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
Hwang, Liang-dar; Hurvitz, Philip M.; Duncan, Glen E. (2016). Cross Sectional Association between Spatially Measured Walking Bouts and Neighborhood Walkability. International Journal Of Environmental Research And Public Health, 13(4).
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Abstract
Walking is the most popular choice of aerobic physical activity to improve health among U.S. adults. Physical characteristics of the home neighborhood can facilitate or hinder walking. The purpose of this study was to quantify neighborhood walking, using objective methods and to examine the association between counts of walking bouts in the home neighborhood and neighborhood walkability. This was a cross-sectional study of 106 adults who wore accelerometers and GPS devices for two weeks. Walking was quantified within 1, 2, and 3 km Euclidean (straight-line) and network buffers around the geocoded home location. Walkability was estimated using a commercially available index. Walking bout counts increased with buffer size and were associated with walkability, regardless of buffer type or size (p < 0.001). Quantification of walking bouts within (and outside) of pre-defined neighborhood buffers of different sizes and types allowed for the specification of walking locations to better describe and elucidate walking behaviors. These data support the concept that neighborhood characteristics can influence walking among adults.
Keywords
Physical-activity; Accelerometer Data; United-states; Urban Form; Land-use; Validation; Health; Transportation; Environments; Intensity; Geographic Information Systems; Residence Characteristics; Twins; Walking
Muni, Kennedy; Kobusingye, Olive; Mock, Charlie; Hughes, James P.; Hurvitz, Philip M.; Guthrie, Brandon. (2019). Motorcycle Taxi Programme is Associated with Reduced Risk of Road Traffic Crash among Motorcycle Taxi Drivers in Kampala, Uganda. International Journal Of Injury Control & Safety Promotion, 26(3), 294 – 301.
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Abstract
SafeBoda is a transportation company that provides road safety training and helmets to its motorcycle taxi drivers in Kampala. We sought to determine whether risk of road traffic crash (RTC) was lower in SafeBoda compared to regular (non-SafeBoda) motorcycle taxi drivers during a 6-month follow-up period. We collected participant demographic and behavioural data at baseline using computer-assisted personal interview, and occurrence of RTC every 2 months using text messaging and telephone interview from a cohort of 342 drivers. There were 85 crashes (31 in SafeBoda and 54 in regular drivers) during follow-up. Over the 6-month follow-up period, SafeBoda drivers were 39% less likely to be involved in a RTC than regular drivers after adjusting for age, possession of a driver's license, and education (RR: 0.61, 95% CI: 0.39-0.97, p = .04). These findings suggest that the SafeBoda programme results in safer driving and fewer RTCs among motorcycle taxi drivers in Kampala.
Keywords
Motorcyclists; Motorcycle Helmets; Text Messages; Telephone Interviewing; Motorcycles; Kampala (uganda); Uganda; Boda-boda; Crash; Injury; Road Safety; Injuries; Burden; Riders; Kenya; Traffic Accidents; Transportation; Risk Management; Crashes; Demographics; Transportation Safety; Short Message Service; Traffic; Traffic Accidents & Safety; Roads; Risk Reduction; Taxicabs; Protective Equipment; Drivers Licenses; Kampala Uganda
Rhew, Isaac C.; Hurvitz, Philip M.; Lyles-riebli, Rose; Lee, Christine M. (2022). Geographic Ecological Momentary Assessment Methods to Examine Spatio-temporal Exposures Associated with Marijuana Use Among Young Adults: A Pilot Study. Spatial And Spatio-temporal Epidemiology, 41.
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Abstract
Background: This study demonstrates the use of geographic ecological momentary assessment (GEMA) methods among young adult marijuana users. Method: Participants were 14 current marijuana users ages 21-27 living in Greater Seattle, Washington. They completed brief surveys four times per day for 14 consecutive days, including measures of marijuana use and desire to use. They also carried a GPS data logger that tracked their spatial movements over time. Results: Participants completed 80.1% of possible EMA surveys. Using the GPS data, we calculated daily number of exposures to (i.e., within 100-m of) marijuana retail outlets (mean = 3.9 times per day; SD = 4.4) and time spent per day in high poverty census tracts (mean = 7.3 h per day in high poverty census tracts; SD = 5.1). Conclusions: GEMA may be a promising approach for studying the role spatio-temporal factors play in marijuana use and related factors.
Keywords
Geographic Ecological Momentary Assessment; Spatio-temporal Factors; Marijuana; Young Adults; Geographic Information System; Poverty; Substance Use; Alcohol; Tracking
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