Evidence map›Paper›PMID 33924462›Full record

ArticleInternational journal of environmental research and public health2021

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

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 27% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. Impact of Different Greenspace Metrics on Cardiovascular Disease Incidence in Urban Settings: A Comparative Analysis.Journal of urban health : bulletin of the New York Academy of Medicine · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 2 countries.

Soumya MazumdarSouth Western Sydney Clinical School, University of New South Wales Medicine, Liverpool, NSW 2170, Australia.ORCID 0000-0003-3694-2318
Shanley ChongSouth Western Sydney Clinical School, University of New South Wales Medicine, Liverpool, NSW 2170, Australia.
Thomas Astell-BurtPopulation 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.
Xiaoqi FengPopulation 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.
Geoffrey MorganUniversity Centre for Rural Health, School of Public Health, University of Sydney, Lismore, NSW 2480, Australia.ORCID 0000-0003-4046-2405
Bin JalaludinPopulation Health Intelligence, South Western Sydney Local Health District, Liverpool, NSW 2170, Australia.
UNSW Sydney · AUThe University of Sydney · AUUniversity of Wollongong · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Diabetes Mellitus, Type 2Parks, RecreationalHumanscircular buffergreen spacehealth outcomesnetwork buffertype 2 diabetes

Identifiers

PMID33924462
PMCPMC8068830
OpenAlexW3153253300

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.