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Which Green Space Metric Best Predicts a Lowered Odds of Type 2 Diabetes?

Author

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  • Soumya Mazumdar

    (South Western Sydney Clinical School, University of New South Wales Medicine, Liverpool, NSW 2170, Australia
    Population Health Intelligence, South Western Sydney Local Health District, Liverpool, NSW 2170, Australia)

  • Shanley Chong

    (South Western Sydney Clinical School, University of New South Wales Medicine, Liverpool, NSW 2170, Australia
    Population Health Intelligence, South Western Sydney Local Health District, Liverpool, NSW 2170, Australia)

  • Thomas Astell-Burt

    (Population Wellbeing and Environment Research Lab (Power Lab), School of Health and Society, Faculty of Arts, Social Sciences and Humanities, University of Wollongong, Wollongong, NSW 2522, Australia
    Menzies Centre for Health Policy, School of Public Health, University of Sydney, Sydney, NSW 2006, Australia
    Chinese Center for Disease Control and Prevention, National Institute of Environmental Health, Beijing 102206, China
    School of Public Health, Peking Union Medical College and The Chinese Academy of Medical Sciences, Beijing 102206, China)

  • Xiaoqi Feng

    (Population Wellbeing and Environment Research Lab (Power Lab), School of Health and Society, Faculty of Arts, Social Sciences and Humanities, University of Wollongong, Wollongong, NSW 2522, Australia
    School of Population Health, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW 2052, Australia)

  • Geoffrey Morgan

    (University Centre for Rural Health, School of Public Health, University of Sydney, Lismore, NSW 2480, Australia)

  • Bin Jalaludin

    (Population Health Intelligence, South Western Sydney Local Health District, Liverpool, NSW 2170, Australia
    School of Population Health, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW 2052, Australia)

Abstract

The choice of a green space metric may affect what relationship is found with health outcomes. In this research, we investigated the relationship between percent green space area, a novel metric developed by us (based on the average contiguous green space area a spatial buffer has contact with), in three different types of buffers and type 2 diabetes (T2D). We obtained information about diagnosed T2D and relevant covariates at the individual level from the large and representative 45 and Up Study. Average contiguous green space and the percentage of green space within 500 m, 1 km, and 2 km of circular buffer, line-based road network (LBRN) buffers, and polygon-based road network (PBRN) buffers around participants’ residences were used as proxies for geographic access to green space. Generalized estimating equation regression models were used to determine associations between access to green space and T2D status of individuals. It was found that 30%–40% green space within 500 m LBRN or PBRN buffers, and 2 km PBRN buffers, but not within circular buffers, significantly reduced the risk of T2D. The novel average green space area metric did not appear to be particularly effective at measuring reductions in T2D. This study complements an existing research body on optimal buffers for green space measurement.

Suggested Citation

  • Soumya Mazumdar & Shanley Chong & Thomas Astell-Burt & Xiaoqi Feng & Geoffrey Morgan & Bin Jalaludin, 2021. "Which Green Space Metric Best Predicts a Lowered Odds of Type 2 Diabetes?," IJERPH, MDPI, vol. 18(8), pages 1-13, April.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:8:p:4088-:d:535156
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    References listed on IDEAS

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    1. Soumya Mazumdar & Alison Dunshea & Shanley Chong & Bin Jalaludin, 2020. "Tree Canopy Cover Is Best Associated with Perceptions of Greenspace: A Short Communication," IJERPH, MDPI, vol. 17(18), pages 1-9, September.
    2. 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.
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    Cited by:

    1. Liqing Zhang & Yue Wu, 2022. "Negative Associations between Quality of Urban Green Spaces and Health Expenditures in Downtown Shanghai," Land, MDPI, vol. 11(8), pages 1-18, August.

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