Duncan, Glen E.; Mills, Brianna; Strachan, Eric; Hurvitz, Philip; Huang, Ruizhu; Moudon, Anne Vernez; Turkheimer, Eric. (2014). Stepping Towards Causation in Studies of Neighborhood and Environmental Effects: How Twin Research Can Overcome Problems of Selection and Reverse Causation. Health & Place, 27, 106 – 111.
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Abstract
No causal evidence is available to translate associations between neighborhood characteristics and health outcomes into beneficial changes to built environments. Observed associations may be causal or result from uncontrolled confounds related to family upbringing. Twin designs can help neighborhood effects studies overcome selection and reverse causation problems in specifying causal mechanisms. Beyond quantifying genetic effects (i.e., heritability coefficients), we provide examples of innovative measures and analytic methods that use twins as quasi-experimental controls for confounding by environmental effects. We conclude that collaboration among investigators from multiple fields can move the field forward by designing studies that step toward causation. (C) 2014 Elsevier Ltd. All rights reserved,
Keywords
Residential Location; Methylation; Gene; Interplay; Obesity; Causality; Environment Design; Lifestyle Risk Reduction; Social And Built Environments; Twin Studies
Stewart, Orion T.; Carlos, Heather A.; Lee, Chanam; Berke, Ethan M.; Hurvitz, Philip M.; Li, Li; Moudon, Anne Vernez; Doescher, Mark P. (2016). Secondary GIS Built Environment Data for Health Research: Guidance for Data Development. Journal Of Transport & Health, 3(4), 529 – 539.
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Abstract
Built environment (BE) data in geographic information system (GIS) format are increasingly available from public agencies and private providers. These data can provide objective, low-cost BE data over large regions and are often used in public health research and surveillance. Yet challenges exist in repurposing GIS data for health research. The GIS data do not always capture desired constructs; the data can be of varying quality and completeness; and the data definitions, structures, and spatial representations are often inconsistent across sources. Using the Small Town Walkability study as an illustration, we describe (a) the range of BE characteristics measurable in a GIS that may be associated with active living, (b) the availability of these data across nine U.S. small towns, (c) inconsistencies in the GIS BE data that were available, and (d) strategies for developing accurate, complete, and consistent GIS BE data appropriate for research. Based on a conceptual framework and existing literature, objectively measurable characteristics of the BE potentially related to active living were classified under nine domains: generalized land uses, morphology, density, destinations, transportation system, traffic conditions, neighborhood behavioral conditions, economic environment, and regional location. At least some secondary GIS data were available across all nine towns for seven of the 9 BE domains. Data representing high-resolution or behavioral aspects of the BE were often not available. Available GIS BE data - especially tax parcel data often contained varying attributes and levels of detail across sources. When GIS BE data were available from multiple sources, the accuracy, completeness, and consistency of the data could be reasonable ensured for use in research. But this required careful attention to the definition and spatial representation of the BE characteristic of interest. Manipulation of the secondary source data was often required, which was facilitated through protocols. (C) 2015 Elsevier Ltd. All rights reserved.
Keywords
Geographic Information-systems; Physical-activity; Land-use; Walking; Neighborhood; Associations; Density; Design; Adults; Travel; Active Travel; Pedestrian; Urban Design; Community Health; Rural
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
Lin, Lin; Chen, Xueming (Jimmy); Moudon, Anne Vernez. (2021). Measuring the Urban Forms of Shanghai’s City Center and Its New Districts: A Neighborhood-Level Comparative Analysis. Sustainability, 13(15).
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Abstract
Rapid urban expansion has radically transformed the city centers and the new districts of Chinese cities. Both areas have undergone unique redevelopment and development over the past decades, generating unique urban forms worthy of study. To date, few studies have investigated development patterns and land use intensities at the neighborhood level. The present study aims to fill the gap and compare the densities of different types of developments and the spatial compositions of different commercial uses at the neighborhood level. We captured the attributes of their built environment that support instrumental activities of daily living of 710 neighborhoods centered on the public elementary schools of the entire Shanghai municipality using application programming interfaces provided in Baidu Map services. The 200 m neighborhood provided the best fit to capture the variations of the built environment. Overall, city center neighborhoods had significantly higher residential densities and housed more daily routine destinations than their counterparts in the new districts. Unexpectedly, however, the total length of streets was considerably smaller in city-center neighborhoods, likely reflecting the prominence of the wide multilane vehicular roads surrounding large center city redevelopment projects. The findings point to convergence between the city center's urban forms and that of the new districts.
