Scully, Jason Y.; Moudon, Anne Vernez; Hurvitz, Philip M.; Aggarwal, Anju; Drewnowski, Adam. (2019). A Time-Based Objective Measure of Exposure to the Food Environment. International Journal Of Environmental Research And Public Health, 16(7).
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Abstract
Exposure to food environments has mainly been limited to counting food outlets near participants' homes. This study considers food environment exposures in time and space using global positioning systems (GPS) records and fast food restaurants (FFRs) as the environment of interest. Data came from 412 participants (median participant age of 45) in the Seattle Obesity Study II who completed a survey, wore GPS receivers, and filled out travel logs for seven days. FFR locations were obtained from Public Health Seattle King County and geocoded. Exposure was conceptualized as contact between stressors (FFRs) and receptors (participants' mobility records from GPS data) using four proximities: 21 m, 100 m, 500 m, and 1/2 mile. Measures included count of proximal FFRs, time duration in proximity to 1 FFR, and time duration in proximity to FFRs weighted by FFR counts. Self-reported exposures (FFR visits) were excluded from these measures. Logistic regressions tested associations between one or more reported FFR visits and the three exposure measures at the four proximities. Time spent in proximity to an FFR was associated with significantly higher odds of FFR visits at all proximities. Weighted duration also showed positive associations with FFR visits at 21-m and 100-m proximities. FFR counts were not associated with FFR visits. Duration of exposure helps measure the relationship between the food environment, mobility patterns, and health behaviors. The stronger associations between exposure and outcome found at closer proximities (<100 m) need further research.
Keywords
Global Positioning Systems; Physical-activity; Health Research; Land-use; Neighborhood; Gps; Obesity; Tracking; Validity; Mobility; Fast Food; Spatio-temporal Exposure; Mobility Patterns; Selective Mobility Bias
Kang, Bumjoon; Moudon, Anne V.; Hurvitz, Philip M.; Reichley, Lucas; Saelens, Brian E. (2013). Walking Objectively Measured: Classifying Accelerometer Data with GPS and Travel Diaries. Medicine & Science In Sports & Exercise, 45(7), 1419 – 1428.
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Abstract
Purpose: This study developed and tested an algorithm to classify accelerometer data as walking or nonwalking using either GPS or travel diary data within a large sample of adults under free-living conditions. Methods: Participants wore an accelerometer and a GPS unit and concurrently completed a travel diary for seven consecutive days. Physical activity (PA) bouts were identified using accelerometry count sequences. PA bouts were then classified as walking or nonwalking based on a decision-tree algorithm consisting of seven classification scenarios. Algorithm reliability was examined relative to two independent analysts' classification of a 100-bout verification sample. The algorithm was then applied to the entire set of PA bouts. Results: The 706 participants' (mean age = 51 yr, 62% female, 80% non-Hispanic white, 70% college graduate or higher) yielded 4702 person-days of data and had a total of 13,971 PA bouts. The algorithm showed a mean agreement of 95% with the independent analysts. It classified PA into 8170 walking bouts (58.5 %) and 5337 nonwalking bouts (38.2%); 464 bouts (3.3%) were not classified for lack of GPS and diary data. Nearly 70% of the walking bouts and 68% of the nonwalking bouts were classified using only the objective accelerometer and GPS data. Travel diary data helped classify 30% of all bouts with no GPS data. The mean + SD duration of PA bouts classified as walking was 15.2 + 12.9 min. On average, participants had 1.7 walking bouts and 25.4 total walking minutes per day. Conclusions: GPS and travel diary information can be helpful in classifying most accelerometer-derived PA bouts into walking or nonwalking behavior.
Keywords
Walking; Algorithms; Decision Trees; Geographic Information Systems; Research Funding; Travel; Accelerometry; Diary (literary Form); Descriptive Statistics; Algorithm; Classification; Physical Activity; Walk Trip; Global Positioning Systems; Physical-activity; Environment; Behaviors; Validity; Location
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
Buszkiewicz, James; Rose, Chelsea; Gupta, Shilpi; Ko, Linda K.; Mou, Jin; Moudon, Anne, V; Hurvitz, Philip M.; Cook, Andrea; Aggarwal, Anju; Drewnowski, Adam. (2020). A Cross-Sectional Analysis of Physical Activity and Weight Misreporting in Diverse Populations: The Seattle Obesity Study III. Obesity Science & Practice, 6(6), 615 – 627.
