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ABSTRACT: Purpose
To investigate the association between long-term exposure to ambient air pollution and lung cancer incidence in Koreans.Materials and methods
This was a population-based case-control study covering 908 lung cancer patients and 908 controls selected from a random sample of people within each Korean province and matched according to age, sex, and smoking status. We developed land-use regression models to estimate annual residential exposure to particulate matter (PM₁₀) and nitrogen dioxide (NO₂) over a 20-year exposure period. Logistic regression was used to estimate odds ratios (ORs) and their corresponding 95% confidence intervals (CI).Results
Increases in lung cancer incidence (expressed as adjusted OR) were 1.09 (95% CI: 0.96-1.23) with a ten-unit increase in PM₁₀ (μg/m³) and 1.10 (95% CI: 1.00-1.22) with a ten-unit increase in NO₂ (ppb). Tendencies for stronger associations between air pollution and lung cancer incidence were noted among never smokers, among those with low fruit consumption, and among those with a higher education level. Air pollution was more strongly associated with squamous cell and small cell carcinomas than with adenocarcinoma of the lung.Conclusion
This study provides evidence that PM10 and NO₂ contribute to lung cancer incidence in Korea.
SUBMITTER: Lamichhane DK
PROVIDER: S-EPMC5653475 | biostudies-literature | 2017 Nov
REPOSITORIES: biostudies-literature
Lamichhane Dirga Kumar DK Kim Hwan Cheol HC Choi Chang Min CM Shin Myung Hee MH Shim Young Mog YM Leem Jong Han JH Ryu Jeong Seon JS Nam Hae Seong HS Park Sung Min SM
Yonsei medical journal 20171101 6
<h4>Purpose</h4>To investigate the association between long-term exposure to ambient air pollution and lung cancer incidence in Koreans.<h4>Materials and methods</h4>This was a population-based case-control study covering 908 lung cancer patients and 908 controls selected from a random sample of people within each Korean province and matched according to age, sex, and smoking status. We developed land-use regression models to estimate annual residential exposure to particulate matter (PM₁₀) and ...[more]