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<p><strong>Introduction: </strong>Hypertension is an important worldwide public health concern and is a concomitant risk factor for brain, kidney and cardiovascular disease, such as myocardial infarction (MI). Highly Active Antiretroviral Therapy (HAART) has greatly increased life expectancy of HIV-positive persons, but has been associated with adverse effects.</p> <p><strong>Objectives: </strong>To assess the association between antiretroviral therapy and incident hypertension; to estimate the incidence of hypertension; and to explore known and potential risk factors for hypertension among HIV-positive individuals in Tanzania and Canada.</p> <p><strong>Methods: </strong>Subjects, 18 years and older, were enrolled into two retrospective cohort studies in Tanzania and Canada. Population and descriptive characteristics were summarized. Hypertension was defined as having a SBP>140 mmHg, DBP>90 mmHg, a diagnosis of high blood pressure, or receiving antihypertensive therapy. Statistical analyses, including independent t-tests, Chi-square tests, multiple linear regression, multivariable logistic and Cox regression were performed to assess for statistical significance (p<0.05) in SPSS14.0.</p> <p><strong>Results: </strong>In Tanzania, 52 HIV-positive, normotensive subjects initiating antiretroviral therapy were enrolled. Subjects had a mean age (SD) of 39.5 (7.9) years, were predominantly Black and 53.8% were male. After one year, 4 (7.7%, 95% CI: 2.1-18.7%) developed hypertension. Blood pressure, weight and body mass index (BMI) significantly increased (p<0.05) by 12 months.</p> <p>In Canada, 486 HIV-positive and normotensive subjects were enrolled; 303 (62.3%) initiated antiretroviral therapy and 183 (37.7%) remained ARV-naive during the study. Subjects were predominantly White (>70%) and male (>75%) with a mean age (SD) of 45.1 (10.0) years. Nine-year incidence of hypertension for ARV-treated and ARV-naïve cohorts was 12.5% (95% CI: 8.8-16.2%) and 8.2% (95% CI: 4.2-12.2%) respectively. Hypertensive individuals were significantly older, heavier, and more likely to have abnormal lipids.</p> <p>In the final multivariable Cox regression model for incident hypertension, antiretroviral therapy was associated with a 125% increased risk (p=0.018), adjusted for age, sex and race. Individuals >50 compared to <40 years had an increased risk of approximately>280% (p=0.003). Current weight (10 kg increments) was associated with a 37% increased risk (p<0.001). An inverse association between CD4-T-lymphocyte count change and hypertension was observed: a positive change of >500 cell/ml compared to a decrease in CD4-T-lymphocyte count was associated with an 80% lower risk (p=0.032).</p> <p><strong> </strong></p> <p><strong>Conclusion: </strong>Hypertension is common among HIV-positive individuals in Tanzania and Canada and expected to increase over time. Hypertension is associated with antiretroviral therapy; however, further research is needed to understand this relationship.<strong> </strong></p> / Master of Science (MSc)

<p>The measurement of compliance is essential in clinical trials to assess the efficacy and side effects of treatment. Multiple methods of measuring compliance and several predictors of it are recognized. However, noncompliance has been defined using arbitrary "cutting" points on scales measuring compliance. Such cutting points should be validated against an external measurement.</p> <p>In the Study of Recent Recurrent Presumed Cerebral Emboli, multiple measurements affected by the drugs (which are meant to prevent such events) are available on multiple occasions in the same subjects. This thesis explores ways in which one can assess the extent to which these measurements agree as indices of the intake of those drugs. Furthermore, it explores how such measurements can be validated against an external measurement, the outcome desired (i.e. the control of cerebral emboli) in order to choose a valid "cutting point" to define compliance and non-compliance. Finally, it suggests methodologies to predict whether a subject will be compliant or non-compliant and to study whether compliance is a constant characteristic of certain subjects or (varies through time, being affected by time or various events in the course of therapy. Thus, this thesis proposes a methodology to obtain a valid index of compliance which will predict outcomes and a methodology to study the factors which predict such compliance.</p> / Master of Engineering (ME)

Dr. Megan Quinn, an assistant professor in the Department of Biostatistics and Epidemiology in the College of Public Health, will discuss “Raising Awareness about Cervical Cancer in Nicaragua: Working with Health Promoters to Increase Pap Smear Uptake” in the second of five “Women on Wednesdays” lectures sponsored this spring by the Women’s Studies Program. A light lunch will be provided. The lecture series promotes the research, scholarship and community engagement of women at ETSU; provides a venue where women on campus and in the community can discuss and support each other’s work; and gives students an opportunity to meet faculty who could become mentors for their studies.

