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em DigitalCommons@The Texas Medical Center


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Education is related to health. In cross-sectional data, education level has been associated with physical functioning. Also, lower levels of education have been associated with health behaviors including smoking, alcohol use, and greater body weight. In school, students may benefit from greater exposed to health-related messages, while students who have dropped out may be more susceptible to influences regarding negative health behaviors such as smoking. ^ Improved school retention might improve long-term health outcomes. However, there is limited evidence regarding modifiable factors that predict likelihood of dropping out. Two likely psychosocial measures are locus of control and parent-child academic conversations. In the current study, data from two waves of a population-based longitudinal survey, the National Education Longitudinal Survey, were utilized to evaluate whether these two psychosocial measures could predict likelihood of dropping out, for students (n = 16,749) in tenth grade at 1990, with dropout status determined at 1992, while controlling for recognized sociodemographic predictors including parental income, parental education level, race/ethnicity, and sex. Locus of control was measured with the Pearlin Mastery Scale, and parent-child academic conversations were measured by three questions concerning course selection at school, school activities and events, and things the student studied in class. ^ In a logistic regression model, with the sociodemographic control measures entered in a first step before entry of the psychosocial measures in a second step, this study determined that lower levels of locus of control were associated with greater likelihood of dropping out after two years (odds ratio (OR) = 1.11, 95% confidence interval (CI) 108 to 1.15, p < .001), and two of the three parent-child academic discussion items were associated with greater likelihood of dropping out after two years (OR = 1.69, CI 1.48-1.93, p < .001; OR = 1.22, CI 1.05-1.41, p = .01; OR = 1.01, CI .88-1.15, p = .94). ^ It is possible that interventions aimed at improving locus of control, and aimed at building parent-child academic conversations, could lower the likelihood of students dropping out, and this in turn could yield improved heath behaviors and health status in the child's future. ^

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Based on asthma prevalence data collected from the 2000 BRFSS survey, approximately 14.7 million U.S. adults had current asthma, accounting for 7.2% of the total U.S. population. In Texas alone, state data extrapolated from the 1999-2003 Texas BRFSS suggested that approximately 1 million Texas adults were reporting current asthma and approximately 11% of the adult population has been diagnosed with the illness during their lifetime. From a public health perspective, the disease is manageable. Comprehensive state-specific asthma surveillance data are necessary to identify disparities in asthma prevalence and asthma-control characteristics among subpopulations and to develop targeted public health interventions. The purpose of this study was to determine the relative importance of various risk factors of asthma and to examine the impact of asthma on health-related quality of life among adult residents of Texas. ^ The study employed a cross-sectional study of respondents in Texas. The study extracted all the variables related to asthma along with their associated demographic, socioeconomic, and quality of life variables from the 2007 BRFSS data for 17,248 adult residents of Texas aged 18 and older. Chi-square test and logistic regression using SPSS were used in various data analyses on weighted data, adjusting for the complex sample design of the BRFSS data. All chi-square analyses were carried out using SPSS's CSTABULATE command. In addition, logistic regression models were fitted using SPSS's CSLOGISTIC command. ^ Risks factors significantly associated with reporting current asthma included BMI, race/ethnicity, gender, and income. Holding all other variables constant, obese adults were almost twice as likely to report current asthma as those adults who were normal weight (odds ratio [OR], 1.78; 95% confidence interval [CI], 1.25 to 2.53). Other non-Hispanic adults were significantly more likely to report current asthma than non-Hispanic Whites (OR, 2.43; 95% CI, 1.38 to 4.25), while Hispanics were significantly less likely to report current asthma than non-Hispanic Whites (OR, 0.38; 95% CI, 0.25 to 0.60), after controlling for all other variables. After adjusting for all other variables, adult females were almost twice as likely to report current asthma as males (OR, 1.97; 95% CI, 1.49 to 2.60). Adults with household income of less than $15,000 were almost twice as likely to report current asthma as those persons with an annual household income of $50,000 or more (OR, 1.98; 95% CI, 1.33 to 2.94). In regards to the association between asthma and health-related quality of life, after adjusting for age, race/ethnicity, gender, tobacco use, body mass index (BMI), exercise, education, and income, adults with current asthma compared to those without asthma were more likely to report having more than 15 days of unhealthy physical health (OR, 1.84; 95% CI, 1.29 to 2.60). ^ Overall, the findings of this study provide insight and valuable information into the populations in Texas most adversely affected by asthma and health-related consequences of the disease condition. Further research could build on the findings of this study by replicating this study as closely as possible in other asthma settings, and look at the relationship for hospitalization rates, asthma severity, and mortality.^

