Concentration-dependent health effects of air pollution in controlled human exposures

Air pollution is a leading contributor to premature mortality worldwide and is often represented by particulate matter (PM), a key contributor to its harmful health effects. Concentration-response relationships are useful for quantifying the effects of air pollution in relevant populations and in considering potential effect thresholds. Controlled human exposures can provide data on acute effects and concentration-response relationships that complement epidemiological studies.

We examined PM concentration-responses after controlled human air pollution exposures to examine exposure-response markers, assess effect modifiers, and identify potential effect thresholds.

We reviewed primary research from published controlled human exposure studies where responses were reported at multiple target PM concentrations or summarized per unit change in PM to identify concentration-dependent effects.

Of the 191 publications identified through PubMed and supplementary searches, 31 were eligible. Eligible studies collectively represented four pollutant models: concentrated ambient particles, engineered carbon nanoparticles, diesel exhaust, and woodsmoke. We identified concentration-dependent effects on oxidative stress markers, inflammation, and cardiovascular function that overlapped across different pollutants. Metabolic syndrome and glutathione s-transferase mu 1 genotype were identified as potential effect modifiers.

Improved understanding of concentration-response relationships is integral to biomonitoring and mitigation of health effects through impact assessment and policy. Although we identified potential concentration-response markers, thresholds, and modifiers, our conclusions on these relationships were limited by a dearth of eligible publications, considerable variability in methodology, and inconsistent reporting standards between studies. More research is required to validate these observations. We recommend that future studies harmonize estimate reporting to facilitate the identification of robust response markers across research and applied settings.