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Ambient Cumulative PM2.5 Exposure and the Risk of Lung Cancer Incidence and Mortality: A Retrospective Cohort Study.

ABSTRACT: Smoking, sex, air pollution, lifestyle, and diet may act independently or in concert with each other to contribute to the different outcomes of lung cancer (LC). This study aims to explore their associations with the carcinogenesis of LC, which will be useful for formulating further preventive strategies. This retrospective, longitudinal follow-up cohort study was carried out by connecting to the MJ Health Database, Taiwan Cancer Registry database, and Taiwan cause of death database from 2000 to 2015. The studied subjects were persons attending the health check-ups, distributed throughout the main island of Taiwan. Cox proportional hazards regression models were used to investigate the risk factors associated with LC development and mortality after stratifying by smoking status, with a special emphasis on ambient two-year average PM_2.5 exposure, using a satellite-based spatiotemporal model at a resolution of 1 km², and on dietary habit including consumption of fruits and vegetables. After a median follow-up of 12.3 years, 736 people developed LC, and 401 people died of LC-related causes. For never smokers, the risk of developing LC (aHR: 1.32, 95%CI: 1.12-1.56) and dying from LC-related causes (aHR: 1.28, 95%CI: 1.01-1.63) rises significantly with every 10 μg/m³ increment of PM_2.5 exposure, but not for ever smokers. Daily consumption of more than two servings of vegetables and fruits is associated with lowering LC risk in ever smokers (aHR: 0.68, 95%CI: 0.47-0.97), and preventing PM_2.5 exposure is associated with lowering LC risk for never smokers.

SUBMITTER: Huang HL

PROVIDER: S-EPMC8656990 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:We conducted a meta-analysis to examinine the relationship between exposure to PM2.5 and lung cancer incidence and mortality. In total, 17 studies met our inclusion criteria and provided information necessary to estimate the change in lung cancer risk per 10 ?g/m3 increase in exposure to PM2.5. The random-effects model was used to estimate the relative risk (RR) for specific PM2.5 values. The meta-estimate for lung cancer risk associated with PM2.5 was 1.11 for mortality (95% CI: 1.05, 1.18) and 1.08 (95% CI: 1.03, 1.12) for incidence. Analyses by continent showed that the meta-estimate for lung cancer mortality associated with PM2.5 was greatest in North America [1.15 (95% CI: 1.07, 1.24)], followed by Asia [1.12 (95% CI: 0.94, 1.35)], and then Europe [1.05 (95% CI: 1.01, 1.10)]. Lung cancer incidence associated with PM2.5 was greatest in Asia [1.09 (95% CI: 1.03, 1.15)], followed by North America [1.06 (95% CI: 1.01, 1.11)], and then Europe [1.03 (95% CI: 0.61, 1.75)]. In subgroup analyses of country, the mortality meta-estimate for developed countries was 1.14 (95% CI: 1.06, 1.23), and for developing countries was 1.03 (95% CI: 1.00, 1.07). The incidence meta-estimate for developed countries was 1.07 (95% CI: 0.96, 1.20), and was similar to that of developing countries, 1.07 (95% CI: 1.06, 1.09). In subgroup analyses of males and females, the meta-estimate for lung cancer mortality associated with PM2.5 was greater for males [1.26 (95% CI: 1.15, 1.40)] than for females [1.17 (95% CI: 0.98, 1.39)]. The meta-estimate for lung cancer incidence associated with PM2.5 was greater for males [1.23 (95% CI: 0.83, 1.81)] than for females [1.15 (95% CI: 1.12, 1.18)]. In subgroup analyses of smoking status, the meta-estimate for lung cancer mortality associated with PM2.5 for former smokers was 1.46 (95% CI: 0.84, 2.55), for current smokers was 1.33 (95% CI: 1.20, 1.49), and for never smokers was 1.16 (95% CI: 1.02, 1.33), respectively. The meta-estimate for lung cancer incidence associated with PM2.5 for former smokers was 1.19 (95% CI: 0.95, 1.50), for never smokers was 1.10 (95% CI: 0.76, 1.59), and for current smokers was 1.03 (95% CI: 0.87, 1.21). The relative risks of a relationship between PM2.5 and lung cancer incidence and mortality were 1.08 (95% CI: 1.03, 1.12) and 1.11 (95% CI: 1.05, 1.18), respectively. These findings will provide some evidence for policy makers and public health practitioners worldwide.

Project description:Using a case-crossover study design and conditional logistic regression, we compared the relative odds of transmural (full-wall) myocardial infarction (MI) calculated using exposure surrogates that account for human activity patterns and the indoor transport of ambient PM(2.5) with those calculated using central-site PM(2.5) concentrations to estimate exposure to PM(2.5) of outdoor origin (exposure to ambient PM(2.5)). Because variability in human activity and indoor PM(2.5) transport contributes exposure error in epidemiologic analyses when central-site concentrations are used as exposure surrogates, we refer to surrogates that account for this variability as "refined" surrogates. As an alternative analysis, we evaluated whether the relative odds of transmural MI associated with increases in ambient PM(2.5) is modified by residential air exchange rate (AER), a variable that influences the fraction of ambient PM(2.5) that penetrates and persists indoors. Use of refined exposure surrogates did not result in larger health effect estimates (ORs=1.10-1.11 with each interquartile range (IQR) increase), narrower confidence intervals, or better model fits compared with the analysis that used central-site PM(2.5). We did observe evidence for heterogeneity in the relative odds of transmural MI with residential AER (effect-modification), with residents of homes with higher AERs having larger ORs than homes in lower AER tertiles. For the level of exposure-estimate refinement considered here, our findings add support to the use of central-site PM(2.5) concentrations for epidemiological studies that use similar case-crossover study designs. In such designs, each subject serves as his or her own matched control. Thus, exposure error related to factors that vary spatially or across subjects should only minimally impact effect estimates. These findings also illustrate that variability in factors that influence the fraction of ambient PM(2.5) in indoor air (e.g., AER) could possibly bias health effect estimates in study designs for which a spatiotemporal comparison of exposure effects across subjects is conducted.

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Ambient Cumulative PM2.5 Exposure and the Risk of Lung Cancer Incidence and Mortality: A Retrospective Cohort Study.

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