6 resultados para Illinois. Air National Guard

em DigitalCommons@The Texas Medical Center


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Identifying accurate numbers of soldiers determined to be medically not ready after completing soldier readiness processing may help inform Army leadership about ongoing pressures on the military involved in long conflict with regular deployment. In Army soldiers screened using the SRP checklist for deployment, what is the prevalence of soldiers determined to be medically not ready? Study group. 15,289 soldiers screened at all 25 Army deployment platform sites with the eSRP checklist over a 4-month period (June 20, 2009 to October 20, 2009). The data included for analysis included age, rank, component, gender and final deployment medical readiness status from MEDPROS database. Methods.^ This information was compiled and univariate analysis using chi-square was conducted for each of the key variables by medical readiness status. Results. Descriptive epidemiology Of the total sample 1548 (9.7%) were female and 14319 (90.2%) were male. Enlisted soldiers made up 13,543 (88.6%) of the sample and officers 1,746 (11.4%). In the sample, 1533 (10.0%) were soldiers over the age of 40 and 13756 (90.0%) were age 18-40. Reserve, National Guard and Active Duty made up 1,931 (12.6%), 2,942 (19.2%) and 10,416 (68.1%) respectively. Univariate analysis. Overall 1226 (8.0%) of the soldiers screened were determined to be medically not ready for deployment. Biggest predictive factor was female gender OR (2.8; 2.57-3.28) p<0.001. Followed by enlisted rank OR (2.01; 1.60-2.53) p<0.001. Reserve component OR (1.33; 1.16-1.53) p<0.001 and Guard OR (0.37; 0.30-0.46) p<0.001. For age > 40 demonstrated OR (1.2; 1.09-1.50) p<0.003. Overall the results underscore there may be key demographic groups relating to medical readiness that can be targeted with programs and funding to improve overall military medical readiness.^

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Under the Clean Air Act, Congress granted discretionary decision making authority to the Administrator of the Environmental Protection Agency (EPA). This discretionary authority involves setting standards to protect the public's health with an "adequate margin of safety" based on current scientific knowledge. The Administrator of the EPA is usually not a scientist, and for the National Ambient Air Quality Standard (NAAQS) for particulate matter (PM), the Administrator faced the task of revising a standard when several scientific factors were ambiguous. These factors included: (1) no identifiable threshold below which health effects are not manifested, (2) no biological basis to explain the reported associations between particulate matter and adverse health effects, and (3) no consensus among the members of the Clean Air Scientific Advisory Committee (CASAC) as to what an appropriate PM indicator, averaging period, or value would be for the revised standard. ^ This project recommends and demonstrates a tool, integrated assessment (IA), to aid the Administrator in making a public health policy decision in the face of ambiguous scientific factors. IA is an interdisciplinary approach to decision making that has been used to deal with complex issues involving many uncertainties, particularly climate change analyses. Two IA approaches are presented; a rough set analysis by which the expertise of CASAC members can be better utilized, and a flag model for incorporating the views of stakeholders into the standard setting process. ^ The rough set analysis can describe minimal and maximal conditions about the current science pertaining to PM and health effects. Similarly, a flag model can evaluate agreement or lack of agreement by various stakeholder groups to the proposed standard in the PM review process. ^ The use of these IA tools will enable the Administrator to (1) complete the NAAQS review in a manner that is in closer compliance with the Clean Air Act, (2) expand the input from CASAC, (3) take into consideration the views of the stakeholders, and (4) retain discretionary decision making authority. ^

