Safety & Health & Wellbeing Archives - Page 19 of 29

Increased Walking’s Additive and No Substitution Effect on Total Physical Activity

Kang, Bumjoon; Moudon, Anne V.; Hurvitz, Philip M.; Saelens, Brian E. (2018). Increased Walking’s Additive and No Substitution Effect on Total Physical Activity. Medicine & Science In Sports & Exercise, 50(3), 468 – 475.

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Abstract

Purpose We assessed the associations between a change in time spent walking and a change in total physical activity (PA) time within an urban living adult sample to test for additive or substitution effects. Methods Participants living in the greater Seattle area were assessed in 2008-2009 and again 1-2 yr later (2010-2011). At each time point, they wore accelerometers and GPS units and recorded trips and locations in a travel diary for seven consecutive days. These data streams were combined to derive a more objective estimate of walking and total PA. Participants also completed the International Physical Activity Questionnaire to provide self-reported estimates of walking and total PA. Regression analyses assessed the associations between within-participant changes in objective and self-reported walking and total PA. Results Data came from 437 participants. On average, a 1-min increase in total walking was associated with an increase in total PA of 1 min, measured by objective data, and 1.2-min, measured by self-reported data. A similar additive effect was consistently found with utilitarian, transportation, or job-related walking, measured by both objective and self-reported data. For recreational walking, the effect of change was mixed between objective and self-reported results. Conclusion Both objective and self-reported data confirmed an additive effect of utilitarian and total walking on PA.

Keywords

Accelerometers; Global Positioning System; Metropolitan Areas; Questionnaires; Recreation; Self-evaluation; Time; Walking; Physical Activity; Accelerometer; Gps; Ipaq; Longitudinal Study; Self-reported Measures; Light-rail Construction; Built Environment; Accelerometer Data; Older-adults; Urban Form; Transit Use; Travel; Neighborhood; Interventions; Calibration

The Moving to Health (M2H) Approach to Natural Experiment Research: A Paradigm Shift for Studies on Built Environment and Health

Drewnowski, A.; Arterburn, D.; Zane, J.; Aggarwal, A.; Gupta, S.; Hurvitz, P. M.; Moudon, A., V; Bobb, J.; Cook, A.; Lozano, P.; Rosenberg, D. (2019). The Moving to Health (M2H) Approach to Natural Experiment Research: A Paradigm Shift for Studies on Built Environment and Health. Ssm-population Health, 7.

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Improving the built environment (BE) is viewed as one strategy to improve community diets and health. The present goal is to review the literature on the effects of BE on health, highlight its limitations, and explore the growing use of natural experiments in BE research, such as the advent of new supermarkets, revitalized parks, or new transportation systems. Based on recent studies on movers, a paradigm shift in built-environment health research may be imminent. Following the classic Moving to Opportunity study in the US, the present Moving to Health (M2H) strategy takes advantage of the fact that changing residential location can entail overnight changes in multiple BE variables. The necessary conditions for applying the M2H strategy to Geographic Information Systems (GIS) databases and to large longitudinal cohorts are outlined below. Also outlined are significant limitations of this approach, including the use of electronic medical records in lieu of survey data. The key research question is whether documented changes in BE exposure can be linked to changes in health outcomes in a causal manner. The use of geo-localized clinical information from regional health care systems should permit new insights into the social and environmental determinants of health.

Keywords

Body-mass Index; Neighborhood Food Environment; Residential Property-values; Cardiometabolic Risk-factors; New-york-city; Physical-activity; Obesity Rates; King County; Weight-gain; Land-use; Built Environment (be); Geographic Information Systems (gis); Electronic Medical Records; Natural Experiments; Obesity; Diabetes; Residential Mobility

Owning vs. Renting: The Benefits of Residential Stability?

Acolin, Arthur. (2020). Owning vs. Renting: The Benefits of Residential Stability? Housing Studies, 37(4), 644-647.

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Abstract

In housing research, owning, as compared to renting, is generally depicted as more desirable and associated with better outcomes. This paper explores differences in outcomes between owners and renters in 25 European countries and whether these differences are systematically smaller in countries in which owners and renters have more similar levels of residential stability (smaller tenure length gap). The results indicate that the direction of the relationship between tenure type and the selected outcomes is largely similar across countries. Owners generally exhibit more desirable outcomes (including life satisfaction, civic participation, educational outcomes for children, and physical and mental health). However, when looking at the relationship between outcomes and country level differences in tenure length gap, findings suggest that renters have outcomes that are more similar to owners in countries in which tenure length gaps are smaller. These results point to the potential benefits of policies that would increase residential stability, particularly for renters.

