Impact of lifetime air pollution exposure patterns on the risk of chronic disease

Cheng Yu Tsai, Chien Ling Su, Yuan Hung Wang, Sheng Ming Wu, Wen Te Liu, Wen Hua Hsu, Arnab Majumdar, Marc Stettler, Kuan Yuan Chen, Ya Ting Lee, Chaur Jong Hu, Kang Yun Lee, Ben Jei Tsuang, Chien Hua Tseng*

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

10 Scopus citations

Abstract

Long-term exposure to air pollution can lead to cardiovascular disease, metabolic syndrome, and chronic respiratory disease. However, from a lifetime perspective, the critical period of air pollution exposure in terms of health risk is unknown. This study aimed to evaluate the impact of air pollution exposure at different life stages. The study participants were recruited from community centers in Northern Taiwan between October 2018 and April 2021. Their annual averages for fine particulate matter (PM2.5) exposure were derived from a national visibility database. Lifetime PM2.5 exposures were determined using residential address information and were separated into three stages (<20, 20–40, and >40 years). We employed exponentially weighted moving averages, applying different weights to the aforementioned life stages to simulate various weighting distribution patterns. Regression models were implemented to examine associations between weighting distributions and disease risk. We applied a random forest model to compare the relative importance of the three exposure life stages. We also compared model performance by evaluating the accuracy and F1 scores (the harmonic mean of precision and recall) of late-stage (>40 years) and lifetime exposure models. Models with 89% weighting on late-stage exposure showed significant associations between PM2.5 exposure and metabolic syndrome, hypertension, diabetes, and cardiovascular disease, but not gout or osteoarthritis. Lifetime exposure models showed higher precision, accuracy, and F1 scores for metabolic syndrome, hypertension, diabetes, and cardiovascular disease, whereas late-stage models showed lower performance metrics for these outcomes. We conclude that exposure to high-level PM2.5 after 40 years of age may increase the risk of metabolic syndrome, hypertension, diabetes, and cardiovascular disease. However, models considering lifetime exposure showed higher precision, accuracy, and F1 scores and lower equal error rates than models incorporating only late-stage exposures. Future studies regarding long-term air pollution modelling are required considering lifelong exposure pattern. .1

Original languageEnglish
Article number115957
Pages (from-to)115957
JournalEnvironmental Research
Volume229
DOIs
StatePublished - 15 07 2023
Externally publishedYes

Bibliographical note

Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.

Keywords

  • Air pollution
  • Cardiovascular disease
  • Fine particulate matter
  • Metabolic syndrome
  • Respiratory disease
  • Hypertension
  • Air Pollutants/toxicity
  • Metabolic Syndrome/epidemiology
  • Humans
  • Cardiovascular Diseases/chemically induced
  • Air Pollution/adverse effects
  • Environmental Exposure/analysis
  • Particulate Matter/toxicity
  • Chronic Disease

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