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Rosenberg DE, Cruz MF, Mooney SJ, Bobb JF, Drewnowski A, Moudon AV, Cook AJ, Hurvitz PM, Lozano P, Anau J, Theis MK, Arterburn DE. Neighborhood built and food environment in relation to glycemic control in people with type 2 diabetes in the moving to health study. Health Place 2024; 86:103216. [PMID: 38401397 PMCID: PMC10957299 DOI: 10.1016/j.healthplace.2024.103216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 01/05/2024] [Accepted: 02/16/2024] [Indexed: 02/26/2024]
Abstract
OBJECTIVE To examine whether built environment and food metrics are associated with glycemic control in people with type 2 diabetes. RESEARCH DESIGN AND METHODS We included 14,985 patients with type 2 diabetes using electronic health records from Kaiser Permanente Washington. Patient addresses were geocoded with ArcGIS using King County and Esri reference data. Built environment exposures estimated from geocoded locations included residential unit density, transit threshold residential unit density, park access, and having supermarkets and fast food restaurants within 1600-m Euclidean buffers. Linear mixed effects models compared mean changes of HbA1c from baseline at 1, 3 (primary) and 5 years by each built environment variable. RESULTS Patients (mean age = 59.4 SD = 13.2, 49.5% female, 16.6% Asian, 9.8% Black, 5.5% Latino/Hispanic, 57.1% White, 20% insulin dependent, mean BMI = 32.7±7.7) had an average of 6 HbA1c measures available. Participants in the 1st tertile of residential density (lowest) had a greater decline in HbA1c (-0.42, -0.43, and -0.44 in years 1, 3, and 5 respectively) than those in the 3rd tertile (HbA1c = -0.37 at 1- and 3-years and -0.36 at 5-years; all p-values <0.05). Having any supermarkets within 1600 m of home was associated with a greater decrease in HbA1c at 1-year and 3-years compared to having none (all p-values <0.05). CONCLUSIONS Lower residential density and better proximity to supermarkets may benefit HbA1c control in people with people with type 2 diabetes. However, effects were small and indicate limited clinical significance.
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Affiliation(s)
| | - Maricela F Cruz
- Kaiser Permanente Washington Health Research Institute, USA.
| | | | - Jennifer F Bobb
- Kaiser Permanente Washington Health Research Institute, USA.
| | | | | | - Andrea J Cook
- Kaiser Permanente Washington Health Research Institute, USA.
| | - Philip M Hurvitz
- University of Washington, Center for Studies in Demography and Ecology, USA.
| | - Paula Lozano
- Kaiser Permanente Washington Health Research Institute, USA.
| | - Jane Anau
- Kaiser Permanente Washington Health Research Institute, USA.
| | - Mary Kay Theis
- Kaiser Permanente Washington Health Research Institute, USA.
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Jayakumar P, Bozic K. Journal of the American Academy of Orthopaedic Surgeons Patient-Reported Outcome Measurements (PROMs) Special Issue: The Value of PROMs in Orthopaedic Surgery. J Am Acad Orthop Surg 2023; 31:1048-1056. [PMID: 37670717 DOI: 10.5435/jaaos-d-23-00500] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Accepted: 06/07/2023] [Indexed: 09/07/2023] Open
Affiliation(s)
- Prakash Jayakumar
- From the the University of Texas at Austin, Dell Medical School, Austin, TX
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Reid SC, Wang V, Assaf RD, Kaloper S, Murray AT, Shoptaw S, Gorbach P, Cassels S. Novel Location-Based Survey Using Cognitive Interviews to Assess Geographic Networks and Hotspots of Sex and Drug Use: Implementation and Validation Study. JMIR Form Res 2023; 7:e45188. [PMID: 37347520 DOI: 10.2196/45188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 04/13/2023] [Accepted: 04/14/2023] [Indexed: 06/23/2023] Open
Abstract
BACKGROUND The Ending the HIV Epidemic initiative in the United States relies on HIV hotspots to identify where to geographically target new resources, expertise, and technology. However, interventions targeted at places with high HIV transmission and infection risk, not just places with high HIV incidence, may be more effective at reducing HIV incidence and achieving health equity. OBJECTIVE We described the implementation and validation of a web-based activity space survey on HIV risk behaviors. The survey was intended to collect geographic information that will be used to map risk behavior hotspots as well as the geography of sexual networks in Los Angeles County. METHODS The survey design team developed a series of geospatial questions that follow a 3-level structure that becomes more geographically precise as participants move through the levels. The survey was validated through 9 cognitive interviews and iteratively updated based on participant feedback until the saturation of topics and technical issues was reached. RESULTS In total, 4 themes were identified through the cognitive interviews: functionality of geospatial questions, representation and accessibility, privacy, and length and understanding of the survey. The ease of use for the geospatial questions was critical as many participants were not familiar with mapping software. The inclusion of well-known places, landmarks, and road networks was critical for ease of use. The addition of a Google Maps interface, which was familiar to many participants, aided in collecting accurate and precise location information. The geospatial questions increased the length of the survey and warranted the inclusion of features to simplify it and speed it up. Using nicknames to refer to previously entered geographic locations limited the number of geospatial questions that appeared in the survey and reduced the time taken to complete it. The long-standing relationship between participants and the research team improved comfort to disclose sensitive geographic information related to drug use and sex. Participants in the cognitive interviews highlighted how trust and inclusive and validating language in the survey alleviated concerns related to privacy and representation. CONCLUSIONS This study provides promising results regarding the feasibility of using a web-based mapping survey to collect sensitive location information relevant to ending the HIV epidemic. Data collection at several geographic levels will allow for insights into spatial recall of behaviors as well as future sensitivity analysis of the spatial scale of hotspots and network characteristics. This design also promotes the privacy and comfort of participants who provide location information for sensitive topics. Key considerations for implementing this type of survey include trust from participants, community partners, or research teams to overcome concerns related to privacy and comfort. The implementation of similar surveys should consider local characteristics and knowledge when crafting the geospatial components.
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Affiliation(s)
- Sean C Reid
- Department of Geography, University of California, Santa Barbara, Santa Barbara, CA, United States
| | - Vania Wang
- Department of Geography, University of California, Santa Barbara, Santa Barbara, CA, United States
| | - Ryan D Assaf
- Benioff Homelessness and Housing Initiative, Center for Vulnerable Populations, Department of Medicine, University of California, San Francisco, San Francisco, CA, United States
| | - Sofia Kaloper
- Department of Geography, University of California, Santa Barbara, Santa Barbara, CA, United States
| | - Alan T Murray
- Department of Geography, University of California, Santa Barbara, Santa Barbara, CA, United States
| | - Steven Shoptaw
- Family Medicine and Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States
| | - Pamina Gorbach
- Department of Epidemiology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Susan Cassels
- Department of Geography, University of California, Santa Barbara, Santa Barbara, CA, United States
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Duncan GE, Sun F, Avery AR, Hurvitz PM, Moudon AV, Tsang S, Williams BD. Cross-Sectional Study of Location-Based Built Environments, Physical Activity, Dietary Intake, and Body Mass Index in Adult Twins. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:4885. [PMID: 36981789 PMCID: PMC10049069 DOI: 10.3390/ijerph20064885] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 03/02/2023] [Accepted: 03/08/2023] [Indexed: 06/18/2023]
Abstract
We examined relationships between walkability and health behaviors between and within identical twin pairs, considering both home (neighborhood) walkability and each twin's measured activity space. Continuous activity and location data (via accelerometry and GPS) were obtained in 79 pairs over 2 weeks. Walkability was estimated using Walk Score® (WS); home WS refers to neighborhood walkability, and GPS WS refers to the mean of individual WSs matched to every GPS point collected by each participant. GPS WS was assessed within (WHN) and out of the neighborhood (OHN), using 1-mile Euclidean (air1mi) and network (net1mi) buffers. Outcomes included walking and moderate-to-vigorous physical activity (MVPA) bouts, dietary energy density (DED), and BMI. Home WS was associated with WHN GPS WS (b = 0.71, SE = 0.03, p < 0.001 for air1mi; b = 0.79, SE = 0.03, p < 0.001 for net1mi), and OHN GPS WS (b = 0.18, SE = 0.04, p < 0.001 for air1mi; b = 0.22, SE = 0.04, p < 0.001 for net1mi). Quasi-causal relationships (within-twin) were observed for home and GPS WS with walking (ps < 0.01), but not MVPA, DED, or BMI. Results support previous literature that neighborhood walkability has a positive influence on walking.
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Affiliation(s)
- Glen E. Duncan
- Department of Nutrition and Exercise Physiology, Elson S. Floyd College of Medicine, Washington State University Health Sciences Spokane, Spokane, WA 99202, USA
| | - Feiyang Sun
- Department of Urban Design and Planning, College of Built Environments, University of Washington, Seattle, WA 98195, USA
| | - Ally R. Avery
- Department of Nutrition and Exercise Physiology, Elson S. Floyd College of Medicine, Washington State University Health Sciences Spokane, Spokane, WA 99202, USA
| | - Philip M. Hurvitz
- Department of Urban Design and Planning, College of Built Environments, University of Washington, Seattle, WA 98195, USA
- Center for Studies in Demography & Ecology, College of Arts and Sciences, University of Washington, Seattle, WA 98195, USA
| | - Anne Vernez Moudon
- Department of Urban Design and Planning, College of Built Environments, University of Washington, Seattle, WA 98195, USA
| | - Siny Tsang
- Department of Nutrition and Exercise Physiology, Elson S. Floyd College of Medicine, Washington State University Health Sciences Spokane, Spokane, WA 99202, USA
| | - Bethany D. Williams
- Department of Nutrition and Exercise Physiology, Elson S. Floyd College of Medicine, Washington State University Health Sciences Spokane, Spokane, WA 99202, USA
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Duncan GE, Avery AA, Hurvitz P, Vernez-Moudon A, Tsang S. Cross-sectional associations between neighbourhood walkability and objective physical activity levels in identical twins. BMJ Open 2022; 12:e064808. [PMID: 36385026 PMCID: PMC9670932 DOI: 10.1136/bmjopen-2022-064808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
OBJECTIVES Physical activity is a cornerstone of chronic disease prevention and treatment, yet most US adults do not perform levels recommended for health. The neighborhood-built environment (BE) may support or hinder physical activity levels. This study investigated whether identical twins who reside in more walkable BEs have greater activity levels than twins who reside in less walkable BEs (between-twin analysis), and whether associations remain significant when controlling for genetic and shared environmental factors (within-twin analysis). DESIGN A cross-sectional study. SETTING The Puget Sound region around Seattle, Washington, USA. PARTICIPANTS The sample consisted of 112 identical twin pairs who completed an in-person assessment and 2-week at-home measurement protocol using a global positioning system (GPS)monitor and accelerometer. EXPOSURE The walkability of each participants' place of residence was calculated using three BE dimensions (intersection density, population density and destination accessibility). For each variable, z scores were calculated and summed to produce the final walkability score. OUTCOMES Objectively measured bouts of walking and moderate-to-vigorous physical activity (MVPA), expressed as minutes per week. RESULTS Walkability was associated with walking bouts (but not MVPA) within the neighbourhood, both between (b=0.58, SE=0.13, p<0.001) and within pairs (b=0.61, SE=0.18, p=0.001). For a pair with a 2-unit difference in walkability, the twin in a more walkable neighbourhood is likely to walk approximately 16 min per week more than the co-twin who lives in a less walkable neighbourhood. CONCLUSIONS This study provides robust evidence of an association between walkability and objective walking bouts. Improvements to the neighbourhood BE could potentially lead to increased activity levels in communities throughout the USA.
