Sources Of Variation In Levels Research Articles

Inter- and intra-individual sources of variation in levels of urinary styrene metabolites.

Given the paucity of studies that have examined variability in biological measures of exposure to workplace contaminants, we quantified the intra- and inter-individual sources of variation in urinary levels of mandelic acid (MA) and phenylglyoxylic acid (PGA) among workers exposed to styrene. A secondary objective was to examine effects of job task and the timing of sampling during the workweek on the variation in workers' urinary styrene metabolite levels. As part of routine biological monitoring, a total of 1,714 measurements of MA and PGA collected from 331 workers between 1985 and 1999 from eight reinforced-plastics plants were abstracted from laboratory reports. To evaluate sources of variation in levels of urinary styrene metabolites, we applied random-effects models. The influence of job task and day of sampling on metabolite levels was examined using mixed-effects models. PGA levels were characterized by less variation than levels of MA, as were metabolite levels expressed in terms of urinary creatinine concentration. The relative magnitude of the inter-individual to the intra-individual source of variation was generally higher for post-shift urine samples than for pre-shift urine samples. As expected, urinary metabolite levels were highest for laminators and for samples collected at the latter end of the workweek. Owing to the effects of variation from day-to-day, estimates of workers' exposures that rely on single measurements would generally perform poorly in a regression analysis designed to examine effects resulting from chronic exposure. However, the bias in an observed slope coefficient would be diminished if a second or third urine sample were collected. Quantification of the intra- and inter-individual sources of variation provides useful information that can be used to design optimal sampling strategies, which would allow for the collection of sufficient data to estimate workers' exposures reliably when evaluating health risks associated with occupational contaminants.