Huang, R.; Moudon, A. V.; Cook, A. J.; Drewnowski, A. (2015). The Spatial Clustering of Obesity: Does the Built Environment Matter? Journal Of Human Nutrition & Dietetics, 28(6), 604 – 612.
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Abstract
BackgroundObesity rates in the USA show distinct geographical patterns. The present study used spatial cluster detection methods and individual-level data to locate obesity clusters and to analyse them in relation to the neighbourhood built environment. MethodsThe 2008-2009 Seattle Obesity Study provided data on the self-reported height, weight, and sociodemographic characteristics of 1602 King County adults. Home addresses were geocoded. Clusters of high or low body mass index were identified using Anselin's Local Moran's I and a spatial scan statistic with regression models that searched for unmeasured neighbourhood-level factors from residuals, adjusting for measured individual-level covariates. Spatially continuous values of objectively measured features of the local neighbourhood built environment (SmartMaps) were constructed for seven variables obtained from tax rolls and commercial databases. ResultsBoth the Local Moran's I and a spatial scan statistic identified similar spatial concentrations of obesity. High and low obesity clusters were attenuated after adjusting for age, gender, race, education and income, and they disappeared once neighbourhood residential property values and residential density were included in the model. ConclusionsUsing individual-level data to detect obesity clusters with two cluster detection methods, the present study showed that the spatial concentration of obesity was wholly explained by neighbourhood composition and socioeconomic characteristics. These characteristics may serve to more precisely locate obesity prevention and intervention programmes.
Keywords
Real Property; Ecology; Age Distribution; Anthropometry; Black People; Cluster Analysis (statistics); Communities; Computer Software; Epidemiological Research; Geographic Information Systems; Hispanic Americans; Mathematics; Obesity; Population Geography; Probability Theory; Race; Regression Analysis; Research Funding; Restaurants; Statistical Sampling; Self-evaluation; Sex Distribution; Shopping; Surveys; Telephones; Transportation; White People; Socioeconomic Factors; Body Mass Index; Data Analysis Software; Medical Coding; Statistical Models; Descriptive Statistics; Odds Ratio; Economics; Washington (state); Built Environment; Local Moran's I; Spatial Scan Statistic; Body-mass Index; Physical-activity; United-states; Risk-factors; Neighborhood; Association; Density; Disease; Disparities; Prevalence
Stewart, Orion T.; Moudon, Anne Vernez; Saelens, Brian E.; Lee, Chanam; Kang, Bumjoon; Doescher, Mark P. (2016). Comparing Associations between the Built Environment and Walking in Rural Small Towns and a Large Metropolitan Area. Environment And Behavior, 48(1), 13 – 36.
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Abstract
The association between the built environment (BE) and walking has been studied extensively in urban areas, yet little is known whether the same associations hold for smaller, rural towns. This analysis examined objective measures of the BE around participants' residence and their utilitarian and recreational walking from two studies, one in the urban Seattle area (n = 464) and the other in nine small U.S. towns (n = 299). After adjusting for sociodemographics, small town residents walked less for utilitarian purposes but more for recreational purposes. These differences were largely explained by differential associations of the BE on walking in the two settings. In Seattle, the number of neighborhood restaurants was positively associated with utilitarian walking, but in small towns, the association was negative. In small towns, perception of slow traffic on nearby streets was positively associated with recreational walking, but not in Seattle. These observations suggest that urban-rural context matters when planning BE interventions to support walking.
Keywords
Physical-activity; Utilitarian Walking; Transportation; Obesity; Adults; Travel; Urban; Prevalence; Strategies; Physical Activity; Walkability; City Planning; Urban Design; Community Health; Gis (geographic Information System); Gps (global Positioning System); Accelerometer; Effect Modification
Sun, Feiyang; Chen, Peng; Jiao, Junfeng. (2018). Promoting Public Bike-Sharing: A Lesson from the Unsuccessful Pronto System. Transportation Research: Part D, 63, 533 – 547.
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Abstract
In 2014, Seattle implemented its own bike-sharing system, Pronto. However, the system ultimately ceased operation three years later on March 17th, 2017. To learn from this failure, this paper seeks to understand factors that encourage, or discourage, bike-sharing trip generation and attraction at the station level. This paper investigates the effects of land use, roadway design, elevation, bus trips, weather, and temporal factors on three-hour long bike pickups and returns at each docking station. To address temporal autocorrelations and the nonlinear seasonality, the paper implements a generalized additive mixed model (GAMM) that incorporates the joint effects of a time metric and time-varying variables. The paper estimates models on total counts of pickups and returns, as well as pickups categorized by user types and by location. The results clarify that effects of hilly terrain and the rainy weather, two commonly perceived contributors to the failure. Additionally, results suggest that users in the University District, presumably mostly university students, tend to use shared bikes in neighborhoods with a higher household density and a higher percentage of residential land use, and make bike-sharing trips regardless workdays or non-workdays. The paper also contributes to the discussion on the relationship between public transportation service and bike-sharing. In general, users tend to use bike-sharing more at stations that have more scheduled bus trips nearby. However, some bike-sharing users may shift to bus services during peak hours and rainy weather. Several strategies are proposed accordingly to increase bike ridership in the future.