Recent discussion in the epidemiologic methods and teaching literatures centers around the importance of clearly stating study goals, disentangling the goal of causation from prediction (or description), and clarifying the statistical tools that can address each goal. This discussion illuminates different ways in which mismatches can occur between study goals, methods, and interpretations, which this dissertation synthesizes into the concept of “misalignment”; misalignment occurs when the study methods and/or interpretations are inappropriate for (i.e., do not match) the study’s goal. While misalignments can occur and may cause problems, their pervasiveness and consequences have not been examined in the epidemiologic literature. Thus, the overall purpose of this dissertation was to document and examine the effects of misalignment problems seen in epidemiologic practice. First, a review was conducted to document misalignment in a random sample of epidemiologic studies and explore how the framing of study goals contributes to its occurrence. Among the reviewed articles, full alignment between study goals, methods, and interpretations was infrequently observed, although “clearly causal” studies (those that framed causal goals using causal language) were more often fully aligned (5/13, 38%) than “seemingly causal” ones (those that framed causal goals using associational language; 3/71, 4%). Next, two simulation studies were performed to examine the potential consequences of different types of misalignment problems seen in epidemiologic practice. They are based on the observation that, often, studies that are causally motivated perform analyses that appear disconnected from, or “misaligned” with, their causal goal. A primary aim of the first simulation study was to examine goal--methods misalignment in terms of inappropriate variable selection for exposure effect estimation (a causal goal). The main difference between predictive and causal models is the conceptualization and treatment of “covariates”. Therefore, exposure coefficients were compared from regression models built using different variable selection approaches that were either aligned (appropriate for causation) or misaligned (appropriate for prediction) with the causal goal of the simulated analysis. The regression models were characterized by different combinations of variable pools and inclusion criteria to select variables from the pools into the models. Overall, for valid exposure effect estimation in a causal analysis, the creation of the variable pool mattered more than the specific inclusion criteria, and the most important criterion when creating the variable pool was to exclude mediators. The second simulation study concretized the misalignment problem by examining the consequences of goal--method misalignment in the application of the structured life course approach, a statistical method for distinguishing among different causal life course models of disease (e.g., critical period, accumulation of risk). Although exchangeability must be satisfied for valid results using this approach, in its empirical applications, confounding is often ignored. These applications are misaligned because they use methods for description (crude associations) for a causal goal (identifying causal processes). Simulations were used to mimic this misaligned approach and examined its consequences. On average, when life course data was generated under a “no confounding” scenario - an unlikely real-world scenario - the structured life course approach was quite accurate in identifying the life course model that generated the data. However, in the presence of confounding, the wrong underlying life course model was often identified. Five life course confounding structures were examined; as the complexity of examined confounding scenarios increased, particularly when this confounding was strong, incorrect model selection using the structured life course approach was common. The misalignment problem is recognized but underappreciated in the epidemiologic literature. This dissertation contributes to the literature by documenting, simulating, and concretizing problems of misalignment in epidemiologic practice.

Master of Health Sciences (MSc)

<p> Small-study effects, which are factors resulting in dependencies between treatment effect size and precision, are an important source of bias in meta-analyses of randomized controlled trials. However, established nonparametric tests for detection of small-study effects that are based on rank correlation lack statistical power, while established parametric tests that are based on linear regression are not robust in the presence of between-study heterogeneity. </p><p> A novel method for detection of small-study effects is proposed that is designed to overcome these limitations. The method uses repeated one-sample Wald-Wolfowitz runs tests to evaluate the null hypothesis of serial independence among trial treatment effect size estimates that are ranked by precision. This dissertation describes lower-tailed, upper-tailed, and two-tailed versions of the proposed method for detection of small-study effects and compares the proposed method to established tests using simulation. The novel method is implemented in Stata using various procedures for control of type 1 error, including the Bonferroni and Sidak corrections, Hochberg&rsquo;s step-up procedure, and the Benjamini-Hochberg procedure for control of the false discovery rate. The type 1 error rate and power of the novel method are then compared to those of existing tests, including the nonparametric rank correlation test of Begg and Mazumdar and the commonly-used regression-based tests of Egger, Harbord, and Peters. Factors known to affect the performance of established tests, including effect size, number of trials in each meta-analysis, degree of between-study heterogeneity, and degree and type of publication bias (a specific cause of small-study effects) are simulated to reflect characteristics of meta-analyses in the biomedical literature. </p><p> The simulation demonstrated that all of the procedures evaluated for control of type 1 error in the novel method maintained an error rate below the nominal rate under all scenarios, suggesting that any of these procedures may be used to implement the novel method. In contrast, error rates for the established tests of Begg and Mazumdar, Egger, Harbord, and Peters were at or above the nominal rate under most scenarios. The lower-tailed, upper-tailed, and two-tailed novel tests showed little power in excess of the type 1 error rate under all conditions. In contrast, established tests demonstrated variable power depending on the conditions. Specifically, the power of established tests increased with an increase in effect size, an increase in the number of trials in each meta-analysis, an increase in the severity of publication bias, and publication bias that operated by effect size rather than by <i> p</i>-value. In contrast, the power of established tests decreased with an increase in heterogeneity. Overall, Egger&rsquo;s test demonstrated the highest power. Despite the low power of the novel method, selected circumstances under which it may be useful are described.</p>

