Evidence map›Paper›PMID 41327094›Full record

ArticleBMC public health2025

Exposure to fine particulate matter constituents increases sarcopenia risk in middle-aged and elderly Chinese adults.

Zong-Lei Zhou, Li-Li Gao, Xian-Zhi Li, Kun-Peng Li, Xiao-Qi Wang, Ting Wang, Guo-Zhen Zhang, Ji-Yu Li, Wu Wang

Abstract read
In one paragraph

Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

9 authors.

Zong-Lei ZhouCenter for Medical Research and Innovation, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, 201399, China.
Li-Li GaoCenter for Medical Research and Innovation, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, 201399, China.
Xian-Zhi LiMeteorological Medical Research Center, Clinical Medical Research Center, Panzhihua Central Hospital, Panzhihua, 617067, China.
Kun-Peng LiSchool of Exercise and Health, Shanghai University of Sport, Shanghai, 200438, China.
Xiao-Qi WangDepartment of Scientific Research, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, 201399, China.
Ting WangCenter for Medical Research and Innovation, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, 201399, China.
Guo-Zhen ZhangDepartment of Rehabilitation, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, 201399, China.
Ji-Yu LiIntegrated Clinic of Multi-Disciplinary Treatment for Chronic Disease Rehabilitation and Weight Management, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, 201399, China. lijiyu@fudan.edu.cn.
Wu WangDepartment of Rehabilitation, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, 201399, China. wangwu0727@163.com.

Funding

AI-Driven Causal Analytics for Multimodal Disease Data in Healthcare Management 202401065Fudan University Pudong Medical Center Research Project Tszb2024-09Integrated Large Model Platform Project of Clinical and Scientific Research for Chronic Disease Management RZ-CYAI-01-24-0258Panzhihua Meteorological Medical Research Center 2025WSKJ-01Sichuan Science and Technology Program 2025ZNSFSC1600
6 · The paper itself

Abstract

backgroundGrowing evidence has underscored the adverse role of air pollutants in the pathogenesis of sarcopenia, while there lacks knowledge over the relationships between PM2.5 constituents and sarcopenia.

methodsThis study included 6666 participants aged 45 years and above from the China Health and Retirement Longitudinal Study in 2011, of which 2538 were followed up until 2015. Average concentrations of PM2.5 and its constituents (sulfate, nitrate, ammonium, organic matter [OM], black carbon [BC]) were retrieved from Tracking Air Pollution in China (TAP) database. In the cross-sectional analyses, we employed multivariate logistic regression, generalized linear model, and restricted cubic spline function to analyze the individual relationships of air pollutants with sarcopenia prevalence and sarcopenia-related index (SI). A lower SI is generally associated with a greater risk of sarcopenia. Quantile-based g-computation model was used to clarify the joint effect of multiple PM2.5 components and their relative weights of contributions. Cox proportional hazard model was established to ascertain the longitudinal impacts of air pollutants on sarcopenia incidence.

resultsFor each interquartile range increment of PM2.5, sulfate, nitrate, ammonium, OM, and BC, the adjusted ORs for sarcopenia were 1.42 (95% CI, 1,14 to 1.77), 1.42 (95% CI, 1.14 to 1.76), 1.38 (95% CI, 1.09 to 1.75), 1.36 (95% CI, 1.09 to 1.70), 1.35 (95% CI, 1.09 to 1.67), and 1.39 (95% CI, 1.15 to 1.68), respectively. Consistently, we found a negative relationship between air pollutants and SI. Multi-pollutant analyses suggested that sarcopenia risk was linearly associated with exposure mixtures, with sulfate identified as the dominant driver of joint effect. In addition, the findings from concentration-response curves, subgroup analyses, sensitivity analyses, and longitudinal analyses further supported the harm of PM2.5 and its constituents on sarcopenia development.

conclusionOur study demonstrates a positive association of single and joint exposure to PM2.5 and its components with sarcopenia risk, offering additional implications on early screening and management of sarcopenia.

Indexed as

Air PollutantsEnvironmental ExposureParticulate MatterSarcopeniaAgedChinaCross-Sectional StudiesFemaleHumansLongitudinal StudiesMaleMiddle AgedRisk FactorsAir PollutantsParticulate MatterCreatinineCystatin CFine particulate matterMixed effectSarcopenia

Identifiers

PMID41327094
PMCPMC12777192

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.