Quistberg, D. Alex; Howard, Eric J.; Ebel, Beth E.; Moudon, Anne V.; Saelens, Brian E.; Hurvitz, Philip M.; Curtin, James E.; Rivara, Frederick P. (2015). Multilevel Models for Evaluating the Risk of Pedestrian-Motor Vehicle Collisions at Intersections and Mid-Blocks. Accident Analysis & Prevention, 84, 99 – 111.
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Abstract
Walking is a popular form of physical activity associated with clear health benefits. Promoting safe walking for pedestrians requires evaluating the risk of pedestrian motor vehicle collisions at specific roadway locations in order to identify where road improvements and other interventions may be needed. The objective of this analysis was to estimate the risk of pedestrian collisions at intersections and mid-blocks in Seattle, WA. The study used 2007-2013 pedestrian motor vehicle collision data from police reports and detailed characteristics of the microenvironment and macroenvironment at intersection and mid-block locations. The primary outcome was the number of pedestrian motor vehicle collisions over time at each location (incident rate ratio [IRR] and 95% confidence interval [95% CI]). Multilevel mixed effects Poisson models accounted for correlation within and between locations and census blocks over time. Analysis accounted for pedestrian and vehicle activity (e.g., residential density and road classification). In the final multivariable model, intersections with 4 segments or 5 or more segments had higher pedestrian collision rates compared to mid-blocks. Non-residential roads had significantly higher rates than residential roads, with principal arterials having the highest collision rate. The pedestrian collision rate was higher by 9% per 10 feet of street width. Locations with traffic signals had twice the collision rate of locations without a signal and those with marked crosswalks also had a higher rate. Locations with a marked crosswalk also had higher risk of collision. Locations with a one-way road or those with signs encouraging motorists to cede the right-of-way to pedestrians had fewer pedestrian collisions. Collision rates were higher in locations that encourage greater pedestrian activity (more bus use, more fast food restaurants, higher employment, residential, and population densities). Locations with higher intersection density had a lower rate of collisions as did those in areas with higher residential property values. The novel spatiotemporal approach used that integrates road/crossing characteristics with surrounding neighborhood characteristics should help city agencies better identify high-risk locations for further study and analysis. Improving roads and making them safer for pedestrians achieves the public health goals of reducing pedestrian collisions and promoting physical activity. (C) 2015 Elsevier Ltd. All rights reserved.
Keywords
Pedestrian Accidents; Road Interchanges & Intersections; Built Environment; Pedestrian Crosswalks; Correlation (statistics); Collision Risk; Multilevel Model; Pedestrians; Geographic Information-systems; Road-traffic Injuries; Physical-activity; Signalized Intersections; Impact Speed; Urban Form; Land-use; Safety; Walking
Kang, Bumjoon; Moudon, Anne V.; Hurvitz, Philip M.; Saelens, Brian E. (2018). Increased Walking’s Additive and No Substitution Effect on Total Physical Activity. Medicine & Science In Sports & Exercise, 50(3), 468 – 475.
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Abstract
Purpose We assessed the associations between a change in time spent walking and a change in total physical activity (PA) time within an urban living adult sample to test for additive or substitution effects. Methods Participants living in the greater Seattle area were assessed in 2008-2009 and again 1-2 yr later (2010-2011). At each time point, they wore accelerometers and GPS units and recorded trips and locations in a travel diary for seven consecutive days. These data streams were combined to derive a more objective estimate of walking and total PA. Participants also completed the International Physical Activity Questionnaire to provide self-reported estimates of walking and total PA. Regression analyses assessed the associations between within-participant changes in objective and self-reported walking and total PA. Results Data came from 437 participants. On average, a 1-min increase in total walking was associated with an increase in total PA of 1 min, measured by objective data, and 1.2-min, measured by self-reported data. A similar additive effect was consistently found with utilitarian, transportation, or job-related walking, measured by both objective and self-reported data. For recreational walking, the effect of change was mixed between objective and self-reported results. Conclusion Both objective and self-reported data confirmed an additive effect of utilitarian and total walking on PA.
Keywords
Accelerometers; Global Positioning System; Metropolitan Areas; Questionnaires; Recreation; Self-evaluation; Time; Walking; Physical Activity; Accelerometer; Gps; Ipaq; Longitudinal Study; Self-reported Measures; Light-rail Construction; Built Environment; Accelerometer Data; Older-adults; Urban Form; Transit Use; Travel; Neighborhood; Interventions; Calibration
Mooney, Stephen J.; Hurvitz, Philip M.; Moudon, Anne Vernez; Zhou, Chuan; Dalmat, Ronit; Saelens, Brian E. (2020). Residential Neighborhood Features Associated with Objectively Measured Walking Near Home: Revisiting Walkability Using the Automatic Context Measurement Tool (ACMT). Health & Place, 63.