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Affiliation(s)
- Glen E Duncan
- Department of Nutrition and Exercise Physiology, Washington State University, Spokane, Washington, USA
| | - Ally A Avery
- Department of Nutrition and Exercise Physiology, Washington State University, Spokane, Washington, USA
| | - Philip Hurvitz
- Urban Design and Planning, University of Washington, Seattle, Washington, USA
| | - Anne Vernez-Moudon
- Urban Design and Planning, University of Washington, Seattle, Washington, USA
| | - Siny Tsang
- Department of Nutrition and Exercise Physiology, Washington State University, Spokane, Washington, USA
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Cruz M, Drewnowski A, Bobb JF, Hurvitz PM, Moudon AV, Cook A, Mooney SJ, Buszkiewicz JH, Lozano P, Rosenberg DE, Kapos F, Theis MK, Anau J, Arterburn D. Differences in Weight Gain Following Residential Relocation in the Moving to Health (M2H) Study. Epidemiology 2022; 33:747-755. [PMID: 35609209 PMCID: PMC9378543 DOI: 10.1097/ede.0000000000001505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
BACKGROUND Neighborhoods may play an important role in shaping long-term weight trajectory and obesity risk. Studying the impact of moving to another neighborhood may be the most efficient way to determine the impact of the built environment on health. We explored whether residential moves were associated with changes in body weight. METHODS Kaiser Permanente Washington electronic health records were used to identify 21,502 members aged 18-64 who moved within King County, WA between 2005 and 2017. We linked body weight measures to environment measures, including population, residential, and street intersection densities (800 m and 1,600 m Euclidian buffers) and access to supermarkets and fast foods (1,600 m and 5,000 m network distances). We used linear mixed models to estimate associations between postmove changes in environment and changes in body weight. RESULTS In general, moving from high-density to moderate- or low-density neighborhoods was associated with greater weight gain postmove. For example, those moving from high to low residential density neighborhoods (within 1,600 m) gained an average of 4.5 (95% confidence interval [CI] = 3.0, 5.9) lbs 3 years after moving, whereas those moving from low to high-density neighborhoods gained an average of 1.3 (95% CI = -0.2, 2.9) lbs. Also, those moving from neighborhoods without fast-food access (within 1600m) to other neighborhoods without fast-food access gained less weight (average 1.6 lbs [95% CI = 0.9, 2.4]) than those moving from and to neighborhoods with fast-food access (average 2.8 lbs [95% CI = 2.5, 3.2]). CONCLUSIONS Moving to higher-density neighborhoods may be associated with reductions in adult weight gain.
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Affiliation(s)
- Maricela Cruz
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, 98195, USA
| | - Adam Drewnowski
- Center for Public Health Nutrition, 305 Raitt Hall, #353410, University of Washington, Seattle, WA, 98195-3410, USA
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, 98195, USA
| | - Jennifer F. Bobb
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, 98195, USA
| | - Philip M Hurvitz
- Urban Form Lab, Department of Urban Design and Planning, College of Built Environments, University of Washington, 4333 Brooklyn Ave NE, Seattle, Washington 98195, USA
- Center for Studies in Demography and Ecology, University of Washington, Seattle, WA, 98195-3410, USA
| | - Anne Vernez Moudon
- Urban Form Lab, Department of Urban Design and Planning, College of Built Environments, University of Washington, 4333 Brooklyn Ave NE, Seattle, Washington 98195, USA
| | - Andrea Cook
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, 98195, USA
| | - Stephen J. Mooney
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, 98195, USA
| | - James H. Buszkiewicz
- Center for Public Health Nutrition, 305 Raitt Hall, #353410, University of Washington, Seattle, WA, 98195-3410, USA
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, 98195, USA
| | - Paula Lozano
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
| | - Dori E. Rosenberg
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
| | - Flavia Kapos
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, 98195, USA
| | - Mary Kay Theis
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
| | - Jane Anau
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
| | - David Arterburn
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
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Associations between neighborhood built environment, residential property values, and adult BMI change: The Seattle Obesity Study III. SSM Popul Health 2022; 19:101158. [PMID: 35813186 PMCID: PMC9260622 DOI: 10.1016/j.ssmph.2022.101158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 06/24/2022] [Accepted: 06/25/2022] [Indexed: 11/25/2022] Open
Abstract
Objective To examine associations between neighborhood built environment (BE) variables, residential property values, and longitudinal 1- and 2-year changes in body mass index (BMI). Methods The Seattle Obesity Study III was a prospective cohort study of adults with geocoded residential addresses, conducted in King, Pierce, and Yakima Counties in Washington State. Measured heights and weights were obtained at baseline (n = 879), year 1 (n = 727), and year 2 (n = 679). Tax parcel residential property values served as proxies for individual socioeconomic status. Residential unit and road intersection density were captured using Euclidean-based SmartMaps at 800 m buffers. Counts of supermarket (0 versus. 1+) and fast-food restaurant availability (0, 1–3, 4+) were measured using network based SmartMaps at 1600 m buffers. Density measures and residential property values were categorized into tertiles. Linear mixed-effects models tested whether baseline BE variables and property values were associated with differential changes in BMI at year 1 or year 2, adjusting for age, gender, race/ethnicity, education, home ownership, and county of residence. These associations were then tested for potential disparities by age group, gender, race/ethnicity, and education. Results Road intersection density, access to food sources, and residential property values were inversely associated with BMI at baseline. At year 1, participants in the 3rd tertile of density metrics and with 4+ fast-food restaurants nearby showed less BMI gain compared to those in the 1st tertile or with 0 restaurants. At year 2, higher residential property values were predictive of lower BMI gain. There was evidence of differential associations by age group, gender, and education but not race/ethnicity. Conclusion Inverse associations between BE metrics and residential property values at baseline demonstrated mixed associations with 1- and 2-year BMI change. More work is needed to understand how individual-level sociodemographic factors moderate associations between the BE, property values, and BMI change. Strong, inverse cross-sectional relationships between the built environment, residential property values (a proxy for individual socioeconomic status), and measured BMI were observed. Measures of the built environment and residential property values showed modest and inconsistent associations with 1- and 2-year BMI change. There was suggestive evidence that age may moderate the association between urban density and 1- and 2-year BMI change while education may moderate the association between residential property values and 2-year BMI change.
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Ribeiro R, Trifan A, Neves AJR. Lifelog Retrieval From Daily Digital Data: Narrative Review. JMIR Mhealth Uhealth 2022; 10:e30517. [PMID: 35499858 PMCID: PMC9112086 DOI: 10.2196/30517] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 09/14/2021] [Accepted: 03/11/2022] [Indexed: 11/13/2022] Open
Abstract
Background Over the past decade, the wide availability and small size of different types of sensors, together with the decrease in pricing, have allowed the acquisition of a substantial amount of data about a person’s life in real time. These sensors can be incorporated into personal electronic devices available at a reasonable cost, such as smartphones and small wearable devices. They allow the acquisition of images, audio, location, physical activity, and physiological signals among other data. With these data, usually denoted as lifelog data, we can then analyze and understand personal experiences and behaviors. This process is called lifelogging. Objective The objective of this paper was to present a narrative review of the existing literature about lifelogging over the past decade. To achieve this goal, we analyzed lifelogging applications used to retrieve relevant information from daily digital data, some of them with the purpose of monitoring and assisting people with memory issues and others designed for memory augmentation. We aimed for this review to be used by researchers to obtain a broad idea of the type of data used, methodologies, and applications available in this research field. Methods We followed a narrative review methodology to conduct a comprehensive search for relevant publications in Google Scholar and Scopus databases using lifelog topic–related keywords. A total of 411 publications were retrieved and screened. Of these 411 publications, 114 (27.7%) publications were fully reviewed. In addition, 30 publications were manually included based on our bibliographical knowledge of this research field. Results From the 144 reviewed publications, a total of 113 (78.5%) were selected and included in this narrative review based on content analysis. The findings of this narrative review suggest that lifelogs are prone to become powerful tools to retrieve memories or increase knowledge about an individual’s experiences or behaviors. Several computational tools are already available for a considerable range of applications. These tools use multimodal data of different natures, with visual lifelogs being one of the most used and rich sources of information. Different approaches and algorithms to process these data are currently in use, as this review will unravel. Moreover, we identified several open questions and possible lines of investigation in lifelogging. Conclusions The use of personal lifelogs can be beneficial to improve the quality of our life, as they can serve as tools for memory augmentation or for providing support to people with memory issues. Through the acquisition and analysis of lifelog data, lifelogging systems can create digital memories that can be potentially used as surrogate memory. Through this narrative review, we understand that contextual information can be extracted from lifelogs, which provides an understanding of the daily life of a person based on events, experiences, and behaviors.
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Affiliation(s)
- Ricardo Ribeiro
- Institute of Electronics and Informatics Engineering of Aveiro, University of Aveiro, Aveiro, Portugal
| | - Alina Trifan
- Institute of Electronics and Informatics Engineering of Aveiro, University of Aveiro, Aveiro, Portugal
| | - António J R Neves
- Institute of Electronics and Informatics Engineering of Aveiro, University of Aveiro, Aveiro, Portugal
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Wang Y, Moudon AV, Shen Q. How Does Ride-Hailing Influence Individual Mode Choice? An Examination Using Longitudinal Trip Data from the Seattle Region. TRANSPORTATION RESEARCH RECORD 2022; 2676:621-633. [PMID: 35694240 PMCID: PMC9176857 DOI: 10.1177/03611981211055669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
This study investigates the impacts of ride-hailing, which we define as mobility services consisting of both conventional taxis and app-based services offered by transportation network companies, on individual mode choice. We examine whether ride-hailing substitutes for or complements travel by driving, public transit, or walking and biking. The study overcomes some of the limitations of convenience samples or cross-sectional surveys used in past research by employing a longitudinal dataset of individual travel behavior and socio-demographic information. The data include three waves of travel log data collected between 2012 to 2018 in transit-rich areas of the Seattle region. We conducted individual-level panel data modeling, estimating independently pooled models and fixed-effect models of average daily trip count and duration for each mode, while controlling for various factors that affect travel behavior. The results provide evidence of substitution effects of ride-hailing on driving. We found that cross-sectionally, participants who used more ride-hailing tended to drive less, and that longitudinally, an increase in ride-hailing usage was associated with fewer driving trips. No significant associations were found between ride-hailing and public transit usage or walking and biking. Based on detailed travel data of a large population in a major US metropolitan area, the study highlights the value of collecting and analyzing longitudinal data to understand the impacts of new mobility services.
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Affiliation(s)
- Yiyuan Wang
- Interdisciplinary PhD Program in Urban Design and Planning, University of Washington, Seattle, WA, 98195
| | - Anne Vernez Moudon
- Department of Urban Design and Planning, University of Washington, Seattle, WA, 98195
| | - Qing Shen
- Department of Urban Design and Planning, Interdisciplinary PhD Program in Urban Design and Planning, University of Washington, Seattle, WA, 98195
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Edney SM, Park SH, Tan L, Chua XH, Dickens BSL, Rebello SA, Petrunoff N, Müller AM, Tan CS, Müller-Riemenschneider F, van Dam RM. Advancing understanding of dietary and movement behaviours in an Asian population through real-time monitoring: Protocol of the Continuous Observations of Behavioural Risk Factors in Asia study (COBRA). Digit Health 2022; 8:20552076221110534. [PMID: 35795338 PMCID: PMC9251970 DOI: 10.1177/20552076221110534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 06/13/2022] [Indexed: 11/17/2022] Open
Abstract
Background Modifiable risk factors for non-communicable diseases, including eating an unhealthy diet and being physically inactive, are influenced by complex and dynamic interactions between people and their social and physical environment. Therefore, understanding patterns and determinants of these risk factors as they occur in real life is essential to enable the design of precision public health interventions. Objective This paper describes the protocol for the Continuous Observations of Behavioural Risk Factors in Asia study (COBRA). The study uses real-time data capture methods to gain a comprehensive understanding of eating and movement behaviours, including how these differ by socio-demographic characteristics and are shaped by people's interaction with their social and physical environment. Methods COBRA is an observational study in free-living conditions. We will recruit 1500 adults aged 21-69 years from a large prospective cohort study. Real-time data capture methods will be used for nine consecutive days: an ecological momentary assessment app with a global positioning system enabled to collect location data, accelerometers to measure movement, and wearable sensors to monitor blood glucose levels. Participants receive six EMA surveys per day between 8 a.m. and 9.30 p.m. to capture information on behavioural risk factors including eating behaviours and diet composition movement behaviours (physical activity, sedentary behaviour, sleep), and related contextual factors. The second wave of ecological momentary assessment surveys with a global positioning system enabled will be sent 6 months later. Data will be analysed using generalised linear models to examine associations between behavioural risk factors and contextual determinants. Discussion Findings from this study will advance our understanding of dietary and movement behaviours as they occur in real-life and inform the development of personalised interventions to prevent chronic diseases.
