Sexual Behavior Patterns and Condom Use in Newly Sexually Active Female University Students

Thesis (Master's)--University of Washington, 2016-06

Power, privilege and HIV prevalence: examination of sexual HIV-risk factors in MSM and transgender women who engage in transactional sex

Thesis (Master's)--University of Washington, 2016-06

Multi-level zero-inflated Poisson regression modelling of correlated count data with excess zeros

Count data with excess zeros relative to a Poisson distribution are common in many biomedical applications. A popular approach to the analysis of such data is to use a zero-inflated Poisson (ZIP) regression model. Often, because of the hierarchical Study design or the data collection procedure, zero-inflation and lack of independence may occur simultaneously, which tender the standard ZIP model inadequate. To account for the preponderance of zero counts and the inherent correlation of observations, a class of multi-level ZIP regression model with random effects is presented. Model fitting is facilitated using an expectation-maximization algorithm, whereas variance components are estimated via residual maximum likelihood estimating equations. A score test for zero-inflation is also presented. The multi-level ZIP model is then generalized to cope with a more complex correlation structure. Application to the analysis of correlated count data from a longitudinal infant feeding study illustrates the usefulness of the approach.

Are lipid ratios less susceptible to change with systemic inflammation than individual lipid components in patients with rheumatoid arthritis?

Rheumatoid arthritis (RA) associates with excess cardiovascular risk and there is a need to assess that risk. However, individual lipid levels may be influenced by disease activity and drug use, whereas lipid ratios may be more robust. A cross-sectional cohort of 400 consecutive patients was used to establish factors that influenced individual lipid levels and lipid ratios in RA, using multiple regression models. A further longitudinal cohort of 550 patients with RA was used to confirm these findings, using generalized estimating equations. Cross-sectionally, higher C-reactive protein (CRP) levels correlated with lower levels of total cholesterol (TC), low-density lipoprotein-cholesterol (LDL-C), and high-density lipoprotein-cholesterol ([HDL-C] P = .015), whereas lipid ratios did not correlate with CRP. The findings were broadly replicated in the longitudinal data. In summary, the effects of inflammation on individual lipid levels may underestimate lipid-associated cardiovascular disease (CVD) risk in RA, thus lipid ratios may be more appropriate for CVD risk stratification in RA.

Influence of birth cohort on age of onset cluster analysis in bipolar I disorder

PURPOSE: Two common approaches to identify subgroups of patients with bipolar disorder are clustering methodology (mixture analysis) based on the age of onset, and a birth cohort analysis. This study investigates if a birth cohort effect will influence the results of clustering on the age of onset, using a large, international database. METHODS: The database includes 4037 patients with a diagnosis of bipolar I disorder, previously collected at 36 collection sites in 23 countries. Generalized estimating equations (GEE) were used to adjust the data for country median age, and in some models, birth cohort. Model-based clustering (mixture analysis) was then performed on the age of onset data using the residuals. Clinical variables in subgroups were compared. RESULTS: There was a strong birth cohort effect. Without adjusting for the birth cohort, three subgroups were found by clustering. After adjusting for the birth cohort or when considering only those born after 1959, two subgroups were found. With results of either two or three subgroups, the youngest subgroup was more likely to have a family history of mood disorders and a first episode with depressed polarity. However, without adjusting for birth cohort (three subgroups), family history and polarity of the first episode could not be distinguished between the middle and oldest subgroups. CONCLUSION: These results using international data confirm prior findings using single country data, that there are subgroups of bipolar I disorder based on the age of onset, and that there is a birth cohort effect. Including the birth cohort adjustment altered the number and characteristics of subgroups detected when clustering by age of onset. Further investigation is needed to determine if combining both approaches will identify subgroups that are more useful for research.

Nursing Activities Score: avaliação da carga de trabalho de enfermagem em unidade de terapia intensiva adulto

The sizing of nursing human resources is an essential management tool to meet the needs of the patients and the institution. Regarding to the Intensive Care Unit, where the most critical patients are treated and the most advanced life-support equipments are used, requiring a high number of skilled workers, the use of specific indicators to measure the workload of the team becomes necessary. The Nursing Activities Score is a validated instrument for measuring nursing workload in the Intensive Care Unit that has demonstrated effectiveness. It is a cross-sectional study with the primary objective of assessing the workload of nursing staff in an adult Intensive Care Unit through the application of the Nursing Activities Score. The study was conducted in a private hospital specialized in the treatment of patients with cancer, which is located in the city of Natal (Rio Grande do Norte – Brazil). The study was approved by the Research Ethics Committee of the hospital (Protocol number 558.799; CAAE 24966013.7.0000.5293). For data collection, a form of sociodemographic characteristics of the patients was used; the Nursing Activities Score was used to identify the workload of nursing staff; and the instrument of Perroca, which classifies patients and provides data related to the their need for nursing care, was also used. The collected data were analyzed using a statistical package. The categorical variables were described by absolute and relative frequency, while the number by median and interquartile range. Considering the inferential approach, the Spearman test, the Wald chi-square, Kruskal Wallis and Mann-Whitney test were used. The statistically significant variables were those with p values <0.05. The evaluation of the overall averages of NAS, considering the first 15 days of hospitalization, was performed by the analysis of Generalized Estimating Equations (GEE), with adjust for the variable length of hospitalization. The sample consisted of 40 patients, in the period of June to August 2014. The results showed a mean age of 62,1 years (±23,4) with a female predominance (57,5%). The most frequent type of treatment was clinical (60,0%), observing an average stay of 6,9 days (±6,5). Considering the origin, most patients (35%) came from the Surgical Center. There was a mortality rate of 27,5%. 277 measures of NAS score and Perroca were performed, and the averages of 69,8% (±24,1) and 22,7% (±4.2) were obtained, respectively. There was an association between clinical outcome and value of the Nursing Activities Score in 24 hours (p <0.001), and between the degree of dependency of patients and nursing workload (rp 0,653, p<0,001). The achieved workload of the nursing staff, in the analyzed period, was presented high, showing that hospitalized patients required a high demand for care. These findings create subsidies for sizing of staff and allocation of human resources in the sector, in order to achieve greater safety and patient satisfaction as a result of intensive care, as well as an environment conducive to quality of life for the professionals

