Environmental Health Perspectives · 2002 · 94 citations · 29 references
Environmental MonitoringEngineeringAir QualityBuilt EnvironmentFungal DiversityIndoor AerosolEnvironmental ExposureEnvironmental HealthMicrobial EcologyAirborne FungiPublic HealthPrincipal Component AnalysisPca FactorsAir SamplingBioaerosol ConcentrationsFungal PathogenAerobiologyBiological PollutantMicrobiologyIndoor Air QualityAir Pollution
Bioaerosol concentrations in office environments and their roles in causing building-related symptoms have drawn much attention in recent years. Most bioaerosol studies have been cross-sectional. We conducted a longitudinal study to examine the characteristics of airborne fungal populations and correlations with other environmental parameters in office environments. We investigated four office buildings in Boston, Massachusetts, during 1 year beginning May 1997, recruiting 21 offices with open workstations. We conducted intensive bioaerosol sampling every 6 weeks resulting in 10 sets of measurement events at each workstation, and recorded relative humidity, temperature, and CO2 concentrations continuously. We used principal component analysis (PCA) to identify groups of culturable fungal taxa that covaried in air. Four major groupings (PCA factors) were derived where the fungal taxa in the same groupings shared similar ecological requirements. Total airborne fungal concentrations varied significantly by season (highest in summer, lowest in winter) and were positively correlated with relative humidity and negatively related to CO2 concentrations. The first and second PCA factors had similar correlations with environmental variables compared with total fungi. The results of this study provide essential information on the variability within airborne fungal populations in office environments over time. These data also provide background against which cross-sectional data can be compared to facilitate interpretation. More studies are needed to correlate airborne fungi and occupants' health, controlling for seasonal effects and other important environmental factors.
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Applied Regression Analysis and Other Multivariable Methods
Esteban Walker, David G. Kleinbaum, Lawrence L. Kupper et al. · Technometrics · 1989 · 8.3K citations
Engineering, Estimation Statistic, Best Regression Equation +12
Richard A. Brown, Trevor Hastie, Robert Tibshirani · Biometrics · 1991 · 8.3K citations
Statistical Modeling, Statistics, Generalized Additive Models +1