Kerfeld, Cheryl I.; Hurvitz, Philip M.; Bjornson, Kristie F. (2021). Physical Activity Measurement in Children Who Use Mobility Assistive Devices: Accelerometry and Global Positioning System. Pediatric Physical Therapy, 33(2), 92 – 99.
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Abstract
Purpose: To explore the usefulness of combining accelerometry, global positioning systems, and geographic information systems, to describe the time spent in different locations and physical activity (PA) duration/count levels by location for 4 children with cerebral palsy (CP) who use assistive devices (AD). Methods: A descriptive multiple-case study. Results: Combining the 3 instruments was useful in describing and differentiating duration by location, and amount and location of PA across differing functional levels and AD. For example, the child classified with a Gross Motor Function Classification System (GMFCS) level II exhibited large amounts of PA in community settings. In contrast, the child classified with a GMFCS level V had small amounts of PA and spent most measured time at home. Conclusions: Combined accelerometry, global positioning system, and geographic information system have potential to capture time spent and amount/intensity of PA relative to locations within daily environments for children with CP who use AD.
Keywords
Cerebral-palsy; Objective Measures; Fitness; Youth; Disabilities; Adolescents; Exercise; Adults; Accelerometer; Cerebral Palsy; Environment; Global Positioning System; Mobility Assistive Devices; Physical Activity
Drewnowski, Adam; Aggarwal, Anju; Hurvitz, Philip M.; Monsivais, Pablo; Moudon, Anne V. (2012). Obesity and Supermarket Access: Proximity or Price? American Journal Of Public Health, 102(8), e74 – e80.
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Abstract
Objectives. We examined whether physical proximity to supermarkets or supermarket price was more strongly associated with obesity risk. Methods. The Seattle Obesity Study (SOS) collected and geocoded data on home addresses and food shopping destinations for a representative sample of adult residents of King County, Washington. Supermarkets were stratified into 3 price levels based on average cost of the market basket. Sociodemographic and health data were obtained from a telephone survey. Modified Poisson regression was used to test the associations between obesity and supermarket variables. Results. Only 1 in 7 respondents reported shopping at the nearest supermarket. The risk of obesity was not associated with street network distances between home and the nearest supermarket or the supermarket that SOS participants reported as their primary food source. The type of supermarket, by price, was found to be inversely and significantly associated with obesity rates, even after adjusting for individual-level sociodemographic and lifestyle variables, and proximity measures (adjusted relative risk = 0.34; 95% confidence interval = 0.19, 0.63) Conclusions. Improving physical access to supermarkets may be one strategy to deal with the obesity epidemic; improving economic access to healthy foods is another. [ABSTRACT FROM AUTHOR]; Copyright of American Journal of Public Health is the property of American Public Health Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Keywords
Natural Foods; Obesity Risk Factors; Surveys; Cluster Analysis (statistics); Confidence Intervals; Correlation (statistics); Food Service; Geographic Information Systems; Poisson Distribution; Population Geography; Research Funding; User Charges; Residential Patterns; Socioeconomic Factors; Relative Medical Risk; Statistical Models; Descriptive Statistics; Economics; Washington (state)
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
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
Robinson, Jamaica R. M.; Phipps, Amanda, I; Barrington, Wendy E.; Hurvitz, Philip M.; Sheppard, Lianne; Malen, Rachel C.; Newcomb, Polly A. (2021). Associations of Household Income with Health-Related Quality of Life Following a Colorectal Cancer Diagnosis Varies with Neighborhood Socioeconomic Status. Cancer Epidemiology Biomarkers & Prevention, 30(7), 1366 – 1374.
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Abstract
Background: Existing evidence indicates household income as a predictor of health-related quality of life (HRQoL) following a colorectal cancer diagnosis. This association likely varies with neighborhood socioeconomic status (nSES), but evidence is limited. Methods: We included data from 1,355 colorectal cancer survivors participating in the population-based Puget Sound Colorectal Cancer Cohort (PSCCC). Survivors reported current annual household income; we measured HRQoL via the Functional Assessment of Cancer Therapy - Colorectal (FACT-C) tool. Using neighborhood data summarized within a 1-km radial buffer of Census block group centroids, we constructed a multidimensional nSES index measure. We employed survivors' geocoded residential addresses to append nSES score for Census block group of residence. With linear generalized estimating equations clustered on survivor location, we evaluated associations of household income with differences in FACT-C mean score, overall and stratified by nSES. We used separate models to explore relationships for wellbeing subscales. Results: We found lower household income to be associated with clinically meaningful differences in overall FACT-C scores [<$30K: -13.6; 95% confidence interval (CI): -16.8 to -10.4] and subscale wellbeing after a recent colorectal cancer diagnosis. Relationships were slightly greater in magnitude for survivors living in lower SES neighborhoods. Conclusions: Our findings suggest that recently diagnosed lower income colorectal cancer survivors are likely to report lower HRQoL, and modestly more so in lower SES neighborhoods. Impact: The findings from this work will aid future investigators' ability to further consider the contexts in which the income of survivors can be leveraged as a means of improving HRQoL
Keywords
Built Environment Factors; Functional Assessment; Fact-c; Population-density; Physical-activity; Survivors; Care; Disparities; Impact; Mortality
Hurvitz, Philip M.; Moudon, Anne Vernez. (2012). Home Versus Nonhome Neighborhood: Quantifying Differences in Exposure to the Built Environment. American Journal Of Preventive Medicine, 42(4), 411 – 417.
