Background: Metrics of culturable airborne microorganisms for either total organisms or suspected harmful subgroups have generally not been associated with symptoms among building occupants. However, the visible presence of moisture damage or mold in residences and other buildings has consistently been associated with respiratory symptoms and other health effects. This relationship is presumably caused by adverse but uncharacterized exposures to moisturerelated microbiological growth. In order to assess this hypothesis, we studied relationships in U.S. office buildings between the prevalence of respiratory and irritant symptoms, the concentrations of airborne microorganisms that require moist surfaces on which to grow, and the presence of visible water damage.Methods: For these analyses we used data on buildings, indoor environments, and occupants collected from a representative sample of 100 U.S. office buildings in the U.S. Environmental Protection Agency's Building Assessment Survey and Evaluation (EPA BASE) study. We created 19 alternate metrics, using scales ranging from 3-10 units, that summarized the concentrations of airborne moisture-indicating microorganisms (AMIMOs) as indicators of moisture in buildings. Two were constructed to resemble a metric previously reported to be associated with lung function changes in building occupants; the others were based on another metric from the same group of Finnish researchers, concentration cutpoints from other studies, and professional judgment. We assessed three types of associations: between AMIMO metrics and symptoms in office workers, between evidence of water damage and symptoms, and between water damage and AMIMO metrics. We estimated (as odds ratios (ORs) with 95% confidence intervals) the unadjusted and adjusted associations between the 19 metrics and two types of weekly, work-related symptoms -lower respiratory and mucous membrane -using logistic regression models. Analyses used the original AMIMO metrics and were repeated with simplified dichotomized metrics. The multivariate models adjusted for other potential confounding variables associated with respondents, occupied spaces, buildings, or ventilation systems. Models excluded covariates for moisture-related risks hypothesized to increase