Article ID Journal Published Year Pages File Type
5748644 Environmental Pollution 2017 9 Pages PDF
Abstract

•Systematic review and meta-analysis of 17 time-series and case-crossover studies.•Positive & significant associations for air pollutants and pediatric pneumonia.•Highest excess risk was 2.9% for SO2 followed by PM2.5, O3, PM10, NO2, and CO.•Associations remained significant regardless of country location and age.•Most homogenous results were found for PM2.5 (I-squared = 38%) over 13 studies.

Ambient air pollution has been associated with respiratory diseases in children. However, its effects on pediatric pneumonia have not been meta-analyzed. We conducted a systematic review and meta-analysis of the short-term association between ambient air pollution and hospitalization of children due to pneumonia. We searched the Web of Science and PubMed for indexed publications up to January 2017. Pollutant-specific excess risk percentage (ER%) and confidence intervals (CI) were estimated using random effect models for particulate matter (PM) with diameter ≤ 10 (PM10) and ≤2.5 μm (PM2.5), sulfur dioxide (SO2), ozone (O3), nitrogen dioxide (NO2), and carbon monoxide (CO). Results were further stratified by subgroups (children under five, emergency visits versus hospital admissions, income level of study location, and exposure period). Seventeen studies were included in the meta-analysis. The ER% per 10 μg/m3 increase of pollutants was 1.5% (95% CI: 0.6%-2.4%) for PM10 and 1.8% (95% CI: 0.5%-3.1%) for PM2.5. The corresponding values per 10 ppb increment of gaseous pollutants were 2.9% (95% CI: 0.4%-5.3%) for SO2, 1.7% (95% CI: 0.5%-2.8%) for O3, and 1.4% (95% CI: 0.4%-2.4%) for NO2. ER% per 1000 ppb increment of CO was 0.9% (95% CI: 0.0%-1.9%). Associations were not substantially different between subgroups. This meta-analysis shows a positive association between daily levels of ambient air pollution markers and hospitalization of children due to pneumonia. However, lack of studies from low-and middle-income countries limits the quantitative generalizability given that susceptibilities to the adverse effects of air pollution may be different in those populations. The meta-regression in our analysis further demonstrated a strong effect of country income level on heterogeneity.

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Life Sciences Environmental Science Environmental Chemistry
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