Keywords

European Union; Homeownership Benefits; Length Of Residence; Tenure; Home-ownership; Homeownership

Impact of Built Environments on Body Weight (The Moving to Health Study): Protocol for a Retrospective Longitudinal Observational Study

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

Differential Associations of the Built Environment on Weight Gain by Sex and Race/Ethnicity but Not Age

Buszkiewicz, James H.; Bobb, Jennifer F.; Kapos, Flavia; Hurvitz, Philip M.; Arterburn, David; Moudon, Anne Vernez; Cook, Andrea; Mooney, Stephen J.; Cruz, Maricela; Gupta, Shilpi; Lozano, Paula; Rosenberg, Dori E.; Theis, Mary Kay; Anau, Jane; Drewnowski, Adam. (2021). Differential Associations of the Built Environment on Weight Gain by Sex and Race/Ethnicity but Not Age. International Journal Of Obesity, 45(12), 2648 – 2656.

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Abstract

Objective To explore the built environment (BE) and weight change relationship by age, sex, and racial/ethnic subgroups in adults. Methods Weight trajectories were estimated using electronic health records for 115,260 insured Kaiser Permanente Washington members age 18-64 years. Member home addresses were geocoded using ArcGIS. Population, residential, and road intersection densities and counts of area supermarkets and fast food restaurants were measured with SmartMaps (800 and 5000-meter buffers) and categorized into tertiles. Linear mixed-effect models tested whether associations between BE features and weight gain at 1, 3, and 5 years differed by age, sex, and race/ethnicity, adjusting for demographics, baseline weight, and residential property values. Results Denser urban form and greater availability of supermarkets and fast food restaurants were associated with differential weight change across sex and race/ethnicity. At 5 years, the mean difference in weight change comparing the 3rd versus 1st tertile of residential density was significantly different between males (-0.49 kg, 95% CI: -0.68, -0.30) and females (-0.17 kg, 95% CI: -0.33, -0.01) (P-value for interaction = 0.011). Across race/ethnicity, the mean difference in weight change at 5 years for residential density was significantly different among non-Hispanic (NH) Whites (-0.47 kg, 95% CI: -0.61, -0.32), NH Blacks (-0.86 kg, 95% CI: -1.37, -0.36), Hispanics (0.10 kg, 95% CI: -0.46, 0.65), and NH Asians (0.44 kg, 95% CI: 0.10, 0.78) (P-value for interaction <0.001). These findings were consistent for other BE measures. Conclusion The relationship between the built environment and weight change differs across demographic groups. Careful consideration of demographic differences in associations of BE and weight trajectories is warranted for investigating etiological mechanisms and guiding intervention development.

Keywords

Body-mass Index; Socioeconomic-status; Food Environment; Obesity; Health; Outcomes; Scale; Risk; Minority & Ethnic Groups; Urban Environments; Etiology; Demographics; Sex; Residential Density; Supermarkets; Age; Race; Ethnicity; Property Values; Body Weight Gain; Electronic Medical Records; Fast Food; Electronic Health Records; Real Estate; Subgroups; Demography; Trajectory Analysis; Weight

Multi-Hazard Perceptions at Long Valley Caldera, California, USA

Peers, Justin B.; Lindell, Michael K.; Gregg, Christopher E.; Reeves, Ashleigh K.; Joyner, Andrew T.; Johnston, David M. (2021). Multi-Hazard Perceptions at Long Valley Caldera, California, USA. International Journal Of Disaster Risk Reduction, 52.

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Abstract

Caldera systems such as Long Valley Caldera, California; Taupo, New Zealand; and Campi Flegrei, Italy, experience centuries to millennia without eruption, but have the potential for large eruptions. This raises questions about how local residents' behavioral responses to these low-probability high-consequence events differ from their responses to events, such as wildfires and earthquakes, that have higher probabilities. To examine this issue, a multi-hazard mail survey of 229 households explored perceptions of-and responses to-volcano, earthquake and wildfire hazards in the Long Valley Volcanic Region. Response efficacy was the only significant predictor of emergency preparedness, which suggests that hazard managers can increase household emergency preparedness by emphasizing this attribute of protective actions. In addition to response efficacy, expected personal consequences, hazard intrusiveness, and affective responses were all significantly related to information seeking. This indicates that hazard managers can also increase households' information seeking about local hazards and appropriate protective actions by communicating the certainty and severity of hazard impacts (thus increasing expected personal consequences) and that they communicate this information repeatedly (thus increasing hazard intrusiveness) to produce significant emotional involvement (thus increasing affective response).

