Saelens, Brian E.; Moudon, Anne Vernez; Kang, Bumjoon; Hurvitz, Philip M.; Zhou, Chuan. (2014). Relation between Higher Physical Activity and Public Transit Use. American Journal Of Public Health, 104(5), 854 – 859.
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Abstract
Objectives. We isolated physical activity attributable to transit use to examine issues of substitution between types of physical activity and potential confounding of transit-related walking with other walking. Methods. Physical activity and transit use data were collected in 2008 to 2009 from 693 Travel Assessment and Community study participants from King County, Washington, equipped with an accelerometer, a portable Global Positioning System, and a 7-day travel log. Physical activity was classified into transit-and non-transit-related walking and nonwalking time. Analyses compared physical activity by type between transit users and nonusers, between less and more frequent transit users, and between transit and nontransit days for transit users. Results. Transit users had more daily overall physical activity and more total walking than did nontransit users but did not differ on either non-transit-related walking or nonwalking physical activity. Most frequent transit users had more walking time than least frequent transit users. Higher physical activity levels for transit users were observed only on transit days, with 14.6 minutes (12.4 minutes when adjusted for demographics) of daily physical activity directly linked with transit use. Conclusions. Because transit use was directly related to higher physical activity, future research should examine whether substantive increases in transit access and use lead to more physical activity and related health improvements.
Keywords
Transportation; Analysis Of Covariance; Analysis Of Variance; Chi-squared Test; Comparative Studies; Confidence Intervals; Geographic Information Systems; Research Funding; Statistics; Walking; Data Analysis; Accelerometry; Cross-sectional Method; Exercise Intensity; Physical Activity; Diary (literary Form); Descriptive Statistics; Washington (state); Work; Car; Impact
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
Eisenberg-Guyot, Jerzy; Moudon, Anne V.; Hurvitz, Philip M.; Mooney, Stephen J.; Whitlock, Kathryn B.; Saelens, Brian E. (2019). Beyond the Bus Stop: Where Transit Users Walk. Journal Of Transport & Health, 14.
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Abstract
Objectives: Extending the health benefits of public-transit investment requires understanding how transit use affects pedestrian activity, including pedestrian activity not directly temporally or spatially related to transit use. In this study, we identified where transit users walked on transit days compared with non-transit days within and beyond 400 m and 800 m buffers surrounding their home and work addresses. Methods: We used data collected from 2008 to 2013 in King County, Washington, from 221 non-physically-disabled adult transit users, who were equipped with an accelerometer, global positioning system (GPS), and travel diary. We assigned walking activity to the following buffer locations: less than and at least 400 m or 800 m from home, work, or home/work (the home and work buffers comprised the latter buffer). We used Poisson generalized estimating equations to estimate differences in minutes per day of total walking and minutes per day of non-transit-related walking on transit days compared with non-transit days in each location. Results: We found that durations of total walking and non-transit-related walking were greater on transit days than on non-transit days in all locations studied. When considering the home neighborhood in isolation, most of the greater duration of walking occurred beyond the home neighborhood at both 400 m and 800 m; results were similar when considering the work neighborhood in isolation. When considering the neighborhoods jointly (i.e., by using the home/work buffer), at 400 m, most of the greater duration of walking occurred beyond the home/work neighborhood. However, at 800 m, most of the greater duration of walking occurred within the home/work neighborhood. Conclusions: Transit days were associated with greater durations of total walking and non-transit related walking within and beyond the home and work neighborhoods. Accordingly, research, design, and policy strategies focused on transit use and pedestrian activity should consider locations outside the home and work neighborhoods, in addition to locations within them.
Keywords
Physical-activity; Public-transit; Accelerometer Data; Combining Gps; United-states; Travel; Transportation; Health; Time; Neighborhood
Wang, Yiyuan; Moudon, Anne Vernez; Shen, Qing. (2022). How Does Ride-Hailing Influence Individual Mode Choice? An Examination Using Longitudinal Trip Data from the Seattle Region. Transportation Research Record, 2676(3), 621 – 633.
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Abstract
This study investigates the impacts of ride-hailing, which we define as mobility services consisting of both conventional taxis and app-based services offered by transportation network companies, on individual mode choice. We examine whether ride-hailing substitutes for or complements travel by driving, public transit, or walking and biking. The study overcomes some of the limitations of convenience samples or cross-sectional surveys used in past research by employing a longitudinal dataset of individual travel behavior and socio-demographic information. The data include three waves of travel log data collected between 2012 and 2018 in transit-rich areas of the Seattle region. We conducted individual-level panel data modeling, estimating independently pooled models and fixed-effect models of average daily trip count and duration for each mode, while controlling for various factors that affect travel behavior. The results provide evidence of substitution effects of ride-hailing on driving. We found that cross-sectionally, participants who used more ride-hailing tended to drive less, and that longitudinally, an increase in ride-hailing usage was associated with fewer driving trips. No significant associations were found between ride-hailing and public transit usage or walking and biking. Based on detailed travel data of a large population in a major U.S. metropolitan area, the study highlights the value of collecting and analyzing longitudinal data to understand the impacts of new mobility services.
Keywords
Shared Mobility; Ride-hailing; Longitudinal Data; Substitution Between Travel Modes; Complementarity Between Travel Modes; Services; Uber
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
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
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
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
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
Stewart, Orion; Moudon, Anne Vernez; Claybrooke, Charlotte. (2014). Multistate Evaluation of Safe Routes to School Programs. American Journal Of Health Promotion, 28, S89 – S96.
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Abstract
Purpose. State Safe Routes to School (SRTS) programs provide competitive grants to local projects that support safe walking, bicycling, and other modes of active school travel (AST). This study assessed changes in rates of AST after implementation of SRTS projects at multiple sites across four states. Design. One-group pretest and posttest. Setting. Florida, Mississippi, Washington, and Wisconsin. Subjects. Convenience sample of 48 completed SRTS projects and 53 schools affected by a completed SRTS project. Intervention. State-funded SRTS project. Measures. AST was measured as the percentage of students walking, bicycling, or using any AST mode. SRTS project characteristics were measured at the project, school, and school neighborhood levels. Analysis. Paired-samples t-tests were used to assess changes in AST. Bivariate analysis was used to identify SRTS project characteristics associated with increases in AST. Data were analyzed separately at the project (n = 48) and school (n = 53) levels. Results. Statistically significant increases in AST were observed across projects in all four states. All AST modes increased from 12.9% to 17.6%; walking from 9.8% to 14.2%; and bicycling from 2.5% to 3.0%. Increases in rates of bicycling were negatively correlated with baseline rates of bicycling. Conclusion. State-funded SRTS projects are achieving one of the primary program goals of increasing rates of AST. They may be particularly effective at introducing bicycling to communities where it is rare. The evaluation framework introduced in this study can be used to continue tracking the effect of state SRTS programs as more projects are completed.
Keywords
Transportation Of School Children; Physical Activity Measurement; Health Promotion; Cycling; Walking; School Children -- United States; Bicycling; Children; Commuting; Health Focus: Fitness/physical Activity; Manuscript Format: Research; Outcome Measure: Behavioral; Prevention Research; Research Purpose: Program Evaluation; Schools; Setting: School; Strategy: Skill Building/behavior Change, Built Environment; Study Design: Quasi-experimental; Target Population Age: Youth; Target Population Circumstances: Geographic Location; Physical-activity; Mental-health; Travel; Association; Validity; Mode; Bus