Keywords
Bicycle Sharing Programs; Urban Transportation; Transportation & The Environment; Land Use Planning; Time-varying Systems; Bike-sharing; Built Environment; Generalized Additive Mixed Model; Pronto; Temporal Factors; Built Environment Factors; Bicycle; Impact; Transportation; Walking; Usage
Le, Vi T.; Dannenberg, Andrew L. (2020). Moving Toward Physical Activity Targets by Walking to Transit: National Household Transportation Survey, 2001-2017. American Journal Of Preventive Medicine, 59(3), E115 – E123.
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Abstract
Introduction: Public transportation systems can help people engage in physical activity. This study assesses sociodemographic correlates and trends in the daily time spent walking to and from transit in the U.S. from 2001 to 2017. Methods: This cross-sectional study used data from the 2001, 2009, and 2017 National Household Transportation Survey. Data were analyzed in 2019 to assess the daily level of physical activity attained solely by walking to and from transit. Regression models were used to examine predictors of daily transit-associated walking. Results: Compared with the full National Household Transportation Survey sample, transit users who walked to and from transit tended to be younger, from households earning <$25,000 per year, in areas with rail infrastructure, and did not have a household-owned car. Transit walkers spent a median of 20 minutes per day (95% CI=18.5, 21.5) walking to and from transit in 2017, compared with a median of 19 minutes (95% CI=17.5, 20.5) in 2001. Among transit walkers, daily transitassociated physical activity was 27% higher for those residing in areas with rail infrastructure (adjusted coefficient=1.27, 95% CI=1.11, 1.46) and 34% higher for those from households earning $99,999 per year (adjusted coefficient=1.34, 95% CI=1.15, 1.56). Conclusions: As documented in a growing literature, most public transit trips include at least some walking; thus, efforts to encourage transit use are favorable to public health. Continued monitoring by transportation surveys is important as new forms of mobility and changing demographics may impact future transit use and associated physical activity. (C) 2020 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.
Keywords
Physical Activity; Household Surveys; Public Transit; Cross-sectional Method; Public Health; Walking; Exercise; Research Funding; Transportation; Replacing Sedentary Time; Public-transit; Travel; Mortality; Adults; Health; Work
Bassok, Alon; Hurvitz, Phil M.; Bae, C-H. Christine; Larson, Timothy. (2010). Measuring Neighbourhood Air Pollution: The Case of Seattle’s International District. Journal Of Environmental Planning & Management, 53(1), 23 – 39.
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Abstract
Current US regulatory air quality monitoring networks measure ambient levels of pollutants and cannot capture the effects of mobile sources at the micro-scale. Despite the fact that overall air quality has been getting better, more vulnerable populations (children, the elderly, minorities and the poor) continue to suffer from traffic-related air pollution. As development intensifies in urban areas, more people are exposed to road-related air pollution. However, the only consideration given to air quality, if any, is based on ambient measures. This paper uses an inexpensive, portable Particle Soot Absorption Photometer (PSAP) to measure Black Carbon (BC) emissions, a surrogate for diesel fuels emissions, in Seattle's International District. With the aid of a GPS receiver, street-level BC data were geocoded in real space-time. It was found that pollution levels differed substantially across the study area. The results show the need for street-level air pollution monitoring, revisions in current land use and transportation policies, and air quality planning practice.
Keywords
Emission Standards; Air Pollution; Atmospheric Deposition; Social Groups; Waste Products; Sanitary Landfills; Black Carbon; Freeway Air Pollution Sheds (faps); Land Use; Mobile Monitoring; Neighbourhood Air Quality; Aerosol Light-absorption; Respiratory Health; Coefficient; Exposure; Symptoms; Children; Pollutants; Particles; Exhaust; Asthma
Stewart, Orion. (2011). Findings from Research on Active Transportation to School and Implications for Safe Routes to School Programs. Journal Of Planning Literature, 26(2), 127 – 150.
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Abstract
This literature review identified common factors associated with active transportation to school (ATS). It used a conceptual framework of a child's commute mode to school to classify 480 variables from forty-two studies that were tested for association with ATS. Four factors most frequently influenced ATS: distance, income, traffic and crime fears, and parental attitudes and schedules. Regular ATS results in more physical activity but research is lacking on other outcomes. Safe Routes to School, a program designed to increase rates and safety of ATS, can use an understanding of these influences and outcomes to more effectively allocate its limited resources.
Keywords
Physical-activity Levels; Travel Mode; Urban Form; Environmental-factors; Elementary-schools; Weight Status; Walking; Children; Prevalence; Bus; Active Transportation To School; Safe Routes To School; Biking
Dannenberg, Andrew L.; Ricklin, Anna; Ross, Catherine L.; Schwartz, Michael; West, Julie; White, Steve; Wier, Megan L. (2014). Use of Health Impact Assessment for Transportation Planning Importance of Transportation Agency Involvement in the Process. Transportation Research Record, 2452, 71 – 80.