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The purpose of this study was to exam the relationship between internet use and depression among a population of individuals who have sustained spinal cord injury. This was cross-sectional survey design conducted among spinal cord injury (SCI) patients in the Model Spinal Cord Injury System. We included a total of 1,011 SCI-patients who were interviewed face-to-face or by telephone interview over approximately a three year time period (2004–2006). All data were collected through a telephone survey which included the Patient Health Questionnaire-9 (PHQ-9) to assess depression. We examined various scales of this survey, included a reduced 3-item scale (items 1, 2 and 6) to avoid the presence of somatic symptoms among SCI patients from influencing classification of depression. The frequency of internet usage was grouped as daily/weekly/monthly/non user. Covariates examined as possible confounders included demographic characteristics, occupational status, educational level, injury type, daily function of living, pain level, self-perceived health status and satisfaction with life. We observed a negative association between the frequency of internet use and the level of depression. Daily use of internet was associated with lower PHQ-9 score and depression; however this association did not reach statistical significance after for the mentioned covariates. In conclusion, the factors related to lower depression in SCI patients who use the internet are complicated. Daily internet usage was associated with lower levels of depression. The accuracy of 3-item scale needs further validation and investigation. Further study of internet usage pattern in SCI patient is recommended. ^

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The purpose of this study was to assess the accuracy and precision of airborne volatile organic compound (VOC) concentrations measured using passive air samplers (3M 3500 organic vapor monitors) over extended sampling durations (9 and 15 days). A total of forty-five organic vapor monitor samples were collected at a State of Texas air monitoring site during two different sampling periods (July/August and November 2008). The results of this study indicate that for most of the tested compounds, there was no significant difference between long-term (9 or 15 days) sample concentrations and the means of parallel consecutive short-term (3 days) sample concentrations. Biases of 9 or 15-day measurements vs. consecutive 3-day measurements showed considerable variability. Those compounds that had percent bias values of <10% are suggested as acceptable for long-term sampling (9 and 15 days). Of the twenty-one compounds examined, 10 compounds are classified as acceptable for long-term sampling; these include m,p-xylene, 1,2,4-trimethylbenzene, n-hexane, ethylbenzene, benzene, toluene, o-xylene, d-limonene, dimethylpentane and methyl tertbutyl ether. The ratio of sampling procedure variability relative to variability within days was approximately 1.89 for both sampling periods for the 3-day vs. 9-day comparisons and approximately 2.19 for both sampling periods for the 3-day vs. 15-day comparisons. Considerably higher concentrations of most VOCs were measured during the November sampling period compared to the July/August period. These differences may be a result of varying meteorological conditions during these two time periods, e.g., the differences in wind direction, and wind speed. Further studies are suggested to further evaluate the accuracy and precision of 3M 3500 organic vapor monitors over extended sampling durations. ^

