Evidence map›Paper›PMID 39655197›Full record

ArticleThe Lancet regional health. Western Pacific2024

The burden of type 2 diabetes attributable to air pollution across China and its provinces, 1990-2021: an analysis for the Global Burden of Disease Study 2021.

Chunnan Li, Jinlei Qi, Peng Yin, Xinhui Yu, Haoran Sun, Maigeng Zhou, Wannian Liang

Abstract read
In one paragraph

Article in The Lancet regional health. Western Pacific, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

7 authors.

Chunnan LiDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, 02115, Massachusetts, USA.
Jinlei QiNational Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100050, China.
Peng YinNational Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100050, China.
Xinhui YuNational Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100050, China.
Haoran SunVanke School of Public Health, Tsinghua University, Beijing, 100190, China.
Maigeng ZhouNational Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100050, China.
Wannian LiangVanke School of Public Health, Tsinghua University, Beijing, 100190, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Temporal trends and geographical disparities in type 2 diabetes burden attributable to air pollution, including ambient and household, are not fully understood within China. This study aims to estimate the burden of type 2 diabetes attributable to air pollution at national and provincial levels from 1990 to 2021. Methods: We assessed air pollution exposure across 33 Chinese provinces, autonomous regions, municipalities, and special administrative regions, focusing on two common forms of air pollution: ambient particulate matter pollution (defined as the annual gridded concentration of PM Findings: In 2021, about a fifth of the national type 2 diabetes burden was attributable to air pollution, with an age-standardised estimate of 1.76 deaths and 110.79 DALYs per 100,000 population, higher in males. Ambient PM Interpretation: Air pollution, especially ambient PM Funding: Sanming Project of Medicine in Shenzhen (NO. SZSM202111001).

Indexed as

Air pollutionChinaDisease burdenType 2 diabetes

Identifiers

PMID39655197
PMCPMC11626817

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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.