Anne Vernez Moudon Archives - Page 2 of 9

Associations between Neighborhood Built Environment, Residential Property Values, and Adult BMI Change: The Seattle Obesity Study III

Buszkiewicz, James H.; Rose, Chelsea M.; Ko, Linda K.; Mou, Jin; Moudon, Anne Vernez; Hurvitz, Philip M.; Cook, Andrea J.; Drewnowski, Adam. (2022). Associations between Neighborhood Built Environment, Residential Property Values, and Adult BMI Change: The Seattle Obesity Study III. SSM-Population Health, 19.

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Abstract

Objective: To examine associations between neighborhood built environment (BE) variables, residential property values, and longitudinal 1-and 2-year changes in body mass index (BMI). Methods: The Seattle Obesity Study III was a prospective cohort study of adults with geocoded residential addresses, conducted in King, Pierce, and Yakima Counties in Washington State. Measured heights and weights were obtained at baseline (n = 879), year 1 (n = 727), and year 2 (n = 679). Tax parcel residential property values served as proxies for individual socioeconomic status. Residential unit and road intersection density were captured using Euclidean-based SmartMaps at 800 m buffers. Counts of supermarket (0 versus. 1+) and fast-food restaurant availability (0, 1-3, 4+) were measured using network based SmartMaps at 1600 m buffers. Density measures and residential property values were categorized into tertiles. Linear mixed-effects models tested whether baseline BE variables and property values were associated with differential changes in BMI at year 1 or year 2, adjusting for age, gender, race/ethnicity, education, home ownership, and county of residence. These associations were then tested for potential disparities by age group, gender, race/ethnicity, and education. Results: Road intersection density, access to food sources, and residential property values were inversely associated with BMI at baseline. At year 1, participants in the 3rd tertile of density metrics and with 4+ fast-food restaurants nearby showed less BMI gain compared to those in the 1st tertile or with 0 restaurants. At year 2, higher residential property values were predictive of lower BMI gain. There was evidence of differential associations by age group, gender, and education but not race/ethnicity. Conclusion: Inverse associations between BE metrics and residential property values at baseline demonstrated mixed associations with 1-and 2-year BMI change. More work is needed to understand how individual-level sociodemographic factors moderate associations between the BE, property values, and BMI change.

Keywords

Body-mass Index; Physical-activity; Food Environment; Socioeconomic-status; Weight-gain; Health; Quality

City Planning Policies to Support Health and Sustainability: An International Comparison of Policy Indicators for 25 Cities

Lowe, Melanie; Adlakha, Deepti; Sallis, James F.; Salvo, Deborah; Cerin, Ester; Moudon, Anne Vernez; Higgs, Carl; Hinckson, Erica; Arundel, Jonathan; Boeing, Geoff; Liu, Shiqin; Mansour, Perla; Gebel, Klaus; Puig-ribera, Anna; Mishra, Pinki Bhasin; Bozovic, Tamara; Carson, Jacob; Dygryn, Jan; Florindo, Alex A.; Ho, Thanh Phuong; Hook, Hannah; Hunter, Ruth F.; Lai, Poh-chin; Molina-garcia, Javier; Nitvimol, Kornsupha; Oyeyemi, Adewale L.; Ramos, Carolina D. G.; Resendiz, Eugen; Troelsen, Jens; Witlox, Frank; Giles-corti, Billie. (2022). City Planning Policies to Support Health and Sustainability: An International Comparison of Policy Indicators for 25 Cities. Lancet Global Health, 10(6), E882-E894.

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Abstract

City planning policies influence urban lifestyles, health, and sustainability. We assessed policy frameworks for city planning for 25 cities across 19 lower-middle-income countries, upper-middle-income countries, and high-income countries to identify whether these policies supported the creation of healthy and sustainable cities. We systematically collected policy data for evidence-informed indicators related to integrated city planning, air pollution, destination accessibility, distribution of employment, demand management, design, density, distance to public transport, and transport infrastructure investment. Content analysis identified strengths, limitations, and gaps in policies, allowing us to draw comparisons between cities. We found that despite common policy rhetoric endorsing healthy and sustainable cities, there was a paucity of measurable policy targets in place to achieve these aspirations. Some policies were inconsistent with public health evidence, which sets up barriers to achieving healthy and sustainable urban environments. There is an urgent need to build capacity for health-enhancing city planning policy and governance, particularly in low-income and middle-income countries.