Keywords

Households Expected Responses; Risk Information-seeking; Volcanic Risk; Earthquake; Model; Adjustment; Mitigation; Communication; Preparedness; Predictors; Volcano Hazard Perception; Earthquake Hazard Perception; Wildfire Hazard Perception; Emergency Preparedness; Information Seeking

A Neighborhood Wealth Metric for Use in Health Studies

Moudon, Anne Vernez; Cook, Andrea J.; Ulmer, Jared; Hurvitz, Philip M.; Drewnowski, Adam. (2011). A Neighborhood Wealth Metric for Use in Health Studies. American Journal Of Preventive Medicine, 41(1), 88 – 97.

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Abstract

Background: Measures of neighborhood deprivation used in health research are typically based on conventional area-based SES. Purpose: The aim of this study is to examine new data and measures of SES for use in health research. Specifically, assessed property values are introduced as a new individual-level metric of wealth and tested for their ability to substitute for conventional area-based SES as measures of neighborhood deprivation. Methods: The analysis was conducted in 2010 using data from 1922 participants in the 2008-2009 survey of the Seattle Obesity Study (SOS). It compared the relative strength of the association between the individual-level neighborhood wealth metric (assessed property values) and area-level SES measures (including education, income, and percentage above poverty as single variables, and as the composite Singh index) on the binary outcome fair/poor general health status. Analyses were adjusted for gender, categoric age, race, employment status, home ownership, and household income. Results: The neighborhood wealth measure was more predictive of fair/poor health status than area-level SES measures, calculated either as single variables or as indices (lower DIC measures for all models). The odds of having a fair/poor health status decreased by 0.85 (95% CI=0.77, 0.93) per $50,000 increase in neighborhood property values after adjusting for individual-level SES measures. Conclusions: The proposed individual-level metric of neighborhood wealth, if replicated in other areas, could replace area-based SES measures, thus simplifying analyses of contextual effects on health. (Am J Prev Med 2011; 41(1): 88-97) (C) 2011 American Journal of Preventive Medicine

Keywords

Health -- Social Aspects; Social Status; Public Health Research; Home Ownership; Income; Real Property; Deprivation (psychology); Health Education; Disparities Geocoding Project; Body-mass Index; Socioeconomic-status; Ecological Fallacy; Built Environment; Deprivation Indexes; Multilevel Analysis; Individual-level; Social-class; Inequalities

The Built Environment and Utilitarian Walking in Small U.S. Towns

Doescher, Mark P.; Lee, Chanam; Berke, Ethan M.; Adachi-mejia, Anna M.; Lee, Chun-kuen; Stewart, Orion; Patterson, Davis G.; Hurvitz, Philip M.; Carlos, Heather A.; Duncan, Glen E.; Moudon, Anne Vernez. (2014). The Built Environment and Utilitarian Walking in Small U.S. Towns. Preventive Medicine, 69, 80 – 86.

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Abstract

Objectives. The role of the built environment on walking in rural United States (U.S.) locations is not well characterized. We examined self-reported and measured built environment correlates of walking for utilitarian purposes among adult residents of small rural towns. Methods. In 2011-12, we collected telephone survey and geographic data from 2152 adults in 9 small towns from three U.S. regions. We performed mixed-effects logistic regression modeling to examine relationships between built environment measures and utilitarian walking (any versus none; high [>= 150 min per week] versus low [<150 min per week]) to retail, employment and public transit destinations. Results. Walking levels were lower than those reported for populations living in larger metropolitan areas. Environmental factors significantly (p < 0.05) associated with higher odds of utilitarian walking in both models included self-reported presence of crosswalks and pedestrian signals and availability of park/natural recreational areas in the neighborhood, and also objectively measured manufacturing land use. Conclusions. Environmental factors associated with utilitarian walking in cities and suburbs were important in small rural towns. Moreover, manufacturing land use was associated with utilitarian walking. Modifying the built environment of small towns could lead to increased walking in a sizeable segment of the U.S. population. (C) 2014 Elsevier Inc. All rights reserved.

Keywords

Cities & Towns -- Environmental Conditions; Walking; Telephone Surveys; Logistic Regression Analysis; Public Transit; Cities & Towns; Rural Conditions; United States; Exercise/physical Activity; Health Promotion; Physical Environment; Prevention; Rural Health; Social Environment; Physical-activity; Postmenopausal Women; Adults; Health; Risk; Transportation; Associations; Neighborhood; Travel; Determinants

The Spatial Clustering of Obesity: Does the Built Environment Matter?