Introduction Colorectal cancer is a cancer that forms in the tissues of the colon and/ or rectum and more than 95% of colorectal cancers are adenocarcinomas. It is the third most common cancer in incidence and mortality rates, accounting for 9% of all cancer cases and for 8% of all cancer related deaths (2002). The established risk factors of colorectal cancer include personal or family history of previous colorectal cancer or adenomatous polyps, chronic bowel inflammatory disease and presence of any of the hereditary syndromes. In addition, due to the fact that the majority of colorectal cancer cases (approximately 90%) occur after the age of 50, advanced age is also considered as a risk factor. Finally, evidence for significant associations between colorectal cancer and other risk factors, including diet, body weight, physical activity, smoking, alcohol intake, NSAIDs intake and HRT in post-menopausal women, is promising and increasing. Aims and objectives The main aims of this project were: 1) to investigate the associations between colorectal cancer and specific nutrients, including flavonoids, fatty acids, folate, vitamin B2, vitamin B6, vitamin B12, alcohol, vitamin D and calcium (prior hypotheses 1-4) and 2) to conduct an overall as well as forward and backward stepwise regression analyses of demographic, lifestyle and dietary risk factors. Methods The analysis of this thesis was based on a population-based case-control study of colorectal cancer (Scottish Colorectal Cancer Study; SOCCS). In total 3,417 colorectal cancer cases and 3,396 controls were recruited in the study. Dietary and lifestyle data were collected by two questionnaires (Lifestyle & Cancer and Food Frequency Questionnaire) and were available for 2,061 cases and 2,776 controls. For the analysis of the first two hypotheses (flavonoids and fatty acids) a matched dataset of 1,489 casecontrol pairs was used and conditional logistic regression models were applied, whereas for the analysis of the last two hypotheses (folate, vitamin B2, vitamin B6, vitamin B12, alcohol, vitamin D and calcium) an unmatched dataset including 2,061 cases and 2,776 v controls was used and unconditional logistic regression models were applied. For the overall and stepwise regression analyses the unmatched dataset was used (2,061 cases and 2,776 controls). Forward and backward stepwise regression was applied on three different sets of variables and the stability of the resultant models was checked in 100 bootstrap samples. Results Regarding the first two hypotheses, statistically significant odds ratios (ORs) (matched on sex, age and health board are and adjusted for family history of cancer, BMI, physical activity, smoking, and intakes of total energy, fibre, alcohol and NSAIDs) for highest versus lowest intakes (quartiles) were observed for flavonols OR (95% CI), p-value for trend: 0.78 (0.60, 0.99), 0.08) and for the individual flavonoid compounds quercetin and catechin (OR (95% CI), p-value for trend: 0.77 (0.60, 0.99), 0.04; 0.75 (0.58-0.97), 0.02; respectively); for the 3PUFAs fatty acids (OR (95% CI), p-value for trend: 0.75 (0.59, 0.97), 0.01) and for the individual fatty acids stearic acid, EPA and DHA (OR (95% CI), p-value for trend: 1.46 (1.11, 1.91), 0.01; 0.74 (0.58, 0.95), 0.02; 0.74 (0.58, 0.95), 0.02; respectively). Regarding the last two hypotheses, statistically significant odds ratios (ORs) (adjusted for age, sex, deprivation score, family history of cancer, BMI, physical activity, smoking, and intakes of total energy, fibre, alcohol and NSAIDs) for highest versus lowest intakes (quartiles) were observed for vitamin B6, vitamin B12 and alcohol (OR (95% CI), p-value for trend: 0.86 (0.72, 1.03), 0.08; 0.80 (0.67, 0.97), 0.05; 0.83 (0.68, 1.00), 0.03); and for vitamin D (OR (95% CI), p-value for trend: 0.83 (0.69, 0.99), 0.03). Regarding the second aim of the project, several risk factors were found to be significantly associated with colorectal cancer in the overall analysis including demographic and lifestyle factors (family history of cancer, NSAIDs intake, dietary energy intake, HRT intake and physical activity), food group variables (vegetables, eggs, sweets, fruit/ vegetable juice, oily fish, coffee, fruit, savoury foods and white fish) and nutrient variables (tMUFAs, 3PUFAs, SFAs, tFAs, MUFAs, quercetin, catechin, phytoestrogen, cholesterol, fibre, protein, starch, magnesium, potassium, manganese, copper, iron, zinc, phosphorus, selenium, niacin, vitamin B6, carotenes, vitamin C, vi vitamin A, potential niacin, biotin, folate, pantothenic acid, vitamin D, vitamin B1 and vitamin B12). In addition, the variables that were selected to be included in 100% of the models after applying forward and backward stepwise regression analyses were family history, NSAIDs, sweets and fruit/ vegetable juice. Finally according to the findings from the bootstrap analysis, the variables that were selected to be included in models for the majority of the bootstrap samples (more than 90%) were family history, NSAIDs, dietary energy, eggs, sweets, fruit/ vegetable juice and white fish. Discussion The particular dietary factors that were found to be inversely associated with colorectal cancer after applying several multivariable logistic regression models were: flavonols, quercetin, catechin, 3PUFAs, EPA, DHA, vitamin B6, vitamin B12 and vitamin D. In addition, high intakes of stearic acid were found to be positively associated with colorectal cancer. In contrast, high intakes of dietary and total folate were associated with a decreased colorectal cancer risk in the energy-adjusted model, but this inverse association was attenuated after further adjustment for several confounding factors including fibre. Regarding alcohol intake, when it was divided into quartiles, high alcohol consumption was associated with a statistically significant and dose-dependent decreased colorectal cancer risk. However, when alcohol intake was divided in categories an increased colorectal cancer risk for intakes of higher than 60 g/day was observed. Intakes of 3PUFAs, vitamin D and vitamin B12 were highly correlated due to having the same food source (oily fish) and therefore it is difficult to draw specific conclusions regarding which nutrient is truly associated with colorectal cancer and which not. Finally, it was observed that for calcium intakes to be inversely associated with colorectal cancer, a dosage of 1500mg/day or higher was necessary. The majority of these results are in accordance with results of previous epidemiological and laboratory studies; however their confirmation in further large-scale studies is required. Results from the overall and stepwise regression analysis supported previous findings of an increased colorectal cancer risk due to a high or moderate family history risk. In addition, high intakes of dietary energy were found to be positively associated with increased colorectal cancer risk in the overall analysis and in addition dietary energy was vii selected to be included in the majority of the stepwise regression models. On the other hand, regular intake of NSAIDs was found to be inversely associated with colorectal cancer risk in the overall analysis and in the majority of the stepwise regression models. Finally, the overall and stepwise regression analyses generated a few new hypotheses suggesting that low intakes of fruit/ vegetable juice, eggs, white fish and sweets (a combined variable of high-fat and high-sugar foods) and high intakes of coffee and magnesium were associated with a decreased colorectal cancer. These findings, though interesting and important for generation of new hypotheses, need further investigation (as prior hypotheses) in large-scale observational studies.

