Abstract

Background: Panel studies have been used to investigate the short term effects of outdoor particulate air pollution across a wide range of environmental settings.

Aims: To systematically review the results of such studies in children, estimate summary measures of effect, and investigate potential sources of heterogeneity.

Methods: Studies were identified by searching electronic databases to June 2002, including those where outcomes and particulate level measurements were made at least daily for ⩾8 weeks, and analysed using an appropriate regression model. Study results were compared using forest plots, and fixed and random effects summary effect estimates obtained. Publication bias was considered using a funnel plot.

Results: Twenty two studies were identified, all except two reporting PM₁₀ (24 hour mean) >50 μg.m⁻³. Reported effects of PM₁₀ on PEF were widely spread and smaller than those for PM_2.5 (fixed effects summary: −0.012 v −0.063 l.min⁻¹ per μg.m⁻³ rise). A similar pattern was evident for symptoms. Random effects models produced larger estimates. Overall, in between-study comparisons, panels of children with diagnosed asthma or pre-existing respiratory symptoms appeared less affected by PM₁₀ levels than those without, and effect estimates were larger where studies were conducted in higher ozone conditions. Larger PM₁₀ effect estimates were obtained from studies using generalised estimating equations to model autocorrelation and where results were derived by pooling subject specific regression coefficients. A funnel plot of PM₁₀ results for PEF was markedly asymmetrical.

Conclusions: The majority of identified studies indicate an adverse effect of particulate air pollution that is greater for PM_2.5 than PM₁₀. However, results show considerable heterogeneity and there is evidence consistent with publication bias, so limited confidence may be placed on summary estimates of effect. The possibility of interaction between particle and ozone effects merits further investigation, as does variability due to analytical differences that alter the interpretation of final estimates.