Background: The misuse and addiction to opioids are one of the major health and social problem that is associated with an increase in morbidity and mortality. Both Buprenorphine (BUP) and Methadone (MET) are FDA-approved treatments for opioid dependence. This longitudinal study is to determine the effects of BUP and MET on hypertension in patients with opioid dependence using a Generalized Estimating Equation(GEE) Model. Methods: The data is from National Drug Abuse Treatment Clinical TrialsNetwork (CTN) protocol CTN-0027. This is a randomized study of 1,934 opioid dependence participants seeking treatment that followed for up to 32 weeks. A total of1,284 males and 631 females participated at the Baseline (visit1) of the study. At the endof 32 weeks (10 visits), 499 males and 243 female patients completed the study. Blood pressure of all the patients was checked at every visit beginning visit 1 to visit 10. For this analysis, the dependent variable was hypertension which was defined as having asystolic blood pressure higher than 140 mmHg and/or a diastolic blood pressure higher than 90 mmHg. These participants were randomly assigned to receive BUP (n= 740) or MET (n= 529). The GEE model with exchangeable correlation was used to determine the efficacy of both the drugs on hypertension. The analysis was performed using PROCGENMOD in SAS 9.4. Results: Time increased the odds of hypertension (adjusted odds ratio (aOR): 1.04, 95% confidence interval (CI): 1.02-1.06, pConclusion: Findings suggest that BUP had a slightly less chance of causing hypertension among patients with opioid dependence comparing with MET controlling for other risk factors, but neither one of Page 54 2017 Appalachian Student Research Forum them had any significant effect on hypertension among patients with opioid dependence. Further analysis will be essential to detect gender x treatment interaction.

Background- Bullying victimization, both physical and electronic, has been associated with health risk behaviors such as smoking and substance use; and chronic conditions such as obesity, depression and sleep disorders. The purpose of this study was to examine the association between bullying victimization and risky sexual behavior. Failure to use condom in last sexual intercourse was used as an indicator of engagement in risky sexual activities. Methods- Data from the 2015 Youth Risk Behavior Survey (YRBS), a biennial nationally representative survey of 9-12 grade students (N=15,624) were used. After cleaning and re-coding the data set, a total of 5,037 students who reported ever having sex in their lifetime were included in the analyses. The explanatory variable included in the multiple logistic regression analysis was bullying victimization. Marijuana use and feeling of sadness or hopelessness in a row for two weeks or more during past twelvemonths were included as covariates. The analyses were adjusted for age and race, and odds ratios were stratified by gender. Results- No significant association was found between being a bullying victim at school property and not using condom in last sexual intercourse for both male (OR: 1.08, 95% CI: 0.71-1.65) and female (OR: 0.98, 95% CI:0.65-1.47) students. This finding was consistent for both male (OR: 1.80, 95% CI: 0.89-3.65) and female (OR: 1.04, 95% CI: 0.70-1.55) victims of electronic bullying. Failure to use condom in last sexual intercourse was found to be associated with male students who were sad or hopeless in a row for two weeks or more during past 12 months (OR: 1.49,95% CI: 1.13-1.96). Conclusions- Failure to use condom in last sexual intercourse was not found to be significantly associated with bullying victimization. Other risky sexual behaviors such as having multiple sex partners, use of protective methods other than condom and use of drugs or alcohol before engaging into sexual relationship should be examined in further studies.

Objectives: This study examined the relation of multiple aspects of the home food environment to dietary intake and body weight among overweight and obese children in southern Appalachia. Methods: The study used baseline data from a cluster-randomized controlled trial, Parent-Led Activity and Nutrition for Healthy Living, evaluating a parent-mediated approach to treating child overweight and obesity in the primary care setting in southern Appalachia. Sixty-seven children ages 5 to 11 years were recruited from four primary care clinics. Multiple linear regression was used to estimate the relation between multiple aspects of the home food environment to dietary intake (fruit and vegetable intake, fat and sweets intake), and standardized body mass index (zBMI), adjusted for baseline family characteristics (education, smoking status during the past month, BMI) and child characteristics (sex, age, Medicaid/TennCare). Results: Findings showed greater parental restriction and pressure in feeding were associated with greater fruit and vegetable intake in children (β = 0.33, β = 0.30, respectively; both P < 0.05). The availability of chips and sweets in a child’s home and parental inappropriate modeling of eating were associated with an increased risk for consumption of fats and sweets by children (β = 0.47, β = 0.54, respectively; both P < 0.01). Parental monitoring of the child’s eating was associated with a reduced risk for fat and sweets intake (β = −0.24; P < 0.01). Finally, parental responsibility for feeding the child was associated with lower zBMI (β = −0.20; P < 0.05). Conclusions: The home food environment, including food availability and parenting behaviors, was associated with overweight and obese children’s dietary intake and weight. This study adds to evidence suggesting that programs aimed at improving overweight and obese children’s eating patterns may target both aspects of the physical home environment and parental behaviors surrounding eating.

