Abstract

Volatile organic compounds (VOCs) are suspected to contribute significantly to ''Sick Building Syndrome'' (SBS), a complex of subchronic symptoms that occurs during and in general decreases away from occupancy of the building in question. A new approach takes into account individual VOC potencies, as well as the highly correlated nature of the complex VOC mixtures found indoors. The new VOC metrics are statistically significant predictors of symptom outcomes from the California Healthy Buildings Study data. Multivariate logistic regression analyses were used to test the hypothesis that a summary measure of the VOC mixture, other risk factors, and covariates for each worker will lead to better prediction of symptom outcome. VOC metrics based on animal irritancy measures and principal component analysis had the most influence in the prediction of eye, dermal, and nasal symptoms. After adjustment, a water-based paints and solvents source was found to be associated with dermal and eye irritation. The more typical VOC exposure metrics used in prior analyses were not useful in symptom prediction in the adjusted model (total VOC (TVOC), or sum of individually identified VOCs ({Sigma}VOC{sub i})). Also not useful were three other VOC metrics that took into account potency, but did not adjust formore » the highly correlated nature of the data set, or the presence of VOCs that were not measured. High TVOC values (2--7 mg m{sup {minus}3}) due to the presence of liquid-process photocopiers observed in several study spaces significantly influenced symptoms. Analyses without the high TVOC values reduced, but did not eliminate the ability of the VOC exposure metric based on irritancy and principal component analysis to explain symptom outcome.« less

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