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Abstract
Background: Built environment and health research have focused on characteristics of home neighborhoods, whereas overall environmental exposures occur over larger spatial ranges. Purpose: Differences in built environment characteristics were analyzed for home and nonhome locations using GPS data. Methods: GPS data collected in 2007-2008 were analyzed for 41 subjects in the Seattle area in 2010. Environmental characteristics for 3.8 million locations were measured using novel GIS data sets called SmartMaps, representing spatially continuous values of local built environment variables in the domains of neighborhood composition, utilitarian destinations, transportation infrastructure, and traffic conditions. Using bootstrap sampling, CIs were estimated for differences in built environment values for home (1666 m) GPS locations. Results: Home and nonhome built environment values were significantly different for more than 90% of variables across subjects (p < 0.001). Only 51% of subjects had higher counts of supermarkets near than away from home. Different measures of neighborhood parks yielded varying results. Conclusions: SmartMaps helped measure local built environment characteristics for a large set of GPS locations. Most subjects had significantly different home and nonhome built environment exposures. Considering the full range of individuals' environmental exposures may improve understanding of effects of the built environment on behavior and health outcomes. (Am J Prev Med 2012;42(4):411-417) (C) 2012 American Journal of Preventive Medicine
Keywords
Built Environment; Public Health Research; Individual Differences; Neighborhoods; Environmental Exposure; Health Of Homeless People; Global Positioning System; Data Analysis; Quantitative Research; Seattle (wash.); Washington (state); Geographic Information-systems; Global Positioning Systems; Physical-activity; Health Research; Urban Form; Land-use; Associations; Transportation; Availability; Walkability
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
Moudon, Anne Vernez; Huang, Ruizhu; Stewart, Orion T.; Cohen-Cline, Hannah; Noonan, Carolyn; Hurvitz, Philip M.; Duncan, Glen E. (2019). Probabilistic Walking Models Using Built Environment and Sociodemographic Predictors. Population Health Metrics, 17(1).
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Abstract
BackgroundIndividual sociodemographic and home neighborhood built environment (BE) factors influence the probability of engaging in health-enhancing levels of walking or moderate-to-vigorous physical activity (MVPA). Methods are needed to parsimoniously model the associations.MethodsParticipants included 2392 adults drawn from a community-based twin registry living in the Seattle region. Objective BE measures from four domains (regional context, neighborhood composition, destinations, transportation) were taken for neighborhood sizes of 833 and 1666 road network meters from home. Hosmer and Lemeshow's methods served to fit logistic regression models of walking and MVPA outcomes using sociodemographic and BE predictors. Backward elimination identified variables included in final models, and comparison of receiver operating characteristic (ROC) curves determined model fit improvements.ResultsBuilt environment variables associated with physical activity were reduced from 86 to 5 or fewer. Sociodemographic and BE variables from all four BE domains were associated with activity outcomes but differed by activity type and neighborhood size. For the study population, ROC comparisons indicated that adding BE variables to a base model of sociodemographic factors did not improve the ability to predict walking or MVPA.ConclusionsUsing sociodemographic and built environment factors, the proposed approach can guide the estimation of activity prediction models for different activity types, neighborhood sizes, and discrete BE characteristics. Variables associated with walking and MVPA are population and neighborhood BE-specific.
Keywords
Walking; Confidence Intervals; Research Funding; Transportation; Logistic Regression Analysis; Built Environment; Socioeconomic Factors; Predictive Validity; Receiver Operating Characteristic Curves; Data Analysis Software; Descriptive Statistics; Psychology; Washington (state); Active Travel; Home Neighborhood Domains; Physical Activity; Physical-activity; United-states; Life Stage; Adults; Attributes; Health; Associations; Destination; Pitfalls
Rhew, Isaac C.; Guttmannova, Katarina; Kilmer, Jason R.; Fleming, Charles B.; Hultgren, Brittney A.; Hurvitz, Philip M.; Dilley, Julia A.; Larimer, Mary E. (2022). Associations of Cannabis Retail Outlet Availability and Neighborhood Disadvantage with Cannabis Use and Related Risk Factors Among Young Adults in Washington State. Drug & Alcohol Dependence, 232.
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Abstract
Background: This study examined associations of local cannabis retail outlet availability and neighborhood disadvantage with cannabis use and related risk factors among young adults. Methods: Data were from annual cross-sectional surveys administered from 2015 to 2019 to individuals ages 18-25 residing in Washington State (N = 10,009). As outcomes, this study assessed self-reported cannabis use at different margins/frequencies (any past year, at least monthly, at least weekly, at least daily) and perceived ease of access to cannabis and acceptability of cannabis use in the community. Cannabis retail outlet availability was defined as the presence of at least one retail outlet within a 1-kilometer road network buffer of one's residence. Sensitivity analyses explored four other spatial metrics to define outlet availability (any outlet within 0.5-km, 2-km, and the census tract; and census tract density per 1000 residents). Census tract level disadvantage was a composite of five US census variables. Results: Adjusting for individual- and area-level covariates, living within 1-kilometer of at least one cannabis retail outlet was statistically significantly associated with any past year and at least monthly cannabis use as well as high perceived access to cannabis. Results using a 2-km buffer and census tract-level metrics for retail outlet availability showed similar findings. Neighborhood disadvantage was statistically significantly associated with at least weekly and at least daily cannabis use and with greater perceived acceptability of cannabis use. Conclusions: Results may have implications for regulatory and prevention strategies to reduce the population burden of cannabis use and related harms.
Keywords
Outlet Stores; Young Adults; Neighborhoods; Older People; Sensitivity Analysis; Washington (state); Cannabis; Cannabis Retail Outlets; Neighborhood Disadvantage; Alcohol-use; Marijuana Use; Density; Proximity; Health; Norms
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