Três alternativas estocásticas para modelar morbimortalidade por doenças respiratórias e cardiovasculares via variáveis atmosféricas

Climate and air pollution, among others, are responsible factors for increase of health vulnerability of the populations that live in urban centers. Climate changes combined with high concentrations of atmospheric pollutants are usually associated with respiratory and cardiovascular diseases. In this sense, the main objective of this research is to model in different ways the climate and health relation, specifically for the children and elderly population which live in São Paulo. Therefore, data of meteorological variables, air pollutants, hospitalizations and deaths from respiratory and cardiovascular diseases a in 11-year period (2000-2010) were used. By using modeling via generalized estimating equations, the relative risk was obtained. By dynamic regression, it was possible to predict the number of deaths through the atmospheric variables and the betabinomial-poisson model was able to estimate the number of deaths and simulate scenarios. The results showed that the risk of hospitalizations due to asthma increases approximately twice for children exposed to high concentrations of particulate matter than children who are not exposed. The risk of death by acute myocardial infarction in elderly increase in 3%, 6%, 4% and 9% due to high concentrations CO, SO2, O3 and PM10, respectively. Regarding the dynamic regression modeling, the results showed that deaths by respiratory diseases can be predicted consistently. The beta-binomial-poisson model was able to reproduce an average number of deaths by heart insufficiency. In the region of Santo Amaro the observed number was 2.462 and the simulated was 2.508, in the Sé region 4.308 were observed and 4.426 simulated, which allowed for the generation of scenarios that may be used as a parameter for decision. Making with these results, it is possible to contribute for methodologies that can improve the understanding of the relation between climate and health and proved support to managers in environmental planning and public health policies.

Empirical likelihood based longitudinal studies

In longitudinal data analysis, our primary interest is in the regression parameters for the marginal expectations of the longitudinal responses; the longitudinal correlation parameters are of secondary interest. The joint likelihood function for longitudinal data is challenging, particularly for correlated discrete outcome data. Marginal modeling approaches such as generalized estimating equations (GEEs) have received much attention in the context of longitudinal regression. These methods are based on the estimates of the first two moments of the data and the working correlation structure. The confidence regions and hypothesis tests are based on the asymptotic normality. The methods are sensitive to misspecification of the variance function and the working correlation structure. Because of such misspecifications, the estimates can be inefficient and inconsistent, and inference may give incorrect results. To overcome this problem, we propose an empirical likelihood (EL) procedure based on a set of estimating equations for the parameter of interest and discuss its characteristics and asymptotic properties. We also provide an algorithm based on EL principles for the estimation of the regression parameters and the construction of a confidence region for the parameter of interest. We extend our approach to variable selection for highdimensional longitudinal data with many covariates. In this situation it is necessary to identify a submodel that adequately represents the data. Including redundant variables may impact the model’s accuracy and efficiency for inference. We propose a penalized empirical likelihood (PEL) variable selection based on GEEs; the variable selection and the estimation of the coefficients are carried out simultaneously. We discuss its characteristics and asymptotic properties, and present an algorithm for optimizing PEL. Simulation studies show that when the model assumptions are correct, our method performs as well as existing methods, and when the model is misspecified, it has clear advantages. We have applied the method to two case examples.

Online information seeking by patients with bipolar disorder:results from an international multisite survey

