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Person: Anne Vernez Moudon

Does the Built Environment Have Independent Obesogenic Power? Urban Form and Trajectories of Weight Gain

Buszkiewicz, James H.; Bobb, Jennifer F.; 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). Does the Built Environment Have Independent Obesogenic Power? Urban Form and Trajectories of Weight Gain. International Journal Of Obesity, 45(9), 1914 – 1924.

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Abstract

Objective To determine whether selected features of the built environment can predict weight gain in a large longitudinal cohort of adults. Methods Weight trajectories over a 5-year period were obtained from electronic health records for 115,260 insured patients aged 18-64 years in the Kaiser Permanente Washington health care system. Home addresses were geocoded using ArcGIS. Built environment variables were population, residential unit, and road intersection densities captured using Euclidean-based SmartMaps at 800-m buffers. Counts of area supermarkets and fast food restaurants were obtained using network-based SmartMaps at 1600, and 5000-m buffers. Property values were a measure of socioeconomic status. Linear mixed effects models tested whether built environment variables at baseline were associated with long-term weight gain, adjusting for sex, age, race/ethnicity, Medicaid insurance, body weight, and residential property values. Results Built environment variables at baseline were associated with differences in baseline obesity prevalence and body mass index but had limited impact on weight trajectories. Mean weight gain for the full cohort was 0.06 kg at 1 year (95% CI: 0.03, 0.10); 0.64 kg at 3 years (95% CI: 0.59, 0.68), and 0.95 kg at 5 years (95% CI: 0.90, 1.00). In adjusted regression models, the top tertile of density metrics and frequency counts were associated with lower weight gain at 5-years follow-up compared to the bottom tertiles, though the mean differences in weight change for each follow-up year (1, 3, and 5) did not exceed 0.5 kg. Conclusions Built environment variables that were associated with higher obesity prevalence at baseline had limited independent obesogenic power with respect to weight gain over time. Residential unit density had the strongest negative association with weight gain. Future work on the influence of built environment variables on health should also examine social context, including residential segregation and residential mobility.

Keywords

Body-mass Index; Physical-activity; Food Environment; Structural Racism; Obesity; Neighborhoods; Associations; Health; Walkability; Exposure; Environment Models; Minority & Ethnic Groups; Urban Environments; Regression Analysis; Regression Models; Residential Density; Body Mass Index; Property Values; Body Weight Gain; Government Programs; Body Weight; Electronic Medical Records; Electronic Health Records; Fast Food; Buffers; Real Estate; Body Mass; Body Size; Socioeconomics; Health Care

A Neighborhood Wealth Metric for Use in Health Studies

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

Environments Perceived as Obesogenic Have Lower Residential Property Values

Drewnowski, Adam; Aggarwal, Anju; Rehm, Colin D.; Cohen-Cline, Hannah; Hurvitz, Philip M.; Moudon, Anne V. (2014). Environments Perceived as Obesogenic Have Lower Residential Property Values. American Journal Of Preventive Medicine, 47(3), 260 – 274.

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Abstract

Background: Studies have tried to link obesity rates and physical activity with multiple aspects of the built environment. Purpose: To determine the relation between residential property values and multiple perceived (self-reported) measures of the obesogenic environment. Methods: The Seattle Obesity Study (SOS) used a telephone survey of a representative, geographically distributed sample Of 2,001 King County adults, collected in 2008-2009 and analyzed in 2012-2013. Home addresses were geocoded. Residential property values at the tax parcel level were obtained from the King County tax assessor. Mean residential property values within a 10-minute walk (833-m buffer) were calculated for each respondent. Data on multiple perceived measures of the obesogenic environment were collected by self-report. Correlations and multi-variable linear regression analyses, stratified by residential density, were used to examine the associations among perceived environmental measures, property values, and BMI. Results: Perceived measures of the environment such as crime, heavy traffic, and proximity to bars, liquor stores, and fast food were all associated with lower property values. By contrast, living in neighborhoods that were perceived as safe, quiet, clean, and attractive was associated with higher property values. Higher property values were associated, in turn, with lower BMIs among women. The observed associations between perceived environment measures and BMI were largely attenuated after accounting for residential property values. Conclusions: Environments perceived as obesogenic are associated with lower property values. Studies in additional locations need to explore to what extent other perceived environment measures can be reflected in residential property values. (C) 2014 American Journal of Preventive Medicine

Keywords

Body-mass Index; Physical-activity; Objective Measures; Childhood Obesity; Food Stores; Neighborhood Disorder; Atherosclerosis Risk; Collective Efficacy; Racial Composition; Built Environment

Obesity, Diet Quality, Physical Activity, and the Built Environment: The Need for Behavioral Pathways

Drewnowski, Adam; Aggarwal, Anju; Tang, Wesley; Hurvitz, Philip M.; Scully, Jason; Stewart, Orion; Moudon, Anne Vernez. (2016). Obesity, Diet Quality, Physical Activity, and the Built Environment: The Need for Behavioral Pathways. BMC Public Health, 16.

