A simulation-based assessment of the ability to detect thresholds in chronic risk concentration-response functions in the presence of exposure measurement error.

An important question when setting appropriate air quality standards for fine particulate matter (PM2.5) is whether there exists a "threshold" in the concentration-response (C-R) function, such that PM2.5 levels below this threshold are not expected to produce adverse health effects. We hypothesize that measurement error may affect the recognition of a threshold in long-term cohort epidemiological studies. This study conducts what is, to the best of our knowledge, the first simulation of the effects of measurement error on the statistical models commonly employed in long-term cohort studies. We test the degree to which classical-type measurement error, such as differences between the true population-weighted exposure level to a pollutant and the observed measures of that pollutant, affects the ability to statistically detect a C-R threshold. The results demonstrate that measurement error can obscure the existence of a threshold in a cohort study's C-R function for health risks from chronic exposures. With increased measurement error the ability to statistically detect a C-R threshold decreases, and both the estimated location of the C-R threshold and the estimated hazard ratio associated with PM2.5 are attenuated. This result has clear implications for determining appropriate air quality standards for pollutants.