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Background. EAP programs for airline pilots in companies with a well developed recovery management program are known to reduce pilot absenteeism following treatment. Given the costs and safety consequences to society, it is important to identify pilots who may be experiencing an AOD disorder to get them into treatment. ^ Hypotheses. This study investigated the predictive power of workplace absenteeism in identifying alcohol or drug disorders (AOD). The first hypothesis was that higher absenteeism in a 12-month period is associated with higher risk that an employee is experiencing AOD. The second hypothesis was that AOD treatment would reduce subsequent absence rates and the costs of replacing pilots on missed flights. ^ Methods. A case control design using eight years (time period) of monthly archival absence data (53,000 pay records) was conducted with a sample of (N = 76) employees having an AOD diagnosis (cases) matched 1:4 with (N = 304) non-diagnosed employees (controls) of the same profession and company (male commercial airline pilots). Cases and controls were matched on the variables age, rank and date of hire. Absence rate was defined as sick time hours used over the sum of the minimum guarantee pay hours annualized using the months the pilot worked for the year. Conditional logistic regression was used to determine if absence predicts employees experiencing an AOD disorder, starting 3 years prior to the cases receiving the AOD diagnosis. A repeated measures ANOVA, t tests and rate ratios (with 95% confidence intervals) were conducted to determine differences between cases and controls in absence usage for 3 years pre and 5 years post treatment. Mean replacement costs were calculated for sick leave usage 3 years pre and 5 years post treatment to estimate the cost of sick leave from the perspective of the company. ^ Results. Sick leave, as measured by absence rate, predicted the risk of being diagnosed with an AOD disorder (OR 1.10, 95% CI = 1.06, 1.15) during the 12 months prior to receiving the diagnosis. Mean absence rates for diagnosed employees increased over the three years before treatment, particularly in the year before treatment, whereas the controls’ did not (three years, x = 6.80 vs. 5.52; two years, x = 7.81 vs. 6.30, and one year, x = 11.00cases vs. 5.51controls. In the first year post treatment compared to the year prior to treatment, rate ratios indicated a significant (60%) post treatment reduction in absence rates (OR = 0.40, CI = 0.28, 0.57). Absence rates for cases remained lower than controls for the first three years after completion of treatment. Upon discharge from the FAA and company’s three year AOD monitoring program, case’s absence rates increased slightly during the fourth year (controls, x = 0.09, SD = 0.14, cases, x = 0.12, SD = 0.21). However, the following year, their mean absence rates were again below those of the controls (controls, x = 0.08, SD = 0.12, cases, x¯ = 0.06, SD = 0.07). Significant reductions in costs associated with replacing pilots calling in sick, were found to be 60% less, between the year of diagnosis for the cases and the first year after returning to work. A reduction in replacement costs continued over the next two years for the treated employees. ^ Conclusions. This research demonstrates the potential for workplace absences as an active organizational surveillance mechanism to assist managers and supervisors in identifying employees who may be experiencing or at risk of experiencing an alcohol/drug disorder. Currently, many workplaces use only performance problems and ignore the employee’s absence record. A referral to an EAP or alcohol/drug evaluation based on the employee’s absence/sick leave record as incorporated into company policy can provide another useful indicator that may also carry less stigma, thus reducing barriers to seeking help. This research also confirms two conclusions heretofore based only on cross-sectional studies: (1) higher absence rates are associated with employees experiencing an AOD disorder; (2) treatment is associated with lower costs for replacing absent pilots. Due to the uniqueness of the employee population studied (commercial airline pilots) and the organizational documentation of absence, the generalizability of this study to other professions and occupations should be considered limited. ^ Transition to Practice. The odds ratios for the relationship between absence rates and an AOD diagnosis are precise; the OR for year of diagnosis indicates the likelihood of being diagnosed increases 10% for every hour change in sick leave taken. In practice, however, a pilot uses approximately 20 hours of sick leave for one trip, because the replacement will have to be paid the guaranteed minimum of 20 hour. Thus, the rate based on hourly changes is precise but not practical. ^ To provide the organization with practical recommendations the yearly mean absence rates were used. A pilot flies on average, 90 hours a month, 1080 annually. Cases used almost twice the mean rate of sick time the year prior to diagnosis (T-1) compared to controls (cases, x = .11, controls, x = .06). Cases are expected to use on average 119 hours annually (total annual hours*mean annual absence rate), while controls will use 60 hours. The cases’ 60 hours could translate to 3 trips of 20 hours each. Management could use a standard of 80 hours or more of sick time claimed in a year as the threshold for unacceptable absence, a 25% increase over the controls (a cost to the company of approximately of $4000). At the 80-hour mark, the Chief Pilot would be able to call the pilot in for a routine check as to the nature of the pilot’s excessive absence. This management action would be based on a company standard, rather than a behavioral or performance issue. Using absence data in this fashion would make it an active surveillance mechanism. ^