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Abstract

Background: The built environment ( BE) is said to influence local obesity rates. Few studies have explored causal pathways between home-neighborhood BE variables and health outcomes such as obesity. Such pathways are likely to involve both physical activity and diet. Methods: The Seattle Obesity Study ( SOS II) was a longitudinal cohort of 440 adult residents of King Co, WA. Home addresses were geocoded. Home-neighborhood BE measures were framed as counts and densities of food sources and physical activity locations. Tax parcel property values were obtained from County tax assessor. Healthy Eating Index ( HEI 2010) scores were constructed using data from food frequency questionnaires. Physical activity ( PA) was obtained by self-report. Weights and heights were measured at baseline and following 12 months' exposure. Multivariable regressions examined the associations among BE measures at baseline, health behaviors ( HEI-2010 and physical activity) at baseline, and health outcome both cross-sectionally and longitudinally. Results: None of the conventional neighborhood BE metrics were associated either with diet quality, or with meeting PA guidelines. Only higher property values did predict better diets and more physical activity. Better diets and more physical activity were associated with lower obesity prevalence at baseline and 12 mo, but did not predict weight change. Conclusion: Any links between the BE and health outcomes critically depend on establishing appropriate behavioral pathways. In this study, home-centric BE measures, were not related to physical activity or to diet. Further studies will need to consider a broader range of BE attributes that may be related to diets and health.

Keywords

Body-mass Index; Local Food Environment; Residential Property-values; Supermarket Accessibility; Park Proximity; Neighborhood Walkability; Vegetable Consumption; Atherosclerosis Risk; Restaurant Food; Associations; Built Environment; Physical Activity; Obesity; Diet Quality

Why Neighborhood Park Proximity Is Not Associated with Total Physical Activity

Stewart, Orion T.; Moudon, Anne Vernez; Littman, Alyson J.; Seto, Edmund; Saelens, Brian E. (2018). Why Neighborhood Park Proximity Is Not Associated with Total Physical Activity. Health & Place, 52, 163 – 169.

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Abstract

This study explored how parks within the home neighborhood contribute to total physical activity (PA) by isolating park-related PA. Seattle-area adults (n = 634) were observed using time-matched accelerometer, Global Positioning System (GPS), and travel diary instruments. Of the average 42.3 min of daily total PA, only 11% was related to parks. Both home neighborhood park count and area were associated with park-based PA, but not with PA that occurred elsewhere, which comprised 89% of total PA. This study demonstrates clear benefits of neighborhood parks for contributing to park-based PA while helping explain why proximity to parks is rarely associated with overall PA.

Keywords

Physical Activity; Parks; Urban Planning; Environmental Health; Global Positioning System; Built Environment; Green Space; Recreation; Social Determinants Of Health; Health Research; Accelerometer Data; Self-selection; United-states; Public Parks; Older Women; Walking; Adults; Facilities

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

Transportation-Efficient Land Use Mapping Index (TELUMI), a Tool to Assess Multimodal Transportation Options in Metropolitan Regions

Moudon, Anne Vernez; Sohn, D. W.; Kavage, Sarah E.; Mabry, Jean E. (2011). Transportation-Efficient Land Use Mapping Index (TELUMI), a Tool to Assess Multimodal Transportation Options in Metropolitan Regions. International Journal Of Sustainable Transportation, 5(2), 111 – 133.

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Abstract

The Transportation-Efficient Land Use Mapping Index (TELUMI) is a tool to visualize and to quantify micro-level metropolitan land use and development patterns as they affect travel demand. It can assist transportation and urban planning authorities in identifying zones where land use supports multimodal travel and in determining a region's transportation system efficiency. An application of the TELUMI in the Seattle region showed that residential units and employment concentrated in transportation-efficient areas covering less than 20 percent of the region. An interactive, multi-scaled tool, the TELUMI can also support scenario building to simulate land use changes that improve transportation system performance.

Keywords

Urban; Geographic Information Systems; Land Use; Mapping Index; Metropolitan; Multimodal Travel; Transportation Efficiency

The Geography of Diabetes by Census Tract in a Large Sample of Insured Adults in King County, Washington, 2005-2006

Drewnowski, Adam; Rehm, Colin D.; Moudon, Anne V.; Arterburn, David. (2014). The Geography of Diabetes by Census Tract in a Large Sample of Insured Adults in King County, Washington, 2005-2006. Preventing Chronic Disease, 11.