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Affiliation(s)
- Sarah Martine Edney
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Su Hyun Park
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Linda Tan
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Xin Hui Chua
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Borame Sue Lee Dickens
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Salome A Rebello
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Nick Petrunoff
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Andre Matthias Müller
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Cheun Seng Tan
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Falk Müller-Riemenschneider
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Digital Health Center, Berlin Institute of Health, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Departments of Exercise and Nutrition Sciences and Epidemiology, Milken Institute of Public Health, The George Washington University, Washington, DC, USA
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Patel M, Oh AY, Dwyer LA, D'Angelo H, Stinchcomb DG, Liu B, Yu M, Nebeling LC. Effects of Buffer Size and Shape on the Association of Neighborhood SES and Adult Fruit and Vegetable Consumption. Front Public Health 2021; 9:706151. [PMID: 34858916 PMCID: PMC8631279 DOI: 10.3389/fpubh.2021.706151] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Accepted: 10/11/2021] [Indexed: 11/24/2022] Open
Abstract
Introduction: Neighborhood environment factors are relevant for dietary behaviors, but associations between home neighborhood context and disease prevention behaviors vary depending on the definition of neighborhood. The present study uses a publicly available dataset to examine whether associations between neighborhood socioeconomic status (NSES) and fruit/vegetable (FV) consumption vary when NSES is defined by different neighborhood sizes and shapes. Methods: We analyzed data from 1,736 adults with data in GeoFLASHE, a geospatial extension of the National Cancer Institute's Family Life, Activity, Sun, Health, and Eating Study (FLASHE). We examined correlations of NSES values across neighborhood buffer shapes (circular or street network) and sizes (ranging from 400 to 1,200 m) and ran weighted simple and multivariable regressions modeling frequency of FV consumption by NSES for each neighborhood definition. Regressions were also stratified by gender. Results: NSES measures were highly correlated across various neighborhood buffer definitions. In models adjusted for socio-demographics, circular buffers of all sizes and street buffers 750 m and larger were significantly associated with FV consumption frequency for women only. Conclusion: NSES may be particularly relevant for women's FV consumption, and further research can examine whether these associations are explained by access to food stores, food shopping behavior, and/or psychosocial variables. Although different NSES buffers are highly correlated, researchers should conceptually determine spatial areas a priori.
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Affiliation(s)
- Minal Patel
- Behavioral Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
| | - April Y Oh
- Behavioral Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
| | - Laura A Dwyer
- Cape Fox Facilities Services, Manassas, VA, United States
| | - Heather D'Angelo
- Behavioral Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
| | | | - Benmei Liu
- Surveillance Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
| | - Mandi Yu
- Surveillance Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
| | - Linda C Nebeling
- Behavioral Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
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12
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Buszkiewicz JH, Bobb JF, Kapos F, Hurvitz PM, Arterburn D, Moudon AV, Cook A, Mooney SJ, Cruz M, Gupta S, Lozano P, Rosenberg DE, Theis MK, Anau J, Drewnowski A. Differential associations of the built environment on weight gain by sex and race/ethnicity but not age. Int J Obes (Lond) 2021; 45:2648-2656. [PMID: 34453098 PMCID: PMC8608695 DOI: 10.1038/s41366-021-00937-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Revised: 07/19/2021] [Accepted: 08/04/2021] [Indexed: 11/18/2022]
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.
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Affiliation(s)
- James H Buszkiewicz
- Center for Public Health Nutrition, 305 Raitt Hall, #353410, University of Washington, Seattle, WA, USA.
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA.
| | - Jennifer F Bobb
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Flavia Kapos
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
| | - Philip M Hurvitz
- Urban Form Lab, Department of Urban Design and Planning, College of Built Environments, University of Washington, Seattle, WA, USA
- Center for Studies in Demography and Ecology, University of Washington, Raitt Hall, Seattle, WA, USA
| | - David Arterburn
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Anne Vernez Moudon
- Urban Form Lab, Department of Urban Design and Planning, College of Built Environments, University of Washington, Seattle, WA, USA
| | - Andrea Cook
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Stephen J Mooney
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
| | - Maricela Cruz
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Shilpi Gupta
- Center for Public Health Nutrition, 305 Raitt Hall, #353410, University of Washington, Seattle, WA, USA
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
| | - Paula Lozano
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Dori E Rosenberg
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Mary Kay Theis
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Jane Anau
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Adam Drewnowski
- Center for Public Health Nutrition, 305 Raitt Hall, #353410, University of Washington, Seattle, WA, USA
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
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13
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Steel C, Crist K, Grimes A, Bejarano C, Ortega A, Hibbing PR, Schipperijn J, Carlson JA. Validity of a Global Positioning System-Based Algorithm and Consumer Wearables for Classifying Active Trips in Children and Adults. JOURNAL FOR THE MEASUREMENT OF PHYSICAL BEHAVIOUR 2021; 4:321-332. [PMID: 36237517 PMCID: PMC9555805 DOI: 10.1123/jmpb.2021-0019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
OBJECTIVE To investigate the convergent validity of a global positioning system (GPS)-based and two consumer-based measures with trip logs for classifying pedestrian, cycling, and vehicle trips in children and adults. METHODS Participants (N = 34) wore a Qstarz GPS tracker, Fitbit Alta, and Garmin vivosmart 3 on multiple days and logged their outdoor pedestrian, cycling, and vehicle trips. Logged trips were compared with device-measured trips using the Personal Activity Location Measurement System (PALMS) GPS-based algorithms, Fitbit's SmartTrack, and Garmin's Move IQ. Trip- and day-level agreement were tested. RESULTS The PALMS identified and correctly classified the mode of 75.6%, 94.5%, and 96.9% of pedestrian, cycling, and vehicle trips (84.5% of active trips, F1 = 0.84 and 0.87) as compared with the log. Fitbit and Garmin identified and correctly classified the mode of 26.8% and 17.8% (22.6% of active trips, F1 = 0.40 and 0.30) and 46.3% and 43.8% (45.2% of active trips, F1 = 0.58 and 0.59) of pedestrian and cycling trips. Garmin was more prone to false positives (false trips not logged). Day-level agreement for PALMS and Garmin versus logs was favorable across trip modes, though PALMS performed best. Fitbit significantly underestimated daily cycling. Results were similar but slightly less favorable for children than adults. CONCLUSIONS The PALMS showed good convergent validity in children and adults and were about 50% and 27% more accurate than Fitbit and Garmin (based on F1). Empirically-based recommendations for improving PALMS' pedestrian classification are provided. Since the consumer devices capture both indoor and outdoor walking/running and cycling, they are less appropriate for trip-based research.
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Affiliation(s)
- Chelsea Steel
- Center for Children's Healthy Lifestyles & Nutrition, Children's Mercy Hospital, Kansas City, MO, USA
| | - Katie Crist
- Department of Family Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Amanda Grimes
- School of Nursing and Health Studies, University of Missouri-Kansas City, Kansas City, MO, USA
| | - Carolina Bejarano
- Clinical Child Psychology Program, University of Kansas, Lawrence, KS, USA
| | - Adrian Ortega
- Clinical Child Psychology Program, University of Kansas, Lawrence, KS, USA
| | - Paul R Hibbing
- Center for Children's Healthy Lifestyles & Nutrition, Children's Mercy Hospital, Kansas City, MO, USA
| | - Jasper Schipperijn
- Department of Sport Sciences and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark
| | - Jordan A Carlson
- Center for Children's Healthy Lifestyles & Nutrition, Children's Mercy Hospital, Kansas City, MO, USA
- Department of Pediatrics, Children's Mercy Hospital, University of Missouri Kansas City, Kansas City, MO, USA
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14
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Buszkiewicz JH, Bobb JF, Hurvitz PM, Arterburn D, Moudon AV, Cook A, Mooney SJ, Cruz M, Gupta S, Lozano P, Rosenberg DE, Theis MK, Anau J, Drewnowski A. Does the built environment have independent obesogenic power? Urban form and trajectories of weight gain. Int J Obes (Lond) 2021; 45:1914-1924. [PMID: 33976378 PMCID: PMC8592117 DOI: 10.1038/s41366-021-00836-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 04/23/2021] [Indexed: 02/05/2023]
Abstract
OBJECTIVE To determine whether selected features of the built environment can predict weight gain in a large longitudinal cohort of adults. METHODS Weight trajectories over a 5-year period were obtained from electronic health records for 115,260 insured patients aged 18-64 years in the Kaiser Permanente Washington health care system. Home addresses were geocoded using ArcGIS. Built environment variables were population, residential unit, and road intersection densities captured using Euclidean-based SmartMaps at 800-m buffers. Counts of area supermarkets and fast food restaurants were obtained using network-based SmartMaps at 1600, and 5000-m buffers. Property values were a measure of socioeconomic status. Linear mixed effects models tested whether built environment variables at baseline were associated with long-term weight gain, adjusting for sex, age, race/ethnicity, Medicaid insurance, body weight, and residential property values. RESULTS Built environment variables at baseline were associated with differences in baseline obesity prevalence and body mass index but had limited impact on weight trajectories. Mean weight gain for the full cohort was 0.06 kg at 1 year (95% CI: 0.03, 0.10); 0.64 kg at 3 years (95% CI: 0.59, 0.68), and 0.95 kg at 5 years (95% CI: 0.90, 1.00). In adjusted regression models, the top tertile of density metrics and frequency counts were associated with lower weight gain at 5-years follow-up compared to the bottom tertiles, though the mean differences in weight change for each follow-up year (1, 3, and 5) did not exceed 0.5 kg. CONCLUSIONS Built environment variables that were associated with higher obesity prevalence at baseline had limited independent obesogenic power with respect to weight gain over time. Residential unit density had the strongest negative association with weight gain. Future work on the influence of built environment variables on health should also examine social context, including residential segregation and residential mobility.
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Affiliation(s)
- James H. Buszkiewicz
- Center for Public Health Nutrition, 305 Raitt Hall, #353410, University of Washington, Seattle, WA, 98195-3410, USA,Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, 98195, USA
| | - Jennifer F. Bobb
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
| | - Philip M Hurvitz
- Urban Form Lab, Department of Urban Design and Planning, College of Built Environments, University of Washington, 4333 Brooklyn Ave NE, Seattle, Washington 98195, USA,Center for Studies in Demography and Ecology, University of Washington, Seattle, WA, 98195-3410, USA
| | - David Arterburn
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
| | - Anne Vernez Moudon
- Urban Form Lab, Department of Urban Design and Planning, College of Built Environments, University of Washington, 4333 Brooklyn Ave NE, Seattle, Washington 98195, USA
| | - Andrea Cook
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
| | - Stephen J. Mooney
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, 98195, USA
| | - Maricela Cruz
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
| | - Shilpi Gupta
- Center for Public Health Nutrition, 305 Raitt Hall, #353410, University of Washington, Seattle, WA, 98195-3410, USA,Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, 98195, USA
| | - Paula Lozano
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
| | - Dori E. Rosenberg
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
| | - Mary Kay Theis
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
| | - Jane Anau
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
| | - Adam Drewnowski
- Center for Public Health Nutrition, 305 Raitt Hall, #353410, University of Washington, Seattle, WA, 98195-3410, USA,Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, 98195, USA
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15
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Boakye KA, Amram O, Schuna JM, Duncan GE, Hystad P. GPS-based built environment measures associated with adult physical activity. Health Place 2021; 70:102602. [PMID: 34139613 PMCID: PMC8328940 DOI: 10.1016/j.healthplace.2021.102602] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 06/03/2021] [Accepted: 06/04/2021] [Indexed: 10/21/2022]
Abstract
Studies often rely on home locations to access built environment (BE) influences on physical activity (PA). We use GPS and accelerometer data collected for 288 individuals over a two-week period to examine eight GPS-derived BE characteristics and moderate-to-vigorous PA (MVPA) and light-to-moderate-vigorous PA (LMVPA). NDVI, parks, blue space, pedestrian-orientated intersections, and population density were associated with increased odds of LMVPA and MVPA, while traffic air pollution and noise were associated with decreased odds of LMVPA and MVPA. Associations varied by population density and when accounting for multiple BE measures. These findings provide further information on where individuals choose to be physically active.
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Affiliation(s)
- Kwadwo A Boakye
- School of Biological and Population Health Sciences, Oregon State University, Corvallis, OR, USA.
| | - Ofer Amram
- Department of Nutrition and Exercise Physiology, Elson S. Floyd School of Medicine, Washington State University, Spokane, WA, 99202, USA; Paul G. Allen School for Global Animal Health, Washington State University, Pullman, WA, 99164, USA.
| | - John M Schuna
- School of Biological and Population Health Sciences, Oregon State University, Corvallis, OR, USA.
| | - Glen E Duncan
- Department of Nutrition and Exercise Physiology, Elson S. Floyd School of Medicine, Washington State University, Spokane, WA, 99202, USA.
| | - Perry Hystad
- School of Biological and Population Health Sciences, Oregon State University, Corvallis, OR, USA.