Keywords
Quantifying Spatiotemporal Patterns; Fast-food Restaurants; Instrumental Activities; Physical-activity; Chinese Cities; Land; Schools; Redevelopment; Expansion; Transformation; Built Environment; Planning; Neighborhood; Urban Form; Shanghai
Duncan, Glen E.; Dansie, Elizabeth J.; Strachan, Eric; Munsell, Melissa; Huang, Ruizhu; Moudon, Anne Vernez; Goldberg, Jack; Buchwald, Dedra. (2012). Genetic and Environmental Influences on Residential Location in the US. Health & Place, 18(3), 515 – 519.
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Abstract
We used a classical twin design and measures of neighborhood walkability and social deprivation, using each twin's street address, to examine genetic and environmental influences on the residential location of 1389 same-sex pairs from a US community-based twin registry. Within-pair correlations and structural equation models estimated these influences on walkability among younger (ages 18-24.9) and older (ages 25+) twins. Adjusting for social deprivation, walkability of residential location was primarily influenced by common environment with lesser contributions of unique environment and genetic factors among younger twins, while unique environment most strongly influenced walkability, with small genetic and common environment effects, among older twins. Thus, minimal variance in walkability was explained by shared genetic effects in younger and older twins, and confirms the importance of environmental factors in walkability of residential locations. (c) 2012 Elsevier Ltd. All rights reserved.
Keywords
Homesites; Community Life -- Social Aspects; Structural Equation Modeling; Genetics; Analysis Of Variance; Environmental Health; Walking; United States; Environment; Neighborhood; Twins; Walkability; Physical-activity; Twin Registry; Epidemiology; Preferences; Selection; Zygosity
Hurvitz, Philip M.; Moudon, Anne V.; Kang, Bumjoon; Fesinmeyer, Megan D.; Saelens, Brian E. (2014). How Far from Home? The Locations of Physical Activity in an Urban US Setting. Preventive Medicine, 69, 181 – 186.
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Abstract
Little is known about where physical activity (PA) occurs, or whether different demographic groups accumulate PA in different locations. Method. Objective data on PA and location from 611 adults over 7 days were collected in King County, WA in 2008-2009. The relative amounts of time spent in sedentary-to-low and moderate-to-vigorous PA (MVPA) were quantified at three locations: home (1666 m). Differences in MVPA by demographics and location were examined. The percent of daily time in MVPA was estimated using a mixed model adjusted for location, sex, age, race/ethnicity, employment, education, BMI, and income. Results. Most MVPA time occurred in nonhome locations, and disproportionately near home; this location was associated with 16.46% greater time in MVPA, compared to at-home activity (p< 0.001), whereas more time spent at away locations was associated with 3.74% greater time in MVPA (p< 0.001). Location was found to be a predictor of MVPA independent of demographic factors. Conclusion. A large proportion of MVPA time is spent at near locations, corresponding to the home neighborhood studied in previous PA research. Away locations also host time spent in MVPA and should be the focus of future research. (C) 2014 Elsevier Inc All rights reserved.
Keywords
Accelerometer Data; Built Environment; United-states; Neighborhood Walkability; Exercise Intensity; Time Use; Land-use; Walking; Health; Behavior; Physical Activity; Objective Measurement; Gps; Accelerometry; Gis
Stewart, Orion T.; Moudon, Anne Vernez; Fesinmeyer, Megan D.; Zhou, Chuan; Saelens, Brian E. (2016). The Association between Park Visitation and Physical Activity Measured with Accelerometer, GPS, and Travel Diary. Health & Place, 38, 82 – 88.
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Abstract
Public parks are promoted as places that support physical activity (PA), but evidence of how park visitation contributes to overall PA is limited. This study observed adults living in the Seattle metropolitan area (n=671) for one week using accelerometer, GPS, and travel diary. Park visits, measured both objectively (GPS) and subjectively (travel diary), were temporally linked to accelerometer-measured PA. Park visits occurred at 1.4 per person-week. Participants who visited parks at least once (n=308) had an adjusted average of 14.3 (95% Cl: 8.9, 19.6) min more daily PA than participants who did not visit a park. Even when park-related activity was excluded, park visitors still obtained more minutes of daily PA than non-visitors. Park visitation contributes to a more active lifestyle, but is not solely responsible for it. Parks may best serve to complement broader public health efforts to encourage PA. (C) 2016 Elsevier Ltd. All rights reserved.