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Southeast Texas, including Houston, has a large presence of industrial facilities and has been documented to have poorer air quality and significantly higher cancer rates than the remainder of Texas. Given citizens’ concerns in this 4th largest city in the U.S., Mayor Bill White recently partnered with the UT School of Public Health to determine methods to evaluate the health risks of hazardous air pollutants (HAPs). Sexton et al. (2007) published a report that strongly encouraged analytic studies linking these pollutants with health outcomes. In response, we set out to complete the following aims: 1. determine the optimal exposure assessment strategy to assess the association between childhood cancer rates and increased ambient levels of benzene and 1,3-butadiene (in an ecologic setting) and 2. evaluate whether census tracts with the highest levels of benzene or 1,3-butadiene have higher incidence of childhood lymphohematopoietic cancer compared with census tracts with the lowest levels of benzene or 1,3-butadiene, using Poisson regression. The first aim was achieved by evaluating the usefulness of four data sources: geographic information systems (GIS) to identify proximity to point sources of industrial air pollution, industrial emission data from the U.S. EPA’s Toxic Release Inventory (TRI), routine monitoring data from the U.S. EPA Air Quality System (AQS) from 1999-2000 and modeled ambient air levels from the U.S. EPA’s 1999 National Air Toxic Assessment Project (NATA) ASPEN model. Further, once these four data sources were evaluated, we narrowed them down to two: the routine monitoring data from the AQS for the years 1998-2000 and the 1999 U.S. EPA NATA ASPEN modeled data. We applied kriging (spatial interpolation) methodology to the monitoring data and compared the kriged values to the ASPEN modeled data. Our results indicated poor agreement between the two methods. Relative to the U.S. EPA ASPEN modeled estimates, relying on kriging to classify census tracts into exposure groups would have caused a great deal of misclassification. To address the second aim, we additionally obtained childhood lymphohematopoietic cancer data for 1995-2004 from the Texas Cancer Registry. The U.S. EPA ASPEN modeled data were used to estimate ambient levels of benzene and 1,3-butadiene in separate Poisson regression analyses. All data were analyzed at the census tract level. We found that census tracts with the highest benzene levels had elevated rates of all leukemia (rate ratio (RR) = 1.37; 95% confidence interval (CI), 1.05-1.78). Among census tracts with the highest 1,3-butadiene levels, we observed RRs of 1.40 (95% CI, 1.07-1.81) for all leukemia. We detected no associations between benzene or 1,3-butadiene levels and childhood lymphoma incidence. This study is the first to examine this association in Harris and surrounding counties in Texas and is among the first to correlate monitored levels of HAPs with childhood lymphohematopoietic cancer incidence, evaluating several analytic methods in an effort to determine the most appropriate approach to test this association. Despite recognized weakness of ecologic analyses, our analysis suggests an association between childhood leukemia and hazardous air pollution.^

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Recent studies have reported positive associations between maternal exposures to air pollutants and several adverse birth outcomes. However, there have been no assessments of the association between environmental hazardous air pollutants (HAPs) such as benzene, toluene, ethylbenzene, and xylene (BTEX) and neural tube defects (NTDs) a common and serious group of congenital malformations. Before examining this association, two important methodological questions must be addressed: (1) is maternal residential movement likely to result in exposure misclassification and (2) is it appropriate to lump defects of the neural tube, such as anencephaly and spina bifida, into a composite disease endpoint (i.e., NTDs). ^ Data from the National Birth Defects Prevention Study and Texas Birth Defects Registry were used to: (1) assess the extent to which change of residence may result in exposure misclassification when exposure is based on the address at delivery; (2) formally assess heterogeneity of the associations between known risk factors for NTDs, using polytomous logistic regression; and (3) conduct a case-control study assessing the association between ambient air levels of BTEX and the risk of NTDs among offspring. ^ Regarding maternal residential mobility, this study suggests address at delivery was not significantly different from using address at conception when assigning quartile of benzene exposure (OR 1.0, 95% CI 0.9, 1.3). On the question of effect heterogeneity among NTDs, the effect estimates for infant sex P = 0.017), maternal body mass index P = 0.016), and folate supplementation P = 0.050) were significantly different for anencephaly and spina bifida, suggesting it is often more appropriate to assess potential risk factors among subgroups of NTDs. For the main study question on the association between environmental HAPs and NTDs, mothers who have offspring with isolated spina bifida are 2.4 times likely to live in areas with the highest benzene levels (95% CI 1.1, 5.0). However, no other significant associations were observed.^ This project is the first to include not only an assessment of the relationship between environmental levels of BTEX and NTDs, but also two separate studies addressing important methodological issues associated with this question. Our results contribute to the growing body of evidence regarding air pollutant exposure and adverse birth outcomes. ^

