Christopher Schaffer

Visually observed mold and moldy odor versus quantitatively measured microbial exposure in homes

The main study objective was to compare different methods for assessing mold exposure in conjunction with an epidemiologic study on the development of childrens asthma. Homes of 184 children were assessed for mold by visual observations and dust sampling at childs age 1 (Year 1). Similar assessment supplemented with air sampling was conducted in Year 7. Samples were analyzed for endotoxin, (1-3)-β-D-glucan, and fungal spores. The Mold Specific Quantitative Polymerase Chain Reaction assay was used to analyze 36 mold species in dust samples, and the Environmental Relative Moldiness Index (ERMI) was calculated. Homes were categorized based on three criteria: 1) visible mold damage, 2) moldy odor, and 3) ERMI. Even for homes where families had not moved, Year 7 endotoxin and (1-3)-β-d-glucan exposures were significantly higher than those in Year 1 (p<0.001), whereas no difference was seen for ERMI (p=0.78). Microbial concentrations were not consistently associated with visible mold damage categories, but were consistently higher in homes with moldy odor and in homes that had high ERMI. Low correlations between results in air and dust samples indicate different types or durations of potential microbial exposures from dust vs. air. Future analysis will indicate which, if any, of the assessment methods is associated with the development of asthma.

Influence of home characteristics on airborne and dustborne endotoxin and β-D-glucan

The aim of this study was to assess the associations between airborne and dustborne microbial contaminants (endotoxin and β-D-glucan) and estimate the effects of home characteristics on exposure levels of these microbial contaminants. Endotoxin and β-D-glucan concentrations in airborne inhalable particles, airborne PM1 (<1 μm) and vacuumed dust from 184 residential homes were determined using specific Limulus amebocyte assays. Home characteristics were recorded by visual inspection and questionnaires. Linear regression and correlation analyses were performed. Inhalable endotoxin correlated with dust endotoxin (r = 0.34, p < 0.001) and PM1 endotoxin (r = 0.33, p < 0.001). Inhalable β-D-glucan correlated with dust β-D-glucan (r = 0.18, p < 0.01), but not with PM1 β-D-glucan. Significant correlation was also found between PM1 and dust concentrations for endotoxin (r = 0.26, p < 0.001), but not for β-D-glucan. Multivariate regression analyses showed only one significant association between airborne contaminants and environmental characteristics: inhalable β-D-glucan was positively associated with relative humidity with an effect size (change in the dependent variable corresponding to a unit increase in the independent variable) of 2.32 and p < 0.05. In contrast, several associations were found between dust concentrations and environmental characteristics. Dust endotoxin was positively associated with temperature (2.87, p < 0.01) and number of inhabitants (2.76, p < 0.01), whereas dust β-D-glucan was inversely associated with the presence of dogs (-2.24, p < 0.05) and carpet (-3.05, p < 0.01) in the home. In conclusion, dustborne contaminants were more strongly affected by home characteristics than airborne contaminants. Furthermore, even though statistically significant, the correlations between airborne and dustborne contaminants were weak. This indicates that airborne concentrations cannot be reliably predicted based on dustborne concentrations.

Indoor air quality in green-renovated vs. non-green low-income homes of children living in a temperate region of US (Ohio).