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Abstract
Background: In-person assessments of physical activity (PA) and body weight can be burdensome for participants and cost prohibitive for researchers. This study examined self-reported PA and weight accuracy and identified patterns of misreporting in a diverse sample. Methods: King, Pierce and Yakima county residents, aged 21-59 years (n= 728), self-reported their moderate-to-vigorous PA (MVPA) and weight, in kilograms. Self-reports were compared with minutes of bout-level MVPA, from 3 days of accelerometer data, and measured weights. Regression models examined characteristics associated with underreporting and overreporting of MVPA and weight, the potential bias introduced using each measure and the relation between perceived and measured PA and weight. Results: MVPA underreporting was higher among males and college educated participants; however, there was no differential MVPA overreporting. Weight underreporting was higher among males, those age 40-49 years and persons with obesity. Weight overreporting was higher among Hispanic participants and those reporting stress, unhappiness and fair or poor health. The estimated PA-obesity relation was similar using measured and self-reported PA but not self-reported weight. Perceived PA and weight predicted measured values. Conclusion: Self-reported PA and weight may be useful should objective measurement be infeasible; however, though population-specific adjustment for differential reporting should be considered.
Keywords
Self-reported Weight; Sedentary Behavior; Validation; Accuracy; Height; Adults; Health Disparity; Obesity; Physical Activity; Self-reported Outcomes
Moudon, Anne Vernez; Drewnowski, Adam; Duncan, Glen E.; Hurvitz, Philip M.; Saelens, Brian E.; Scharnhorst, Eric. (2013). Characterizing the Food Environment: Pitfalls and Future Directions. Public Health Nutrition, 16(7), 1238 – 1243.
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Abstract
Objective: To assess a county population's exposure to different types of food sources reported to affect both diet quality and obesity rates. Design: Food permit records obtained from the local health department served to establish the full census of food stores and restaurants. Employing prior categorization schemes which classified the relative healthfulness of food sources based on establishment type (i.e. supermarkets v. convenience stores, or full-service v. fast-food restaurants), food establishments were assigned to the healthy, unhealthy or undetermined groups. Setting: King County, WA, USA. Subjects: Full census of food sources. Results: According to all categorization schemes, most food establishments in King County fell into the unhealthy and undetermined groups. Use of the food permit data showed that large stores, which included supermarkets as healthy food establishments, contained a sizeable number of bakery/delis, fish/meat, ethnic and standard quick-service restaurants and coffee shops, all food sources that, when housed in a separate venue or owned by a different business establishment, were classified as either unhealthy or of undetermined value to health. Conclusions: To fully assess the potential health effects of exposure to the extant food environment, future research would need to establish the health value of foods in many such common establishments as individually owned grocery stores and ethnic food stores and restaurants. Within-venue exposure to foods should also be investigated.
Keywords
Food Chemistry; Obesity; Health Boards; Dietary Supplements; Food Cooperatives; Restaurant Reviews; Coffee Shops; Food Consumption; Food Quality; Census Of Food Sources; Exposure; Health Value; Neighborhood Characteristics; Store Availability; Racial Composition; Physical-activity; Weight Status; Restaurants; Association; Proximity; Access; Business Enterprises; Fast Food Restaurants; Fish; Grocery Stores; Healthy Diet; Meat; Nutritional Adequacy; Supermarkets
James, Peter; Hart, Jaime E.; Hipp, J. Aaron; Mitchell, Jonathan A.; Kerr, Jacqueline; Hurvitz, Philip M.; Glanz, Karen; Laden, Francine. (2017). GPS-Based Exposure to Greenness and Walkability and Accelerometry-Based Physical Activity. Cancer Epidemiology Biomarkers & Prevention, 26(4), 525 – 532.