Keywords

Physical-activity; Population Health; Walkability

Deciphering the Impact of Urban Built Environment Density on Respiratory Health Using a Quasi-cohort Analysis of 5495 Non-smoking Lung Cancer Cases

Wang, Lan; Sun, Wenyao; Moudon, Anne Vernez; Zhu, Yong-guan; Wang, Jinfeng; Bao, Pingping; Zhao, Xiaojing; Yang, Xiaoming; Jia, Yinghui; Zhang, Surong; Wu, Shuang; Cai, Yuxi. (2022). Deciphering the Impact of Urban Built Environment Density on Respiratory Health Using a Quasi-cohort Analysis of 5495 Non-smoking Lung Cancer Cases. Science Of The Total Environment, 850.

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Abstract

Introduction: Lung cancer is a major health concern and is influenced by air pollution, which can be affected by the den-sity of urban built environment. The spatiotemporal impact of urban density on lung cancer incidence remains unclear, especially at the sub-city level. We aimed to determine cumulative effect of community-level density attributes of the built environment on lung cancer incidence in high-density urban areas. Methods: We selected 78 communities in the central city of Shanghai, China as the study site; communities included in the analysis had an averaged population density of 313 residents per hectare. Using data from the city cancer surveil-lance system, an age-period-cohort analysis of lung cancer incidence was performed over a five-year period (2009-2013), with a total of 5495 non-smoking/non-secondhand smoking exposure lung cancer cases. Community -level density measures included the density of road network, facilities, buildings, green spaces, and land use mixture. Results: In multivariate models, built environment density and the exposure time duration had an interactive effect on lung cancer incidence. Lung cancer incidence of birth cohorts was associated with road density and building coverage across communities, with a relative risk of 1middot142 (95 % CI: 1middot056-1middot234, P = 0middot001) and 1middot090 (95 % CI: 1middot053-1middot128, P < 0middot001) at the baseline year (2009), respectively. The relative risk increased exponentially with the exposure timeduration. As for the change in lung cancer incidence over the five-year period, lung cancer incidence of birth cohorts tended to increase faster in communities with a higher road density and building coverage. Conclusion: Urban planning policies that improve road network design and building layout could be important strate-gies to reduce lung cancer incidence in high-density urban areas.

Keywords

Air-quality; Pollutant Dispersion; Risk-factors; Land-use; Mortality; Exposure; Cities; Transport; Compact City; Longitudinal Analysis; Lung Cancer; Urban Planning

Differences in Weight Gain Following Residential Relocation in the Moving to Health (M2H) Study

Cruz, Maricela; Drewnowski, Adam; Bobb, Jennifer F.; Hurvitz, Philip M.; Moudon, Anne Vernez; Cook, Andrea; Mooney, Stephen J.; Buszkiewicz, James H.; Lozano, Paula; Rosenberg, Dori E.; Kapos, Flavia; Theis, Mary Kay; Anau, Jane; Arterburn, David. (2022). Differences in Weight Gain Following Residential Relocation in the Moving to Health (M2H) Study. Epidemiology, 33(5), 747-755.

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Abstract

Background: Neighborhoods may play an important role in shaping long-term weight trajectory and obesity risk. Studying the impact of moving to another neighborhood may be the most efficient way to determine the impact of the built environment on health. We explored whether residential moves were associated with changes in body weight. Methods: Kaiser Permanente Washington electronic health records were used to identify 21,502 members aged 18-64 who moved within King County, WA between 2005 and 2017. We linked body weight measures to environment measures, including population, residential, and street intersection densities (800 m and 1,600 m Euclidian buffers) and access to supermarkets and fast foods (1,600 m and 5,000 m network distances). We used linear mixed models to estimate associations between postmove changes in environment and changes in body weight. Results: In general, moving from high-density to moderate- or low-density neighborhoods was associated with greater weight gain postmove. For example, those moving from high to low residential density neighborhoods (within 1,600 m) gained an average of 4.5 (95% confidence interval [CI] = 3.0, 5.9) lbs 3 years after moving, whereas those moving from low to high-density neighborhoods gained an average of 1.3 (95% CI = -0.2, 2.9) lbs. Also, those moving from neighborhoods without fast-food access (within 1600m) to other neighborhoods without fast-food access gained less weight (average 1.6 lbs [95% CI = 0.9, 2.4]) than those moving from and to neighborhoods with fast-food access (average 2.8 lbs [95% CI = 2.5, 3.2]). Conclusions: Moving to higher-density neighborhoods may be associated with reductions in adult weight gain.