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16
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Duncan GE, Hurvitz PM, Moudon AV, Avery AR, Tsang S. Measurement of neighborhood-based physical activity bouts. Health Place 2021; 70:102595. [PMID: 34090126 PMCID: PMC8328921 DOI: 10.1016/j.healthplace.2021.102595] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Revised: 05/13/2021] [Accepted: 05/15/2021] [Indexed: 12/30/2022]
Abstract
This study examined how buffer type (shape), size, and the allocation of activity bouts inside buffers that delineate the neighborhood spatially produce different estimates of neighborhood-based physical activity. A sample of 375 adults wore a global positioning system (GPS) data logger and accelerometer over 2 weeks under free-living conditions. Analytically, the amount of neighborhood physical activity measured objectively varies substantially, not only due to buffer shape and size, but by how GPS-based activity bouts are identified with respect to containment within neighborhood buffers. To move the "neighborhood-effects" literature forward, it is critical to delineate the spatial extent of the neighborhood, given how different ways of measuring GPS-based activity containment will result in different levels of physical activity across different buffer types and sizes.
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Affiliation(s)
- Glen E Duncan
- Department of Nutrition and Exercise Physiology, Washington State University Health Sciences Spokane, Spokane, WA, USA.
| | - Philip M Hurvitz
- Urban Form Lab, University of Washington, Seattle, WA, USA; Center for Studies in Demography and Ecology, University of Washington, Seattle, WA, USA
| | | | - Ally R Avery
- Department of Nutrition and Exercise Physiology, Washington State University Health Sciences Spokane, Spokane, WA, USA
| | - Siny Tsang
- Department of Nutrition and Exercise Physiology, Washington State University Health Sciences Spokane, Spokane, WA, USA
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17
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Smith M, Cui J, Ikeda E, Mavoa S, Hasanzadeh K, Zhao J, Rinne TE, Donnellan N, Kyttä M. Objective measurement of children's physical activity geographies: A systematic search and scoping review. Health Place 2020; 67:102489. [PMID: 33302122 PMCID: PMC7883215 DOI: 10.1016/j.healthplace.2020.102489] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 11/20/2020] [Accepted: 11/20/2020] [Indexed: 12/21/2022]
Abstract
This study aimed to systematically identify, map out, and describe geographical information systems (GIS)-based approaches that have been employed to measure children's neighborhood geographies for physical activity behaviors. Forty studies were included, most were conducted in the USA. Heterogeneity in GIS methods and measures was found. The majority of studies estimated children's environments using Euclidean or network buffers ranging from 100 m to 5 km. No singular approach to measuring children's physical activity geographies was identified as optimal. Geographic diversity in studies as well as increased use of measures of actual neighborhood exposure are needed. Improved consistency and transparency in reporting research methods is urgently required. Varied GIS measures of children's physical activity geographies were identified. Evidence was heterogeneous and predominantly from the USA. Most research used Euclidean or network buffers ranging from 100 m to 5 km. Larger buffer sizes (i.e., ≥800 m) performed better than smaller buffer sizes. No optimal approach to measuring children's activity geographies was determined.
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Affiliation(s)
- Melody Smith
- School of Nursing, The University of Auckland, Auckland, New Zealand.
| | - Jianqiang Cui
- School of Environment and Science, Griffith University, Brisbane, Australia.
| | - Erika Ikeda
- Centre for Diet & Activity Research (CEDAR), MRC Epidemiology Unit, University of Cambridge, Cambridge, UK.
| | - Suzanne Mavoa
- Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.
| | | | - Jinfeng Zhao
- School of Nursing, The University of Auckland, Auckland, New Zealand.
| | - Tiina E Rinne
- Active Life Lab, South-Eastern Finland University of Applied Sciences, Mikkeli, Finland.
| | - Niamh Donnellan
- School of Nursing, University of Auckland, Auckland, New Zealand.
| | - Marketta Kyttä
- Department of Built Environment, Aalto University, Espoo, Finland.
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18
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The Moderating Effect of Distance on Features of the Built Environment and Active School Transport. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17217856. [PMID: 33120926 PMCID: PMC7662262 DOI: 10.3390/ijerph17217856] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 10/19/2020] [Accepted: 10/22/2020] [Indexed: 12/11/2022]
Abstract
Despite growing research supporting the impact of the built environment on active school transport (AST), distance persists as the most powerful predictor of walking and biking to school. There is a need to better understand how environmental features interact with distance to affect AST, and whether the influence of environmental factors persist across different distance thresholds. Multilevel models using cluster-robust standard errors were used to examine for interactions between objectively measured macroscale environmental features and several reported distances from home to school (up to ¼, ¼ up to ½, ½ up to 1, 1+ miles) on the likelihood of parent reported AST for children grades 3-8 (n = 2751) at 35 schools who completed a Safe Routes to School Parent Survey about Walking and Biking to School (SRTS Parent Survey). An interaction between both intersection density and food-related land use with distance was observed. The likelihood of AST decreased as intersection density and distance increased (i.e., 31.0% reduced odds among those living within ¼ mile compared to 18.2% using ½-1-mile criterion). The likelihood of using AST were reduced as food-related land use and distance increased (i.e., 43.67% reduced odds among those living under ¼ mile compared to 19.83% reduced odds among those living ½-1 mile). Programs and infrastructure improvements focused on overcoming environmental barriers to promote AST may be most effective when targeting neighborhoods within ¼ mile of schools.
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Resch B, Puetz I, Bluemke M, Kyriakou K, Miksch J. An Interdisciplinary Mixed-Methods Approach to Analyzing Urban Spaces: The Case of Urban Walkability and Bikeability. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:E6994. [PMID: 32987877 PMCID: PMC7579167 DOI: 10.3390/ijerph17196994] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/25/2020] [Revised: 09/17/2020] [Accepted: 09/21/2020] [Indexed: 11/17/2022]
Abstract
Human-centered approaches are of particular importance when analyzing urban spaces in technology-driven fields, because understanding how people perceive and react to their environments depends on several dynamic and static factors, such as traffic volume, noise, safety, urban configuration, and greenness. Analyzing and interpreting emotions against the background of environmental information can provide insights into the spatial and temporal properties of urban spaces and their influence on citizens, such as urban walkability and bikeability. In this study, we present a comprehensive mixed-methods approach to geospatial analysis that utilizes wearable sensor technology for emotion detection and combines information from sources that correct or complement each other. This includes objective data from wearable physiological sensors combined with an eDiary app, first-person perspective videos from a chest-mounted camera, and georeferenced interviews, and post-hoc surveys. Across two studies, we identified and geolocated pedestrians' and cyclists' moments of stress and relaxation in the city centers of Salzburg and Cologne. Despite open methodological questions, we conclude that mapping wearable sensor data, complemented with other sources of information-all of which are indispensable for evidence-based urban planning-offering tremendous potential for gaining useful insights into urban spaces and their impact on citizens.
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Affiliation(s)
- Bernd Resch
- Department of Geoinformatics—Z_GIS, University of Salzburg, 5020 Salzburg, Austria; (I.P.); (K.K.); (J.M.)
- Institute for Quantitative Social Science, Harvard University, Cambridge, MA 02138, USA
| | - Inga Puetz
- Department of Geoinformatics—Z_GIS, University of Salzburg, 5020 Salzburg, Austria; (I.P.); (K.K.); (J.M.)
| | - Matthias Bluemke
- GESIS—Leibniz Institute for the Social Sciences, 68159 Mannheim, Germany;
| | - Kalliopi Kyriakou
- Department of Geoinformatics—Z_GIS, University of Salzburg, 5020 Salzburg, Austria; (I.P.); (K.K.); (J.M.)
| | - Jakob Miksch
- Department of Geoinformatics—Z_GIS, University of Salzburg, 5020 Salzburg, Austria; (I.P.); (K.K.); (J.M.)
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20
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Mooney SJ, Hurvitz PM, Moudon AV, Zhou C, Dalmat R, Saelens BE. Residential neighborhood features associated with objectively measured walking near home: Revisiting walkability using the Automatic Context Measurement Tool (ACMT). Health Place 2020; 63:102332. [PMID: 32543423 PMCID: PMC7306420 DOI: 10.1016/j.healthplace.2020.102332] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Revised: 03/26/2020] [Accepted: 03/31/2020] [Indexed: 10/24/2022]
Abstract
Many distinct characteristics of the social, natural, and built neighborhood environment have been included in walkability measures, and it is unclear which measures best describe the features of a place that support walking. We developed the Automatic Context Measurement Tool, which measures neighborhood environment characteristics from public data for any point location in the United States. We explored these characteristics in home neighborhood environments in relation to walking identified from integrated GPS, accelerometer, and travel log data from 681 residents of King Country, WA. Of 146 neighborhood characteristics, 92 (63%) were associated with walking bout counts after adjustment for individual characteristics and correction for false discovery. The strongest built environment predictor of walking bout count was housing unit count. Models using data-driven and a priori defined walkability measures exhibited similar fit statistics. Walkability measures consisting of different neighborhood characteristic measurements may capture the same underlying variation in neighborhood conditions.
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Affiliation(s)
- Stephen J Mooney
- Department of Epidemiology, University of Washington, Seattle, WA, United States.
| | - Philip M Hurvitz
- Urban Form Lab, University of Washington, Seattle, WA, United States; Center for Studies in Demography and Ecology, University of Washington, Seattle, WA, United States
| | | | - Chuan Zhou
- Seattle Children's Research Institute, Seattle, WA, United States; Department of Pediatrics, University of Washington, Seattle, WA, United States
| | - Ronit Dalmat
- Department of Epidemiology, University of Washington, Seattle, WA, United States
| | - Brian E Saelens
- Seattle Children's Research Institute, Seattle, WA, United States; Department of Pediatrics, University of Washington, Seattle, WA, United States
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21
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Mooney SJ, Bobb JF, Hurvitz PM, Anau J, Theis MK, Drewnowski A, Aggarwal A, Gupta S, Rosenberg DE, Cook AJ, Shi X, Lozano P, Moudon AV, Arterburn D. Impact of Built Environments on Body Weight (the Moving to Health Study): Protocol for a Retrospective Longitudinal Observational Study. JMIR Res Protoc 2020; 9:e16787. [PMID: 32427111 PMCID: PMC7268006 DOI: 10.2196/16787] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Revised: 12/20/2019] [Accepted: 01/07/2020] [Indexed: 01/01/2023] Open
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. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) DERR1-10.2196/16787.
