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Research Theme: Safety & Health & Wellbeing

Scholarship on supporting human safety, health and well-being, from the individual, to built environment industries, to the region

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

Findings from Research on Active Transportation to School and Implications for Safe Routes to School Programs

Stewart, Orion. (2011). Findings from Research on Active Transportation to School and Implications for Safe Routes to School Programs. Journal Of Planning Literature, 26(2), 127 – 150.

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Abstract

This literature review identified common factors associated with active transportation to school (ATS). It used a conceptual framework of a child's commute mode to school to classify 480 variables from forty-two studies that were tested for association with ATS. Four factors most frequently influenced ATS: distance, income, traffic and crime fears, and parental attitudes and schedules. Regular ATS results in more physical activity but research is lacking on other outcomes. Safe Routes to School, a program designed to increase rates and safety of ATS, can use an understanding of these influences and outcomes to more effectively allocate its limited resources.

Keywords

Physical-activity Levels; Travel Mode; Urban Form; Environmental-factors; Elementary-schools; Weight Status; Walking; Children; Prevalence; Bus; Active Transportation To School; Safe Routes To School; Biking

Food Environment and Socioeconomic Status Influence Obesity Rates in Seattle and in Paris

Drewnowski, A.; Moudon, A. V.; Jiao, J.; Aggarwal, A.; Charreire, H.; Chaix, B. (2014). Food Environment and Socioeconomic Status Influence Obesity Rates in Seattle and in Paris. International Journal Of Obesity, 38(2), 306 – 314.

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Abstract

OBJECTIVE: To compare the associations between food environment at the individual level, socioeconomic status (SES) and obesity rates in two cities: Seattle and Paris. METHODS: Analyses of the SOS (Seattle Obesity Study) were based on a representative sample of 1340 adults in metropolitan Seattle and King County. The RECORD (Residential Environment and Coronary Heart Disease) cohort analyses were based on 7131 adults in central Paris and suburbs. Data on sociodemographics, health and weight were obtained from a telephone survey (SOS) and from in-person interviews (RECORD). Both studies collected data on and geocoded home addresses and food shopping locations. Both studies calculated GIS (Geographic Information System) network distances between home and the supermarket that study respondents listed as their primary food source. Supermarkets were further stratified into three categories by price. Modified Poisson regression models were used to test the associations among food environment variables, SES and obesity. RESULTS: Physical distance to supermarkets was unrelated to obesity risk. By contrast, lower education and incomes, lower surrounding property values and shopping at lower-cost stores were consistently associated with higher obesity risk. CONCLUSION: Lower SES was linked to higher obesity risk in both Paris and Seattle, despite differences in urban form, the food environments and in the respective systems of health care. Cross-country comparisons can provide new insights into the social determinants of weight and health.

Keywords

Obesity; Health & Social Status; Social Status; Supermarkets; Grocery Shopping; Physiology; Body-mass Index; Dietary Energy Density; Atherosclerosis Risk; Weight Status; Us Adults; Associations; Health; French; Access; Socioeconomic Status (ses); Access To Supermarket; Food Environment; Food Shopping

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

Perceptions, Behavioral Expectations, and Implementation Timing for Response Actions in a Hurricane Emergency

Huang, Shih-kai; Wu, Hao-che; Lindell, Michael K.; Wei, Hung-lung; Samuelson, Charles D. (2017). Perceptions, Behavioral Expectations, and Implementation Timing for Response Actions in a Hurricane Emergency. Natural Hazards, 88(1), 533 – 558.

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Abstract

This study examined the perceived attributes, behavioral expectations, and expected implementation timing of 11 organizational emergency response actions for hurricane emergencies. The perceived attributes of the hurricane response actions were characterized by two hazard-related attributes (effectiveness for person protection and property protection) and five resource-related attributes (financial costs, required knowledge/skill, required equipment, required time/effort, and required cooperation). A total of 155 introductory psychology students responded to a hypothetical scenario involving an approaching Category 4 hurricane. The data collected in this study explain previous findings of untimely protective action decision making. Specifically, these data reveal distinctly different patterns for the expected implementation of preparatory actions and evacuation recommendations. Participants used the hazard-related and resource-related attributes to differentiate among the response actions and the expected timing of implementation. Moreover, participants' behavioral expectations and expected implementation timing for the response actions were most strongly correlated with those actions' effectiveness for person protection. Finally, participants reported evacuation implementation times that were consistent with a phased evacuation strategy in which risk areas are evacuated in order of their proximity to the coast. However, the late initiation of evacuation in risk areas closest to the coast could lead to very late evacuation of risk areas farther inland.

