Effects of air pollution on asthma hospitalization rates in different age groups in metropolitan cities of Korea

Many studies have shown relationships between air pollution and the rate of hospital admissions for asthma. A few studies have controlled for age-specific effects by adding separate smoothing functions for each age group. However, it has not yet been reported whether air pollution effects are significantly different for different age groups. This lack of information is the motivation for this study, which tests the hypothesis that air pollution effects on asthmatic hospital admissions are significantly different by age groups. Each air pollutant's effect on asthmatic hospital admissions by age groups was estimated separately. In this study, daily time-series data for hospital admission rates from seven cities in Korea from June 1999 through 2003 were analyzed. The outcome variable, daily hospital admission rates for asthma, was related to five air pollutants which were used as the independent variables, namely particulate matter <10 micrometers (μm) in aerodynamic diameter (PM10), carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), and sulfur dioxide (SO2). Meteorological variables were considered as confounders. Admission data were divided into three age groups: children (<15 years of age), adults (ages 15-64), and elderly (≥ 65 years of age). The adult age group was considered to be the reference group for each city. In order to estimate age-specific air pollution effects, the analysis was separated into two stages. In the first stage, Generalized Additive Models (GAMs) with cubic spline for smoothing were applied to estimate the age-city-specific air pollution effects on asthmatic hospital admission rates by city and age group. In the second stage, the Bayesian Hierarchical Model with non-informative prior which has large variance was used to combine city-specific effects by age groups. The hypothesis test showed that the effects of PM10, CO and NO2 were significantly different by age groups. Assuming that the air pollution effect for adults is zero as a reference, age-specific air pollution effects were: -0.00154 (95% confidence interval(CI)= (-0.0030,-0.0001)) for children and 0.00126 (95% CI = (0.0006, 0.0019)) for the elderly for PM 10; -0.0195 (95% CI = (-0.0386,-0.0004)) for children for CO; and 0.00494 (95% CI = (0.0028, 0.0071)) for the elderly for NO2. Relative rates (RRs) were 1.008 (95% CI = (1.000-1.017)) in adults and 1.021 (95% CI = (1.012-1.030)) in the elderly for every 10 μg/m3 increase of PM10 , 1.019 (95% CI = (1.005-1.033)) in adults and 1.022 (95% CI = (1.012-1.033)) in the elderly for every 0.1 part per million (ppm) increase of CO; 1.006 (95%CI = (1.002-1.009)) and 1.019 (95%CI = (1.007-1.032)) in the elderly for every 1 part per billion (ppb) increase of NO2 and SO2, respectively. Asthma hospital admissions were significantly increased for PM10 and CO in adults, and for PM10, CO, NO2 and SO2 in the elderly.^

Predictors of HIV testing among injection drug users

The current analysis examined the association of several demographic and behavioral variables with prior HIV testing within a population of injection drug users (IDUs) living in Harris County, Texas in 2005 (n=563). After completing the initial univariate analyses of all potential predictors, a multivariable model was created. This model was designed to guide future intervention efforts. Data used in this analysis were collected by the University of Texas School of Public Health in association with the Houston Department of Health and Human Services for the first IDU cycle of the National HIV Behavioral Surveillance System. About 76% of the IDUs reported previously being tested for HIV. Demographic variables that displayed a significant association with prior testing during the univariate analyses include age, race/ethnicity, birth outside the United States, education level, recent arrest, and current health insurance coverage. Several drug-related and sexual behaviors also demonstrated significant associations with prior testing, including age of first injection drug use, heroin use, methamphetamine use, source of needles or syringes, consistent use of new needles, recent visits to a shooting gallery or similar location, previous alcohol or drug treatment, condom use during their most recent sexual encounter, and having sexual partners who also used injection drugs. Additionally, the univariate analyses revealed that recent use of health or HIV prevention services was associated with previously testing for HIV. The final multivariable model included age, race/ethnicity, recent arrest, previous alcohol or drug treatment, and heroin use. ^

Outcomes of tuberculosis positive non-injection drug users in Harris County from October 1995 through September 2004