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Affiliation(s)
- Stephen J Mooney
- Department of Epidemiology, University of Washington, Seattle, WA, United States.,Harborview Injury Prevention & Research Center, University of Washington, Seattle, WA, United States
| | - Jennifer F Bobb
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, United States
| | - Philip M Hurvitz
- Department of Urban Design and Planning, College of Built Environments, University of Washington, Seattle, WA, United States
| | - Jane Anau
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, United States
| | - Mary Kay Theis
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, United States
| | - Adam Drewnowski
- Department of Epidemiology, University of Washington, Seattle, WA, United States.,Center for Public Health Nutrition, University of Washington, Seattle, WA, United States
| | - Anju Aggarwal
- Department of Epidemiology, University of Washington, Seattle, WA, United States.,Center for Public Health Nutrition, University of Washington, Seattle, WA, United States
| | - Shilpi Gupta
- Department of Epidemiology, University of Washington, Seattle, WA, United States.,Center for Public Health Nutrition, University of Washington, Seattle, WA, United States
| | - Dori E Rosenberg
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, United States
| | - Andrea J Cook
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, United States
| | - Xiao Shi
- Department of Urban Design and Planning, College of Built Environments, University of Washington, Seattle, WA, United States
| | - Paula Lozano
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, United States
| | - Anne Vernez Moudon
- Department of Urban Design and Planning, College of Built Environments, University of Washington, Seattle, WA, United States
| | - David Arterburn
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, United States
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22
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Duncan GE, Avery A, Hurvitz PM, Moudon AV, Tsang S, Turkheimer E. Cohort Profile: TWINS study of environment, lifestyle behaviours and health. Int J Epidemiol 2020; 48:1041-1041h. [PMID: 30428089 DOI: 10.1093/ije/dyy224] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- Glen E Duncan
- Department of Nutrition and Exercise Physiology, Washington State University - Health Sciences Spokane, Spokane, WA, USA
| | - Ally Avery
- Department of Nutrition and Exercise Physiology, Washington State University - Health Sciences Spokane, Spokane, WA, USA
| | - Philip M Hurvitz
- Department of Urban Design and Planning, University of Washington, Seattle, WA, USA
| | - Anne Vernez Moudon
- Department of Urban Design and Planning, University of Washington, Seattle, WA, USA
| | - Siny Tsang
- Department of Epidemiology, Columbia University, New York, NY, USA
| | - Eric Turkheimer
- Department of Psychology, University of Virginia, Charlottesville, VA, USA
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23
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Direito A, Tooley M, Hinbarji M, Albatal R, Jiang Y, Whittaker R, Maddison R. Tailored Daily Activity: An Adaptive Physical Activity Smartphone Intervention. Telemed J E Health 2020; 26:426-437. [DOI: 10.1089/tmj.2019.0034] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Affiliation(s)
- Artur Direito
- National Institute for Health Innovation, University of Auckland, Auckland, New Zealand
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Mark Tooley
- National Institute for Health Innovation, University of Auckland, Auckland, New Zealand
| | - Moohamad Hinbarji
- The Insight Centre for Data Analytics, Dublin City University, Dublin, Ireland
| | - Rami Albatal
- The Insight Centre for Data Analytics, Dublin City University, Dublin, Ireland
| | - Yannan Jiang
- National Institute for Health Innovation, University of Auckland, Auckland, New Zealand
| | - Robyn Whittaker
- National Institute for Health Innovation, University of Auckland, Auckland, New Zealand
| | - Ralph Maddison
- National Institute for Health Innovation, University of Auckland, Auckland, New Zealand
- Institute for Physical Activity and Nutrition, Deakin University, Melbourne, Australia
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24
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Chen YC, Dobra A. Measuring human activity spaces from GPS data with density ranking and summary curves. Ann Appl Stat 2020. [DOI: 10.1214/19-aoas1311] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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25
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Loidl M, Stutz P, Fernandez Lapuente de Battre MD, Schmied C, Reich B, Bohm P, Sedlacek N, Niebauer J, Niederseer D. Merging self-reported with technically sensed data for tracking mobility behavior in a naturalistic intervention study. Insights from the GISMO study. Scand J Med Sci Sports 2020; 30 Suppl 1:41-49. [PMID: 32034943 PMCID: PMC7496425 DOI: 10.1111/sms.13636] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Revised: 01/30/2020] [Accepted: 02/04/2020] [Indexed: 11/27/2022]
Abstract
Sound exposure data are central for any intervention study. In the case of utilitarian mobility, where studies cannot be conducted in controlled environments, exposure data are commonly self‐reported. For short‐term intervention studies, wearable devices with location sensors are increasingly employed. We aimed to combine self‐reported and technically sensed mobility data, in order to provide more accurate and reliable exposure data for GISMO, a long‐term intervention study. Through spatio‐temporal data matching procedures, we are able to determine the amount of mobility for all modes at the best possible accuracy level. Self‐reported data deviate ±10% from the corrected reference. Derived modal split statistics prove high compliance to the respective recommendations for the control group (CG) and the two intervention groups (IG‐PT, IG‐C). About 73.7% of total mileage was travelled by car in CG. This share was 10.3% (IG‐PT) and 9.7% (IG‐C), respectively, in the intervention groups. Commuting distances were comparable in CG and IG, but annual mean travel times differ between
x¯
= 8,458 min (σ = 6,427 min) for IG‐PT,
x¯
= 8,444 min (σ = 5,961 min) for IG‐C, and
x¯
= 5,223 min (σ = 5,463 min) for CG. Seasonal variabilities of modal split statistics were observable. However, in IG‐PT and IG‐C no shift toward the car occurred during winter months. Although no perfect single‐method solution for acquiring exposure data in mobility‐related, naturalistic intervention studies exists, we achieved substantially improved results by combining two data sources, based on spatio‐temporal matching procedures.
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Affiliation(s)
- Martin Loidl
- Department of Geoinformatics, Paris Lodron University of Salzburg, Salzburg, Austria
| | - Petra Stutz
- Department of Geoinformatics, Paris Lodron University of Salzburg, Salzburg, Austria
| | - Maria Dolores Fernandez Lapuente de Battre
- University Institute of Sports Medicine, Prevention and Rehabilitation and Research Institute of Molecular Sports Medicine and Rehabilitation, Paracelsus Medical University, Salzburg, Austria
| | - Christian Schmied
- Department of Cardiology, University Heart Center Zurich, University of Zurich, Zurich, Switzerland
| | - Bernhard Reich
- University Institute of Sports Medicine, Prevention and Rehabilitation and Research Institute of Molecular Sports Medicine and Rehabilitation, Paracelsus Medical University, Salzburg, Austria
| | - Philipp Bohm
- Department of Cardiology, University Heart Center Zurich, University of Zurich, Zurich, Switzerland
| | | | - Josef Niebauer
- University Institute of Sports Medicine, Prevention and Rehabilitation and Research Institute of Molecular Sports Medicine and Rehabilitation, Paracelsus Medical University, Salzburg, Austria
| | - David Niederseer
- Department of Cardiology, University Heart Center Zurich, University of Zurich, Zurich, Switzerland
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26
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Drewnowski A, Buszkiewicz J, Aggarwal A, Rose C, Gupta S, Bradshaw A. Obesity and the Built Environment: A Reappraisal. Obesity (Silver Spring) 2020; 28:22-30. [PMID: 31782242 PMCID: PMC6986313 DOI: 10.1002/oby.22672] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2019] [Accepted: 09/25/2019] [Indexed: 12/16/2022]
Abstract
The built environment (BE) has been viewed as an important determinant of health. Numerous studies have linked BE exposure, captured using a variety of methods, to diet quality and to area prevalence of obesity, diabetes, and cardiovascular disease. First-generation studies defined the neighborhood BE as the area around the home. Second-generation studies turned from home-centric to person-centric BE measures, capturing an individual's movements in space and time. Those studies made effective uses of global positioning system tracking devices and mobile phones, sometimes coupled with accelerometers and remote sensors. Activity space metrics explored travel paths, modes, and destinations to assess BE exposure that was both person and context specific. However, as measures of the contextual exposome have become ever more fine-grained and increasingly complex, connections to long-term chronic diseases with complex etiologies, such as obesity, are in danger of being lost. Furthermore, few studies on obesity and the BE have included intermediate energy balance behaviors, such as diet and physical activity, or explored the potential roles of social interactions or psychosocial pathways. Emerging survey-based applications that identify habitual destinations and associated travel patterns may become the third generation of tools to capture health-relevant BE exposures in the long term.
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Affiliation(s)
- Adam Drewnowski
- Center for Public Health Nutrition, School of Public Health, University of Washington
- Department of Epidemiology, School of Public Health, University of Washington
| | - James Buszkiewicz
- Department of Epidemiology, School of Public Health, University of Washington
| | - Anju Aggarwal
- Center for Public Health Nutrition, School of Public Health, University of Washington
- Department of Epidemiology, School of Public Health, University of Washington
| | - Chelsea Rose
- Center for Public Health Nutrition, School of Public Health, University of Washington
| | - Shilpi Gupta
- Center for Public Health Nutrition, School of Public Health, University of Washington
| | - Annie Bradshaw
- Department of Epidemiology, School of Public Health, University of Washington
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27
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Yi L, Wilson JP, Mason TB, Habre R, Wang S, Dunton GF. Methodologies for assessing contextual exposure to the built environment in physical activity studies: A systematic review. Health Place 2019; 60:102226. [PMID: 31797771 PMCID: PMC7377908 DOI: 10.1016/j.healthplace.2019.102226] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Revised: 09/14/2019] [Accepted: 09/26/2019] [Indexed: 01/07/2023]
Abstract
Growing research has integrated Global Positioning Systems (GPS), Geographic Information Systems (GIS), and accelerometry in studying effects of built environment on physical activity outcomes. This systematic review aimed to summarize current geospatial methods of assessing contextual exposure to the built environment in these studies. Based on reviewing 79 eligible articles, methods were identified and grouped into three main categories based on similarities in their approaches as follows: domain-based (67% of studies), buffer-based (22%), and activity space-based (11%). Additionally, technical barriers and potential sources of uncertainties in each category were discussed and recommendations on methodological improvements were made.
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Affiliation(s)
- Li Yi
- Spatial Sciences Institute, University of Southern California, 3616 Trousdale Parkway, AHF B55, Los Angeles, CA, 90089, United States.
| | - John P Wilson
- Spatial Sciences Institute, University of Southern California, 3616 Trousdale Parkway, AHF B55, Los Angeles, CA, 90089, United States
| | - Tyler B Mason
- Department of Preventive Medicine, University of Southern California, 2001 North Soto Street, Los Angeles, CA, 90033, United States
| | - Rima Habre
- Department of Preventive Medicine, University of Southern California, 2001 North Soto Street, Los Angeles, CA, 90033, United States
| | - Shirlene Wang
- Department of Preventive Medicine, University of Southern California, 2001 North Soto Street, Los Angeles, CA, 90033, United States
| | - Genevieve F Dunton
- Department of Preventive Medicine, University of Southern California, 2001 North Soto Street, Los Angeles, CA, 90033, United States
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28
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The measurement of interpersonal interactions with continuous spatiotemporal data: Application to a study of the effects of resource competition on racial group interactions. Behav Res Methods 2019; 52:881-900. [PMID: 31482484 DOI: 10.3758/s13428-019-01287-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
We describe a sequential qualitative ➔ quantitative mixed-method procedure used to construct conceptually grounded quantitative metrics of interpersonal behavior from continuous spatiotemporal data. Metrics were developed from data collected during an experiment in which racially diverse participants interacted with self-resembling avatars at social events hosted in the virtual world Second Life. In the qualitative stage, the researchers conceptualized four distinct patterns of movement from overhead video recreations of participants interacting during the social events. In the quantitative stage, these patterns of movement were operationalized into metrics to reflect each type of observed interpersonal behavior. The metrics were normalized through a series of transformations, and construct validity was assessed through correlations with self-report measures of intergroup behavior. Finally, the metrics were applied to an analysis of the virtual-world study examining the influence of resource competition on racial group interactions. The findings contribute to our understanding of the influence of resource competition on Blacks', Asians', and Whites' group dynamics. Applications of these metrics for the future of the psychological study of interpersonal behavior are discussed.
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29
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Abstract
Public health research has witnessed a rapid development in the use of location, environmental, behavioral, and biophysical sensors that provide high-resolution objective time-stamped data. This burgeoning field is stimulated by the development of novel multisensor devices that collect data for an increasing number of channels and algorithms that predict relevant dimensions from one or several data channels. Global positioning system (GPS) tracking, which enables geographic momentary assessment, permits researchers to assess multiplace personal exposure areas and the algorithm-based identification of trips and places visited, eventually validated and complemented using a GPS-based mobility survey. These methods open a new space-time perspective that considers the full dynamic of residential and nonresidential momentary exposures; spatially and temporally disaggregates the behavioral and health outcomes, thus replacing them in their immediate environmental context; investigates complex time sequences; explores the interplay among individual, environmental, and situational predictors; performs life-segment analyses considering infraindividual statistical units using case-crossover models; and derives recommendations for just-in-time interventions.
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Affiliation(s)
- Basile Chaix
- Nemesis Team, Pierre Louis Institute of Epidemiology and Public Health, UMR-S 1136 (Inserm, Sorbonne Universités), 75012, Paris, France;
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30
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Zenk SN, Matthews SA, Kraft AN, Jones KK. How many days of global positioning system (GPS) monitoring do you need to measure activity space environments in health research? Health Place 2019; 51:52-60. [PMID: 29549754 DOI: 10.1016/j.healthplace.2018.02.004] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2017] [Revised: 01/20/2018] [Accepted: 02/09/2018] [Indexed: 10/16/2022]
Abstract
This study examined the number of days of global positioning system (GPS) monitoring needed to measure attributes of an individual's routine activity space. Multiple alternative activity space representations (cumulative, mean daily), measures (kernel density, route buffer, convex hull), and attributes (area size, supermarkets, fast food restaurants, parks) were examined. Results suggested wide variability in required GPS days to obtain valid estimates of activity space attributes (1-23 days). In general, fewer days were needed for mean daily activity space representations, kernel density measures, and densities of environmental exposures (vs. counts). While kernel density measures reliably estimated between-person differences in attributes after just a few days, most variability in environmental attributes for convex hull and route buffer measures was within-person. Based on these results, a minimum of 14 days of valid GPS data is recommended to measure activity spaces.
