Evidence map›Paper›PMID 39316790›Full record

ArticleJMIR public health and surveillance2024

The Effect of Long-Term Particulate Matter Exposure on Respiratory Mortality: Cohort Study in China.

Ying Wang, Zhuohao Wang, Jie Jiang, Tong Guo, Shimin Chen, Zhiqiang Li, Zhupei Yuan, Qiaoxuan Lin, Zhicheng Du, Jing Wei and 2 more

Abstract read
In one paragraph

Article in JMIR public health and surveillance, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. 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

12 authors.

Ying Wang *Department of Medical Statistics, School of Public Health & Research Center for Health Information, Sun Yat-sen Global Health Institute, Sun Yat-sen University, 2nd Zhongshan Road, Guangzhou, 510000, China.ORCID 0009-0002-6852-8357
Zhuohao Wang *School of Public Health, Sun Yat-sen University, Guangzhou, China.ORCID 0009-0000-9015-4342
Jie JiangDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Peking, China.ORCID 0000-0001-7496-5647
Tong GuoDepartment of Medical Statistics, School of Public Health & Research Center for Health Information, Sun Yat-sen Global Health Institute, Sun Yat-sen University, 2nd Zhongshan Road, Guangzhou, 510000, China.ORCID 0009-0001-1431-9173
Shimin ChenDepartment of Medical Statistics, School of Public Health & Research Center for Health Information, Sun Yat-sen Global Health Institute, Sun Yat-sen University, 2nd Zhongshan Road, Guangzhou, 510000, China.ORCID 0009-0003-5874-4870
Zhiqiang LiDepartment of Medical Statistics, School of Public Health & Research Center for Health Information, Sun Yat-sen Global Health Institute, Sun Yat-sen University, 2nd Zhongshan Road, Guangzhou, 510000, China.ORCID 0009-0009-8601-9311
Zhupei YuanDepartment of Medical Statistics, School of Public Health & Research Center for Health Information, Sun Yat-sen Global Health Institute, Sun Yat-sen University, 2nd Zhongshan Road, Guangzhou, 510000, China.ORCID 0009-0005-9977-7382
Qiaoxuan LinDepartment of Statistics, Guangzhou Health Technology Identification, Human Resources Assessment Center, Guangzhou, China.ORCID 0000-0003-0745-0162
Zhicheng DuDepartment of Medical Statistics, School of Public Health & Research Center for Health Information, Sun Yat-sen Global Health Institute, Sun Yat-sen University, 2nd Zhongshan Road, Guangzhou, 510000, China.ORCID 0000-0002-1155-8443
Jing WeiDepartment of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, United States.ORCID 0000-0002-8803-7056
Yuantao HaoPeking University Center for Public Health and Epidemic Preparedness & Response, Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Peking, China.ORCID 0000-0001-8024-5312
Wangjian ZhangDepartment of Medical Statistics, School of Public Health & Research Center for Health Information, Sun Yat-sen Global Health Institute, Sun Yat-sen University, 2nd Zhongshan Road, Guangzhou, 510000, China.ORCID 0000-0001-9655-6385

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Particulate matter (PM), which affects respiratory health, has been well documented; however, substantial evidence from large cohorts is still limited, particularly in highly polluted countries and for PM1. Objective: Our objective was to examine the potential causal links between long-term exposure to PMs (PM2.5, PM10, and more importantly, PM1) and respiratory mortality. Methods: A total of 580,757 participants from the Guangzhou area, China, were recruited from 2009 to 2015 and followed up through 2020. The annual average concentrations of PMs at a 1-km spatial resolution around the residential addresses were estimated using validated spatiotemporal models. The marginal structural Cox model was used to estimate the associations of PM exposure with respiratory mortality, accounting for time-varying PM exposure. Results were stratified by demographics and lifestyle behaviors factors. Results: Among the participants, the mean age was 48.33 (SD 17.55) years, and 275,676 (47.47%) of them were men. During the follow-up period, 7260 deaths occurred due to respiratory diseases. The annual average concentrations of PM1, PM2.5, and PM10 showed a declining trend during the follow-up period. After adjusting for confounders, a 6.6% (95% CI 5.6%-7.6%), 4.2% (95% CI 3.6%-4.7%), and 4.0% (95% CI 3.6%-4.5%) increase in the risk of respiratory mortality was observed following each 1-μg/m3 increase in concentrations of PM1, PM2.5, and PM10, respectively. In addition, older participants, nonsmokers, participants with higher exercise frequency, and those exposed to a lower normalized difference vegetation index tended to be more susceptible to the effects of PMs. Furthermore, participants in the low-exposure group tended to be at a 7.6% and 2.7% greater risk of respiratory mortality following PM1 and PM10 exposure, respectively, compared to the entire cohort. Conclusions: This cohort study provides causal clues of the respiratory impact of long-term ambient PM exposure, indicating that PM reduction efforts may continuously benefit the population's respiratory health.

Indexed as

Environmental ExposureParticulate MatterRespiratory Tract DiseasesAdultAgedAir PollutantsAir PollutionChinaCohort StudiesFemaleHumansMaleMiddle AgedAir PollutantsParticulate Mattercausal inferencecohort studymortalityparticulate matterrespiratory disease

Identifiers

PMID39316790
PMCPMC11444524

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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.