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
Kang, Bumjoon; Scully, Jason Y.; Stewart, Orion; Hurvitz, Philip M.; Moudon, Anne V. (2015). Split-Match-Aggregate (SMA) Algorithm: Integrating Sidewalk Data with Transportation Network Data in GIS. International Journal Of Geographical Information Science, 29(3), 440 – 453.
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Abstract
Sidewalk geodata are essential to understand walking behavior. However, such geodata are scarce, only available at the local jurisdiction and not at the regional level. If they exist, the data are stored in geometric representational formats without network characteristics such as sidewalk connectivity and completeness. This article presents the Split-Match-Aggregate (SMA) algorithm, which automatically conflates sidewalk information from secondary geometric sidewalk data to existing street network data. The algorithm uses three parameters to determine geometric relationships between sidewalk and street segments: the distance between streets and sidewalk segments; the angle between sidewalk and street segments; and the difference between the lengths of matched sidewalk and street segments. The SMA algorithm was applied in urban King County, WA, to 13 jurisdictions' secondary sidewalk geodata. Parameter values were determined based on agreement rates between results obtained from 72 pre-specified parameter combinations and those of a trained geographic information systems (GIS) analyst using a randomly selected 5% of the 79,928 street segments as a parameter-development sample. The algorithm performed best when the distances between sidewalk and street segments were 12m or less, their angles were 25 degrees or less, and the tolerance was set to 18m, showing an excellent agreement rate of 96.5%. The SMA algorithm was applied to classify sidewalks in the entire study area and it successfully updated sidewalk coverage information on the existing regional-level street network data. The algorithm can be applied for conflating attributes between associated, but geometrically misaligned line data sets in GIS.
Keywords
Geodatabases; Sidewalks; Algorithms; Pedestrians; Digital Mapping; Algorithm; Gis; Pedestrian Network Data; Polyline Conflation; Sidewalk; Built Environment; Physical-activity; Mode Choice; Urban Form; Land-use; Travel; Generation; Walking
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
Drewnowski, Adam; Aggarwal, Anju; Tang, Wesley; Hurvitz, Philip M.; Scully, Jason; Stewart, Orion; Moudon, Anne Vernez. (2016). Obesity, Diet Quality, Physical Activity, and the Built Environment: The Need for Behavioral Pathways. BMC Public Health, 16.
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Abstract
Background: The built environment ( BE) is said to influence local obesity rates. Few studies have explored causal pathways between home-neighborhood BE variables and health outcomes such as obesity. Such pathways are likely to involve both physical activity and diet. Methods: The Seattle Obesity Study ( SOS II) was a longitudinal cohort of 440 adult residents of King Co, WA. Home addresses were geocoded. Home-neighborhood BE measures were framed as counts and densities of food sources and physical activity locations. Tax parcel property values were obtained from County tax assessor. Healthy Eating Index ( HEI 2010) scores were constructed using data from food frequency questionnaires. Physical activity ( PA) was obtained by self-report. Weights and heights were measured at baseline and following 12 months' exposure. Multivariable regressions examined the associations among BE measures at baseline, health behaviors ( HEI-2010 and physical activity) at baseline, and health outcome both cross-sectionally and longitudinally. Results: None of the conventional neighborhood BE metrics were associated either with diet quality, or with meeting PA guidelines. Only higher property values did predict better diets and more physical activity. Better diets and more physical activity were associated with lower obesity prevalence at baseline and 12 mo, but did not predict weight change. Conclusion: Any links between the BE and health outcomes critically depend on establishing appropriate behavioral pathways. In this study, home-centric BE measures, were not related to physical activity or to diet. Further studies will need to consider a broader range of BE attributes that may be related to diets and health.
Keywords
Body-mass Index; Local Food Environment; Residential Property-values; Supermarket Accessibility; Park Proximity; Neighborhood Walkability; Vegetable Consumption; Atherosclerosis Risk; Restaurant Food; Associations; Built Environment; Physical Activity; Obesity; Diet Quality
Stewart, Orion T.; Carlos, Heather A.; Lee, Chanam; Berke, Ethan M.; Hurvitz, Philip M.; Li, Li; Moudon, Anne Vernez; Doescher, Mark P. (2016). Secondary GIS Built Environment Data for Health Research: Guidance for Data Development. Journal Of Transport & Health, 3(4), 529 – 539.
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Abstract
Built environment (BE) data in geographic information system (GIS) format are increasingly available from public agencies and private providers. These data can provide objective, low-cost BE data over large regions and are often used in public health research and surveillance. Yet challenges exist in repurposing GIS data for health research. The GIS data do not always capture desired constructs; the data can be of varying quality and completeness; and the data definitions, structures, and spatial representations are often inconsistent across sources. Using the Small Town Walkability study as an illustration, we describe (a) the range of BE characteristics measurable in a GIS that may be associated with active living, (b) the availability of these data across nine U.S. small towns, (c) inconsistencies in the GIS BE data that were available, and (d) strategies for developing accurate, complete, and consistent GIS BE data appropriate for research. Based on a conceptual framework and existing literature, objectively measurable characteristics of the BE potentially related to active living were classified under nine domains: generalized land uses, morphology, density, destinations, transportation system, traffic conditions, neighborhood behavioral conditions, economic environment, and regional location. At least some secondary GIS data were available across all nine towns for seven of the 9 BE domains. Data representing high-resolution or behavioral aspects of the BE were often not available. Available GIS BE data - especially tax parcel data often contained varying attributes and levels of detail across sources. When GIS BE data were available from multiple sources, the accuracy, completeness, and consistency of the data could be reasonable ensured for use in research. But this required careful attention to the definition and spatial representation of the BE characteristic of interest. Manipulation of the secondary source data was often required, which was facilitated through protocols. (C) 2015 Elsevier Ltd. All rights reserved.
Keywords
Geographic Information-systems; Physical-activity; Land-use; Walking; Neighborhood; Associations; Density; Design; Adults; Travel; Active Travel; Pedestrian; Urban Design; Community Health; Rural
Stewart, Orion T.; Moudon, Anne Vernez; Fesinmeyer, Megan D.; Zhou, Chuan; Saelens, Brian E. (2016). The Association between Park Visitation and Physical Activity Measured with Accelerometer, GPS, and Travel Diary. Health & Place, 38, 82 – 88.
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Abstract
Public parks are promoted as places that support physical activity (PA), but evidence of how park visitation contributes to overall PA is limited. This study observed adults living in the Seattle metropolitan area (n=671) for one week using accelerometer, GPS, and travel diary. Park visits, measured both objectively (GPS) and subjectively (travel diary), were temporally linked to accelerometer-measured PA. Park visits occurred at 1.4 per person-week. Participants who visited parks at least once (n=308) had an adjusted average of 14.3 (95% Cl: 8.9, 19.6) min more daily PA than participants who did not visit a park. Even when park-related activity was excluded, park visitors still obtained more minutes of daily PA than non-visitors. Park visitation contributes to a more active lifestyle, but is not solely responsible for it. Parks may best serve to complement broader public health efforts to encourage PA. (C) 2016 Elsevier Ltd. All rights reserved.
Keywords
Physical Activity; Accelerometers; Geographic Information Systems; Park Use; Public Health; Built Environment; Gis; Leisure; Recreation; Substitution; Sedentary Behavior; Public-health; Accessibility; Prevention