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An Analytical Framework for Integrating the Spatiotemporal Dynamics of Environmental Context and Individual Mobility in Exposure Assessment: A Study on the Relationship between Food Environment Exposures and Body Weight

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  • Jue Wang

    (Department of Geography and Geographic Information Science, Natural History Building, 1301 W Green Street University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA)

  • Mei-Po Kwan

    (Department of Geography and Geographic Information Science, Natural History Building, 1301 W Green Street University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA)

Abstract

In past studies, individual environmental exposures were largely measured in a static manner. In this study, we develop and implement an analytical framework that dynamically represents environmental context (the environmental context cube) and effectively integrates individual daily movement (individual space-time tunnel) for accurately deriving individual environmental exposures (the environmental context exposure index). The framework is applied to examine the relationship between food environment exposures and the overweight status of 46 participants using data collected with global positioning systems (GPS) in Columbus, Ohio, and binary logistic regression models. The results indicate that the proposed framework generates more reliable measurements of individual food environment exposures when compared to other widely used methods. Taking into account the complex spatial and temporal dynamics of individual environmental exposures, the proposed framework also helps to mitigate the uncertain geographic context problem (UGCoP). It can be used in other environmental health studies concerning environmental influences on a wide range of health behaviors and outcomes.

Suggested Citation

  • Jue Wang & Mei-Po Kwan, 2018. "An Analytical Framework for Integrating the Spatiotemporal Dynamics of Environmental Context and Individual Mobility in Exposure Assessment: A Study on the Relationship between Food Environment Exposu," IJERPH, MDPI, vol. 15(9), pages 1-24, September.
    • Handle: RePEc:gam:jijerp:v:15:y:2018:i:9:p:2022-:d:170106
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    References listed on IDEAS

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    1. Chen, X. & Kwan, M.-P., 2015. "Contextual uncertainties, human mobility, and perceived food environment: The uncertain geographic context problem in food access research," American Journal of Public Health, American Public Health Association, vol. 105(9), pages 1734-1737.
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    5. Mei-Po Kwan, 2018. "The Limits of the Neighborhood Effect: Contextual Uncertainties in Geographic, Environmental Health, and Social Science Research," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 108(6), pages 1482-1490, November.
    6. Pengxiang Zhao & Mei-Po Kwan & Suhong Zhou, 2018. "The Uncertain Geographic Context Problem in the Analysis of the Relationships between Obesity and the Built Environment in Guangzhou," IJERPH, MDPI, vol. 15(2), pages 1-20, February.
    7. Kwan, Mei-Po, 2009. "From place-based to people-based exposure measures," Social Science & Medicine, Elsevier, vol. 69(9), pages 1311-1313, November.
    8. Dunn, Richard A. & Sharkey, Joseph R. & Horel, Scott, 2012. "The effect of fast-food availability on fast-food consumption and obesity among rural residents: An analysis by race/ethnicity," Economics & Human Biology, Elsevier, vol. 10(1), pages 1-13.
    9. Houle, J.N. & Light, M.T., 2014. "The home foreclosure crisis and rising suicide rates, 2005 to 2010," American Journal of Public Health, American Public Health Association, vol. 104(6), pages 1073-1079.
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    11. Matthew Browning & Kangjae Lee, 2017. "Within What Distance Does “Greenness” Best Predict Physical Health? A Systematic Review of Articles with GIS Buffer Analyses across the Lifespan," IJERPH, MDPI, vol. 14(7), pages 1-21, June.
    12. Zick, Cathleen D. & Smith, Ken R. & Fan, Jessie X. & Brown, Barbara B. & Yamada, Ikuho & Kowaleski-Jones, Lori, 2009. "Running to the Store? The relationship between neighborhood environments and the risk of obesity," Social Science & Medicine, Elsevier, vol. 69(10), pages 1493-1500, November.
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    Cited by:

    1. Xinlin Ma & Xijing Li & Mei-Po Kwan & Yanwei Chai, 2020. "Who Could Not Avoid Exposure to High Levels of Residence-Based Pollution by Daily Mobility? Evidence of Air Pollution Exposure from the Perspective of the Neighborhood Effect Averaging Problem (NEAP)," IJERPH, MDPI, vol. 17(4), pages 1-19, February.
    2. Man Yuan & Haolan Pan & Zhuoran Shan & Da Feng, 2022. "Spatial Differences in the Effect of Communities’ Built Environment on Residents’ Health: A Case Study in Wuhan, China," IJERPH, MDPI, vol. 19(3), pages 1-18, January.

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