Evidence map›Paper›PMID 35556211›Full record

ArticleJournal of urban health : bulletin of the New York Academy of Medicine2022

Neighborhood Greenspace and Socioeconomic Risk are Associated with Diabetes Risk at the Sub-neighborhood Scale: Results from the Prospective Urban and Rural Epidemiology (PURE) Study.

Blake Byron Walker, Sebastian Tobias Brinkmann, Tim Große, Dominik Kremer, Nadine Schuurman, Perry Hystad, Sumathy Rangarajan, Koon Teo, Salim Yusuf, Scott A Lear

Open access · hybridAbstract read
In one paragraph

Article in Journal of urban health : bulletin of the New York Academy of Medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 2 pooled it
0.6field-weighted citation impact, top 35% 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

5 citing papers in PubMed, 2 syntheses or guidelines pooled it, 6 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Article
  5. 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

10 authors at 4 institutions in 3 countries.

Blake Byron WalkerCommunity Health Environments and Social Terrains Lab, Institute for Geography, Friedrich-Alexander-Universität Erlangen-Nürnberg, Wetterkreuz 15, 91058, Erlangen, Germany. blake.walker@fau.de.ORCID 0000-0002-1983-3147
Sebastian Tobias BrinkmannCommunity Health Environments and Social Terrains Lab, Institute for Geography, Friedrich-Alexander-Universität Erlangen-Nürnberg, Wetterkreuz 15, 91058, Erlangen, Germany.
Tim GroßeCommunity Health Environments and Social Terrains Lab, Institute for Geography, Friedrich-Alexander-Universität Erlangen-Nürnberg, Wetterkreuz 15, 91058, Erlangen, Germany.
Dominik KremerCommunity Health Environments and Social Terrains Lab, Institute for Geography, Friedrich-Alexander-Universität Erlangen-Nürnberg, Wetterkreuz 15, 91058, Erlangen, Germany.
Nadine SchuurmanDepartment of Geography, Simon Fraser University, Burnaby, Canada.
Perry HystadSpatial Health Lab, College of Public Health and Human Sciences, Oregon State University, Corvallis, USA.
Sumathy RangarajanPopulation Health Research Institute, McMaster University, Hamilton, Canada.
Koon TeoPopulation Health Research Institute, McMaster University, Hamilton, Canada.
Salim YusufPopulation Health Research Institute, McMaster University, Hamilton, Canada.
Scott A LearFaculty of Health Sciences, Simon Fraser University, Burnaby, Canada.
Friedrich-Alexander-Universität Erlangen-Nürnberg · DEPopulation Health Research Institute · CASimon Fraser University · CAOregon State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Greenspace and socioeconomic status are known correlates of diabetes prevalence, but their combined effects at the sub-neighborhood scale are not yet known. This study derives, maps, and validates a combined socioeconomic/greenspace index of individual-level diabetes risk at the sub-neighborhood scale, without the need for clinical measurements. In two Canadian cities (Vancouver and Hamilton), we computed 4 greenspace variables from satellite imagery and extracted 11 socioeconomic variables from the Canadian census. We mapped 5125 participants from the Prospective Urban and Rural Epidemiology Study by their residential address and used age- and sex-dependent walking speeds to estimate individual exposure zones to local greenspace and socioeconomic characteristics, which were then entered into a principal component analysis to derive a novel diabetes risk index (DRI-GLUCoSE). We mapped index scores in both study areas and validated the index using fully adjusted logistic regression models to predict individual diabetes status. Model performance was then compared to other non-clinical diabetes risk indices from the literature. Diabetes prevalence among participants was 9.9%. The DRI-GLUCoSE index was a significant predictor of diabetes status, exhibiting a small non-significant attenuation with the inclusion of dietary and physical activity variables. The final models achieved a predictive accuracy of 75%, the highest among environmental risk models to date. Our combined index of local greenspace and socioeconomic factors demonstrates that the environmental component of diabetes risk is not sufficiently explained by diet and physical activity, and that increasing urban greenspace may be a suitable means of reducing the burden of diabetes at the community scale.

Indexed as

Diabetes MellitusParks, RecreationalCanadaGlucoseHumansProspective StudiesResidence CharacteristicsSocioeconomic FactorsGlucoseDiabetesGISGreenspaceIndicesSocioeconomic status

Identifiers

PMID35556211
PMCPMC9187823
OpenAlexW4280514617

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.