Associations of long-term exposure to fine particulate matter and its constituents with gynecologic cancer incidence: A prospective cohort study from Beijing

There is limited evidence of the association between long-term exposure to particulate matter with aerodynamic diameter ≤2.5 μm (fine particulate matter, PM 2.5 ) and gynecologic cancer incidence, particularly in developing countries with high air pollution levels. The present study aimed to investigate the associations of long-term exposure to PM 2.5 and its constituents with the incidence of gynecologic cancer, and to identify the primary constituent. A total of 85,500 women from the National Urban Cancer Screening Program in Beijing (2013–2019) were included. 5-year average concentrations of PM 2.5 mass and its constituents, namely carbon black (BC), ammonium (NH 4 + ), nitrate (NO 3 − ), organic matter (OM), and sulfate (SO 4 2− ), were obtained from the Tracking Air Pollution in China (TAP) dataset. Cox proportional hazard models were used to analyze the association between long-term exposure to PM 2.5 and its constituents and gynecologic cancer incidence. Mixture exposure models, including quantile-based g-computation (Qgcomp) and explanatory machine learning model (SHapley Additive exPlanations, SHAP), were used to assess the effect of each constituent. During a mean follow-up of 6.22 years, 524 participants were diagnosed with gynecologic cancer. The adjusted hazard ratios (HRs) for gynecologic cancer incidence associated with 1 standard deviation (SD) increment was 1.10 (95% CI: 1.00–1.22) for PM 2.5 , 1.12 (95% CI: 1.01–1.23) for BC,1.11 (95% CI: 1.00–1.23) for NH 4 + , 1.12 (95% CI: 1.01–1.23) for OM, 1.12 (95% CI: 1.01–1.23) for SO 4 2− , and 1.08 (95% CI: 0.98–1.19) for NO 3 − . The Qgcomp model indicated the association between a mixture of PM 2.5 constituents and gynecologic cancer incidence, with positive weights assigned to BC (61.6%), SO 4 2− (35.9%), and NO 3 − (2.5%). The SHAP model showed that SO 4 2− was the most important constituent, with the mean |SHAP| value of 0.0322, followed by BC (0.0270), OM (0.0232), NO 3 − (0.0212) and NH 4 + (0.0190). Long-term exposure to PM 2.5 was associated with gynecologic cancer incidence, with SO 4 2− and BC contributing significantly to the association.

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Journal
Medicine Plus
Published
2024-11-08
DOI
https://doi.org/10.1016/j.medp.2024.100058
Citations
1
Primary Topic
Air Quality and Health Impacts
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article
Field-Weighted Citation Impact
0.31

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article

Associations of long-term exposure to fine particulate matter and its constituents with gynecologic cancer incidence: A prospective cohort study from Beijing

Ning Kang, Huichao Li, Tong Zhu, Shuo Liu et al.
1 citations
Medicine Plus
Air Quality and Health Impacts
0.31
article

Associations of long-term exposure to fine particulate matter and its constituents with gynecologic cancer incidence: A prospective cohort study from Beijing

Ning Kang, Huichao Li, Tong Zhu, Shuo Liu, Tao Xue, Jinting Guo, Jiafu Ji, Ning Wang, Min Gao, Lei Yang, Lili Cao, Xi Zhang
article en
1 citations

Abstract

There is limited evidence of the association between long-term exposure to particulate matter with aerodynamic diameter ≤2.5 μm (fine particulate matter, PM 2.5 ) and gynecologic cancer incidence, particularly in developing countries with high air pollution levels. The present study aimed to investigate the associations of long-term exposure to PM 2.5 and its constituents with the incidence of gynecologic cancer, and to identify the primary constituent. A total of 85,500 women from the National Urban Cancer Screening Program in Beijing (2013–2019) were included. 5-year average concentrations of PM 2.5 mass and its constituents, namely carbon black (BC), ammonium (NH 4 + ), nitrate (NO 3 − ), organic matter (OM), and sulfate (SO 4 2− ), were obtained from the Tracking Air Pollution in China (TAP) dataset. Cox proportional hazard models were used to analyze the association between long-term exposure to PM 2.5 and its constituents and gynecologic cancer incidence. Mixture exposure models, including quantile-based g-computation (Qgcomp) and explanatory machine learning model (SHapley Additive exPlanations, SHAP), were used to assess the effect of each constituent. During a mean follow-up of 6.22 years, 524 participants were diagnosed with gynecologic cancer. The adjusted hazard ratios (HRs) for gynecologic cancer incidence associated with 1 standard deviation (SD) increment was 1.10 (95% CI: 1.00–1.22) for PM 2.5 , 1.12 (95% CI: 1.01–1.23) for BC,1.11 (95% CI: 1.00–1.23) for NH 4 + , 1.12 (95% CI: 1.01–1.23) for OM, 1.12 (95% CI: 1.01–1.23) for SO 4 2− , and 1.08 (95% CI: 0.98–1.19) for NO 3 − . The Qgcomp model indicated the association between a mixture of PM 2.5 constituents and gynecologic cancer incidence, with positive weights assigned to BC (61.6%), SO 4 2− (35.9%), and NO 3 − (2.5%). The SHAP model showed that SO 4 2− was the most important constituent, with the mean |SHAP| value of 0.0322, followed by BC (0.0270), OM (0.0232), NO 3 − (0.0212) and NH 4 + (0.0190). Long-term exposure to PM 2.5 was associated with gynecologic cancer incidence, with SO 4 2− and BC contributing significantly to the association.

Medicine PlusVol. 1(4)
Peking University (CN), National Health and Family Planning Commission (CN), Peking University Cancer Hospital (CN), Ministry of Education (ET), Inner Mongolia Medical University (CN)
Natural Science Foundation of Beijing Municipality
Openalex Percentile: Top 36%
Air Quality and Health Impacts
0.31
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