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
Chen, Peng. (2015). Built Environment Factors in Explaining the Automobile-Involved Bicycle Crash Frequencies: A Spatial Statistic Approach. Safety Science, 79, 336 – 343.
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Abstract
The objective of this study is to understand the relationship between built environment factors and bicycle crashes with motor vehicles involved in Seattle. The research method employed is a Poisson lognormal random effects model using hierarchal Bayesian estimation. The Traffic Analysis Zone (TAZ) is selected as the unit of analysis to quantify the built environment factors. The assembled dataset provides a rich source of variables, including road network, street elements, traffic controls, travel demand, land use, and socio-demographics. The research questions are twofold: how are the built environment factors associated with the bicycle crashes, and are the TAZ-based bicycle crashes spatially correlated? The findings of this study are: (1) safety improvements should focus on places with more mixed land use; (2) off-arterial bicycle routes are safer than on-arterial bicycle routes; (3) TAZ-based bicycle crashes are spatially correlated; (4) TAZs with more road signals and street parking signs are likely to have more bicycle crashes; and (5) TAZs with more automobile trips have more bicycle crashes. For policy implications, the results suggest that the local authorities should lower the driving speed limits, regulate cycling and driving behaviors in areas with mixed land use, and separate bike lanes from road traffic. (C) 2015 Elsevier Ltd. All rights reserved.
Keywords
Injury Crashes; Risk Analysis; Models; Infrastructure; Dependence; Counts; Level; Bicycle Crash Frequency; Hierarchal Bayesian Estimation; Poisson Lognormal Random Effects Model; Built Environment; Traffic Analysis Zone
Chen, Peng; Shen, Qing. (2016). Built Environment Effects on Cyclist Injury Severity in Automobile-Involved Bicycle Crashes. Accident Analysis & Prevention, 86, 239 – 246.
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Abstract
This analysis uses a generalized ordered logit model and a generalized additive model to estimate the effects of built environment factors on cyclist injury severity in automobile-involved bicycle crashes, as well as to accommodate possible spatial dependence among crash locations. The sample is drawn from the Seattle Department of Transportation bicycle collision profiles. This study classifies the cyclist injury types as property damage only, possible injury, evident injury, and severe injury or fatality. Our modeling outcomes show that: (1) injury severity is negatively associated with employment density; (2) severe injury or fatality is negatively associated with land use mixture; (3) lower likelihood of injuries is observed for bicyclists wearing reflective clothing; (4) improving street lighting can decrease the likelihood of cyclist injuries; (5) posted speed limit is positively associated with the probability of evident injury and severe injury or fatality; (6) older cyclists appear to be more vulnerable to severe injury or fatality; and (7) cyclists are more likely to be severely injured when large vehicles are involved in crashes. One implication drawn from this study is that cities should increase land use mixture and development density, optimally lower posted speed limits on streets with both bikes and motor vehicles, and improve street lighting to promote bicycle safety. In addition, cyclists should be encouraged to wear reflective clothing. (C) 2015 Elsevier Ltd. All rights reserved.
Keywords
Cycling Injuries; Traffic Accidents; Transportation Planning; Data Analysis; Employment; Built Environment; Cyclist Injury Severity; Generalized Additive Model; Generalized Ordered Logit Model; Ordered Response Model; United-states; Helmet; Frameworks; Driver; Risk
Pan, Haixiao; Li, Jing; Chen, Peng. (2016). Study on the Ownership of Motorized and Non-Motorized Vehicles in Suburban Metro Station Areas: A Structural Equation Approach. Urban Rail Transit, 2(2), 47 – 58.
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Abstract
As Chinese megacities are experiencing a large-scale motorization and suburbanization, an ever greater number of households are relocated to suburban towns. The increasing average travel distance surely encourages car growth. China is now the world's largest car consumer, resulting in a series of unforeseen environmental and public health issues. On the other hand, scooters, electric bikes, and motorcycles become attractive options to substitute non-motorized bicycles. The ongoing demographic changes should also be taken in account. China has a rapidly aging population and a higher birth rate following reforms to the one-child policy allowing couples to have a second child. These changes will lead to a dramatic alteration of the household composition in the near future. Under above emerging contexts, this study aims to understand what implies the ownership of motorized and non-motorized vehicles in suburban metro station areas by means of a structural equation model. The data employed in this study are based on a household survey collected from three neighborhoods in Shanghai suburban metro station areas in 2010. The major findings include: (1) Income is a decisive element in car ownership. Specifically, high-income households have higher propensity to own a car, while middle and poor income families tend to own scooters, electric bikes, motorcycles, or bicycles. (2) Workplace built environment features or mode preferences are not essential to understanding vehicle ownership in Chinese context. (3) Stem families are more likely to own cars; the presence of a child or a senior family member increases the probability of owning a car by enlarging the household. (4) The results estimated for core family and DINK (couple with no child) family are highly consistent, and these families are less likely to own cars. Therefore, transport policies may focus more on households. Providing safe, pleasant, and efficient pedestrian and bicycle paths for children and seniors may decrease the attractiveness of owning cars.