Keywords

Action Decision-making; Interrater Agreement; Evacuation; Time; People; Preparatory Actions; Response Action Attributes; Trigger Timing; Hurricane; Psychology; Hurricanes; Costs; Emergency Response; Data; Proximity; Coastal Environments; Hazards; Decision Making; Emergencies; Emergency Preparedness; Risk; Equipment Costs; Cooperation; Protection; Equipment; Evacuations & Rescues; Behavioral Psychology; Time Measurement

Capturing Fine-Scale Travel Behaviors: A Comparative Analysis between Personal Activity Location Measurement System (PALMS) and Travel Diary

Kang, Mingyu; Moudon, Anne V.; Hurvitz, Philip M.; Saelens, Brian E. (2018). Capturing Fine-Scale Travel Behaviors: A Comparative Analysis between Personal Activity Location Measurement System (PALMS) and Travel Diary. International Journal Of Health Geographics, 17(1).

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Abstract

BackgroundDevice-collected data from GPS and accelerometers for identifying active travel behaviors have dramatically changed research methods in transportation planning and public health. Automated algorithms have helped researchers to process large datasets with likely fewer errors than found in other collection methods (e.g., self-report travel diary). In this study, we compared travel modes identified by a commonly used automated algorithm (PALMS) that integrates GPS and accelerometer data with those obtained from travel diary estimates.MethodsSixty participants, who made 2100 trips during seven consecutive days of data collection, were selected from among the baseline sample of a project examining the travel behavior impact of a new light rail system in the greater Seattle, WA (USA) area. GPS point level analyses were first conducted to compare trip/place and travel mode detection results using contingency tables. Trip level analyses were then performed to investigate the effect of proportions of time overlap between travel logs and device-collected data on agreement rates. Global performance (with all subjects' data combined) and subject-level performance of the algorithm were compared at the trip level.ResultsAt the GPS point level, the overall agreement rate of travel mode detection was 77.4% between PALMS and the travel diary. The agreement rate for vehicular trip detection (84.5%) was higher than for bicycling (53.5%) and walking (58.2%). At the trip level, the global performance and subject-level performance of the PALMS algorithm were 46.4% and 42.4%, respectively. Vehicular trip detection showed highest agreement rates in all analyses. Study participants' primary travel mode and car ownership were significantly related to the subject-level mode agreement rates.ConclusionsThe PALMS algorithm showed moderate identification power at the GPS point level. However, trip level analyses found lower agreement rates between PALMS and travel diary data, especially for active transportation. Testing different PALMS parameter settings may serve to improve the detection of active travel and help expand PALMS's applicability in geographically different urbanized areas with a variety of travel modes.

Keywords

Transportation Planning; Public Health; Accelerometers; Global Positioning System; Voyages & Travels; Cycling; Algorithms; Accelerometer; Automated Algorithm; Gis; Gps; Places; Trips; Global Positioning Systems; Physical-activity; Data-collection; Health Research; Gps Data; Accelerometry; Validity

Activity Space Metrics Not Associated with Sociodemographic Variables, Diet or Health Outcomes in the Seattle Obesity Study II

Drewnowski, Adam; Aggarwal, Anju; Rose, Chelsea M.; Gupta, Shilpi; Delaney, Joseph A.; Hurvitz, Philip M. (2019). Activity Space Metrics Not Associated with Sociodemographic Variables, Diet or Health Outcomes in the Seattle Obesity Study II. Spatial And Spatio-temporal Epidemiology, 30.

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Abstract

Background: Activity spaces (AS), captured using GPS tracking devices, are measures of dynamic exposure to the built environment (BE). Methods: Seven days of Global Positioning Systems (GPS) tracking data were obtained for 433 adult participants in the Seattle Obesity Study (SOS II). Heights and weights were measured. Dietary intakes from a food frequency questionnaire were used to calculate Healthy Eating Index (HEI 2010) scores. Linear regression analyses examined associations between AS measures: daily route length, convex hull, and radius of gyration, and diet quality and health outcomes, adjusting for covariates. Results: AS measures did not vary by age, gender, race/ethnicity, or socioeconomic status. AS measures were not associated with diet quality or with self-reported obesity or diabetes. One AS measure, route length (in miles), was associated with being employed, living in the suburbs, and with distance and time commuting to work. Conclusion: Spatial mobility studies based on GPS tracking of environmental exposure need to demonstrate a link to relevant health outcomes. (C) 2019 The Authors. Published by Elsevier Ltd.

Keywords

Local Food Environment; Physical-activity; Gps Data; Exposure; Patterns; Quality; Women; Index; Built Environment (be); Activity Space; Route Length; Hei 2010; Bmi