Anne Vernez Moudon Archives - Page 2 of 9

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.

How to Identify Food Deserts: Measuring Physical and Economic Access to Supermarkets in King County, Washington

Jiao, Junfeng; Moudon, Anne V.; Ulmer, Jared; Hurvitz, Philip M.; Drewnowski, Adam. (2012). How to Identify Food Deserts: Measuring Physical and Economic Access to Supermarkets in King County, Washington. American Journal Of Public Health, 102(10), E32 – E39.

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Abstract

Objectives. We explored new ways to identify food deserts. Methods. We estimated physical and economic access to supermarkets for 5 low-income groups in Seattle-King County, Washington. We used geographic information system data to measure physical access: service areas around each supermarket were delineated by ability to walk, bicycle, ride transit, or drive within 10 minutes. We assessed economic access by stratifying supermarkets into low, medium, and high cost. Combining income and access criteria generated multiple ways to estimate food deserts. Results. The 5 low-income group definitions yielded total vulnerable populations ranging from 4% to 33% of the county's population. Almost all of the vulnerable populations lived within a 10-minute drive or bus ride of a low-or medium-cost supermarket. Yet at most 34% of the vulnerable populations could walk to any supermarket, and as few as 3% could walk to a low-cost supermarket. Conclusions. The criteria used to define low-income status and access to supermarkets greatly affect estimates of populations living in food deserts. Measures of access to food must include travel duration and mode and supermarket food costs.

Keywords

Neighborhood Characteristics; Store Availability; Accessibility; Consumption; Disparities; Environment; Location; Fruit; Pay

Using the Built Environment to Oversample Walk, Transit, and Bicycle Travel

Stewart, Orion Theodore; Moudon, Anne Vernez. (2014). Using the Built Environment to Oversample Walk, Transit, and Bicycle Travel. Transportation Research: Part D, 32, 15 – 23.

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Abstract

Characteristics of the built environment (BE) have been associated with walk, transit, and bicycle travel. These BE characteristics can be used by transportation researchers to oversample households from areas where walk, transit, or bicycle travel is more likely, resulting in more observations of these uncommon travel behaviors. Little guidance, however, is available on the effectiveness of such built environment oversampling strategies. This article presents measures that can be used to assess the effectiveness of BE oversampling strategies and inform future efforts to oversample households with uncommon travel behaviors. The measures are sensitivity and specificity, positive likelihood ratio (LR+), and positive predictive value (PPV). To illustrate these measures, they were calculated for 10 BE-defined oversampling strata applied post-hoc to a Seattle area household travel survey. Strata with an average block size of <10 acres within a 1/4 mile of household residences held the single greatest potential for oversampling households that walk, use transit, and/or bicycle. (C) 2014 Elsevier Ltd. All rights reserved.

Keywords

Cycling; Transportation; Observation (scientific Method); Strategic Planning; Public Transit; Land Use; Bicycle; Household Travel Survey; Non-motorized Travel; Sampling; Screening Tests; Transit; Walk; Land-use; North-america; Renaissance; Policies; Choice; Trends

Validating Self-Reported Food Expenditures against Food Store and Eating-Out Receipts

Tang, W.; Aggarwal, A.; Liu, Z.; Acheson, M.; Rehm, C. D.; Moudon, A. V.; Drewnowski, A. (2016). Validating Self-Reported Food Expenditures against Food Store and Eating-Out Receipts. European Journal Of Clinical Nutrition, 70(3), 352 – 357.

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Abstract

BACKGROUND/OBJECTIVES: To compare objective food store and eating-out receipts with self-reported household food expenditures. SUBJECTS/METHODS: The Seattle Obesity Study II was based on a representative sample of King County adults, Washington, USA. Self-reported household food expenditures were modeled on the Flexible Consumer Behavior Survey (FCBS) Module from 2007 to 2009 National Health and Nutrition Examination Survey (NHANES). Objective food expenditure data were collected using receipts. Self-reported food expenditures for 447 participants were compared with receipts using paired t-tests, Bland-Altman plots and.-statistics. Bias by sociodemographics was also examined. RESULTS: Self-reported expenditures closely matched with objective receipt data. Paired t-tests showed no significant differences between receipts and self-reported data on total food expenditures, expenditures at food stores or eating out. However, the highest-income strata showed weaker agreement. Bland-Altman plots confirmed no significant bias across both methods-mean difference: 6.4; agreement limits: -123.5 to 143.4 for total food expenditures, mean difference 5.7 for food stores and mean difference 1.7 for eating out. The kappa-statistics showed good agreement for each (kappa 0.51, 0.41 and 0.49 respectively. Households with higher education and income had significantly more number of receipts and higher food expenditures. CONCLUSIONS: Self-reported food expenditures using NHANES questions, both for food stores and eating out, serve as a decent proxy for objective household food expenditures from receipts. This method should be used with caution among high-income populations, or with high food expenditures. This is the first validation of the FCBS food expenditures question using food store and eating-out receipts.