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Abstract
Many distinct characteristics of the social, natural, and built neighborhood environment have been included in walkability measures, and it is unclear which measures best describe the features of a place that support walking. We developed the Automatic Context Measurement Tool, which measures neighborhood environment characteristics from public data for any point location in the United States. We explored these characteristics in home neighborhood environments in relation to walking identified from integrated GPS, accelerometer, and travel log data from 681 residents of King Country, WA. Of 146 neighborhood characteristics, 92 (63%) were associated with walking bout counts after adjustment for individual characteristics and correction for false discovery. The strongest built environment predictor of walking bout count was housing unit count. Models using data-driven and a priori defined walkability measures exhibited similar fit statistics. Walkability measures consisting of different neighborhood characteristic measurements may capture the same underlying variation in neighborhood conditions.
Keywords
Built-environment; Physical-activity; Transit; Density; Obesity; Weight; Time; Gps; American Community Survey; Epa Walkability Index; Neighborhood Environment-wide Association; Study; Walking Bouts
Doescher, Mark P.; Lee, Chanam; Berke, Ethan M.; Adachi-mejia, Anna M.; Lee, Chun-kuen; Stewart, Orion; Patterson, Davis G.; Hurvitz, Philip M.; Carlos, Heather A.; Duncan, Glen E.; Moudon, Anne Vernez. (2014). The Built Environment and Utilitarian Walking in Small U.S. Towns. Preventive Medicine, 69, 80 – 86.
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Abstract
Objectives. The role of the built environment on walking in rural United States (U.S.) locations is not well characterized. We examined self-reported and measured built environment correlates of walking for utilitarian purposes among adult residents of small rural towns. Methods. In 2011-12, we collected telephone survey and geographic data from 2152 adults in 9 small towns from three U.S. regions. We performed mixed-effects logistic regression modeling to examine relationships between built environment measures and utilitarian walking (any versus none; high [>= 150 min per week] versus low [<150 min per week]) to retail, employment and public transit destinations. Results. Walking levels were lower than those reported for populations living in larger metropolitan areas. Environmental factors significantly (p < 0.05) associated with higher odds of utilitarian walking in both models included self-reported presence of crosswalks and pedestrian signals and availability of park/natural recreational areas in the neighborhood, and also objectively measured manufacturing land use. Conclusions. Environmental factors associated with utilitarian walking in cities and suburbs were important in small rural towns. Moreover, manufacturing land use was associated with utilitarian walking. Modifying the built environment of small towns could lead to increased walking in a sizeable segment of the U.S. population. (C) 2014 Elsevier Inc. All rights reserved.
Keywords
Cities & Towns -- Environmental Conditions; Walking; Telephone Surveys; Logistic Regression Analysis; Public Transit; Cities & Towns; Rural Conditions; United States; Exercise/physical Activity; Health Promotion; Physical Environment; Prevention; Rural Health; Social Environment; Physical-activity; Postmenopausal Women; Adults; Health; Risk; Transportation; Associations; Neighborhood; Travel; Determinants
Baek, So-Ra; Moudon, Anne Vernez; Saelens, Brian E.; Kang, Bumjoon; Hurvitz, Philip M.; Bae, Chang-hee Christine. (2016). Comparisons of Physical Activity and Walking between Korean Immigrant and White Women in King County, WA. Journal Of Immigrant & Minority Health, 18(6), 1541 – 1546.
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Abstract
Immigrant and minority women are less physically active than White women particularly during leisure time. However, prior research demonstrates that reported household physical activity (PA) and non-leisure time walking/biking were higher among the former. Using accelerometers, GPS, and travel logs, transport-related, home-based, and leisure time PA were measured objectively for 7 days from a convenience sample of 60 first-generation Korean immigrant women and 69 matched White women from the Travel Assessment and Community Project in King County, Washington. Time spent in total PA, walking, and home-based PA was higher among Whites than Korean immigrants regardless of PA type or location. 58 % of the White women but only 20 % of the Korean women met CDC's PA recommendations. Socio-economic status, psychosocial factors, and participants' neighborhood built environmental factors failed to account for the observed PA differences between these groups.
