Evidence map›Paper›PMID 33153466›Full record

ArticleEnvironmental health : a global access science source2020

Association of ambient air pollution with cardiovascular disease risks in people with type 2 diabetes: a Bayesian spatial survival analysis.

Pei-Fang Su, Fei-Ci Sie, Chun-Ting Yang, Yu-Lin Mau, Shihchen Kuo, Huang-Tz Ou

Open access · goldAbstract read
In one paragraph

Article in Environmental health : a global access science source, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 22% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.

  1. Pooled it
  2. Article
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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.

Pei-Fang SuDepartment of Statistics, National Cheng Kung University, Tainan, Taiwan.
Fei-Ci SieDepartment of Statistics, National Cheng Kung University, Tainan, Taiwan.
Chun-Ting YangInstitute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University, 1 University Road, Tainan, 701, Taiwan.
Yu-Lin MauDepartment of Statistics, National Cheng Kung University, Tainan, Taiwan.
Shihchen KuoDivision of Metabolism, Endocrinology & Diabetes, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI, USA.
Huang-Tz OuInstitute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University, 1 University Road, Tainan, 701, Taiwan. huangtz@mail.ncku.edu.tw.ORCID 0000-0002-5475-7848
National Cheng Kung University · TWNational Cheng Kung University Hospital · TWUniversity of Michigan · US

Funding

Research BaseP30DK092926 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MARY ELLEN MICHELE HEISLER, ADESUWA B OLOMU · 2011 to 2026
$10.0M
Ministry of Science and Technology, Taiwan 106-2118-M-006-011-MY3Ministry of Science and Technology, Taiwan MOST 107-2320-B-006 -034NIDDK NIH HHS P30 DK092926
6 · The paper itself

Abstract

backgroundEvidence is limited on excess risks of cardiovascular diseases (CVDs) associated with ambient air pollution in diabetic populations. Survival analyses without considering the spatial structure and possible spatial correlations in health and environmental data may affect the precision of estimation of adverse environmental pollution effects. We assessed the association between air pollution and CVDs in type 2 diabetes through a Bayesian spatial survival approach.

methodsTaiwan's national-level health claims and air pollution databases were utilized. Fine individual-level latitude and longitude were used to determine pollution exposure. The exponential spatial correlation between air pollution and CVDs was analyzed in our Bayesian model compared to traditional Weibull and Cox models.

resultsThere were 2072 diabetic patients included in analyses. PM

conclusionsAgainst traditional non-spatial analyses, our Bayesian spatial survival model enhances the assessment precision for environmental research with spatial survival data to reveal significant adverse cardiovascular effects of air pollution among vulnerable diabetic patients.

Indexed as

AgedAged, 80 and overAir PollutionBayes TheoremCardiovascular DiseasesDiabetes Mellitus, Type 2Environmental ExposureFemaleHumansKaplan-Meier EstimateMaleMiddle AgedRisk FactorsTaiwanBayesian approachCardiovascular diseaseSpatial correlationSurvivalTime-to-eventType 2 diabetes

Identifiers

PMID33153466
PMCPMC7643356
OpenAlexW3096633755

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.