Keywords
Suburban Metro Station Areas; Ownership Of Motorized And Non-motorized Vehicles; Built Environment; Mode Preferences; Family Composition; Structural Equation Model
Cova, Thomas J.; Dennison, Philip E.; Li, Dapeng; Drews, Frank A.; Siebeneck, Laura K.; Lindell, Michael K. (2017). Warning Triggers in Environmental Hazards: Who Should Be Warned to Do What and When? Risk Analysis, 37(4), 601 – 611.
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Abstract
Determining the most effective public warnings to issue during a hazardous environmental event is a complex problem. Three primary questions need to be answered: Who should take protective action? What is the best action? and When should this action be initiated? Warning triggers provide a proactive means for emergency managers to simultaneously answer these questions by recommending that a target group take a specified protective action if a preset environmental trigger condition occurs (e.g., warn a community to evacuate if a wildfire crosses a proximal ridgeline). Triggers are used to warn the public across a wide variety of environmental hazards, and an improved understanding of their nature and role promises to: (1) advance protective action theory by unifying the natural, built, and social themes in hazards research into one framework, (2) reveal important information about emergency managers' risk perception, situational awareness, and threat assessment regarding threat behavior and public response, and (3) advance spatiotemporal models for representing the geography and timing of disaster warning and response (i.e., a coupled natural-built-social system). We provide an overview and research agenda designed to advance our understanding and modeling of warning triggers.
Keywords
Situation Awareness; Evacuation; Model; Management; Simulation; Decisions; Vehicles; Support; Systems; Hazards; Protective Actions; Warning Systems; Emergency Communications Systems; Disasters; Emergency Preparedness; Environmental Hazards; Environmental Conditions; Public Concern; Risk Perception; Emergency Management; Situational Awareness; Information Management; Geography; Emergency Warning Programs; Wildfires; Action; Risk Assessment; Timing; Warnings
Scully, Jason Y.; Moudon, Anne Vernez; Hurvitz, Philip M.; Aggarwal, Anju; Drewnowski, Adam. (2017). GPS or Travel Diary: Comparing Spatial and Temporal Characteristics of Visits to Fast Food Restaurants and Supermarkets. Plos One, 12(4).
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Abstract
To assess differences between GPS and self-reported measures of location, we examined visits to fast food restaurants and supermarkets using a spatiotemporal framework. Data came from 446 participants who responded to a survey, filled out travel diaries of places visited, and wore a GPS receiver for seven consecutive days. Provided by Public Health Seattle King County, addresses from food permit data were matched to King County tax assessor parcels in a GIS. A three-step process was used to verify travel-diary reported visits using GPS records: (1) GPS records were temporally matched if their timestamps were within the time window created by the arrival and departure times reported in the travel diary; (2) the temporally matched GPS records were then spatially matched if they were located in a food establishment parcel of the same type reported in the diary; (3) the travel diary visit was then GPS-sensed if the name of food establishment in the parcel matched the one reported in the travel diary. To account for errors in reporting arrival and departure times, GPS records were temporally matched to three time windows: the exact time, +/-10 minutes, and +/-30 minutes. One third of the participants reported 273 visits to fast food restaurants; 88% reported 1,102 visits to supermarkets. Of these, 77.3 percent of the fast food and 78.6 percent supermarket visits were GPS-sensed using the +/-10-minute time window. At this time window, the mean travel-diary reported fast food visit duration was 14.5 minutes (SD 20.2), 1.7 minutes longer than the GPS-sensed visit. For supermarkets, the reported visit duration was 23.7 minutes (SD 18.9), 3.4 minutes longer than the GPS-sensed visit. Travel diaries provide reasonably accurate information on the locations and brand names of fast food restaurants and supermarkets participants report visiting.
Keywords
Global Positioning System; Fast Food Restaurants; Self-evaluation; Public Health; Supermarkets; Geoinformatics; Comparative Studies; Biology And Life Sciences; Computer And Information Sciences; Diet; Earth Sciences; Eating; Engineering And Technology; Food; Food Consumption; Geographic Information Systems; Geography; Medicine And Health Sciences; Nutrition; Physiological Processes; Physiology; Public And Occupational Health; Research And Analysis Methods; Research Article; Research Design; Survey Research; Surveys; Transportation; Global Positioning Systems; Environment; Neighborhood; Exposure; Health; Consumption; Tracking; Adults; Associations; Dietary
Stewart, Orion T.; Moudon, Anne Vernez; Littman, Alyson J.; Seto, Edmund; Saelens, Brian E. (2018). The Association between Park Facilities and Duration of Physical Activity During Active Park Visits. Journal Of Urban Health, 95(6), 869 – 880.