Keywords
Accelerometer; Gps; Korean Immigrant Women; Objective Measures; Physical Activity; Walking; White Women; Nonleisure Time; Leisure-time; Environment; Transportation; Adults; Women; Socioeconomic Status; Time Use; Home Based; Environmental Aspects; Economic Status; Immigrants; Leisure; Socioeconomic Factors; Bicycles; Psychosocial Factors; Comparative Analysis; Minority & Ethnic Groups; Physical Fitness; Regression Analysis; Accelerometers; Travel; Traveltime; Environmental Factors; Recreation; Neighborhoods; Hispanic Americans; Global Positioning Systems--gps; Social Support; Noncitizens; Data Collection; Asian Americans; Psychological Aspects; Households; White People; Asian People; King County Washington; United States--us
Kang, Mingyu; Moudon, Anne V.; Hurvitz, Philip M.; Saelens, Brian E. (2018). Capturing Fine-Scale Travel Behaviors: A Comparative Analysis between Personal Activity Location Measurement System (PALMS) and Travel Diary. International Journal Of Health Geographics, 17(1).
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Abstract
BackgroundDevice-collected data from GPS and accelerometers for identifying active travel behaviors have dramatically changed research methods in transportation planning and public health. Automated algorithms have helped researchers to process large datasets with likely fewer errors than found in other collection methods (e.g., self-report travel diary). In this study, we compared travel modes identified by a commonly used automated algorithm (PALMS) that integrates GPS and accelerometer data with those obtained from travel diary estimates.MethodsSixty participants, who made 2100 trips during seven consecutive days of data collection, were selected from among the baseline sample of a project examining the travel behavior impact of a new light rail system in the greater Seattle, WA (USA) area. GPS point level analyses were first conducted to compare trip/place and travel mode detection results using contingency tables. Trip level analyses were then performed to investigate the effect of proportions of time overlap between travel logs and device-collected data on agreement rates. Global performance (with all subjects' data combined) and subject-level performance of the algorithm were compared at the trip level.ResultsAt the GPS point level, the overall agreement rate of travel mode detection was 77.4% between PALMS and the travel diary. The agreement rate for vehicular trip detection (84.5%) was higher than for bicycling (53.5%) and walking (58.2%). At the trip level, the global performance and subject-level performance of the PALMS algorithm were 46.4% and 42.4%, respectively. Vehicular trip detection showed highest agreement rates in all analyses. Study participants' primary travel mode and car ownership were significantly related to the subject-level mode agreement rates.ConclusionsThe PALMS algorithm showed moderate identification power at the GPS point level. However, trip level analyses found lower agreement rates between PALMS and travel diary data, especially for active transportation. Testing different PALMS parameter settings may serve to improve the detection of active travel and help expand PALMS's applicability in geographically different urbanized areas with a variety of travel modes.
Keywords
Transportation Planning; Public Health; Accelerometers; Global Positioning System; Voyages & Travels; Cycling; Algorithms; Accelerometer; Automated Algorithm; Gis; Gps; Places; Trips; Global Positioning Systems; Physical-activity; Data-collection; Health Research; Gps Data; Accelerometry; Validity
Rose, Chelsea M.; Gupta, Shilpi; Buszkiewicz, James; Ko, Linda K.; Mou, Jin; Cook, Andrea; Moudon, Anne Vernez; Aggarwal, Anju; Drewnowski, Adam. (2020). Small Increments in Diet Cost Can Improve Compliance with the Dietary Guidelines for Americans. Social Science & Medicine, 266.
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Abstract
Adherence to the Dietary Guidelines for Americans (DGA) may involve higher diet costs. This study assessed the relation between two measures of food spending and diet quality among adult participants (N = 768) in the Seattle Obesity Study (SOS III). All participants completed socio-demographic and food expenditure surveys and the Fred Hutch food frequency questionnaire. Dietary intakes were joined with local supermarket prices to estimate individual-level diet costs. Healthy Eating Index (HEI-2015) scores measured compliance with DGA. Multiple linear regressions using Generalized Estimating Equations with robust standard errors showed that lower food spending was associated with younger age, Hispanic ethnicity, and lower socioeconomic status. Even though higher HEI-2015 scores were associated with higher diet costs per 2000 kcal, much individual variability was observed. A positive curvilinear relationship was observed in adjusted models. At lower cost diets, a $100/ month increase in cost (from $150 to $250) was associated with a 20.6% increase in HEI-2015. For higher levels of diet cost (from $350 to $450) there were diminishing returns (2.8% increase in HEI2015). These findings indicate that increases in food spending at the lower end of the range have the most potential to improve diet quality.