Keywords

Household Food; Supermarket; Obesity; Energy; Purchases; Patterns; Women; Fat

Higher Residential and Employment Densities Are Associated with More Objectively Measured Walking in the Home Neighborhood

Huang, Ruizhu; Moudon, Anne, V; Zhou, Chuan; Saelens, Brian E. (2019). Higher Residential and Employment Densities Are Associated with More Objectively Measured Walking in the Home Neighborhood. Journal Of Transport & Health, 12, 142 – 151.

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Abstract

Introduction: Understanding where people walk and how the built environment influences walking is a priority in active living research. Most previous studies were limited by self-reported data on walking. In the present study, walking bouts were determined by integrating one week of accelerometry, GPS, and a travel log data among 675 adult participants in the baseline sample of the Travel Assessment and Community study at Seattle, Washington in the United State. Methods: Home neighborhood was defined as being within 0.5 mile of each participants' residence (a 10-min walk), with home neighborhood walking defined as walking bout lines with at least one GPS point within the home neighborhood. Home neighborhood walkability was constructed with seven built environment variables derived from spatially continuous objective values (SmartMaps). Collinearity among neighborhood environment variables was analyzed and variables that were strongly correlated with residential density were excluded in the regression analysis to avoid erroneous estimates. A Zero Inflated Negative Binomial (ZINB) served to estimate associations between home neighborhood environment characteristics and home neighborhood walking frequency. Results: The study found that more than half of participants' walking bouts occurred in their own home neighborhood. Higher residential density and job density were the two neighborhood walkability measures related to higher likelihood and more time walking in the home neighborhood, highest tertile residential density (22.4-62.6 unit/ha) (coefficient= 1.43; 95% CI 1.00-2.05) and highest tertile job density (12.4-272.3 jobs/acre) (coefficient= 1.62; 1.10-2.37). Conclusions: The large proportion of walking that takes place in the home neighborhood highlights the importance of continuing to examine the impact of the home neighborhood environment on walking. Potential interventions to increase walking behavior may benefit from increasing residential and employment density within residential areas.

Keywords

Body-mass Index; Built Environment; Physical-activity; Land Uses; Epidemiology; Selection; Location; Obesity; Travel Assessment And Community; Smartmaps; Neighborhood Environment; Physical Activity; Walking

Residential Property Values are Associated with Obesity among Women in King County, WA, USA

Rehm, Colin D.; Moudon, Anne V.; Hurvitz, Philip M.; Drewnowski, Adam. (2012). Residential Property Values are Associated with Obesity among Women in King County, WA, USA. Social Science & Medicine, 75(3), 491 – 495.

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Abstract

Studies of social determinants of weight and health in the US have typically relied on self-reported education and incomes as the two primary measures of socioeconomic status (SES). The assessed value of one's home, an important component of wealth, may be a better measure of the underlying SES construct and a better predictor of obesity. The Seattle Obesity Study (SOS), conducted in 2008-9, was a cross-sectional random digit dial telephone survey of 2001 adults in King County, Washington State, US. Participants' addresses were geocoded and residential property values for each tax parcel were obtained from the county tax assessor's database. Prevalence ratios of obesity by property values, education, and household income were estimated separately for women and men, after adjusting for age, race/ethnicity, household size, employment status and home ownership. Among women, the inverse association between property values and obesity was very strong and independent of other SES factors. Women in the bottom quartile of property values were 3.4 times more likely to be obese than women in the top quartile. No association between property values and obesity was observed for men. The present data strengthen the evidence for a social gradient in obesity among women. Property values may represent a novel and objective measure of SES at the individual level in the US. Measures based on tax assessment data will provide a valuable resource for future health studies. (C) 2012 Elsevier Ltd. All rights reserved.

Keywords

Communities; Employment; Income; Obesity; Poisson Distribution; Probability Theory; Research Funding; Self-evaluation; Sex Distribution; Social Classes; Statistics; Surveys; Data Analysis; Educational Attainment; Cross-sectional Method; Data Analysis Software; Descriptive Statistics; Washington (state); Health Status Disparities; Health Surveys; Social Class; Socioeconomic Factors; Usa; Women; Body-mass Index; Socioeconomic-status; Aged Men; Health; Weight; Disparities; Overweight; Disease; Poverty; Height