Keywords
Physical Activity; Accelerometers; Geographic Information Systems; Park Use; Public Health; Built Environment; Gis; Leisure; Recreation; Substitution; Sedentary Behavior; Public-health; Accessibility; Prevention
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
Wang, Lan; Zhang, Surong; Yang, Zilin; Zhao, Ziyu; Moudon, Anne Vernez; Feng, Huasen; Liang, Junhao; Sun, Wenyao; Cao, Buyang. (2021). What County-level Factors Influence Covid-19 Incidence in the United States? Findings from the First Wave of the Pandemic. Cities, 118.
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Abstract
Effective control of the COVID-19 pandemic via appropriate management of the built environment is an urgent issue. This study develops a research framework to explore the relationship between COVID-19 incidence and influential factors related to protection of vulnerable populations, intervention in transmission pathways, and provision of healthcare resources. Relevant data for regression analysis and structural equation modeling is collected during the first wave of the pandemic in the United States, from counties with over 100 confirmed cases. In addition to confirming certain factors found in the existing literature, we uncover six new factors significantly associated with COVID-19 incidence. Furthermore, incidence during the lockdown is found to significantly affect incidence after the reopening, highlighting that timely quarantining and treating of patients is essential to avoid the snowballing transmission over time. These findings suggest ways to mitigate the negative effects of subsequent waves of the pandemic, such as special attention of infection prevention in neighborhoods with unsanitary and overcrowded housing, minimization of social activities organized by neighborhood associations, and contactless home delivery service of healthy food. Also worth noting is the need to provide support to people less capable of complying with the stay-at-home order because of their occupations or socio-economic disadvantage.
Keywords
Pandemics; Covid-19; Covid-19 Pandemic; Infection Prevention; Stay-at-home Orders; Structural Equation Modeling; United States; Communicable Disease Prevention; Influential Factors; Lockdown; Structural Equation Modeling (sem); Prevalence; Disease; Healthy Food; Social Activities; Counties; Neighborhoods; Housing; Built Environment; Prevention; Minimization; Socioeconomic Factors; Intervention; Health Care; Vulnerability; Occupations; Coronaviruses; Food Service; Disease Transmission; United States--us
Hurvitz, Philip M.; Moudon, Anne Vernez. (2012). Home Versus Nonhome Neighborhood: Quantifying Differences in Exposure to the Built Environment. American Journal Of Preventive Medicine, 42(4), 411 – 417.
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Abstract
Background: Built environment and health research have focused on characteristics of home neighborhoods, whereas overall environmental exposures occur over larger spatial ranges. Purpose: Differences in built environment characteristics were analyzed for home and nonhome locations using GPS data. Methods: GPS data collected in 2007-2008 were analyzed for 41 subjects in the Seattle area in 2010. Environmental characteristics for 3.8 million locations were measured using novel GIS data sets called SmartMaps, representing spatially continuous values of local built environment variables in the domains of neighborhood composition, utilitarian destinations, transportation infrastructure, and traffic conditions. Using bootstrap sampling, CIs were estimated for differences in built environment values for home (1666 m) GPS locations. Results: Home and nonhome built environment values were significantly different for more than 90% of variables across subjects (p < 0.001). Only 51% of subjects had higher counts of supermarkets near than away from home. Different measures of neighborhood parks yielded varying results. Conclusions: SmartMaps helped measure local built environment characteristics for a large set of GPS locations. Most subjects had significantly different home and nonhome built environment exposures. Considering the full range of individuals' environmental exposures may improve understanding of effects of the built environment on behavior and health outcomes. (Am J Prev Med 2012;42(4):411-417) (C) 2012 American Journal of Preventive Medicine
Keywords
Built Environment; Public Health Research; Individual Differences; Neighborhoods; Environmental Exposure; Health Of Homeless People; Global Positioning System; Data Analysis; Quantitative Research; Seattle (wash.); Washington (state); Geographic Information-systems; Global Positioning Systems; Physical-activity; Health Research; Urban Form; Land-use; Associations; Transportation; Availability; Walkability