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Background. Injection drug users (IDUs) are at increased risk for HIV transmission due to unique risk behaviors, such as sharing needles. In Houston, IDUs account for 18% of all HIV/AIDS cases among Black males. ^ Objectives. This analysis compared demographic, behavioral, and psychosocial characteristics of needle sharing and non-sharing IDUs in a population of Black males in Harris County, Texas. ^ Methods. Data used for this analysis were from the second IDU cycle of the National HIV Behavioral Surveillance System. This dataset included a sample of 288 Black male IDUs. Univariate and multivariate statistical analysis were performed to determine statistically significant associations of needle sharing in this population and to create a functional model to inform local HIV prevention programs. ^ Results. Half of the participants in this analysis shared needles in the past 12 months. Compared to non-sharers, sharers were more likely to be homeless (OR=3.70, p<0.01) or arrested in the past year (OR=2.31, p<0.01), inject cocaine (OR=2.07, p<0.01), report male-to-male sex in the past year (OR=6.97, p<0.01), and to exchange sex for money or drugs. Sharers were less likely than non-sharers to graduate high school (OR=0.36, p<0.01), earn $5,000 or more a year (OR=1.15, p=0.05), get needles from a medical source (OR=0.59, p=0.03), and ever test for HIV (OR=0.17, p<0.01). Sharers were more likely to report depressive symptoms (OR=3.49, p<0.01), lower scores on the family support scale (mean difference 0.41, p=0.01) and decision-making confidence scale (mean difference 0.38, p<0.01), and greater risk-taking (mean difference -0.49, p<0.01) than non-sharers. In a multivariable logistic regression, sharers were less likely to have graduated high school (OR=0.33, p<0.01) and have been tested for HIV (OR=0.12, p<0.01) and were more likely to have been arrested in the past year (OR=2.3, p<0.01), get needles from a street source (OR=3.87, p<0.01), report male-to-male sex (OR=7.01, p<0.01), and have depressive symptoms (OR=2.36, p=0.02) and increased risk-taking (OR=1.78, p=0.01). ^ Conclusions. IDUs that shared needles are different from those that did not, reporting lower socioeconomic status, increased sexual and risk behaviors, increased depressive symptoms and increased risk-taking. These findings suggest that intervention programs that also address these demographic, behavioral, and psychosocial factors may be more successful in decreasing needle sharing among this population.^

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Background. Consistent adherence to antiretroviral treatment is necessary for a treatment success. Improving and maintaining adherence rate >95% are challenging for health care professionals. This pilot randomized controlled study aimed to evaluate the impact of the interactive intervention on adherence to GPO-VIR, to describe the feasibility of the interactive intervention in Thailand, and to illustrate the adherence self-efficacy concept among HIV treatment-naïve patients in Thailand who were starting antiretroviral treatment. ^ Methods. The study took place at three HIV clinics located in Phayao, Thailand. Twenty-three patients were randomly assigned into the experimental (n=11) and the control groups (n=12). Each participant in the experimental group and a significant person to the patient received 5 educational sessions with a nurse at the clinics and at their homes. They also received 3 follow-up evaluations during the 6-month period of the study. The participants in the control group received the standard of care provided by HIV clinical personnel plus three follow-up evaluations at the clinic. ^ Results. Seventeen patients (7 in the experimental and 10 in the control group) completed the study. The 4-day recall on the Thai ACTG Adherence Scale demonstrated adherence rate >95% for most participants from both groups. After the first measurement, no experimental group patients reporting missing ART, while one control group participant continuously skipped ART. Participants from both groups had significantly increased CD4 cell counts after the study (F(1, 15) = 29.30, p = .000), but no differences were found between two groups (F(1, 15) = .001, p = .98). Examination of the intervention showed limitations and possibilities to implement it in Thailand. Qualitative data demonstrated self-efficacy expectations, resignation and acceptance as related concepts to improve adherence outcomes. ^ Conclusions. This interactive intervention, after appropriate modifications, is feasible to apply for Thai HIV-treatment naïve patients. Because of limitations the study could not demonstrate whether the interactive intervention improved adherence to ART among HIV-treatment naïve in Thailand. A longitudinal study in a larger sample would be required to test the impact of the intervention. ^ Keyword: antiretroviral treatment, adherence, treatment-naïve, Thailand, randomized controlled study ^