2 resultados para Weather Conditions
em DigitalCommons@The Texas Medical Center
Resumo:
On a global basis rotaviruses are the most important agents involved in childhood diarrhea. In developing countries they account for 6% of all diarrheas and 20% of all diarrhea related deaths of children under 5 years of age, with over 1 billion episodes and over 4 million deaths annually. Given the disease burden, there is a need for better understanding the risk factors involved in rotavirus disease, to identify areas of intervention. In order to provide this information, two areas were developed: a review of the literature, examining the causal evidence for rotavirus diarrhea and a case comparison study. The case comparison study analyzed two areas: identifying climate factors and, identifying environmental and behavioral risk factors. The literature review showed that few analytical studies have identified specific risk factors such as home environment, and a winter seasonal trend for temperate areas, but in key areas evidence is contradictory. The case comparison study for climate factors demonstrated that seasonality occurs in a tropical country like Venezuela and that a complex interplay between weather conditions contribute to the seasonal pattern. A positive association between rain fall (OR 4.1); dew point (OR 2.3) and temperature differential during the day (OR 1.4) and, an inverse association with temperature (OR 0.5) and relative humidity (OR 0.8) was found. This information is useful in understanding the seasonal pattern of rotavirus and for planning health care needs. The second analysis demonstrated that environmental variables such as crowding (OR 14.3), contact with someone with an infectious disease (OR 4.9) and animal ownership (OR 2.3) were important. Restricting the analysis to animal owners demonstrated that living In a rural settling (OR 13.8), defecating in inappropriate places (OR 7.2), crowding(4.2) and indoor animals (4.0) are of importance. Behavioral variables identified were: lack of breast feeding (OR 4.0) and visiting when someone was sick (OR 3.4). Biological and demographic variables of importance were: age, with a dose response relationship; undernurishment (OR 11.3) and household per capita monthly income less than US $ 16.30 (OR 8.5). Using a diarrhea compeer group we found that, although some of the previous variables were of importance, no major differences were found. These findings are important in identifying paths for prevention and further research. ^
Resumo:
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. ^