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In the last two decades, the significance of lead has been addressed in a number of environmental regulations at the national and state levels. This project investigated the environmental regulations (Clean Air Act and Amendments, 1970-1990 and Clean Water Act of 1977) and their cumulative effects on lead in ambient air and water in the state of Texas. For this purpose, historical records from the Texas Water Development Board, Texas Natural Resources Conservation Commission, and the United States Geological Survey have been assembled and analyzed for temporal and spatial trends. These trends might correspond to the phase out of lead in gasoline and other regulations.^ This study concluded that there is a significant correlation (p $\leq$.001) between environmental regulations of lead in gasoline and the concentration of lead in ambient air. Lead concentrations in ambient air have been reduced by over 90 percent in the past twenty years. An overall significant difference (p $\leq$.001) was found in mean (94, 15 respectively) lead concentrations in surface water between two time periods, one at the beginning of the twenty year period and one at the end of the study period. There has been an overall reduction of lead concentrations in surface water in Texas of approximately 84 percent. However, this reduction cannot be statistically associated with any one regulation. Groundwater data could not be analyzed for lead concentrations because of limitations of reporting data as "less than". Approximately two percent of the groundwater data was analyzed by Oneway ANOVA and no significant difference was found between the means (18, 19 respectively) of two time periods, 1977-1979 and 1988-1990. This data is consistent with the regulations having a contributory affect on declining concentrations, but other factors cannot be ruled out as having added to these declines. This study can also serve as a starting point for a more in-depth study of environmental regulations and their impact on the environment. ^

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This cross-sectional analysis of the data from the Third National Health and Nutrition Examination Survey was conducted to determine the prevalence and determinants of asthma and wheezing among US adults, and to identify the occupations and industries at high risk of developing work-related asthma and work-related wheezing. Separate logistic models were developed for physician-diagnosed asthma (MD asthma), wheezing in the previous 12 months (wheezing), work-related asthma and work-related wheezing. Major risk factors including demographic, socioeconomic, indoor air quality, allergy, and other characteristics were analyzed. The prevalence of lifetime MD asthma was 7.7% and the prevalence of wheezing was 17.2%. Mexican-Americans exhibited the lowest prevalence of MD asthma (4.8%; 95% confidence interval (CI): 4.2, 5.4) when compared to other race-ethnic groups. The prevalence of MD asthma or wheezing did not vary by gender. Multiple logistic regression analysis showed that Mexican-Americans were less likely to develop MD asthma (adjusted odds ratio (ORa) = 0.64, 95%CI: 0.45, 0.90) and wheezing (ORa = 0.55, 95%CI: 0.44, 0.69) when compared to non-Hispanic whites. Low education level, current and past smoking status, pet ownership, lifetime diagnosis of physician-diagnosed hay fever and obesity were all significantly associated with MD asthma and wheezing. No significant effect of indoor air pollutants on asthma and wheezing was observed in this study. The prevalence of work-related asthma was 3.70% (95%CI: 2.88, 4.52) and the prevalence of work-related wheezing was 11.46% (95%CI: 9.87, 13.05). The major occupations identified at risk of developing work-related asthma and wheezing were cleaners; farm and agriculture related occupations; entertainment related occupations; protective service occupations; construction; mechanics and repairers; textile; fabricators and assemblers; other transportation and material moving occupations; freight, stock and material movers; motor vehicle operators; and equipment cleaners. The population attributable risk for work-related asthma and wheeze were 26% and 27% respectively. The major industries identified at risk of work-related asthma and wheeze include entertainment related industry; agriculture, forestry and fishing; construction; electrical machinery; repair services; and lodging places. The population attributable risk for work-related asthma was 36.5% and work-related wheezing was 28.5% for industries. Asthma remains an important public health issue in the US and in the other regions of the world. ^