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Abstract

Introduction Identifying areas of high diabetes prevalence can have an impact on public health prevention and intervention programs. Local health practitioners and public health agencies lack small-area data on obesity and diabetes. Methods Clinical data from the Group Health Cooperative health care system were used to estimate diabetes prevalence among 59,767 adults by census tract. Area-based measures of socioeconomic status and the Modified Retail Food Environment Index were obtained at the census-tract level in King County, Washington. Spatial analyses and regression models were used to assess the relationship between census tract level diabetes and area-based socioeconomic status and food environment variables. The mediating effect of obesity on the geographic distribution of diabetes was also examined. Results In this population of insured adults, diabetes was concentrated in south and southeast King County, with smoothed diabetes prevalence ranging from 6.9% to 21.2%. In spatial regression models, home value and college education were more strongly associated with diabetes than was household income. For each 50% increase in median home value, diabetes prevalence was 1.2 percentage points lower. The Modified Retail Food Environment Index was not related to diabetes at the census-tract level. The observed associations between area-based socioeconomic status and diabetes were largely mediated by obesity (home value, 58%; education, 47%). Conclusion The observed geographic disparities in diabetes among insured adults by census tract point to the importance of area socioeconomic status. Small-area studies can help health professionals design community-based programs for diabetes prevention and control.

Keywords

Prevalence; Obesity; Us; Disease

Physical Activity and the Built Environment in Residential Neighborhoods of Seoul and Seattle: An Empirical Study Based on Housewives’ GPS Walking Data and Travel Diaries

Park, Sohyun; Choi, Yeemyung; Seo, Hanlim; Moudon, Anne Vernez; Bae, C. -h. Christine; Baek, So-ra. (2016). Physical Activity and the Built Environment in Residential Neighborhoods of Seoul and Seattle: An Empirical Study Based on Housewives’ GPS Walking Data and Travel Diaries. Journal Of Asian Architecture And Building Engineering, 15(3), 471 – 478.

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Abstract

This paper is based on a collaborative pilot-study to ascertain the characteristic walking patterns and neighborhood features in residential areas of Seoul, Korea and Seattle, USA. As for sample sites, four case neighborhoods were selected: two from Seoul and two from in and outside of the Seattle-Shoreline areas. As for participants, thirty Korean housewives in Seoul and thirty Korean-American housewives in the Seattle area were selected respectively, and their socio-demographic characteristics, GPS records, and travel diary data for seven days were collected and analyzed. Considering the typical rainy seasons in the two cities, data collections, including the physical activity assessment by GPS devices, were carried out from May to June and from September to October in Seoul, and from July to October in Seattle during the year 2010. Noteworthy research findings include the following: Korean participants in Seoul walk about 2.6 km on average per day, while Korean-American participants in Seattle walk about 400m on average per day. In the case sites of Seoul, 75% of grocery shopping activities happen within the neighborhood by walking, while only 17% of those activities on foot happen in the case sites of Seattle. As for the most walking activity, about 70% of total walking amounts are related to utilitarian walking in Seoul sites, while 50% of total walking are related to recreational walking in Seattle sites. Recreational walking and utilitarian walking occur separately in Seattle sites, while the two walking types are often combined in Seoul sites, which also contribute to more walking amounts and farther walking distances in Seoul sites. This paper empirically confirms the widely held assumptions in part that residents in Seoul, a relatively high-density and high mixed-use city, walk more than those in Seattle, a relatively low-density and low mixed-use city. This paper also recognizes that in the case of both cities, more walking activities occur in the neighborhood built environment, where finely-grained street networks, small lots and blocks, various pedestrian destinations, public transit access, etc are provided in close connection. The amount and frequency of walking activities, as well as the fineness of neighborhood features, however, are remarkably different in the two cities, whose implications deserve in-depth exploration in further studies.

Keywords

Urban Design; Physical Activity; Neighborhood Environment; Objective Measures; Gps Walking Data; International Comparative Study

The Association between Park Facilities and the Occurrence of Physical Activity during Park Visits

Stewart, Orion Theodore; Moudon, Anne Vernez; Littman, Alyson; Seto, Edmund; Saelens, Brian E. (2018). The Association between Park Facilities and the Occurrence of Physical Activity during Park Visits. Journal Of Leisure Research, 49(3-5), 217 – 235.

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Abstract

Prior research has found a positive relationship between the variety of park facilities and park-based physical activity (PA) but has not provided an estimate of the effect that additional different PA facilities have on whether an individual is active during a park visit. Using objective measures of park visits and PA from an urban sample of 225 adults in King County, Washington, we compared the variety of PA facilities in parks visited where an individual was active to PA facilities in parks where the same individual was sedentary. Each additional different PA facility at a park was associated with a 6% increased probability of being active during a visit. Adding different PA facilities to a park appears to have a moderate effect on whether an individual is active during a park visit, which could translate into large community health impacts when scaled up to multiple park visitors.

Keywords

Accelerometer Data; Built Environment; Walking; Density; Health; Adults; Size; Gps; Attractiveness; Improvements; Measurement; Parks; Physical Activity; Quantitative Research; Urban Planning