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Affiliation(s)
- Shannon N Zenk
- University of Illinois at Chicago College of Nursing, 845 S. Damen Ave., 9th Floor, Chicago, IL 60612, USA.
| | - Stephen A Matthews
- Pennsylvania State University, Department of Sociology and Criminology, Department of Anthropology, and Popualtion Research Institute, 211 Oswald Tower, University Park, PA 16802-6211, USA.
| | - Amber N Kraft
- University of Illinois at Chicago Department of Psychology, 1007 W Harrison St., Chicago, IL 60607, USA.
| | - Kelly K Jones
- University of Illinois at Chicago College of Nursing, 845 S. Damen Ave., 9th Floor, Chicago, IL 60612, USA.
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31
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Drewnowski A, Arterburn D, Zane J, Aggarwal A, Gupta S, Hurvitz P, Moudon A, Bobb J, Cook A, Lozano P, Rosenberg D. The Moving to Health (M2H) approach to natural experiment research: A paradigm shift for studies on built environment and health. SSM Popul Health 2019; 7:100345. [PMID: 30656207 PMCID: PMC6329830 DOI: 10.1016/j.ssmph.2018.100345] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2018] [Revised: 12/22/2018] [Accepted: 12/26/2018] [Indexed: 12/02/2022] Open
Abstract
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.
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Affiliation(s)
- A. Drewnowski
- Center for Public Health Nutrition, 305 Raitt Hall, #353410, University of Washington, Seattle, WA 98195-03410, USA
| | - D. Arterburn
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA 98101, USA
| | - J. Zane
- Center for Public Health Nutrition, 305 Raitt Hall, #353410, University of Washington, Seattle, WA 98195-03410, USA
| | - A. Aggarwal
- Center for Public Health Nutrition, 305 Raitt Hall, #353410, University of Washington, Seattle, WA 98195-03410, USA
| | - S. Gupta
- Center for Public Health Nutrition, 305 Raitt Hall, #353410, University of Washington, Seattle, WA 98195-03410, USA
| | - P.M. Hurvitz
- Urban Form Lab, Department of Urban Design and Planning, College of Built Environments, University of Washington, 1107 NE 45th Street, Suite 535, Seattle, WA 98195-4802, USA
| | - A.V. Moudon
- Urban Form Lab, Department of Urban Design and Planning, College of Built Environments, University of Washington, 1107 NE 45th Street, Suite 535, Seattle, WA 98195-4802, USA
| | - J. Bobb
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA 98101, USA
| | - A. Cook
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA 98101, USA
| | - P. Lozano
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA 98101, USA
| | - D. Rosenberg
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA 98101, USA
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32
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Huang R, Moudon AV, Zhou C, Saelens BE. Higher residential and employment densities are associated with more objectively measured walking in the home neighborhood. JOURNAL OF TRANSPORT & HEALTH 2019; 12:142-151. [PMID: 31598466 PMCID: PMC6785037 DOI: 10.1016/j.jth.2018.12.002] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
Understanding where people walk and how the built environment influences walking is a priority in active living research. Most previous studies were limited by self-reported data on walking. In the present study, walking bouts were determined by integrating one week of accelerometry, GPS, and a travel log data among 675 adult participants in the baseline sample of the Travel Assessment and Community study. Home neighborhood was defined as being within 0.5 mi of each participants' residence (a 10-minute walk), with home neighborhood walking defined as walking bout lines with at least one GPS point within the home neighborhood. Home neighborhood walkability was constructed with seven built environment variables derived from spatially continuous objective values (SmartMaps). A Zero Inflated Negative Binomial (ZINB) served to estimate associations between home neighborhood environment characteristics and home neighborhood walking frequency. Higher residential density and job density were the two neighborhood walkability measures related to higher likelihood and more time walking in the home neighborhood, highest tertile residential density (22.44 - 62.63 unit/acre) (coefficient=1.434; 95th CI of 1.003, 2.049) and highest tertile job density (12.4 - 272.3 jobs/acre) (coefficient=1.616; 95th CI of 1.102, 2.370). The large proportion of walking that takes place in the home neighborhood highlights the importance of continuing to examine the impact of the home neighborhood environment on walking. Potential interventions to increase walking behavior may benefit from increasing residential and employment density within residential areas.
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Affiliation(s)
- Ruizhu Huang
- Texas Advanced Computing Center, University of Texas, Austin, TX
| | - Anne V. Moudon
- Urban Form Lab and the College of Built Environments Department of Urban Design and Planning, University of Washington, Seattle, WA
| | - Chuan Zhou
- Seattle Children’s Research Institute and School of Medicine/Department of Pediatrics, University of Washington, Seattle, WA
| | - Brian E. Saelens
- Seattle Children’s Research Institute and School of Medicine/Department of Pediatrics, University of Washington, Seattle, WA
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33
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Morgan Hughey S, Kaczynski AT, Porter DE, Hibbert J, Turner-McGrievy G, Liu J. Development and testing of a multicomponent obesogenic built environment measure for youth using kernel density estimations. Health Place 2019; 56:174-183. [DOI: 10.1016/j.healthplace.2019.01.011] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2018] [Revised: 11/28/2018] [Accepted: 01/14/2019] [Indexed: 02/03/2023]
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34
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Jankowska MM, Sears DD, Natarajan L, Martinez E, Anderson CAM, Sallis JF, Matthews SA, Crist K, Dillon L, Johnson E, Barrera-Ng A, Full K, Godbole S, Kerr J. Protocol for a cross sectional study of cancer risk, environmental exposures and lifestyle behaviors in a diverse community sample: the Community of Mine study. BMC Public Health 2019; 19:186. [PMID: 30760246 PMCID: PMC6375220 DOI: 10.1186/s12889-019-6501-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2018] [Accepted: 01/31/2019] [Indexed: 01/08/2023] Open
Abstract
Background Physical inactivity and unhealthy diet are modifiable behaviors that lead to several cancers. Biologically, these behaviors are linked to cancer through obesity-related insulin resistance, inflammation, and oxidative stress. Individual strategies to change physical activity and diet are often short lived with limited effects. Interventions are expected to be more successful when guided by multi-level frameworks that include environmental components for supporting lifestyle changes. Understanding the role of environment in the pathways between behavior and cancer can help identify what environmental conditions are needed for individual behavioral change approaches to be successful, and better recognize how environments may be fueling underlying racial and ethnic cancer disparities. Methods This cross-sectional study was designed to select participants (n = 602 adults, 40% Hispanic, in San Diego County) from a range of neighborhoods ensuring environmental variability in walkability and food access. Biomarkers measuring cancer risk were measured with fasting blood draw including insulin resistance (fasting plasma insulin and glucose levels), systemic inflammation (levels of CRP), and oxidative stress measured from urine samples. Objective physical activity, sedentary behavior, and sleep were measured by participants wearing a GT3X+ ActiGraph on the hip and wrist. Objective measures of locations were obtained through participants wearing a Qstarz Global Positioning System (GPS) device on the waist. Dietary measures were based on a 24-h food recall collected on two days (weekday and weekend). Environmental exposure will be calculated using static measures around the home and work, and dynamic measures of mobility derived from GPS traces. Associations of environment with physical activity, obesity, diet, and biomarkers will be measured using generalized estimating equation models. Discussion Our study is the largest study of objectively measured physical activity, dietary behaviors, environmental context/exposure, and cancer-related biomarkers in a Hispanic population. It is the first to perform high quality measures of physical activity, sedentary behavior, sleep, diet and locations in which these behaviors occur in relation to cancer-associated biomarkers including insulin resistance, inflammation, impaired lipid metabolism, and oxidative stress. Results will add to the evidence-base of how behaviors and the built environment interact to influence biomarkers that increase cancer risk. Trial registration ClinicalTrials.gov NCT02094170, 03/21/2014.
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Affiliation(s)
- Marta M Jankowska
- Calit2/Qualcomm Institute, UCSD, 9500 Gilman Dr, La Jolla, CA, 92093, USA.
| | - Dorothy D Sears
- Nutrition, College of Health Solutions, Arizona State University, 445 N 5th Street, Phoenix, AZ, 85004, USA
| | - Loki Natarajan
- Department of Family Medicine and Public Health, UCSD, 9500 Gilman Dr, La Jolla, CA, 92093, USA.,UCSD Moores Cancer Center, 3855 Health Sciences Dr, La Jolla, CA, 92093, USA
| | - Elena Martinez
- UCSD Moores Cancer Center, 3855 Health Sciences Dr, La Jolla, CA, 92093, USA
| | - Cheryl A M Anderson
- Department of Family Medicine and Public Health, UCSD, 9500 Gilman Dr, La Jolla, CA, 92093, USA
| | - James F Sallis
- Department of Family Medicine and Public Health, UCSD, 9500 Gilman Dr, La Jolla, CA, 92093, USA
| | - Stephen A Matthews
- Department of Sociology & Criminology, Department of Anthropology, Population Research Institute, Old Main, State College, PA, 16801, USA
| | - Katie Crist
- Department of Family Medicine and Public Health, UCSD, 9500 Gilman Dr, La Jolla, CA, 92093, USA
| | - Lindsay Dillon
- Department of Family Medicine and Public Health, UCSD, 9500 Gilman Dr, La Jolla, CA, 92093, USA
| | - Eileen Johnson
- Department of Family Medicine and Public Health, UCSD, 9500 Gilman Dr, La Jolla, CA, 92093, USA
| | - Angelica Barrera-Ng
- Department of Family Medicine and Public Health, UCSD, 9500 Gilman Dr, La Jolla, CA, 92093, USA
| | - Kelsey Full
- Department of Family Medicine and Public Health, UCSD, 9500 Gilman Dr, La Jolla, CA, 92093, USA
| | - Suneeta Godbole
- Department of Family Medicine and Public Health, UCSD, 9500 Gilman Dr, La Jolla, CA, 92093, USA
| | - Jacqueline Kerr
- Department of Family Medicine and Public Health, UCSD, 9500 Gilman Dr, La Jolla, CA, 92093, USA.,UCSD Moores Cancer Center, 3855 Health Sciences Dr, La Jolla, CA, 92093, USA
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Stewart OT, Moudon AV, Littman A, Seto E, Saelens BE. The association between park facilities and the occurrence of physical activity during park visits. JOURNAL OF LEISURE RESEARCH 2019; 49:217-235. [PMID: 31602048 PMCID: PMC6786780 DOI: 10.1080/00222216.2018.1534073] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Prior research has found a positive relationship between the variety of park facilities and park-based physical activity (PA), but has not provided an estimate of the effect that additional different PA facilities have on whether an individual is active during a park visit. Using objective measures of park visits and PA from an urban sample of 225 adults in King County, Washington, we compared the variety of PA facilities in parks visited where an individual was active to PA facilities in parks where the same individual was sedentary. Each additional different PA facility at a park was associated with a 6% increased probability of being active during a visit. Adding additional different PA facilities to a park appears to have a moderate effect on whether an individual is active during a park visit, which could translate into large community health impacts when scaled up to multiple park visitors.
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Affiliation(s)
| | | | - Alyson Littman
- Department of Epidemiology, School of Public Health, University of Washington
| | - Edmund Seto
- Department of Environmental & Occupational Health Sciences, School of Public Health, University of Washington
| | - Brian E. Saelens
- Seattle Children’s Research Institute
- Department of Pediatrics, School of Medicine, University of Washington
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Duncan GE, Seto E, Avery AR, Oie M, Carvlin G, Austin E, Shirai JH, He J, Ockerman B, Novosselov I. Usability of a Personal Air Pollution Monitor: Design-Feedback Iterative Cycle Study. JMIR Mhealth Uhealth 2018; 6:e12023. [PMID: 30578204 PMCID: PMC6320397 DOI: 10.2196/12023] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2018] [Revised: 10/10/2018] [Accepted: 10/13/2018] [Indexed: 11/13/2022] Open
Abstract
Background There is considerable evidence that exposure to fine particulate matter (PM2.5) air pollution is associated with a variety of adverse health outcomes. However, true exposure-outcome associations are hampered by measurement issues, including compliance and exposure misclassification. Objective This paper describes the use of the design-feedback iterative cycle to improve the design and usability of a new portable PM2.5 monitor for use in an epidemiologic study of personal air pollution measures. Methods In total, 10 adults carried on their person a prefabricated PM2.5 monitor for 1 week over 3 waves of the iterative cycle. At the end of each wave, they participated in a 30-minute moderated focus group and completed 2 validated questionnaires on usability and views on research. The topics addressed included positives and negatives of the monitor, charging and battery life, desired features, and changes to the monitor from each previous wave. They also completed a log to record device wear time each day. The log also provided space to record any issues that may have arisen with the device or for general comments during the week of collection. Results The major focus group topics included device size, noise, battery and charge time, and method for carrying the device. These topics formed the basis of iterative design changes; by the final cycle, the device was reasonably smaller, quieter, held a longer charge, and was more convenient to carry. System usability scores improved systematically across each wave (median scores of 50-66 on a 100-point scale), as did median daily wear time (approximately 749-789 minutes). Conclusions Both qualitative and quantitative measures showed an improvement in device usability over the 3 waves. This study demonstrates how the design-feedback iterative cycle can be used to improve the usability of devices manufactured for use in large epidemiologic studies on personal air pollution exposures.
