Multi-model assessment reveals drivers among PM2.5-bound emerging chemical constituents impacting cognitive health of middle-aged and older adults

Introduction Evidence on the cognitive impacts of specific chemicals in ambient PM 2 . 5 remains limited, particularly among aging populations. This study aims to evaluate the associations between emerging PM 2 . 5 -bound chemicals and cognitive function in middle-aged and older adults in China. Methods We conducted a cross-sectional analysis involving 373 participants from seven Chinese cities, in which concentrations of 100 PM 2 . 5 -bound chemical constituents were quantitatively measured. Cognitive function was assessed using the Mini-Mental State Examination (MMSE). Generalized estimating equations (GEE) were adopted as the primary analytical model. We applied LASSO regression combined with directed acyclic graphs (DAG) to select a parsimonious minimal confounder set. Complementary mixture-exposure analyses, including weighted quantile sum (WQS) regression and quantile g-computation (qgcomp), were further implemented to evaluate consistency across different statistical models. Sensitivity analyses were performed using alternative model specifications, including GEE with continuous MMSE cognitive score as the outcome. Results Thirteen chemicals showed suggestive associations with cognitive impairment in primary single-pollutant models. Across complementary multi-model assessments, three chemicals including 2-methyl-benzothiazole (2-Me-BTH), isopropyl myristate (IPM), and 2,6-di-tert-butyl-4-(dimethylamino-methyl)phenol (Ethanox-703) exhibited relatively larger contribution weights in mixture models. These chemicals belong to benzothiazoles (BTHs), fatty-acid-ester (FAE) plasticizers, and synthetic antioxidants (SAOs). Discussion Our integrated analytical approach identifies candidate PM 2 . 5 -bound chemical constituents that may correlate with cognitive impairment in middle-aged and older adults. These findings highlight the need for further mechanistic and prospective epidemiological research to disentangle potential neurocognitive relevance of complex airborne chemical exposomes.

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Publication Details

Journal
Frontiers in Environmental Science
Published
2026-10-27
DOI
https://doi.org/10.3389/fenvs.2026.1977587
Primary Topic
Air Quality and Health Impacts
Type
article
Field-Weighted Citation Impact
0.00

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article

Multi-model assessment reveals drivers among PM2.5-bound emerging chemical constituents impacting cognitive health of middle-aged and older adults

Peng Du, Xuetai Chen, Liping Wang, Yu Shen et al.
1 links
Frontiers in Environmental Science
Air Quality and Health Impacts
article

Multi-model assessment reveals drivers among PM2.5-bound emerging chemical constituents impacting cognitive health of middle-aged and older adults

Peng Du, Xuetai Chen, Liping Wang, Yu Shen, Yuanyuan Liu, Tiantian Li
article en

Abstract

Introduction Evidence on the cognitive impacts of specific chemicals in ambient PM 2 . 5 remains limited, particularly among aging populations. This study aims to evaluate the associations between emerging PM 2 . 5 -bound chemicals and cognitive function in middle-aged and older adults in China. Methods We conducted a cross-sectional analysis involving 373 participants from seven Chinese cities, in which concentrations of 100 PM 2 . 5 -bound chemical constituents were quantitatively measured. Cognitive function was assessed using the Mini-Mental State Examination (MMSE). Generalized estimating equations (GEE) were adopted as the primary analytical model. We applied LASSO regression combined with directed acyclic graphs (DAG) to select a parsimonious minimal confounder set. Complementary mixture-exposure analyses, including weighted quantile sum (WQS) regression and quantile g-computation (qgcomp), were further implemented to evaluate consistency across different statistical models. Sensitivity analyses were performed using alternative model specifications, including GEE with continuous MMSE cognitive score as the outcome. Results Thirteen chemicals showed suggestive associations with cognitive impairment in primary single-pollutant models. Across complementary multi-model assessments, three chemicals including 2-methyl-benzothiazole (2-Me-BTH), isopropyl myristate (IPM), and 2,6-di-tert-butyl-4-(dimethylamino-methyl)phenol (Ethanox-703) exhibited relatively larger contribution weights in mixture models. These chemicals belong to benzothiazoles (BTHs), fatty-acid-ester (FAE) plasticizers, and synthetic antioxidants (SAOs). Discussion Our integrated analytical approach identifies candidate PM 2 . 5 -bound chemical constituents that may correlate with cognitive impairment in middle-aged and older adults. These findings highlight the need for further mechanistic and prospective epidemiological research to disentangle potential neurocognitive relevance of complex airborne chemical exposomes.

Frontiers in Environmental ScienceVol. 14
Xuzhou Medical College (CN), Chinese Center For Disease Control and Prevention (CN), Nantong University (CN), China University of Mining and Technology (CN), Yancheng First People's Hospital (CN), National Institute for Occupational Health and Poison Control (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Good health and well-being
Openalex Percentile: Top 18%
Air Quality and Health Impacts
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