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, 127 (12), 127008

Long-Term Exposure to Ambient Fine Particulate Matter ( PM2.5) and Lung Function in Children, Adolescents, and Young Adults: A Longitudinal Cohort Study

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Long-Term Exposure to Ambient Fine Particulate Matter ( PM2.5) and Lung Function in Children, Adolescents, and Young Adults: A Longitudinal Cohort Study

Cui Guo et al. Environ Health Perspect.

Abstract

Background: The association between long-term exposure to ambient fine particulate matter with aerodynamic diameter 2.5μm (PM2.5) and lung function in young people remains uncertain, particularly in Asia, where air pollution is generally a serious problem.

Objectives: This study investigated the association between long-term exposure to ambient PM2.5 and lung function in Taiwanese children, adolescents, and young adults.

Methods: This study comprised 24,544 participants 6-24 years of age, with 33,506 medical observations made between 2000 and 2014. We used a spatiotemporal model to estimate PM2.5 concentrations at participants' addresses. Spirometry parameters, i.e., forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1), and maximum midexpiratory flow (MMEF), were determined. A generalized linear mixed model was used to examine the associations between long-term exposure to ambient PM2.5 and lung function. The odds ratios (ORs) of poor lung function were also calculated after adjusting for a range of covariates.

Results: Every 10-μg/m3 increase in the 2-y average PM2.5 concentration was associated with decreases of 2.22% [95% confidence interval (CI): -2.60, -1.85], 2.94 (95% CI: -3.36, -2.51), and 2.79% (95% CI: -3.15, -2.41) in the FVC, FEV1, and MMEF, respectively. Furthermore, it was associated with a 20% increase in the prevalence of poor lung function (OR: 1.20; 95% CI: 1.12, 1.29).

Conclusions: Two-year ambient PM2.5 concentrations were inversely associated with lung function and positively associated with the prevalence of poor lung function in children, adolescents, and young adults in Taiwan. https://doi.org/10.1289/EHP5220.

Figures

Figure 1 comprises two box plots, plotting year from 2000 to 2014 (y-axis) across PM sub 2.5 concentrations from 10 to 50 (in micrograms per cubic meter) (x-axis).
Figure 1.
Box plots of particulate matter with aerodynamic diameter 2.5μm (PM2.5) concentration by year in Taiwan. (A,B) Distributions of the 2-y average PM2.5 concentrations (the year of health examination and the previous year) by year. Boxes cover the 25th–75th percentiles [interquartile range (IQR)], with center lines indicating the median concentration. Whiskers extend to the highest observations within three IQRs of the box, with more extreme observations shown as circles. (A) Shows the distribution of 24,544 participants at baseline. (B) Indicates the distribution of 33,506 observations from the 24,544 participants.
Figure 2A comprises two line graphs each plotting percentage difference in FVC and in MMEF (y-axis) across PM sub 2.5 concentrations (micrograms per cubic meter; x-axis). Figure 2B comprises two line graphs each plotting percentage difference in FEV sub 1 and odds ratio (y-axis) across PM sub 2.5 concentrations (micrograms per cubic meter; x-axis).
Figure 2.
Concentration–response associations between fine particulate matter with aerodynamic diameter 2.5μm (PM2.5) and lung function in children, adolescents, and young adults. (A–D) Longitudinal associations of PM2.5 with forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1), maximum midexpiratory flow (MMEF), and the prevalence of poor lung function, respectively. The black solid lines represent the estimated effects on lung function, and the dashed lines refer to the corresponding 95% confidence intervals. Generalized linear mixed model (GLMM) with the log link function was used for FVC, FEV1, and MMEF, and GLMM with logistic link function was used for the prevalence of poor lung function. All models were adjusted for age, sex, height, weight, education, calendar year, season, and lifestyle factors (smoking status, alcohol consumption, physical activity, vegetable intake, and fruit intake).

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