Background: Information seeking is an important coping mechanism for dealing with chronic illness. Despite a growing number of mental health websites, there is little understanding of how patients with bipolar disorder use the Internet to seek information. Methods: A 39 question, paper-based, anonymous survey, translated into 12 languages, was completed by 1222 patients in 17 countries as a convenience sample between March 2014 and January 2016. All patients had a diagnosis of bipolar disorder from a psychiatrist. Data were analyzed using descriptive statistics and generalized estimating equations to account for correlated data. Results: 976 (81 % of 1212 valid responses) of the patients used the Internet, and of these 750 (77 %) looked for information on bipolar disorder. When looking online for information, 89 % used a computer rather than a smartphone, and 79 % started with a general search engine. The primary reasons for searching were drug side effects (51 %), to learn anonymously (43 %), and for help coping (39 %). About 1/3 rated their search skills as expert, and 2/3 as basic or intermediate. 59 % preferred a website on mental illness and 33 % preferred Wikipedia. Only 20 % read or participated in online support groups. Most patients (62 %) searched a couple times a year. Online information seeking helped about 2/3 to cope (41 % of the entire sample). About 2/3 did not discuss Internet findings with their doctor. Conclusion: Online information seeking helps many patients to cope although alternative information sources remain important. Most patients do not discuss Internet findings with their doctor, and concern remains about the quality of online information especially related to prescription drugs. Patients may not rate search skills accurately, and may not understand limitations of online privacy. More patient education about online information searching is needed and physicians should recommend a few high quality websites.

Evaluating the Impact of the Positive Choices Intervention on Substance Use, Psychological, and Care Engagement Outcomes Relevant to Current National HIV Prevention Goals

The HIV epidemic in the United States continues to be a significant public health problem, with approximately 50,000 new infections occurring each year. National public health priorities have shifted in recent years towards targeted HIV prevention efforts among people living with HIV/AIDS (PLWHA) that include: increasing engagement in and retention in care, improving HIV treatment adherence, and increasing screening for and treatment of substance use and psychological difficulties. This study evaluated the efficacy of Positive Choices (PC), a brief, care-based, theory-driven, 3-session counseling intervention for newly HIV-diagnosed men who have sex with men (MSM), in the context of current national HIV prevention priorities. The study involved secondary analysis of data from a preliminary efficacy trial of the PC intervention (n=102). Descriptive statistics examined baseline substance use, psychological characteristics and strategies, and care engagement and HIV-related biological outcomes. Generalized Estimating Equations (GEE) examined longitudinal changes in these variables by study condition. Results indicated that PC improved adherence to HIV treatment, but increased use of illicit drugs, specifically amyl nitrates and other stimulant drugs; additionally, moderation analyses indicated differences in patterns of change over time in viral load by baseline depression status. Implications of the findings and suggestions for future research are discussed.

ART attrition across health facilities implementing Option B+ in Haiti

Thesis (Master's)--University of Washington, 2016-08

Workforce Patterns and the Prevention of Mother-to-Child Transmission of HIV Option B Cascade in Côte d'Ivoire

Thesis (Master's)--University of Washington, 2016-08

Longitudinal Incidence Study of Clinically-Relevant HPV and Vaccine-Type HPV in Young Online Female Daters

Thesis (Master's)--University of Washington, 2016-08

Organisational justice and smoking: the Finnish Public Sector Study

Study Objective: To examine the extent to which justice of decision-making procedures and interpersonal relations is associated with smoking. Setting: Ten municipalities and 21 hospitals in Finland. Design and Participants: Cross-sectional data derived from the Finnish Public Sector Study were analysed with logistic regression analysis models with generalized estimating equations. Analyses of smoking status were based on 34 021 employees. Separate models for heavy smoking (>20 cigarettes per day) were calculated for 6295 current smokers. Main results: After adjustment for age, education, socio-economic position, marital status, job contract, and negative affectivity, smokers who reported low procedural justice were about 1.4 times more likely to smoke >20 cigarettes per day compared with their counterparts with high justice. In a similar way, after adjustments, low justice in interpersonal treatment was significantly associated with an elevated prevalence of heavy smoking (odds ratio (OR) = 1.35, 95% CI = 1.03 to 1.77 for men and OR = 1.41, 95% CI = 1.09 to 1.83 for women). Further adjustment for job strain and effort-reward imbalance had little effect on these results. There were no associations between justice components and smoking status or ex-smoking. Conclusions: The extent to which employees are treated with justice in the workplace seems to be associated with smoking intensity independently of established stressors at work.

Effort-reward imbalance and sedentary lifestyle: an observational study in a large occupational cohort

Objectives: To investigate the association between effort-reward imbalance (ERI) at work and sedentary lifestyle. Methods: Cross-sectional data from the ongoing Finnish Public Sector Study related to 30 433 women and 7718 men aged 17-64 were used (n = 35 918 after exclusion of participants with missing values in covariates). From the responses to a questionnaire, an aggregated mean score for ERI in a work unit was assigned to each participant. The outcome was sedentary lifestyle defined as <2.00 metabolic equivalent task (MET) hours/day. Logistic regression with generalized estimating equations was used as an analysis method to include both individual and work unit level predictors in the models. Adjustments were made for age, marital status, occupational status, job contract, smoking, and heavy drinking. Results: Twenty five percent of women and 27% of men had a sedentary lifestyle. High individual level ERI was associated with a higher likelihood of sedentary lifestyle both among women (odds ratio (OR) = 1.08, 95% CI 1.01 to 1.16) and men (OR = 1.17, 95% CI 1.02 to 1.33). These associations were not explained by relevant confounders and they were also independent of work unit level job strain measured as a ratio of job demands and control. Conclusions: A mismatch between high occupational effort spent and low reward received in turn seems to be associated with an elevated risk of sedentary lifestyle, although this association is relatively weak.