Keywords
Healthy Eating Index; Income Inequality; Quality; Obesity; Adults; Expenditure; Disparities; Strategy; Outcomes; Scores; Food Expenditures; Diet Costs; Food Shopping; Diet Quality; Hei-2015; Ses
Drewnowski, A.; Moudon, A. V.; Jiao, J.; Aggarwal, A.; Charreire, H.; Chaix, B. (2014). Food Environment and Socioeconomic Status Influence Obesity Rates in Seattle and in Paris. International Journal Of Obesity, 38(2), 306 – 314.
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Abstract
OBJECTIVE: To compare the associations between food environment at the individual level, socioeconomic status (SES) and obesity rates in two cities: Seattle and Paris. METHODS: Analyses of the SOS (Seattle Obesity Study) were based on a representative sample of 1340 adults in metropolitan Seattle and King County. The RECORD (Residential Environment and Coronary Heart Disease) cohort analyses were based on 7131 adults in central Paris and suburbs. Data on sociodemographics, health and weight were obtained from a telephone survey (SOS) and from in-person interviews (RECORD). Both studies collected data on and geocoded home addresses and food shopping locations. Both studies calculated GIS (Geographic Information System) network distances between home and the supermarket that study respondents listed as their primary food source. Supermarkets were further stratified into three categories by price. Modified Poisson regression models were used to test the associations among food environment variables, SES and obesity. RESULTS: Physical distance to supermarkets was unrelated to obesity risk. By contrast, lower education and incomes, lower surrounding property values and shopping at lower-cost stores were consistently associated with higher obesity risk. CONCLUSION: Lower SES was linked to higher obesity risk in both Paris and Seattle, despite differences in urban form, the food environments and in the respective systems of health care. Cross-country comparisons can provide new insights into the social determinants of weight and health.
Keywords
Obesity; Health & Social Status; Social Status; Supermarkets; Grocery Shopping; Physiology; Body-mass Index; Dietary Energy Density; Atherosclerosis Risk; Weight Status; Us Adults; Associations; Health; French; Access; Socioeconomic Status (ses); Access To Supermarket; Food Environment; Food Shopping
Drewnowski, Adam; Aggarwal, Anju; Cook, Andrea; Stewart, Orion; Moudon, Anne Vernez. (2016). Geographic Disparities in Healthy Eating Index Scores (HEI-2005 and 2010) by Residential Property Values: Findings from Seattle Obesity Study (SOS). Preventive Medicine, 83, 46 – 55.
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Abstract
Background. Higher socioeconomic status (SES) has been linked with higher-quality diets. New GIS methods allow for geographic mapping of diet quality at a very granular level. Objective. To examine the geographic distribution of two measures of diet quality: Healthy Eating Index (HEI 2005 and HEI 2010) in relation to residential property values in Seattle-King County. Methods. The Seattle Obesity Study (SOS) collected data from a population-based sample of King County adults in 2008-09. Socio-demographic data were obtained by 20-min telephone survey. Dietary data were obtained from food frequency questionnaires (FFQs). Home addresses were geocoded to the tax parcel and residential property values were obtained from the King County tax assessor. Multivariable regression analyses using 1116 adults tested associations between SES variables and diet quality measured (HEI scores). Results. Residential property values, education, and incomes were associated with higher HEI scores in bivariate analyses. Property values were not collinear with either education or income. In adjusted multivariable models, education and residential property were better associated with HEI, compared to than income. Mapping of HEI-2005 and HEI-2010 at the census block level illustrated the geographic distribution of diet quality across Seattle-King County. Conclusion. The use of residential property values, an objective measure of SES, allowed for the first visual exploration of diet quality at high spatial resolution: the census block level. (C) 2015 Elsevier Inc. All rights reserved.
Keywords
Obesity Treatment; Prevention Of Obesity; Disease Mapping; Socioeconomics; Multivariate Analysis; Population Geography; Census; Diet; Housing; Nutrition Policy; Questionnaires; Research Funding; Socioeconomic Factors; Body Mass Index; Health Equity; Cross-sectional Method; Economics; Seattle (wash.); Washington (state); Diet Quality; Geographic Information Systems; Healthy Eating Index; Residential Property Values; Socio-economic Status; Local Food Environment; Vitamin-e Consumption; Socioeconomic Position; United-states; Social-class; Energy-density; Association; Indicators; Trends
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