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Abstract
Public parks provide places for urban residents to obtain physical activity (PA), which is associated with numerous health benefits. Adding facilities to existing parks could be a cost-effective approach to increase the duration of PA that occurs during park visits. Using objectively measured PA and comprehensively measured park visit data among an urban community-dwelling sample of adults, we tested the association between the variety of park facilities that directly support PA and the duration of PA during park visits where any PA occurred. Cross-classified multilevel models were used to account for the clustering of park visits (n=1553) within individuals (n=372) and parks (n=233). Each additional different PA facility at a park was independently associated with a 6.8% longer duration of PA bouts that included light-intensity activity, and an 8.7% longer duration of moderate to vigorous PA time. Findings from this study are consistent with the hypothesis that more PA facilities increase the amount of PA that visitors obtain while already active at a park.
Keywords
Park Facilities; Physical Activity; Park Use; Recreation; Built Environment; Global Positioning System; Accelerometer; Gis; Gps; Accelerometer Data; United-states; Adults; Proximity; Features; Walking; Size; Attractiveness; Improvements; Environment; Parks & Recreation Areas; Parks; Luminous Intensity; Clustering; Urban Areas
Kang, Mingyu; Moudon, Anne Vernez; Kim, Haena; Boyle, Linda Ng. (2019). Intersections and Non-Intersections: A Protocol for Identifying Pedestrian Crash Risk Locations in GIS. International Journal Of Environmental Research And Public Health, 16(19).
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Abstract
Intersection and non-intersection locations are commonly used as spatial units of analysis for modeling pedestrian crashes. While both location types have been previously studied, comparing results is difficult given the different data and methods used to identify crash-risk locations. In this study, a systematic and replicable protocol was developed in GIS (Geographic Information System) to create a consistent spatial unit of analysis for use in pedestrian crash modelling. Four publicly accessible datasets were used to identify unique intersection and non-intersection locations: Roadway intersection points, roadway lanes, legal speed limits, and pedestrian crash records. Two algorithms were developed and tested using five search radii (ranging from 20 to 100 m) to assess the protocol reliability. The algorithms, which were designed to identify crash-risk locations at intersection and non-intersection areas detected 87.2% of the pedestrian crash locations (r: 20 m). Agreement rates between algorithm results and the crash data were 94.1% for intersection and 98.0% for non-intersection locations, respectively. The buffer size of 20 m generally showed the highest performance in the analyses. The present protocol offered an efficient and reliable method to create spatial analysis units for pedestrian crash modeling. It provided researchers a cost-effective method to identify unique intersection and non-intersection locations. Additional search radii should be tested in future studies to refine the capture of crash-risk locations.
Keywords
Traffic Crash; Walking; Collisions; Accidents; Models; Pedestrian Safety; Spatial Autocorrelation; Algorithm
Wang, Kaiwen; Liu, Xiaomang; Tian, Wei; Li, Yanzhong; Liang, Kang; Liu, Changming; Li, Yuqi; Yang, Xiaohua. (2019). Pan Coefficient Sensitivity to Environment Variables across China. Journal Of Hydrology, 572, 582 – 591.
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Abstract
Data of open water evaporation (E-ow), such as evaporation of lake and reservoir, have been widely used in hydraulic and hydrological engineering projects, and water resources planning and management in agriculture, forestry and ecology. Because of the low-cost and maneuverability, measuring the evaporation of a pan has been widely regarded as a reliable approach to estimate E-ow through multiplying an appropriate pan coefficient (K-p). K-p is affected by geometry and materials of a pan, and complex surrounding environment variables. However, the relationship between K-p and different environment variables is unknown. Thus, this study chose China D20 pan as an example, used meteorological observations from 767 stations and introduced the latest PenPan model to analyze the sensitivity of K-p to different environment variables. The results show that, the distribution of annual K-p had a strong spatial gradient. For all the stations, annual K-p ranged from 0.31 to 0.89, and decreased gradually from southeast to northwest. The sensitivity analysis shows that for China as a whole, K-p was most sensitive to relative humidity, followed by air temperature, wind speed and sunshine duration. For 767 stations in China, K-p was most sensitive to relative humidity for almost all the stations. For stations north of Yellow River, wind speed and sunshine duration were the next sensitive variables; while for stations south of Yellow River, air temperature was the next sensitive variable. The method introduced in this study could benefit estimating and predicting K-p under future changing environment.
Keywords
Atmospheric Temperature; Hydraulic Engineering; Meteorological Observations; Humidity; Water Supply; Evaporation (meteorology); Sunshine; Lake Management; China; Kp Most Sensitive To Relative Humidity; Open Water Evaporation; Pan Coefficient (kp); Pan Evaporation; Sensitivity Analysis; Reference Evapotranspiration; Reference Crop; Evaporation; Water; Model; Pan Coefficient (k-p); K-p Most Sensitive To Relative Humidity; Air Temperature; Ecology; Forestry; Geometry; Hydrologic Engineering; Lakes; Maneuverability; Meteorological Data; Models; Planning; Prediction; Relative Humidity; Solar Radiation; Wind Speed; Yellow River
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