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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

A Time-Based Objective Measure of Exposure to the Food Environment

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

What County-level Factors Influence Covid-19 Incidence in the United States? Findings from the First Wave of the Pandemic

Wang, Lan; Zhang, Surong; Yang, Zilin; Zhao, Ziyu; Moudon, Anne Vernez; Feng, Huasen; Liang, Junhao; Sun, Wenyao; Cao, Buyang. (2021). What County-level Factors Influence Covid-19 Incidence in the United States? Findings from the First Wave of the Pandemic. Cities, 118.

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Abstract

Effective control of the COVID-19 pandemic via appropriate management of the built environment is an urgent issue. This study develops a research framework to explore the relationship between COVID-19 incidence and influential factors related to protection of vulnerable populations, intervention in transmission pathways, and provision of healthcare resources. Relevant data for regression analysis and structural equation modeling is collected during the first wave of the pandemic in the United States, from counties with over 100 confirmed cases. In addition to confirming certain factors found in the existing literature, we uncover six new factors significantly associated with COVID-19 incidence. Furthermore, incidence during the lockdown is found to significantly affect incidence after the reopening, highlighting that timely quarantining and treating of patients is essential to avoid the snowballing transmission over time. These findings suggest ways to mitigate the negative effects of subsequent waves of the pandemic, such as special attention of infection prevention in neighborhoods with unsanitary and overcrowded housing, minimization of social activities organized by neighborhood associations, and contactless home delivery service of healthy food. Also worth noting is the need to provide support to people less capable of complying with the stay-at-home order because of their occupations or socio-economic disadvantage.

Keywords

Pandemics; Covid-19; Covid-19 Pandemic; Infection Prevention; Stay-at-home Orders; Structural Equation Modeling; United States; Communicable Disease Prevention; Influential Factors; Lockdown; Structural Equation Modeling (sem); Prevalence; Disease; Healthy Food; Social Activities; Counties; Neighborhoods; Housing; Built Environment; Prevention; Minimization; Socioeconomic Factors; Intervention; Health Care; Vulnerability; Occupations; Coronaviruses; Food Service; Disease Transmission; United States--us

Urban Form Lab

The Urban Form Lab (UFL) research aims to affect policy and to support approaches to the design and planning of more livable environments. The UFL specializes in geospatial analyses of the built environment using multiple micro-scale data in Geographic Information Systems (GIS). Current research includes the development of novel GIS routines for performing spatial inventories and analyses of the built environment, and of spatially explicit sampling techniques. Projects address such topics as land monitoring, neighborhood and street design, active transportation, non-motorized transportation safety, physical activity, and access to food environments. 

Research at the UFL has been supported by the U.S. and Washington State Departments of Transportation, the Centers for Disease Control and Prevention, the Robert Wood Johnson Foundation, the National Institutes of Health, and local agencies.

The Urban Form Lab is directed by Anne Vernez Moudon, Dr es Sc, a leading researcher and educator in quantifying the properties of the built environment as related to health and transportation behaviors. Philip M. Hurvitz, PhD, a veteran of geographic information science and data processing, leads data management and GIS work.

Urban@UW helps BE labs collaborate

The Urban@UW initiative brings together labs that study urban issues from across the University of Washington. Urban@UW works with scholars, policymakers, and community stakeholders in order to strengthen the connection between research and solutions to urban issues through cross-disciplinary and cross-sector collaborative research. Key functions of Urban@UW include amplifying public awareness of ongoing projects, connecting researchers with outside constituencies, providing staff and administrative support services, and providing pilot funding and fundraising assistance. Multiple BE labs are involved, including the Northwest…

New UW Data Collaborative connects BE researchers with restricted data

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