Social-class; Inequalities
Quistberg, D. Alex; Howard, Eric J.; Ebel, Beth E.; Moudon, Anne V.; Saelens, Brian E.; Hurvitz, Philip M.; Curtin, James E.; Rivara, Frederick P. (2015). Multilevel Models for Evaluating the Risk of Pedestrian-Motor Vehicle Collisions at Intersections and Mid-Blocks. Accident Analysis & Prevention, 84, 99 – 111.
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Abstract
Walking is a popular form of physical activity associated with clear health benefits. Promoting safe walking for pedestrians requires evaluating the risk of pedestrian motor vehicle collisions at specific roadway locations in order to identify where road improvements and other interventions may be needed. The objective of this analysis was to estimate the risk of pedestrian collisions at intersections and mid-blocks in Seattle, WA. The study used 2007-2013 pedestrian motor vehicle collision data from police reports and detailed characteristics of the microenvironment and macroenvironment at intersection and mid-block locations. The primary outcome was the number of pedestrian motor vehicle collisions over time at each location (incident rate ratio [IRR] and 95% confidence interval [95% CI]). Multilevel mixed effects Poisson models accounted for correlation within and between locations and census blocks over time. Analysis accounted for pedestrian and vehicle activity (e.g., residential density and road classification). In the final multivariable model, intersections with 4 segments or 5 or more segments had higher pedestrian collision rates compared to mid-blocks. Non-residential roads had significantly higher rates than residential roads, with principal arterials having the highest collision rate. The pedestrian collision rate was higher by 9% per 10 feet of street width. Locations with traffic signals had twice the collision rate of locations without a signal and those with marked crosswalks also had a higher rate. Locations with a marked crosswalk also had higher risk of collision. Locations with a one-way road or those with signs encouraging motorists to cede the right-of-way to pedestrians had fewer pedestrian collisions. Collision rates were higher in locations that encourage greater pedestrian activity (more bus use, more fast food restaurants, higher employment, residential, and population densities). Locations with higher intersection density had a lower rate of collisions as did those in areas with higher residential property values. The novel spatiotemporal approach used that integrates road/crossing characteristics with surrounding neighborhood characteristics should help city agencies better identify high-risk locations for further study and analysis. Improving roads and making them safer for pedestrians achieves the public health goals of reducing pedestrian collisions and promoting physical activity. (C) 2015 Elsevier Ltd. All rights reserved.
Keywords
Pedestrian Accidents; Road Interchanges & Intersections; Built Environment; Pedestrian Crosswalks; Correlation (statistics); Collision Risk; Multilevel Model; Pedestrians; Geographic Information-systems; Road-traffic Injuries; Physical-activity; Signalized Intersections; Impact Speed; Urban Form; Land-use; Safety; Walking
Duncan, Glen E.; Avery, Ally; Hurvitz, Philip M.; Moudon, Anne Vernez; Tsang, Siny; Turkheimer, Eric. (2019). Cohort Profile: Twins Study of Environment, Lifestyle Behaviours and Health. International Journal Of Epidemiology, 48(4), 1041.
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Keywords
Twin Studies; Neighborhoods; Native Americans; Normalized Difference Vegetation Index; Life Style; Twins; Body-mass Index; Physical-activity; Neighborhood Walkability; Waist Circumference; Built Environment; Causal Inference; Deprivation; Validation; Registry; Obesity