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Abstract
A health impact assessment (HIA) is a tool that can be used to inform transportation planners of the potential health consequences of their decisions. Although dozens of transportation-related HIAs have been completed in the United States, the characteristics of these HIAs and the interactions between public health professionals and transportation decision makers in these HIM have not been documented. A master list of completed HIAs was used to identify transportation-related HIAs. Seventy-three transportation-related HIAs conducted in 22 states between 2004 and 2013 were identified. The HIAs were conducted for projects such as road redevelopments, bridge replacements, and development of trails and public transit. Policies such as road pricing, transit service levels, speed limits, complete streets, and safe routes to schools were also assessed. Five HIAs in which substantial interactions between public health and transportation professionals took place during and after the HIA were examined in detail and included HIAs of the road pricing policy in San Francisco, California; a bridge replacement in Seattle, Washington; new transit lines in Baltimore, Maryland, and Portland, Oregon; and the BeltLine transit, trails, and parks project in Atlanta, Georgia. Recommendations from the HIAs led to changes in decisions in some cases and helped to raise awareness of health issues by transportation decision makers in all cases. HIAs are now used for many topics in transportation. The range of involvement of transportation decision makers in the conduct of HIAs varies. These case studies may serve as models for the conduct of future transportation-related HIAs, because the involvement of transportation agencies may increase the likelihood that an HIA will influence subsequent decisions.
Keywords
Policy; Inequalities; Benefits; Justice; Oregon
Jiao, J.; Moudon, A. V.; Kim, S. Y.; Hurvitz, P. M.; Drewnowski, A. (2015). Health Implications of Adults’ Eating at and Living Near Fast Food or Quick Service Restaurants. Nutrition & Diabetes, 5.
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Abstract
BACKGROUND: This paper examined whether the reported health impacts of frequent eating at a fast food or quick service restaurant on health were related to having such a restaurant near home. METHODS: Logistic regressions estimated associations between frequent fast food or quick service restaurant use and health status, being overweight or obese, having a cardiovascular disease or diabetes, as binary health outcomes. In all, 2001 participants in the 2008-2009 Seattle Obesity Study survey were included in the analyses. RESULTS: Results showed eating >= 2 times a week at a fast food or quick service restaurant was associated with perceived poor health status, overweight and obese. However, living close to such restaurants was not related to negative health outcomes. CONCLUSIONS: Frequent eating at a fast food or quick service restaurant was associated with perceived poor health status and higher body mass index, but living close to such facilities was not.
Keywords
Body-mass Index; Socioeconomic-status; Built Environment; Obesity; Association; Consumption; Weight; Proximity; Outlets; Establishments
Way, Thaisa. (2016). The Urban University’s Hybrid Campus. Journal Of Landscape Architecture, 11(1), 42 – 55.
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Abstract
With the growth of urban campuses in the twenty-first century, how can landscape architecture foster the innovation associated with cities and urban neighbourhoods? In Seattle, West Campus at the University of Washington serves as a good urban neighbour while engaging the traditional experiences of a campus. Additionally, the design suggests how an urban campus might generate the culture of an urban innovation district. The contribution of landscapes to innovation districts has rarely been considered in campus design because the focus has been on the architecture of the buildings and the culture of collaboration as social phenomena. This paper explores how the public landscapes of parks, courtyards, and streets shape the experience of an innovation district and contribute to fostering creativity and serendipity. As an extension, the paper suggests the importance of universities in the creation and stewardship of vibrant, creative, and resilient cities.
Keywords
City Planning; Innovation District; Student Residential Planning; University Landscape Design; Urban Campus
Chen, Peng; Hu, Songhua; Shen, Qing; Lin, Hangfei; Xie, Chi. (2019). Estimating Traffic Volume for Local Streets with Imbalanced Data. Transportation Research Record, 2673(3), 598 – 610.
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Abstract
Annual average daily traffic (AADT) is an important measurement used in traffic engineering. Local streets are major components of a road network. However, automatic traffic recorders (ATRs) used to collect AADT are often limited to arterial roads, and such information is, therefore, often unavailable for local streets. Estimating AADT on local streets becomes a necessity as local street traffic continues to grow and the capacity of arterial roads becomes insufficient. A challenge is that an under-represented sample of local street AADT may result in biased estimation. A synthetic minority oversampling technique (SMOTE) is applied to oversample local streets to correct the imbalanced sampling among different road types. A generalized linear mixed model (GLMM) is employed to estimate AADT incorporating various independent variables, including factors of roadway design, socio-demographics, and land use. The model is examined with an AADT dataset from Seattle, WA. Results show that: (1) SMOTE helps to correct imbalanced sampling proportions and improve model performance significantly; (2) the number of lanes and the number of crosswalks are both positively associated with AADT; (3) road segments located in areas with a higher population density or more mixed land use have a higher AADT; (4) distance to the nearest arterial road is negatively correlated with AADT; and (5) AADT creates spatial spillover effects on neighboring road segments. The combination of SMOTE and GLMM improves the estimation accuracy on AADT, which contributes to better data for transportation planning and traffic monitoring, and to cost saving on data collection.
Keywords
Average; Prediction; Network; County