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An important question when setting appropriate air quality standards for fine particulate matter (PM2.5) is whether there exists growing nonlinearity in the concentration-response (C-R) function at lower exposure levels, such that exposures to PM2.5 levels below some level entail increasingly lower adverse health risk. Such nonlinearity is often colloquially referred to and approximated in analyses as a “threshold.” In a recent article in the journal PLOS ONE, NERA Associate Director Dr. Garrett Glasgow, Consultant Bharat Ramkrishnan, and Affiliated Consultant Dr. Anne E. Smith undertake a simulation-based study that examines the effect of measurement error in pollutant exposure on the ability of statistical models to detect such C-R thresholds in long-term air quality cohort studies. 

Their results demonstrate that exposure measurement error can obscure the existence of a threshold in the C-R function when such a threshold exists. Measurement error also leads to attenuated estimates of both the location of the C-R threshold and the hazard ratio associated with PM2.5. The authors conclude that the extent of measurement error in estimates of pollutant exposure should be more carefully quantified, and that its potential effects on uncertainty in the shape of the C-R functions merits consideration by policymakers when setting air quality standards.