No description available.

This research examined if there is a relationship between engagement in quality improvement (QI) and health information technology (HIT) for local health departments (LHDs) controlling for workforce, finance, population, and governance structure. This was a cross-sectional study that analyzed data obtained from the Core questions and Module 1 in the NACCHO 2010 Profile of LHDs. Descriptive statistics, bivariate analyses, and logistic regression analyses were conducted. Findings suggest that LHD engagement in QI has a relationship with utilization of HIT including electronic health records, practice management systems, and electronic syndromic surveillance systems. This study provides baseline information about the HIT use of LHDs. LHDs and their system partners (hospitals, federally qualified health centers, and primary care providers) that utilize HIT as part of their QI decision making may have an easier time of using data to support evidence-based decision making and implementing the provisions of the Patient Protection and Affordable Care Act of 2010 in order to achieve population health for all.

Objectives: The purpose of the study was to examine potential differences between two approaches to defining adolescent weight misperception. Specifically, weight status perception was compared with self-reported weight status and actual weight status (based on body mass index percentiles calculated from self-reported and actual weights and heights, respectively). Furthermore, the accuracy of assigning weight status based on body mass index percentiles calculated from self-reported weights and heights was assessed by comparing them with actual weight status. Methods: Data were extracted from Team Up for Healthy Living, an 8-week, school-based obesity prevention program in southern Appalachia. Participants (N = 1509) were predominately white (93.4%) and ninth graders (89.5%), with approximately equivalent representation of both sexes (50.7% boys). Results: The study revealed significant differences between the approaches to defining weight misperception (χ2 = 16.2; P = 0.0003). Conclusions: Researchers should interpret study findings with awareness of potential differences based on the method of calculating weight misperception.

Objectives are (1) Describe HIV/HCV prevalence in TN and Central Appalachia; (2) Understand syringe access in pharmacy settings. Identify and refer clients to local syringe service programs.

No description available.

Background: Diabetes is the seventh leading cause of death in the United States. More and more people have suffered from diabetes and its serious complications including heart disease, blindness, etc. The U.S. Department of Veterans Affairs (VA) reported that nearly 25% of veterans, enrolled in the Veterans Health Administration (VHA),have diabetes, which is much higher than the general population. Objective: This study aimed to estimate the prevalence of diabetes in the U.S. veterans using the up-to-date National Health and Nutrition Examination Survey (NHANES) data since VHA has a relatively low coverage (less than 30% of veterans each year were enrolled). Methods: Five biennial cross sectional surveys (NHANES) from 2005-2014 were used in this study. Total 2,940 veterans were included to estimate the prevalence of diabetes. Total diabetes was defined as any participant who had at least one of four conditions: (1) a hemoglobin A1c at least 6.5%, (2) fasting plasma glucose (FPG) at least 126mg/dL, (3)a 2-hour plasma glucose (PG) at least 200mg/dL, (4) diagnosed with diabetes by a doctor or other health professional. Results: The overall prevalence of total diabetes(including diagnosed and undiagnosed diabetes), undiagnosed diabetes and obesity were 20.54%, 3.37% and 40.68%, respectively. The family poverty level and education were significantly associated with the presence of diabetes with p=0.005 and 0.03,respectively. Highest prevalence diabetes and obesity existed in veterans aged 65yrs and over and 45-64yrs, respectively. The overall prevalence trend of diabetes significantly increased from 15.52% (95%CI: 12.36-18.68%) in 2005-2006 to 20.54% (95%CI:15.92-25.17%) (p=0.04 for trend test) and prevalence significantly increased in male veterans (p=0.04) and those who did not finish high school education (p=0.04) and who had college education (p=0.03). Conclusion: In 2013-2014, the estimated prevalence of diabetes was 20.54% among U.S. veterans, with higher prevalence among participants who were 65 years old or older, and had low socioeconomic status (including less education and poverty status).

No description available.