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Abstract
Background: Physical inactivity is a risk factor for cancer that may be influenced by environmental factors. Indeed, dense and well-connected built environments and environments with natural vegetation may create opportunities for higher routine physical activity. However, studies have focused primarily on residential environments to define exposure and self-reported methods to estimate physical activity. This study explores the momentary association between minute-level global positioning systems (GPS)-based greenness exposure and time-matched objectively measured physical activity. Methods: Adult women were recruited from sites across the United States. Participants wore a GPS device and accelerometer on the hip for 7 days to assess location and physical activity at minutelevel epochs. GPS records were linked to 250mresolution satellitebased vegetation data and Census Block Group-level U.S. Environmental Protection Agency (EPA) Smart Location Database walkability data. Minute-level generalized additive mixed models were conducted to test for associations between GPS measures and accelerometer count data, accounting for repeated measures within participant and allowing for deviations fromlinearity using splines. Results: Among 360 adult women (mean age of 55.3 +/- 10.2 years), we observed positive nonlinear relationships between physical activity and both greenness and walkability. In exploratory analyses, the relationships between environmental factors and physical activity were strongest among those who were white, had higher incomes, and who were middle-aged. Conclusions: Our results indicate that higher levels of physical activity occurred in areas with higher greenness and higher walkability. Impact: Findings suggest that planning and design policies should focus on these environments to optimize opportunities for physical activity. (C) 2017 AACR.
Keywords
Built Environments; Health Research; Breast-cancer; Obesity; Neighborhood; Validation; Validity; Walking; Risk; Energetics
Jones-Smith, Jessica C.; Walkinshaw, Lina Pinero; Oddo, Vanessa M.; Knox, Melissa; Neuhouser, Marian L.; Hurvitz, Philip M.; Saelens, Brian E.; Chan, Nadine. (2020). Impact of a Sweetened Beverage Tax on Beverage Prices in Seattle, WA. Economics & Human Biology, 39.
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Abstract
Seattle's Sweetened Beverage Tax is an excise tax of 1.75 cents per ounce on sugar-sweetened beverages and is one of the highest beverage taxes in the U.S. This study examined the impact of Seattle's tax on the prices of beverages. We conducted audits of 407 retail food stores and eating places (quick service restaurants and coffee shops) before and 6 months after the tax was implemented in Seattle and in a comparison area. Ordinary least squares difference-in-differences models with store fixed effects were used to estimate the effect of the tax on prices, stratified by beverage type and store type. In secondary analyses, we assessed the effect of the tax on the price of non-taxed beverages and foods. Results from the adjusted difference-in-differences models indicated the tax was associated with an average increase of 1.58 cents per ounce among Seattle retailers, representing 90 % of the price of the tax. By store type, price increases were highest in smaller grocery stores and drug stores. By beverage type, price increases were highest for energy beverages and soda and lowest for bottled coffee and juice drinks. Prices of some nontaxed beverages also increased while the prices of select healthy foods generally did not. The sweetened beverage tax in Seattle is higher than beverage taxes in most other cities, and nearly the full cost of the tax is being passed through to consumers for many beverage types and stores types. (c) 2020 Published by Elsevier B.V.
Keywords
Soda Taxes; Food Policy; Health Policy; Beverage Taxes; Obesity
Aggarwal, Anju; Cook, Andrea J.; Jiao, Junfeng; Seguin, Rebecca A.; Moudon, Anne Vernez; Hurvitz, Philip M.; Drewnowski, Adam. (2014). Access to Supermarkets and Fruit and Vegetable Consumption. American Journal Of Public Health, 104(5), 917 – 923.
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Abstract
Objectives. We examined whether supermarket choice, conceptualized as a proxy for underlying personal factors, would better predict access to supermarkets and fruit and vegetable consumption than mere physical proximity. Methods. The Seattle Obesity Study geocoded respondents' home addresses and locations of their primary supermarkets. Primary supermarkets were stratified into low, medium, and high cost according to the market basket cost of 100 foods. Data on fruit and vegetable consumption were obtained during telephone surveys. Linear regressions examined associations between physical proximity to primary supermarkets, supermarket choice, and fruit and vegetable consumption. Descriptive analyses examined whether supermarket choice outweighed physical proximity among lower-income and vulnerable groups. Results. Only one third of the respondents shopped at their nearest supermarket for their primary food supply. Those who shopped at low-cost supermarkets were more likely to travel beyond their nearest supermarket. Fruit and vegetable consumption was not associated with physical distance but, with supermarket choice, after adjusting for covariates. Conclusions. Mere physical distance may not be the most salient variable to reflect access to supermarkets, particularly among those who shop by car. Studies on food environments need to focus beyond neighborhood geographic boundaries to capture actual food shopping behaviors.