<p> Raccoon rabies in the Northeastern United States rapidly expanded in genetic diversity and spatially from 1977 to 1999 during the Mid-Atlantic outbreak. For a portion this expansion, from 1983 to 1986, the rate of epidemic expansion slowed. This is reflected in a plateau in the effective number of infections and a decrease in the rate of invasion into new areas. I used a mathematical model of rabies dynamics to test alternative hypotheses for the observed reduction in the spread of raccoon rabies. It has been theorized that the geography of the Mid-Atlantic States, particularly the rivers and terrestrial habitat, influenced these changes. I will test ten hypotheses for the slowdown using a spatially explicit model of raccoon rabies dynamics that includes a model of the pathogen&rsquo;s molecular evolution. </p><p> The ten hypotheses were to test if the reduction in rate of spread was caused by 1) a geographic bottleneck created by the Atlantic coast, 2) rivers limiting the movement of raccoons, 3) rivers halting the movement of raccoons, 4) habitat limiting the movement of raccoons 5) a combination of rivers limiting movement, habitat and mountains, 6) a combination of rivers halting movement, habitat and mountains, 7) the Susquehanna River limiting movement, 8) the Susquehanna River halting movement, 9) an unidentified barrier limiting movement and 10) an unidentified barrier halting movement. </p><p> Our model results suggest that the slowdown observed from 1983 to 1987 was caused by a combination of major rivers in the area. The effects of rivers appear to explain the slowdown in the epidemic, but the addition of habitat and mountains is important to explain the sustained high levels of demographic spread in the late stages of the epidemic. In addition, our results indicate that the currently accepted estimate of raccoon dispersal over rivers may be an overestimate.</p>