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Affiliation(s)
- Glen E Duncan
- Washington State University, Spokane, WA, United States
| | - Edmund Seto
- University of Washington, Seattle, WA, United States
| | - Ally R Avery
- Washington State University, Everett, WA, United States
| | - Mike Oie
- Washington State University, Seattle, WA, United States
| | | | - Elena Austin
- University of Washington, Seattle, WA, United States
| | | | - Jiayang He
- University of Washington, Seattle, WA, United States
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Kang M, Moudon AV, Hurvitz PM, Saelens BE. Capturing fine-scale travel behaviors: a comparative analysis between personal activity location measurement system (PALMS) and travel diary. Int J Health Geogr 2018; 17:40. [PMID: 30509275 PMCID: PMC6278002 DOI: 10.1186/s12942-018-0161-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2018] [Accepted: 11/26/2018] [Indexed: 01/08/2023] Open
Abstract
Background Device-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. Methods Sixty 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. Results At 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. Conclusions The 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.
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Affiliation(s)
- Mingyu Kang
- Urban Form Lab, Department of Urban Design and Planning, University of Washington, 1107 NE 45th St, Suite 535, Seattle, WA, 98195, USA.
| | - Anne V Moudon
- Urban Form Lab, Department of Urban Design and Planning, University of Washington, 1107 NE 45th St, Suite 535, Seattle, WA, 98195, USA
| | - Philip M Hurvitz
- Urban Form Lab, Department of Urban Design and Planning, University of Washington, 1107 NE 45th St, Suite 535, Seattle, WA, 98195, USA
| | - Brian E Saelens
- Department of Pediatrics, Seattle Children's Research Institute, University of Washington, 2001 Eighth Avenue, Suite 400, Seattle, WA, 98121, USA
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Stewart OT, Moudon AV, Littman AJ, Seto E, Saelens BE. The Association Between Park Facilities and Duration of Physical Activity During Active Park Visits. J Urban Health 2018; 95:869-880. [PMID: 30232689 PMCID: PMC6286274 DOI: 10.1007/s11524-018-0311-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Abstract
Public parks provide places for urban residents to obtain physical activity (PA), which is associated with numerous health benefits. Adding facilities to existing parks could be a cost-effective approach to increase the duration of PA that occurs during park visits. Using objectively measured PA and comprehensively measured park visit data among an urban community-dwelling sample of adults, we tested the association between the variety of park facilities that directly support PA and the duration of PA during park visits where any PA occurred. Cross-classified multilevel models were used to account for the clustering of park visits (n = 1553) within individuals (n = 372) and parks (n = 233). Each additional different PA facility at a park was independently associated with a 6.8% longer duration of PA bouts that included light-intensity activity, and an 8.7% longer duration of moderate to vigorous PA time. Findings from this study are consistent with the hypothesis that more PA facilities increase the amount of PA that visitors obtain while already active at a park.
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Affiliation(s)
- Orion T Stewart
- Urban Form Lab, University of Washington, 1107 NE 45th Street Suite 535, Seattle, WA, 98105, USA. .,Institute for Population Health Improvement, University of California, Davis, 1631 Alhambra Blvd, Suite 200, Sacramento, CA, 95816, USA.
| | - Anne Vernez Moudon
- Urban Form Lab, University of Washington, 1107 NE 45th Street Suite 535, Seattle, WA, 98105, USA.,College of Built Environments Department of Urban Design and Planning, University of Washington, Box 355740, Seattle, WA, 98195, USA
| | - Alyson J Littman
- School of Public Health Department of Epidemiology, University of Washington, Box 357236, Seattle, WA, 98195, USA
| | - Edmund Seto
- School of Public Health Department of Environmental & Occupational Health Sciences, University of Washington, Box 357234, Seattle, WA, 98195, USA
| | - Brian E Saelens
- Seattle Children's Research Institute, P.O. Box 5371, M/S: CW8-6, Seattle, WA, 98145, USA.,School of Medicine Department of Pediatrics, University of Washington, Box 356320, Seattle, WA, 98195, USA
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Stewart OT, Moudon AV, Littman AJ, Seto E, Saelens BE. Why neighborhood park proximity is not associated with total physical activity. Health Place 2018; 52:163-169. [DOI: 10.1016/j.healthplace.2018.05.011] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2017] [Revised: 05/18/2018] [Accepted: 05/29/2018] [Indexed: 10/14/2022]
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40
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Kang B, Moudon AV, Hurvitz PM, Saelens BE. Differences in Behavior, Time, Location, and Built Environment between Objectively Measured Utilitarian and Recreational Walking. TRANSPORTATION RESEARCH. PART D, TRANSPORT AND ENVIRONMENT 2017; 57:185-194. [PMID: 30220861 PMCID: PMC6136454 DOI: 10.1016/j.trd.2017.09.026] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
OBJECTIVES Utilitarian and recreational walking both contribute to physical activity. Yet walking for these two purposes may be different behaviors. We sought to provide operational definitions of utilitarian and recreational walking and to objectively measure their behavioral, spatial, and temporal differences in order to inform transportation and public health policies and interventions. METHODS Data were collected 2008-2009 from 651 Seattle-King County residents, wearing an accelerometer and a GPS unit, and filling-in a travel diary for 7 days. Walking activity bouts were classified as utilitarian or recreational based on whether walking had a destination or not. Differences between the two walking purposes were analyzed, adjusting for the nested structure of walking activity within participants. RESULTS Of the 4,905 observed walking bouts, 87.4% were utilitarian and 12.6% recreational walking. Utilitarian walking bouts were 45% shorter in duration (-12.1 min) and 9% faster in speed (+0.3km/h) than recreational walking bouts. Recreational walking occurred more frequently in the home neighborhood and was not associated with recreational land uses. Utilitarian walking occurred in areas having higher residential, employment, and street density, lower residential property value, higher area percentage of mixed-use neighborhood destinations, lower percentage of parks/trails, and lower average topographic slope than recreational walking. CONCLUSION Utilitarian and recreational walking are substantially different in terms of frequency, speed, duration, location, and related built environment. Policies that promote walking should adopt type-specific strategies. The high occurrence of recreational walking near home highlights the importance of the home neighborhood for this activity.
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Affiliation(s)
- Bumjoon Kang
- Department of Urban and Regional Planning, University at Buffalo, the State University of New York, 114 Diefendorf Hall, 3435 Main St, Buffalo, NY 14214, USA,
| | - Anne V Moudon
- Urban Form Lab and the Department of Urban Design and Planning, University of Washington, TRAC UW, Box 354802, 1107 NE 45th Street Suite 535, Seattle, WA 98105, USA,
| | - Philip M Hurvitz
- Urban Form Lab and the Department of Urban Design and Planning, University of Washington TRAC UW, Box 354802, 1107 NE 45th Street Suite 535, Seattle, WA 98105, USA,
| | - Brian E Saelens
- Seattle Children's Research Institute and Department of Pediatrics, University of Washington Child Health, Behavior and Development, 2001 8 Ave, Seattle, WA 98121, USA,
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Adlakha D. Quantifying the Modern City: Emerging Technologies and Big Data for Active Living Research. Front Public Health 2017; 5:105. [PMID: 28611973 PMCID: PMC5446990 DOI: 10.3389/fpubh.2017.00105] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2016] [Accepted: 04/27/2017] [Indexed: 11/13/2022] Open
Abstract
Opportunities and infrastructure for active living are an important aspect of a community's design, livability, and health. Features of the built environment influence active living and population levels of physical activity, but objective study of the built environment influence on active living behaviors is challenging. The use of emerging technologies for active living research affords new and promising means to obtain objective data on physical activity behaviors and improve the precision and accuracy of measurements. This is significant for physical activity promotion because precise measurements can enable detailed examinations of where, when, and how physical activity behaviors actually occur, thus enabling more effective targeting of particular behavior settings and environments. The aim of this focused review is to provide an overview of trends in emerging technologies that can profoundly change our ability to understand environmental determinants of active living. It discusses novel technological approaches and big data applications to measure and track human behaviors that may have broad applications across the fields of urban planning, public health, and spatial epidemiology.
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Affiliation(s)
- Deepti Adlakha
- Center for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen’s University Belfast, Belfast, UK
- School of Natural and Built Environment, Queen’s University Belfast, Belfast, UK
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Quistberg DA, Howard EJ, Hurvitz PM, Moudon AV, Ebel BE, Rivara FP, Saelens BE. The Relationship Between Objectively Measured Walking and Risk of Pedestrian-Motor Vehicle Collision. Am J Epidemiol 2017; 185:810-821. [PMID: 28338921 DOI: 10.1093/aje/kwx020] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2015] [Accepted: 07/26/2016] [Indexed: 12/21/2022] Open
Abstract
Safe urban walking environments may improve health by encouraging physical activity, but the relationship between an individual's location and walking pattern and the risk of pedestrian-motor vehicle collision is unknown. We examined associations between individuals' walking bouts and walking risk, measured as mean exposure to the risk of pedestrian-vehicle collision. Walking bouts were ascertained through integrated accelerometry and global positioning system data and from individual travel-diary data obtained from adults in the Travel Assessment and Community Study (King County, Washington) in 2008-2009. Walking patterns were superimposed onto maps of the historical probabilities of pedestrian-vehicle collisions for intersections and midblock segments within Seattle, Washington. Mean risk of pedestrian-vehicle collision in specific walking locations was assessed according to walking exposure (duration, distance, and intensity) and participant demographic characteristics in linear mixed models. Participants typically walked in areas with low pedestrian collision risk when walking for recreation, walking at a faster pace, or taking longer-duration walks. Mean daily walking duration and distance were not associated with collision risk. Males walked in areas with higher collision risk compared with females, while vehicle owners, residents of single-family homes, and parents of young children walked in areas with lower collision risk. These findings may suggest that pedestrians moderate collision risk by using lower-risk routes.
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How Sensors Might Help Define the External Exposome. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2017; 14:ijerph14040434. [PMID: 28420222 PMCID: PMC5409635 DOI: 10.3390/ijerph14040434] [Citation(s) in RCA: 61] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/11/2017] [Revised: 03/14/2017] [Accepted: 03/23/2017] [Indexed: 01/23/2023]
Abstract
The advent of the exposome concept, the advancement of mobile technology, sensors, and the “internet of things” bring exciting opportunities to exposure science. Smartphone apps, wireless devices, the downsizing of monitoring technologies, along with lower costs for such equipment makes it possible for various aspects of exposure to be measured more easily and frequently. We discuss possibilities and lay out several criteria for using smart technologies for external exposome studies. Smart technologies are evolving quickly, and while they provide great promise for advancing exposure science, many are still in developmental stages and their use in epidemiology and risk studies must be carefully considered. The most useable technologies for exposure studies at this time relate to gathering exposure-factor data, such as location and activities. Development of some environmental sensors (e.g., for some air pollutants, noise, UV) is moving towards making the use of these more reliable and accessible to research studies. The possibility of accessing such an unprecedented amount of personal data also comes with various limitations and challenges, which are discussed. The advantage of improving the collection of long term exposure factor data is that this can be combined with more “traditional” measurement data to model exposures to numerous environmental factors.
