Which green space metric best predicts a lowered odds of type 2 diabetes?

Soumya Mazumdar, Shanley Chong, Thomas Astell-Burt, Xiaoqi Feng, Geoffrey Morgan, Bin Jalaludin

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)1-13
Number of pages13
JournalInternational Journal of Environmental Research and Public Health
Issue number8
Publication statusPublished - 13 Apr 2021
Externally publishedYes


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