Huang, R.; Moudon, A. V.; Cook, A. J.; Drewnowski, A. (2015). The Spatial Clustering of Obesity: Does the Built Environment Matter? Journal Of Human Nutrition & Dietetics, 28(6), 604 – 612.

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Abstract

BackgroundObesity rates in the USA show distinct geographical patterns. The present study used spatial cluster detection methods and individual-level data to locate obesity clusters and to analyse them in relation to the neighbourhood built environment. MethodsThe 2008-2009 Seattle Obesity Study provided data on the self-reported height, weight, and sociodemographic characteristics of 1602 King County adults. Home addresses were geocoded. Clusters of high or low body mass index were identified using Anselin's Local Moran's I and a spatial scan statistic with regression models that searched for unmeasured neighbourhood-level factors from residuals, adjusting for measured individual-level covariates. Spatially continuous values of objectively measured features of the local neighbourhood built environment (SmartMaps) were constructed for seven variables obtained from tax rolls and commercial databases. ResultsBoth the Local Moran's I and a spatial scan statistic identified similar spatial concentrations of obesity. High and low obesity clusters were attenuated after adjusting for age, gender, race, education and income, and they disappeared once neighbourhood residential property values and residential density were included in the model. ConclusionsUsing individual-level data to detect obesity clusters with two cluster detection methods, the present study showed that the spatial concentration of obesity was wholly explained by neighbourhood composition and socioeconomic characteristics. These characteristics may serve to more precisely locate obesity prevention and intervention programmes.

Keywords

Real Property; Ecology; Age Distribution; Anthropometry; Black People; Cluster Analysis (statistics); Communities; Computer Software; Epidemiological Research; Geographic Information Systems; Hispanic Americans; Mathematics; Obesity; Population Geography; Probability Theory; Race; Regression Analysis; Research Funding; Restaurants; Statistical Sampling; Self-evaluation; Sex Distribution; Shopping; Surveys; Telephones; Transportation; White People; Socioeconomic Factors; Body Mass Index; Data Analysis Software; Medical Coding; Statistical Models; Descriptive Statistics; Odds Ratio; Economics; Washington (state); Built Environment; Local Moran's I; Spatial Scan Statistic; Body-mass Index; Physical-activity; United-states; Risk-factors; Neighborhood; Association; Density; Disease; Disparities; Prevalence

Spatial Energetics Integrating Data from GPS, Accelerometry, and GIS to Address Obesity and Inactivity

James, Peter; Jankowska, Marta; Marx, Christine; Hart, Jaime E.; Berrigan, David; Kerr, Jacqueline; Hurvitz, Philip M.; Hipp, J. Aaron; Laden, Francine. (2016). Spatial Energetics Integrating Data from GPS, Accelerometry, and GIS to Address Obesity and Inactivity. American Journal Of Preventive Medicine, 51(5), 792 – 800.

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Abstract

To address the current obesity and inactivity epidemics, public health researchers have attempted to identify spatial factors that influence physical inactivity and obesity. Technologic and methodologic developments have led to a revolutionary ability to examine dynamic, high-resolution measures of temporally matched location and behavior data through GPS, accelerometry, and GIS. These advances allow the investigation of spatial energetics, high-spatiotemporal resolution data on location and time-matched energetics, to examine how environmental characteristics, space, and time are linked to activity-related health behaviors with far more robust and detailed data than in previous work. Although the transdisciplinary field of spatial energetics demonstrates promise to provide novel insights on how individuals and populations interact with their environment, there remain significant conceptual, technical, analytical, and ethical challenges stemming from the complex data streams that spatial energetics research generates. First, it is essential to better understand what spatial energetics data represent, the relevant spatial context of analysis for these data, and if spatial energetics can establish causality for development of spatially relevant interventions. Second, there are significant technical problems for analysis of voluminous and complex data that may require development of spatially aware scalable computational infrastructures. Third, the field must come to agreement on appropriate statistical methodologies to account for multiple observations per person. Finally, these challenges must be considered within the context of maintaining participant privacy and security. This article describes gaps in current practice and understanding and suggests solutions to move this promising area of research forward. (C) 2016 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

Keywords

Physical-activity Levels; Built Environment; Activity Monitors; Travel Behavior; Health Research; Neighborhood; Exposure; Validation; Children; Design