The characterization of residential fungal spores and the relationship with housing characteristics in the Houston area

A number of indoor environmental factors, including bioaerosol or aeroallergen concentrations have been identified as exacerbators for asthma and allergenic conditions of the respiratory system. People generally spend 90% to 95% of their time indoors. Therefore, understanding the environmental factors that affect the presence of aeroallergens indoors as well as outdoors is important in determining their health impact, and in identifying potential intervention methods. This study aimed to assess the relationship between indoor airborne fungal spore concentrations and indoor surface mold levels, indoor versus outdoor airborne fungal spore concentrations and the effect of previous as well as current water intrusion. Also, the association between airborne concentration of indoor fungal spores and surface mold levels and the age of the housing structure were examined. Further, the correlation between indoor concentrations of certain species was determined as well. ^ Air and surface fungal measurements and related information were obtained from a Houston-area data set compiled from visits to homes filing insurance claims. During the sampling visit these complaint homes exhibited either visible mold or a combination of visible mold and water intrusion problems. These data were examined to assess the relationships between the independent and dependent variables using simple linear regression analysis, and independent t-tests. To examine the correlation between indoor concentrations of certain species, Spearman correlation coefficients were used. ^ There were 126 houses sampled, with spring, n=43 (34.1%), and winter, n=42 (33.3%), representing the seasons with the most samples. The summer sample illustrated the highest geometric mean concentration of fungal spores, GM=5,816.5 relative to winter, fall and spring (GM=1,743.4, GM=3,683.5 and GM=2,507.4, respectively). In all seasons, greater concentrations of fungal spores were observed during the cloudy weather conditions. ^ The results indicated no statistically significant association between outdoor total airborne fungal spore concentration and total living room airborne fungal spore concentration (β = 0.095, p = 0.491). Second, living room surface mold levels were not associated with living room airborne fungal spore concentration, (β= 0.011, p = 0.669). Third, houses with and without previous water intrusion did not differ significantly with respect to either living room (t(111) = 0.710, p = 0.528) or bedroom (t(111) =1.673, p = 0.162) airborne fungal spore concentrations. Likewise houses with and without current water intrusion did not differ significantly with respect to living room (t(109)=0.716, p = 0.476) or bedroom (t(109) = 1.035, p = 0.304) airborne fungal spore concentration. Fourth, houses with and without current water intrusion did not differ significantly with respect to living room (χ 2 (5) = 5.61, p = 0.346), or bedroom (χ 2 (5) = 1.80, p = 0.875) surface mold levels. Fifth, the age of the house structure did not predict living room (β = 0.023, p = 0.102) and bedroom (β = 0.023, p = 0.065) surface mold levels nor living room (β = 0.002, p = 0.131) and bedroom (β = 0.001, p = 0.650) fungal spore airborne concentration. Sixth, in houses with visually observed mold growth there was statistically significant differences between the mean living room concentrations and mean outdoor concentrations for Cladosporium (t (107) = 11.73, p < 0.0001), Stachybotrys (t (106)=2.288, p = 0.024, and Nigrosporia (t (102) = 2.267, p = 0.025). Finally, there was a significant correlation between several living room fungal species pairs, namely, Cladosporium and Stachybotrys (r = 0.373, p <0.01, n=65), Curvularia and Aspergillus/Penicillium (r = 0.205, p < 0.05, n= 111)), Curvularia and Stachybotrys (r = 0.205, p < 0.05, n=111), Nigrospora and Chaetomium (r = 0.254, p < 0.01, n=105) and Stachybotrys and Nigrospora (r = 0.269, p < 0.01, n=105). ^ This study has demonstrated several positive findings, i.e., significant pairwise correlations of concentrations of several fungal species in living room air, and significant differences between indoor and outdoor concentrations of three fungal species in homes with visible mold. No association was observed between indoor and outdoor fungal spore concentrations. Neither living room nor bedroom airborne spore concentrations and surface mold levels were related to the age of the house or to water intrusion, either previous or current. Therefore, these findings suggest the need for evaluating additional parameters, as well as combinations of factors such as humidity, temperature, age of structure, ventilation, and room size to better understand the determinants of airborne fungal spore concentrations and surface mold levels in homes. ^

Returning Texas Senate Bill 530 back to 1100 Congress Avenue: The need for effective surveillance reporting of student fitness levels to Texas house representatives

Every Texas student is required to complete the FITNESSGRAM fitness assessment under legislation outlined in Senate Bill 530. This study described cardiovascular, body mass index (BMI), and overall fitness levels of students (grades 3–12) in the state of Texas during the 2009–2010 school year, and provides examples of how to effectively present results to Texas House Representatives using three unique health communication strategies. Given the Texas legislature mandates FITNESSGRAM collection yet did not require reporting according to their election district, the data were aggregated to 150 Texas House Representative Districts by sex and grade category to facilitate effective fitness data dissemination. Fitness data were also analyzed with results from the Texas Assessment of Knowledge and Skills (TAKS) to provide insight into potential relationships between fitness and academic achievement. ^ The majority of students in Texas need improvement on at least 1 fitness assessment. In general, female students have superior fitness in elementary and middle school but the fitness edge is erased by high school. Female cardiovascular fitness deteriorates faster from elementary to high school compared to male students. Female BMI deteriorates and male BMI improves from elementary to high school. Cardiovascular fitness and overall fitness decreases from elementary to high school for both male and female students. ^ Student fitness was significantly and strongly independently correlated with academic achievement. Further analysis showed that House Representatives with TAKS scores in the top quartile consistently showed superior fitness. Small significant partial correlations remain between fitness and TAKS assessment after controlling for socioeconomic status. In general, correlations were stronger between female BMI and TAKS assessment compared to male students. Cardiovascular fitness was significantly correlated with TAKS assessment for both genders. This paper supports student fitness as a confounder in the relationship between socioeconomic status and academic achievement. Plus, student fitness has a strong correlation with academic that deserves further exploration. ^ Senate Bill 530 fails to organize and implement a health communication strategy that effectively disseminates the health data collected to stakeholders of interest. The lack of a vital health communication strategy results in an incomplete student health surveillance system. This paper outlines three unique strategies tailored to legislators. It is important to disseminate health information using a variety of methods tailored to your targeted audience. The use of interactive mapping technology presented (GIS) uses new technology that has the potential to effectively reach a large audience.^