Safety & Health & Wellbeing Archives - Page 6 of 29

Spatiotemporal Crime Patterns across Six US Cities: Analyzing Stability and Change in Clusters and Outliers

Walter, Rebecca J.; Tillyer, Marie Skubak; Acolin, Arthur. (2022). Spatiotemporal Crime Patterns across Six US Cities: Analyzing Stability and Change in Clusters and Outliers. Journal Of Quantitative Criminology.

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Abstract

ObjectivesExamine the degree of crime concentration at micro-places across six large cities, the spatial clustering of high and low crime micro-places within cities, the presence of outliers within those clusters, and extent to which there is stability and change in micro-place classification over time. MethodsUsing crime incident data gathered from six U.S. municipal police departments (Chicago, Los Angeles, New York City, Philadelphia, San Antonio, and Seattle) and aggregated to the street segment, Local Moran‚Äö√Ñ√¥s I is calculated to identify statistically significant high and low crime clusters across each city and outliers within those clusters that differ significantly from their local spatial neighbors.ResultsWithin cities, the proportion of segments that are like their neighbors and fall within a statistically significant high or low crime cluster are relatively stable over time. For all cities, the largest proportion of street segments fell into the same classification over time (47.5% to 69.3%); changing segments were less common (4.7% to 20.5%). Changing clusters (i.e., segments that fell into both low and high clusters during the study) were rare. Outliers in each city reveal statistically significant street-to-street variability. ConclusionsThe findings revealed similarities across cities, including considerable stability over time in segment classification. There were also cross-city differences that warrant further investigation, such as varying levels of spatial clustering. Understanding stable and changing clusters and outliers offers an opportunity for future research to explore the mechanisms that shape a city's spatiotemporal crime patterns to inform strategic resource allocation at smaller spatial scales. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Keywords

Micro-places; Spatiotemporal Crime Patterns; Spatial Clusters; Spatial Outliers; No Terms Assigned

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.

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

Lingzi Wu

Lingzi Wu is an Assistant Professor with the Department of Construction Management (CM) at the University of Washington (UW). Prior to joining UW in September 2022, Dr. Wu served as a postdoctoral fellow in the Department of Civil and Environmental Engineering at University of Alberta, where she received her MSc and PhD in Construction Engineering and Management in 2013 and 2020 respectively. Prior to her PhD, Dr. Wu worked in the industrial construction sector as a project coordinator with PCL Industrial Management from 2013 to 2017.

An interdisciplinary scholar focused on advancing digital transformation in construction, Dr. Wu’s current research interests include (1) integration of advanced data analytics and complex system modeling to enhance construction practices and (2) development of human-in-the-loop decision support systems to improve construction performance (e.g., sustainability and safety). Dr. Wu has published 10 papers in top journals and conference proceedings, including the Journal of Construction Engineering and Management, Journal of Computing in Civil Engineering, and Automation in Construction. Her research and academic excellence has received notable recognition, including a “Best Paper Award” at the 17th International Conference on Modeling and Applied Simulation, and the outstanding reviewer award from the Journal of Construction Engineering and Management.

As an educator and mentor, Dr. Wu aims to create an inclusive, innovative, and interactive learning environment where students develop personal, technical, and transferable skills to grow today, tomorrow, and into the future.

Exposure of Bicyclists to Air Pollution in Seattle, Washington Hybrid Analysis Using Personal Monitoring and Land Use Regression

Hong, E-Sok Andy; Bae, Christine. (2012). Exposure of Bicyclists to Air Pollution in Seattle, Washington Hybrid Analysis Using Personal Monitoring and Land Use Regression. Transportation Research Record, 2270, 59 – 66.

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Abstract

The increase in urban bicycling facilities, raises public health concerns for potential exposure of bicyclists to traffic emissions. For an assessment of bicyclists' exposure to local traffic emissions, a hybrid approach is presented; it combines personal monitoring and a land use regression (LUR) model. Black carbon, a proxy variable for traffic-related air pollution, was measured with an Aethalometer along the predesignated bicycle route in Seattle, Washington, for 10 days, during a.m. and p.m. peak hours (20 sampling campaigns). Descriptive statistics and three-dimensional pollution maps were used to explore temporal variations and to identify pollution hot spots. The LUR model was developed to quantify the influence of spatial covariates on black carbon concentrations along the designated route. The results indicated that the black carbon concentrations fluctuated throughout the sampling periods and showed statistically significant diurnal and monthly patterns. The hot spot analysis suggests that proximity to traffic and other physical environments have important impacts on bicyclists' exposure and demand further investigation on the localized effects of traffic emissions on exposure levels. The LUR model explains 46% of the variations in black carbon concentrations, and significant relationships are found with types of bicycle route facility, wind speed, length of truck routes, and transportation and utility land uses. This research is the first application of the LUR approach in quantifying bicyclists' exposure to air pollution in transport microenvironments. This study provides a rationale for encouraging municipalities to develop effective strategies to mitigate the health risks of exposure to local traffic emissions in complex urban bicycling environments.

Keywords

Particulate Matter; Diesel Exhaust; Health; Model; Particles; Asthma; City

Stepping Towards Causation in Studies of Neighborhood and Environmental Effects: How Twin Research Can Overcome Problems of Selection and Reverse Causation

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

Health Impact Assessment: Considering Health in Transportation Decision Making in the United States

Wier, Megan L.; Schwartz, Michael; Dannenberg, Andrew L. (2015). Health Impact Assessment: Considering Health in Transportation Decision Making in the United States. TR News (0738-6826), 299, 11 – 16.

Abstract

The article talks about Health Impact Assessment (HIA) when it comes to transportation decision making in the U.S. and discusses the Collaboration between public health professionals and transportation in order to execute HIA.

Keywords

Health Impact Assessment; Public Health -- United States