Weighted quantile regression to evaluate relative responsiveness of health effects following toxicant exposure
On this page:
Humans are exposed to myriad pollutants, so it is important to identify the most sensitive health effects at low exposure levels. We developed a weighted mixed effects quantile regression approach to determine relative endpoint responsiveness among different organ systems. The lowest observed effect level (LOEL) is the lowest dosage associated with a significant change in an endpoint, so quantiles of LOELs for an organ system were comparable measures for endpoint responsiveness. The no observed effect level (NOEL) is the highest dosage not associated with a significant change, so LOELs close to their respective NOELs are better estimates of a toxicological threshold. Thus, weighted quantile regression of LOELs against organ system, with weights determined by NOEL presence and magnitude and random effects accounting for variation due to the same laboratory reporting multiple LOELs, present a novel approach to rank endpoint responsiveness. Ad hoc analyses of the estimated effects determined if sensitivities were significantly different between systems. We applied this method, using 10% quantiles, on a toxicological database of endpoints measured after exposure to polychlorinated biphenyl (PCB) mixtures.