Green eco-friendly housing includes approaches to reduce indoor air pollutant sources and to increase energy efficiency. Although sealing/tightening buildings can save energy and reduce the penetration of outdoor pollutants, an adverse outcome can be increased buildup of pollutants with indoor sources. The objective of this study was to determine the differences in the indoor air quality (IAQ) between green and non-green homes in low-income housing complexes. In one housing complex, apartments were renovated using green principles (n=28). Home visits were conducted immediately after the renovation, and subsequently at 6 months and at 12 months following the renovation. Of these homes, eight homes had pre-renovation home visits; this allowed pre- and post-renovation comparisons within the same homes. Parallel visits were conducted in non-green (control) apartments (n=14) in a nearby low-income housing complex. The IAQ assessments included PM2.5, black carbon, ultrafine particles, sulfur, total volatile organic compounds (VOCs), formaldehyde, and air exchange rate. Data were analyzed using linear mixed-effects models. None of the indoor pollutant concentrations were significantly different between green and non-green homes. However, we found differences when comparing the concentrations before and after renovation. Measured immediately after renovation, indoor black carbon concentrations were significantly lower averaging 682 ng/m(3) in post-renovation vs. 2364 ng/m(3) in pre-renovation home visits (p=0.01). In contrast, formaldehyde concentrations were significantly higher in post-renovated (0.03 ppm) than in pre-renovated homes (0.01 ppm) (p=0.004). Questionnaire data showed that opening of windows occurred less frequently in homes immediately post-renovation compared to pre-renovation; this factor likely affected the levels of indoor black carbon (from outdoor sources) and formaldehyde (from indoor sources) more than the renovation status itself. To reduce IAQ problems and potentially improve health, careful selection of indoor building materials and ensuring sufficient ventilation are important for green building designs.

Dustborne and airborne Gram-positive and Gram-negative bacteria in high versus low ERMI homes.

The study aimed at investigating Gram-positive and Gram-negative bacteria in moldy and non-moldy homes, as defined by the homes Environmental Relative Moldiness Index (ERMI) value. The ERMI values were determined from floor dust samples in 2010 and 2011 and homes were classified into low (<5) and high (>5) ERMI groups based on the average ERMI values as well as 2011 ERMI values. Dust and air samples were collected from the homes in 2011 and all samples were analyzed for Gram-positive and Gram-negative bacteria using QPCR assays, endotoxin by the LAL assay, and N-acetyl-muramic acid using HPLC. In addition, air samples were analyzed for culturable bacteria. When average ERMI values were considered, the concentration and load of Gram-positive bacteria determined with QPCR in house dust, but not air, were significantly greater in high ERMI homes than in low ERMI homes. Furthermore, the concentration of endotoxin, but not muramic acid, in the dust was significantly greater in high ERMI than in low ERMI homes. In contrast, when ERMI values of 2011 were considered, Gram-negative bacteria determined with QPCR in air, endotoxin in air, and muramic acid in dust were significantly greater in high ERMI homes. The results suggest that both short-term and long-term mold contamination in homes could be linked with the bacterial concentrations in house dust, however, only the current mold status was associated with bacterial concentrations in air. Although correlations were found between endotoxin and Gram-negative bacteria as well as between muramic acid and Gram-positive bacteria in the entire data set, diverging associations were observed between the different measures of bacteria and the home moldiness. It is likely that concentrations of cells obtained by QPCR and concentrations of cell wall components are not equivalent and represent too broad categories to understand the bacterial composition and sources of the home microbiota.

Microbial content of household dust associated with exhaled NO in asthmatic children

Exhaled nitric oxide (eNO) is increasingly used as a non-invasive measure of airway inflammation. Despite this, little information exists regarding the potential effects of indoor microbial components on eNO. We determined the influence of microbial contaminants in house dust and other indoor environmental characteristics on eNO levels in seven-year-olds with and without a physician-diagnosis of asthma. The study included 158 children recruited from a birth cohort study, and 32 were physician-diagnosed as asthmatic. The relationship between eNO levels and exposures to home dust streptomycetes, endotoxin, and molds was investigated. Streptomycetes and endotoxin were analyzed both as loads and concentrations in separate models. Dog, cat, and dust mite allergens also were evaluated. In the multivariate exposure models, high streptomycetes loads and concentrations were significantly associated with a decrease in eNO levels in asthmatic (p<0.001) but not in healthy children. The presence of dog allergen, however, was associated with increased levels of eNO (p=0.001). Dust endotoxin was not significant. The relationship between eNO and indoor exposure to common outdoor molds was u-shaped. In non-asthmatic children, none of the exposure variables was significantly associated with eNO levels. To our knowledge, this is the first study demonstrating a significant association between microbial components in the indoor environment and eNO levels in asthmatic children. This study demonstrates the importance of simultaneously assessing multiple home exposures of asthmatic children to better understand opposing effects. Common components of the indoor Streptomyces community may beneficially influence airway inflammation.