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Jankowska MM, Natarajan L, Godbole S, Meseck K, Sears DD, Patterson RE, Kerr J. Kernel Density Estimation as a Measure of Environmental Exposure Related to Insulin Resistance in Breast Cancer Survivors. Cancer Epidemiol Biomarkers Prev 2017; 26:1078-1084. [PMID: 28258052 DOI: 10.1158/1055-9965.epi-16-0927] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2016] [Revised: 01/11/2017] [Accepted: 02/20/2017] [Indexed: 11/16/2022] Open
Abstract
Background: Environmental factors may influence breast cancer; however, most studies have measured environmental exposure in neighborhoods around home residences (static exposure). We hypothesize that tracking environmental exposures over time and space (dynamic exposure) is key to assessing total exposure. This study compares breast cancer survivors' exposure to walkable and recreation-promoting environments using dynamic Global Positioning System (GPS) and static home-based measures of exposure in relation to insulin resistance.Methods: GPS data from 249 breast cancer survivors living in San Diego County were collected for one week along with fasting blood draw. Exposure to recreation spaces and walkability was measured for each woman's home address within an 800 m buffer (static), and using a kernel density weight of GPS tracks (dynamic). Participants' exposure estimates were related to insulin resistance (using the homeostatic model assessment of insulin resistance, HOMA-IR) controlled by age and body mass index (BMI) in linear regression models.Results: The dynamic measurement method resulted in greater variability in built environment exposure values than did the static method. Regression results showed no association between HOMA-IR and home-based, static measures of walkability and recreation area exposure. GPS-based dynamic measures of both walkability and recreation area were significantly associated with lower HOMA-IR (P < 0.05).Conclusions: Dynamic exposure measurements may provide important evidence for community- and individual-level interventions that can address cancer risk inequities arising from environments wherein breast cancer survivors live and engage.Impact: This is the first study to compare associations of dynamic versus static built environment exposure measures with insulin outcomes in breast cancer survivors. Cancer Epidemiol Biomarkers Prev; 26(7); 1078-84. ©2017 AACR.
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Affiliation(s)
- Marta M Jankowska
- Qualcomm Institute, California Institute for Telecommunications and Information Technology, University of California, San Diego, California.
| | - Loki Natarajan
- Department of Family Medicine and Public Health, University of California, San Diego, California.,Moores UC San Diego Cancer Center, University of California San Diego, California
| | - Suneeta Godbole
- Department of Family Medicine and Public Health, University of California, San Diego, California
| | - Kristin Meseck
- Department of Family Medicine and Public Health, University of California, San Diego, California
| | - Dorothy D Sears
- Department of Family Medicine and Public Health, University of California, San Diego, California.,Department of Medicine, University of California, San Diego, California
| | - Ruth E Patterson
- Department of Family Medicine and Public Health, University of California, San Diego, California.,Moores UC San Diego Cancer Center, University of California San Diego, California
| | - Jacqueline Kerr
- Department of Family Medicine and Public Health, University of California, San Diego, California.,Moores UC San Diego Cancer Center, University of California San Diego, California
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45
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Le A, Mitchell HR, Zheng DJ, Rotatori J, Fahey JT, Ness KK, Kadan-Lottick NS. A home-based physical activity intervention using activity trackers in survivors of childhood cancer: A pilot study. Pediatr Blood Cancer 2017; 64:387-394. [PMID: 27615711 DOI: 10.1002/pbc.26235] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2016] [Revised: 07/29/2016] [Accepted: 08/02/2016] [Indexed: 11/08/2022]
Abstract
BACKGROUND Over 70% of childhood cancer survivors develop late complications from therapy, many of which can be mitigated by physical activity. Survivors engage in exercise at similar or lower rates than their sedentary healthy peers. We piloted a novel home-based exercise intervention with a motivational activity tracker. We evaluated (i) feasibility, (ii) impact on activity levels and physical fitness, and (iii) barriers, preferences, and beliefs regarding physical activity. METHODS Childhood cancer survivors currently 15 years or older and not meeting the Centers for Disease Control and Prevention physical activity guidelines were enrolled and instructed to wear the Fitbit One, a 4.8 cm × 1.8 cm motivational activity tracker, daily for 6 months. Baseline and follow-up evaluations included self-report surveys, an Actigraph accelerometer for 7 days, and a VO2 maximum test by cardiac stress test. RESULTS Nineteen participants were enrolled (13.4% participation rate) with a mean age of 24.3 ± 5.8 years (range 15-35). Four participants withdrew with a 79% retention rate. Participants wore the Fitbit an average of 19.0 ± 4.7 days per month during months 1-3 and 15.0 ± 7.9 days per month during months 4-6. Total weekly moderate to vigorous physical activity increased from 265.6 ± 117.0 to 301.4 ± 135.4 min and VO2 maximum increased from 25.7 ± 7.7 to 27.2 ± 7.4 ml/kg/min. These changes were not statistically significant (P = 0.47 and 0.30, respectively). Survey responses indicated no change in barriers, preferences, and beliefs regarding physical activity. CONCLUSIONS This pilot study of a motivational activity tracker demonstrated feasibility as measured by participant retention, receptivity, and belief of utility. Future studies with a large sample size are needed to demonstrate the efficacy and sustainability of this intervention.
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Affiliation(s)
- Alyssa Le
- Department of Pediatric Hematology/Oncology, Yale School of Medicine, New Haven, Connecticut
| | - Hannah-Rose Mitchell
- Department of Pediatric Hematology/Oncology, Yale School of Medicine, New Haven, Connecticut
| | - Daniel J Zheng
- Department of Pediatric Hematology/Oncology, Yale School of Medicine, New Haven, Connecticut
| | - Jaime Rotatori
- Department of Pediatric Hematology/Oncology, Yale School of Medicine, New Haven, Connecticut
| | - John T Fahey
- Department of Pediatric Cardiology, Yale School of Medicine, New Haven, Connecticut
| | - Kirsten K Ness
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Nina S Kadan-Lottick
- Department of Pediatric Hematology/Oncology, Yale School of Medicine, New Haven, Connecticut.,Yale Cancer Center, New Haven, Connecticut
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McKenzie TL. Context Matters: Systematic Observation of Place-Based Physical Activity. RESEARCH QUARTERLY FOR EXERCISE AND SPORT 2016; 87:334-341. [PMID: 27749158 DOI: 10.1080/02701367.2016.1234302] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Physical activity is place-based, and being able to assess the number of people and their characteristics in specific locations is important both for public health surveillance and for practitioners in their design of physical activity spaces and programs. Although physical activity measurement has improved recently, many investigators avoid or are at a loss regarding the assessment of physical activity in explicit locations, especially in open environments where many people come and go in a seemingly indiscriminate fashion. Direct, systematic observation exceeds other methods in simultaneously assessing physical activity and the contexts in which it occurs. This commentary summarizes the development and use of 2 validated observation tools: the System for Observing Play and Leisure in Youth (SOPLAY) and System for Observing Play and Active Recreation in Communities (SOPARC). Their use is well supported by both behavior-analytic principles and social-ecological theory, and their methods have utility for both researchers and practitioners.
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Drewnowski A, Aggarwal A, Tang W, Hurvitz PM, Scully J, Stewart O, Moudon AV. Obesity, diet quality, physical activity, and the built environment: the need for behavioral pathways. BMC Public Health 2016; 16:1153. [PMID: 27832766 PMCID: PMC5105275 DOI: 10.1186/s12889-016-3798-y] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2016] [Accepted: 11/01/2016] [Indexed: 11/10/2022] Open
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.
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Affiliation(s)
- Adam Drewnowski
- Center for Public Health Nutrition, 1107 NE 45th St, University of Washington, Seattle, WA, 98105, USA. .,University of Washington, Box 353410, Seattle, WA, 98195, USA.
| | - Anju Aggarwal
- Center for Public Health Nutrition, 1107 NE 45th St, University of Washington, Seattle, WA, 98105, USA
| | - Wesley Tang
- Center for Public Health Nutrition, 1107 NE 45th St, University of Washington, Seattle, WA, 98105, USA
| | - Philip M Hurvitz
- Urban Form Lab, 1107 NE 45th St, University of Washington, Seattle, WA, 98105, USA
| | - Jason Scully
- Urban Form Lab, 1107 NE 45th St, University of Washington, Seattle, WA, 98105, USA
| | - Orion Stewart
- Urban Form Lab, 1107 NE 45th St, University of Washington, Seattle, WA, 98105, USA
| | - Anne Vernez Moudon
- Urban Form Lab, 1107 NE 45th St, University of Washington, Seattle, WA, 98105, USA
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James P, Jankowska M, Marx C, Hart JE, Berrigan D, Kerr J, Hurvitz PM, Hipp JA, Laden F. "Spatial Energetics": Integrating Data From GPS, Accelerometry, and GIS to Address Obesity and Inactivity. Am J Prev Med 2016; 51:792-800. [PMID: 27528538 PMCID: PMC5067207 DOI: 10.1016/j.amepre.2016.06.006] [Citation(s) in RCA: 43] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2016] [Revised: 05/05/2016] [Accepted: 06/04/2016] [Indexed: 01/23/2023]
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.
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Affiliation(s)
- Peter James
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
| | | | - Christine Marx
- Division of Public Health Sciences, Washington University School of Medicine, St. Louis, Missouri
| | - Jaime E Hart
- Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts; Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - David Berrigan
- Health Behaviors Research Branch, Behavioral Research Program, National Cancer Institute, Bethesda, Maryland
| | - Jacqueline Kerr
- Department of Family Medicine and Public Health, University of California, San Diego, San Diego, California; Psychology Department, Graduate School of Public Health, San Diego State University, San Diego, California
| | | | - J Aaron Hipp
- Department of Parks, Recreation, and Tourism Management, North Carolina State University, Raleigh, North Carolina
| | - Francine Laden
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts; Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts; Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
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49
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Paus T. Population neuroscience. HANDBOOK OF CLINICAL NEUROLOGY 2016; 138:17-37. [PMID: 27637950 DOI: 10.1016/b978-0-12-802973-2.00002-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
Abstract
Population neuroscience endeavors to identify influences shaping the human brain from conception onwards, thus generating knowledge relevant for building and maintaining brain health throughout the life span. This can be achieved by studying large samples of participants drawn from the general population and evaluated with state-of-the-art tools for assessing (a) genes and their regulation; (b) external and internal environments; and (c) brain properties. This chapter reviews the three elements of population neuroscience (principles, tools, innovations, limitations), and discusses future directions in this field.
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Affiliation(s)
- T Paus
- Rotman Research Institute and Departments of Psychology and Psychiatry, University of Toronto, Toronto; Canada and Child Mind Institute, New York, NY, USA.
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50
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Remmers T, Van Kann D, Thijs C, de Vries S, Kremers S. Playability of school-environments and after-school physical activity among 8-11 year-old children: specificity of time and place. Int J Behav Nutr Phys Act 2016; 13:82. [PMID: 27421643 PMCID: PMC4946175 DOI: 10.1186/s12966-016-0407-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2016] [Accepted: 06/28/2016] [Indexed: 11/12/2022] Open
Abstract
Background Physical Activity (PA) occurs in several behavioral domains (e.g., sports, active transport), and is affected by distinct environmental factors. By filtering objective PA using children’s school schedules, daily PA can be separated into more conceptually meaningful domains. We used an ecological design to investigate associations between “playability” of 21 school-environments and children’s objectively measured after-school PA. We also examined to what extent distinct time-periods after-school and the distance from children’s residence to their school influenced this association. Methods PA was measured in 587 8–11 year-old children by accelerometers, and separated in four two-hour time-periods after-school. For each school-environment, standardized playability-scores were calculated based on standardized audits within 800 m network buffers around each school. Schools and children’s residences were geocoded, and we classified each child to be residing in 400, 800, 1600, or >1600 m crow-fly buffers from their school. The influence of network-distance buffers was also examined using the same approach. Results Playability was associated with light PA and moderate-to-vigorous PA after-school, especially in the time-period directly after-school and among children who lived within 800 m from their school. Playability explained approximately 30 % of the after-school PA variance between schools. Greater distance from children’s residence to their school weakened the association between playability of the school-environments and after-school PA. Conclusions This study demonstrated that relationships between the conceptually matched physical environment and PA can be revealed and made plausible with increasing specificity in time and distance.
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Affiliation(s)
- Teun Remmers
- Department of Epidemiology, Maastricht University (Medical Center+), CAPHRI School for Public Health and Primary Care, P.O. Box 616, 6200MD, Maastricht, The Netherlands.
| | - Dave Van Kann
- Department of Health Promotion, Maastricht University (Medical Center+), CAPHRI School for Public Health and Primary Care, Maastricht, The Netherlands
| | - Carel Thijs
- Department of Epidemiology, Maastricht University (Medical Center+), CAPHRI School for Public Health and Primary Care, P.O. Box 616, 6200MD, Maastricht, The Netherlands
| | - Sanne de Vries
- The Hague University of Applied Sciences, Research group Healthy Lifestyle in a Supporting Environment, The Hague, The Netherlands
| | - Stef Kremers
- Department of Health Promotion, Maastricht University (Medical Center+), NUTRIM School for Nutrition and Translational Research in Metabolism, Maastricht, The Netherlands
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