Global Associations between Air Pollutants and Chronic Obstructive Pulmonary Disease Hospitalizations: A Systematic Review.

Abstract

BACKGROUND: Exacerbations are key events in Chronic Obstructive Pulmonary Disease (COPD), affecting lung function decline and quality of life. The effect of exposure to different air pollutants on COPD exacerbations is not clear. OBJECTIVE: To carry out a systematic review examining associations between air pollutants and hospital admissions for COPD exacerbations. DATA SOURCES: MEDLINE, EMBASE, BIOSIS & Science Citation Index, and the Air Pollution Epidemiology Database were searched from 1980 until September 2015. DATA EXTRACTION: Inclusion criteria focused on studies presenting solely a COPD outcome defined by hospital admissions, and a measure of gaseous air pollutants and particle fractions. The association between each pollutant with COPD admissions was investigated in metaanalyses using random-effects models. Analyses were stratified by geographical clusters to investigate the consistency of the evidence worldwide. SYNTHESIS: 46 studies were included and results for all the pollutants under investigation showed marginal positive associations; however the number of included studies was small with high heterogeneity between them and there was evidence of small-study bias. Geographical clustering of the effects of pollution on COPD hospital admissions was evident and reduced heterogeneity significantly. CONCLUSIONS: The most consistent associations was between a 1mg/m3 increase in carbon monoxide levels with COPD related admissions; Odds Ratio: 1.02 (95%CI: 1.01-1.03). The heterogeneity was moderate and there was a consistent positive association in both Europe and North America, although levels were clearly below WHO guideline values. There is mixed evidence on the effects of environmental pollution on COPD exacerbations. Limitations of previous studies included the low spatiotemporal resolution of pollutants, inadequate control for confounding factors, and the use of aggregated health data that ignore personal characteristics. The need for more targeted exposure estimates in a large number of geographical locations is evident.