MODELING LONG-TERM AVERAGE EXPOSURE IN OCCUPATIONAL EXPOSURE-RESPONSEANALYSIS

Objectives Estimates of long-term average exposure to occupational haz ards are often imprecise because intraindividual variability in exposu re can be large and exposure is usually based on one or few measuremen ts. One potential result is bias of exposure-response relationships. T he possibility was studied of a more valid measure of exposure being o btained by modeling exposure and consequently increasing the number of days with exposure estimates, using simple measurable exposure surrog ates. Methods In a group of 198 Dutch pig farmers, exposure to endotox ins was measured on one workday in summer and one day in winter. Farme rs recorded activity patterns during one week in both seasons, and far m characteristics were evaluated. Relationships between farm character istics and activities and log-transformed measured exposure levels wer e quantified in a multiple regression analysis. Exposure was estimated for 14 d with known activity patterns. Results The ratio of intraindi vidual and interindividual variance in log-transformed measured exposu re was 4.7. Given this ratio, the true regression coefficient of lung function on exposure would potentially be attenuated by 70%. The varia nce ratio for predicted exposures was only 1.2, and the potential atte nuation by variation in exposure estimates was decreased to 8%. There was no relationship between lung function and measured exposure. Model ed long-term average exposure was inversely related to base-line lung function; it reached statistical significance for asymptomatic farmers . Conclusions The results suggest that the presented strategy offers a possibility to minimize measurement effort in occupational epidemiolo gic studies, without apparent loss of statistical power.