Keywords

Body-mass Index; Neighborhood Socioeconomic-status; New-york-city; Built Environment; Physical-activity; Food Environment; Urban Sprawl; Risk-factors; Obesity; Walking; Electronic Medical Records; Fast Foods; Population Density; Residential Density; Residential Moves; Supermarkets

Using Open Data and Open-source Software to Develop Spatial Indicators of Urban Design and Transport Features for Achieving Healthy and Sustainable Cities

Boeing, Geoff; Higgs, Carl; Liu, Shiqin; Giles-corti, Billie; Sallis, James F.; Cerin, Ester; Lowe, Melanie; Adlakha, Deepti; Hinckson, Erica; Moudon, Anne Vernez; Salvo, Deborah; Adams, Marc A.; Barrozo, Ligia, V; Bozovic, Tamara; Delclos-alio, Xavier; Dygryn, Jan; Ferguson, Sara; Gebel, Klaus; Thanh Phuong Ho; Lai, Poh-chin; Martori, Joan C.; Nitvimol, Kornsupha; Queralt, Ana; Roberts, Jennifer D.; Sambo, Garba H.; Schipperijn, Jasper; Vale, David; Van De Weghe, Nico; Vich, Guillem; Arundel, Jonathan. (2022). Using Open Data and Open-source Software to Develop Spatial Indicators of Urban Design and Transport Features for Achieving Healthy and Sustainable Cities. Lancet Global Health, 10(6), E907-E918.

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Abstract

Benchmarking and monitoring of urban design and transport features is crucial to achieving local and international health and sustainability goals. However, most urban indicator frameworks use coarse spatial scales that either only allow between-city comparisons, or require expensive, technical, local spatial analyses for within-city comparisons. This study developed a reusable, open-source urban indicator computational framework using open data to enable consistent local and global comparative analyses. We show this framework by calculating spatial indicators-for 25 diverse cities in 19 countries-of urban design and transport features that support health and sustainability. We link these indicators to cities' policy contexts, and identify populations living above and below critical thresholds for physical activity through walking. Efforts to broaden participation in crowdsourcing data and to calculate globally consistent indicators are essential for planning evidence-informed urban interventions, monitoring policy effects, and learning lessons from peer cities to achieve health, equity, and sustainability goals.

Keywords

Systems; Access; Care

What Next? Expanding Our View of City Planning and Global Health, and Implementing and Monitoring Evidence-informed Policy

Giles-corti, Billie; Moudon, Anne Vernez; Lowe, Melanie; Cerin, Ester; Boeing, Geoff; Frumkin, Howard; Salvo, Deborah; Foster, Sarah; Kleeman, Alexandra; Bekessy, Sarah; De Sa, Thiago Herick; Nieuwenhuijsen, Mark; Higgs, Carl; Hinckson, Erica; Adlakha, Deepti; Arundel, Jonathan; Liu, Shiqin; Oyeyemi, Adewale L.; Nitvimol, Kornsupha; Sallis, James F. (2022). What Next? Expanding Our View of City Planning and Global Health, and Implementing and Monitoring Evidence-informed Policy. Lancet Global Health, 10(6), E919-E926.

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Abstract

This Series on urban design, transport, and health aimed to facilitate development of a global system of health-related policy and spatial indicators to assess achievements and deficiencies in urban and transport policies and features. This final paper in the Series summarises key findings, considers what to do next, and outlines urgent key actions. Our study of 25 cities in 19 countries found that, despite many well intentioned policies, few cities had measurable standards and policy targets to achieve healthy and sustainable cities. Available standards and targets were often insufficient to promote health and wellbeing, and health-supportive urban design and transport features were often inadequate or inequitably distributed. City planning decisions affect human and planetary health and amplify city vulnerabilities, as the COVID-19 pandemic has highlighted. Hence, we offer an expanded framework of pathways through which city planning affects health, incorporating 11 integrated urban system policies and 11 integrated urban and transport interventions addressing current and emerging issues. Our call to action recommends widespread uptake and further development of our methods and open-source tools to create upstream policy and spatial indicators to benchmark and track progress; unmask spatial inequities; inform interventions and investments; and accelerate transitions to net zero, healthy, and sustainable cities.

Genetic and Environmental Influences on Residential Location in the US

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

How Far from Home? The Locations of Physical Activity in an Urban US Setting

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

The Association between Park Visitation and Physical Activity Measured with Accelerometer, GPS, and Travel Diary

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

Cohort Profile: Twins Study of Environment, Lifestyle Behaviours and Health

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