Urinary polycyclic aromatic hydrocarbons and depressive/anxiety symptoms in older adults: an exploratory machine learning analysis

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous neurotoxic pollutants, yet evidence linking PAHs to older adults’ depressive/anxiety symptoms remains scarce. We explored single/mixed urinary PAH-metabolite associations as well as sex- and body-mass index (BMI)-related effect modification among 413 Shenzhen adults aged ≥ 60 years. Symptoms were assessed using the Geriatric Depression Scale (GDS) and Hamilton Anxiety Scale (HAMA). Complementary machine-learning analyses with XGBoost and SHapley Additive exPlanations explored key hydroxylated polycyclic aromatic hydrocarbon (OH-PAH) metabolites to cross-check conventional regression findings. Logistic regression showed that urinary 1-hydroxypyrene (1-OHPyr) and summed hydroxylated phenanthrene metabolites (ΣOH-PHEs) were associated with higher odds of prevalent anxiety symptoms. Sex-stratified analyses linked 3-hydroxyphenanthrene (3-OHPhe) to prevalent anxiety symptoms and 1-OHPyr to prevalent depressive symptoms in females, and stronger 1-OHPyr–anxiety associations were observed in non-overweight participants. Linear regression revealed a significant 1-OHPyr–HAMA association, whereas only a marginal non-significant trend was seen for GDS scores. Bayesian kernel machine regression indicated higher odds of prevalent anxiety symptoms at high mixture exposure, whereas quantile g-computation showed no significant association. The machine-learning analysis flagged 1-OHPyr as the top predictor for anxiety, with suggestive signals for depressive symptoms. Associations between phenanthrene-derived OH-PAHs and anxiety were subject to BMI modification. However, after false discovery rate (FDR) correction, these associations did not remain statistically significant (smallest PFDR = 0.494); the findings should be regarded as hypothesis-generating. This simultaneous assessment of PAH-related mood-symptom associations in older adults highlights the need for prospective cohorts to verify findings and clarify underlying mechanisms.

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Journal
Journal of Environmental Exposure Assessment
Published
2026-10-30
DOI
https://doi.org/10.20517/jeea.2026.47
Primary Topic
Toxic Organic Pollutants Impact
Type
article
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article

Urinary polycyclic aromatic hydrocarbons and depressive/anxiety symptoms in older adults: an exploratory machine learning analysis

Lu Cheng, Han Li, Huaicai Zeng, Zhuoqi Zhu et al.
5 links
Journal of Environmental Exposure Assessment
Toxic Organic Pollutants Impact
article

Urinary polycyclic aromatic hydrocarbons and depressive/anxiety symptoms in older adults: an exploratory machine learning analysis

Lu Cheng, Han Li, Huaicai Zeng, Zhuoqi Zhu, Biwen Wang, Hongzhi Zhao, Yafei Gao, Jiemei Li, Junqi Liu, Yang Peng
article en

Abstract

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous neurotoxic pollutants, yet evidence linking PAHs to older adults’ depressive/anxiety symptoms remains scarce. We explored single/mixed urinary PAH-metabolite associations as well as sex- and body-mass index (BMI)-related effect modification among 413 Shenzhen adults aged ≥ 60 years. Symptoms were assessed using the Geriatric Depression Scale (GDS) and Hamilton Anxiety Scale (HAMA). Complementary machine-learning analyses with XGBoost and SHapley Additive exPlanations explored key hydroxylated polycyclic aromatic hydrocarbon (OH-PAH) metabolites to cross-check conventional regression findings. Logistic regression showed that urinary 1-hydroxypyrene (1-OHPyr) and summed hydroxylated phenanthrene metabolites (ΣOH-PHEs) were associated with higher odds of prevalent anxiety symptoms. Sex-stratified analyses linked 3-hydroxyphenanthrene (3-OHPhe) to prevalent anxiety symptoms and 1-OHPyr to prevalent depressive symptoms in females, and stronger 1-OHPyr–anxiety associations were observed in non-overweight participants. Linear regression revealed a significant 1-OHPyr–HAMA association, whereas only a marginal non-significant trend was seen for GDS scores. Bayesian kernel machine regression indicated higher odds of prevalent anxiety symptoms at high mixture exposure, whereas quantile g-computation showed no significant association. The machine-learning analysis flagged 1-OHPyr as the top predictor for anxiety, with suggestive signals for depressive symptoms. Associations between phenanthrene-derived OH-PAHs and anxiety were subject to BMI modification. However, after false discovery rate (FDR) correction, these associations did not remain statistically significant (smallest PFDR = 0.494); the findings should be regarded as hypothesis-generating. This simultaneous assessment of PAH-related mood-symptom associations in older adults highlights the need for prospective cohorts to verify findings and clarify underlying mechanisms.

Journal of Environmental Exposure AssessmentVol. 5(4)
Guangxi Medical University (CN), Nankai University (CN)
Good health and well-being
Openalex Percentile: Top 18%
Toxic Organic Pollutants Impact
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