Background. The population-based Houston Tuberculosis Initiative (HTI) study has enrolled and gathered demographic, social, behavioral, and disease related data on more than 80% of all reported Mycobacterium Tuberculosis (MTB) cases and 90% of all culture positive patients in Houston/Harris County over a 9 year period (from October 1995-September 2004). During this time period 33% (n=1210) of HTI MTB cases have reported a history of drug use. Of those MTB cases reporting a history of drug use, a majority of them (73.6%), are non-injection drug users (NIDUs). ^ Other than HIV, drug use is the single most important risk factor for progression from latent to infectious tuberculosis (TB). In addition, drug use is associated with increased transmission of active TB, as seen by the increased number of clonally related strains or clusters (see definition on page 30) found in this population. The deregulatory effects of drug use on immune function are well documented. Associations between drug use and increased morbidity have been reported since the late 1970's. However, limited research focused on the immunological consequence of non-injection drug use and its relation to tuberculosis infection among TB patients is available. ^ Methods. TB transmission patterns, symptoms, and prevalence of co-morbidities were a focus of this project. Smoking is known to suppress Nitric Oxide (NO) production and interfere with immune function. In order to limit any possible confounding due to smoking two separate analyses were done. Non-injection drug user smokers (NIDU-S) were compared to non-drug user smokers (NDU-S) and non-injection drug user non-smokers (NIDU-NS) were compared to non-drug user non-smokers (NDU-NS) individually. Specifically proportions, chi-square p-values, and (where appropriate) odds ratios with 95% confidence intervals were calculated to assess characteristics and potential associations of co-morbidities and symptoms of TB among NIDUs HTI TB cases. ^ Results. Significant differences in demographic characteristics and risk factors were found. In addition drug users were found to have a decreased risk for cancer, diabetes mellitus, and chronic pulmonary disease. They were at increased risk of having HIV/AIDS diagnosis, liver disease, and trauma related morbidities. Drug users were more likely to have pulmonary TB disease, and a significantly increased amount of clonally related strains of TB or "clusters" were seen in both smokers and non-smoker drug users when compared to their non-drug user counterparts. Drug users are more likely to belong to print groups (clonally related TB strains with matching spoligotypes) including print one and print three and the Beijing family group, s1. Drug users were found to be no more likely to experience drug resistance to TB therapy and were likely to be cured of disease upon completion of therapy. ^ Conclusion. Drug users demographic and behavioral risk factors put them at an increased risk contracting and spreading TB disease throughout the community. Their increased levels of clustering are evidence of recent transmission and the significance of certain print groups among this population indicate the transmission is from within the social family. For these reasons a focus on this "at risk population" is critical to the success of future public health interventions. Successful completion of directly observed therapy (DOT), the tracking of TB outbreaks and incidence through molecular characterization, and increased diagnostic strategies have led to the stabilization of TB incidence in Houston, Harris County over the past 9 years and proven that the Houston Tuberculosis Initiative has played a critical role in the control and prevention of TB transmission. ^

AN INVESTIGATION OF VOLATILE ORGANIC AIR CONTAMINANTS IN THE INDOOR MANUFACTURED HOUSING ENVIRONMENT (TEXAS)

Manufactured housing has been found to have substantial levels of formaldehyde in the indoor air. Because mobile homes are more affordable than conventional housing, there has been a large increase in their use in the U.S. This increase in mobile home use has been substantial in the sunbelt regions such as Texas, where high temperatures and humidities may enhance out-gassing of formaldehyde and other volatile organic compounds from construction and furnishing materials and increase any potential health hazards.^ The influences of environmental, architectural and temporal factors on the presence of indoor formaldehyde and other organic compounds were investigated in conjunction with the Texas Indoor Air Quality Study of manufactured housing. A matched pair of mobile homes, one with electric heating and cooking utilities and the other with propane gas utilities, were used for a series of controlled experiments over a fourteen month period from October, 1982 through November, 1983.^ Over this fourteen month period formaldehyde levels decreased approximately 33%. Daily fluctuations of 20% to 40% were observed even with a constant indoor temperature. An increase in indoor temperature of 8(DEGREES)C doubled the measured formaldehyde concentration. Opening windows resulted in decreases of indoor formaldehyde levels of up to 50%. Studies of the impact of propane as a cooking source showed no increase in formaldehyde levels with stove use.^ The presence and concentration of selected volatile organic compounds is influenced greatest by occupancy. Occupants continually open and close windows and doors, vary the operation and settings (temperature) of air control systems, and vary in their selection of furnishings and use of consumer products, which may act as sources of indoor air contaminants. ^