Keywords
Confidence Intervals; Correlation (statistics); Fruit; Geographic Information Systems; Ingestion; Multivariate Analysis; Population Geography; Questionnaires; Regression Analysis; Research Funding; Sales Personnel; Shopping; Travel; Vegetables; Predictive Validity; Cross-sectional Method; Statistical Models; Descriptive Statistics; Null Hypothesis; Washington (state); Local Food Environment; Diet Quality; Socioeconomic Position; Atherosclerosis Risk; Stores; Associations; Obesity; Adults; Availability; Communities
Kang, Bumjoon; Moudon, Anne V.; Hurvitz, Philip M.; Saelens, Brian E. (2017). Differences in Behavior, Time, Location, and Built Environment between Objectively Measured Utilitarian and Recreational Walking. Transportation Research: Part D, 57, 185 – 194.
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Abstract
Objectives: Utilitarian and recreational walking both contribute to physical activity. Yet walking for these two purposes may be different behaviors. We sought to provide operational definitions of utilitarian and recreational walking and to objectively measure their behavioral, spatial, and temporal differences in order to inform transportation and public health policies and interventions. Methods: Data were collected 2008-2009 from 651 Seattle-King County residents, wearing an accelerometer and a GPS unit, and filling-in a travel diary for 7 days. Walking activity bouts were classified as utilitarian or recreational based on whether walking had a destination or not. Differences between the two walking purposes were analyzed, adjusting for the nested structure of walking activity within participants. Results: Of the 4905 observed walking bouts, 87.4% were utilitarian and 12.6% recreational walking. Utilitarian walking bouts were 45% shorter in duration (-12.1 min) and 9% faster in speed (+0.3 km/h) than recreational walking bouts. Recreational walking occurred more frequently in the home neighborhood and was not associated with recreational land uses. Utilitarian walking occurred in areas having higher residential, employment, and street density, lower residential property value, higher area percentage of mixed-use neighborhood destinations, lower percentage of parks/trails, and lower average topographic slope than recreational walking. Conclusion: Utilitarian and recreational walking are substantially different in terms of frequency, speed, duration, location, and related built environment. Policies that promote walking should adopt type-specific strategies. The high occurrence of recreational walking near home highlights the importance of the home neighborhood for this activity.
Keywords
Walking; Utilitarianism; Recreation; Behavioral Assessment; Built Environment; Physical Activity Measurement; Accelerometer; Active Transportation; Gps; Home And Non-home Based Walking; Pedestrian; Physical-activity; Us Adults; Accelerometer Data; Trip Purpose; Urban Form; Travel; Neighborhood; Distance; System
Mooney, Stephen J.; Bobb, Jennifer F.; Hurvitz, Philip M.; Anau, Jane; Theis, Mary Kay; Drewnowski, Adam; Aggarwal, Anju; Gupta, Shilpi; Rosenberg, Dori E.; Cook, Andrea J.; Shi, Xiao; Lozano, Paula; Moudon, Anne Vernez; Arterburn, David. (2020). Impact of Built Environments on Body Weight (The Moving to Health Study): Protocol for a Retrospective Longitudinal Observational Study. Jmir Research Protocols, 9(5).
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Abstract
Background: Studies assessing the impact of built environments on body weight are often limited by modest power to detect residential effects that are small for individuals but may nonetheless comprise large attributable risks. Objective: We used data extracted from electronic health records to construct a large retrospective cohort of patients. This cohort will be used to explore both the impact of moving between environments and the long-term impact of changing neighborhood environments. Methods: We identified members with at least 12 months of Kaiser Permanente Washington (KPWA) membership and at least one weight measurement in their records during a period between January 2005 and April 2017 in which they lived in King County, Washington. Information on member demographics, address history, diagnoses, and clinical visits data (including weight) was extracted. This paper describes the characteristics of the adult (aged 18-89 years) cohort constructed from these data. Results: We identified 229,755 adults representing nearly 1.2 million person-years of follow-up. The mean age at baseline was 45 years, and 58.0% (133,326/229,755) were female. Nearly one-fourth of people (55,150/229,755) moved within King County at least once during the follow-up, representing 84,698 total moves. Members tended to move to new neighborhoods matching their origin neighborhoods on residential density and property values. Conclusions: Data were available in the KPWA database to construct a very large cohort based in King County, Washington. Future analyses will directly examine associations between neighborhood conditions and longitudinal changes in body weight and diabetes as well as other health conditions.
Keywords
Residential Location Choice; Physical-activity; Risk-factors; Food Desert; Neighborhood; Obesity; Association; Outcomes; Bmi; Accelerometer; Electronic Health Records; Built Environment; Washington; Geography; Longitudinal Studies