Cesarean section rates have increased worldwide in the last decades. It has had important implications for the health system, such as the increase in maternal morbidity and mortality. An anonymous survey was administered to 132 obstetricians in the City of Havana to identify their opinions regarding the cesarean section rates; to determine what are the causes for such increase and what possible interventions could stop that trend; and the obstetricians' preferences when facing some clinical situations. Most of participants considered the cesarean section rate to be high. Previous caesarean sections, administrative pressures and new technologies were pointed out as possible causes. Asking for a second opinion, the use of the partograph and try a VBAC are interventions probably useful to reduce such rates. Future research should investigate the ideal cesarean section rate and potential measures to decrease it, as well as the barriers that hinder professionals in implementing such interventions.

This study, based on the Canadian Community Health Survey (2004), examined the relationship between food insecurity and overweight/obesity among Canadian adults by sex and family type using logistic regression analysis; we also provided an environmental scan of policies, programs and initiatives to address food insecurity. In our final adjusted models, food insecure women with hunger were significantly more likely to be overweight/obese than food secure women [OR=2.3, CI=1.2, 4.3]. Our environmental scan revealed broad recognition of the importance of addressing food insecurity and concrete recommendations to do so. We found far less recognition of the implications of food insecurity for healthy weights within a policy context. The food insecurity/overweight/obesity relationship and its policy implications are complex; we need a better understanding of how underlying social and economic conditions, sex, and family type relate to income, food security and healthy weights.

Background. Recurrent glomerulonephritis is third most common cause of kidney transplant failure. Methods. We used the United States Renal Data System to determine the association of routine post-transplantation immunosuppressant use with time to renal allograft failure due to recurrent glomerulonephritis. Immunosuppressants were treated as time-varying covariates. The study-cohort included patients with kidney failure due to glomerulonephritis who received first kidney transplant between 1990 and 2003. Important confounders were identified through a systematic review of literature and missing values in the dataset were handled by multiple imputation. Results. The study cohort included 41,272 patients with a median follow-up of 51 (22--90) months. Ten-year overall graft survival (including death as graft loss) and death-censored graft survival was 56.2% (55.5%--56.9%) and 70.5% (69.8%--71.1%) respectively. Ten-year incidence of graft loss due to recurrent glomerulonephritis was 2.6% (2.3--2.8%). Use of cyclosporine, tacrolimus, azathioprine or mycophenolate mofetil was not associated with risk of graft failure due to recurrent glomerulonephritis alter adjusting for important covariates. There was no difference of recurrent glomerulonephritis causing graft failure between cyclosporine and tacrolimus or between azathioprine and mycophenolate mofetil. Change in any immunosuppressant during follow-up was independently associated with graft loss due to recurrence (HR 1.31, 95%CI 1.07--1.60, p=0.01). Conclusion. Routinely used post-transplantation immunosuppressants have no impact on the risk of graft loss due to recurrent glomerulonephritis.

The need to consistently evaluate surveillance systems is vital; without periodic evaluation, decisions informed by surveillance information may be based on incomplete or erroneous data. This evaluation of Cape Town's tuberculosis surveillance system was based on the CDC's Updated Guidelines for Evaluating Public Health Surveillance Systems, modified to reflect the specific context of a high burden of tuberculosis in a Middle-Income country, and emphasizing the importance of public health action that is informed by surveillance data. Findings indicate that: limitations regarding tuberculosis-human immunodeficiency virus as well as drug resistance data exist; increased availability and integration of electronic data would enhance the assessment of control efforts; and that system operations could be improved by increasing software flexibility. The development of a protocol for a trial of system changes builds upon the findings of the evaluation, and applies a logic model and an ecological health model to inform the trial design.

Drug eluting stents (DES) have been found to reduce restenosis and the rate of repeat angiographic procedures related to restenosis. However, an increase in harms with their use has been suspected. Therefore, there may be an important trade-off of efficacy for harms with the use of DES, especially over the long term. We conducted asystematic review and meta-analysis of RCT, examining the efficacy of DES versus bare metal stents (BMS). A separate review was then conducted which included non randomized studies, as well as RCT to evaluate long term harms of DES when compared to BMS. Analysis demonstrated that there was significant efficacy noted for DES over BMS, especially for the sirolimus coated stents. The long-term data demonstrated preserved efficacy of DES with no significant increase in the harms of death, myocardial infarction, stent thrombosis or revascularization for a follow-up extending out to four years.

This thesis addresses the intersection of two important areas in epidemiology and statistics: genetic linkage analysis and missing data methods, respectively. Genetic linkage analysis is a promising method in viral epidemiology which involves learning about transmission patterns by studying clusters of similar gene sequences. For example, similar sequences found in a pair of geographically distinct communities may imply disease transmission between the two locations. However, this analysis is sensitive to missing data, which can introduce substantial bias. This thesis presents a multiple-imputation approach which corrects for much, though not all, of the bias in genetic linkage analysis. It also introduces a novel resampling-based approach that generates a weighted distribution of complete datasets and is even more effective than imputation for reducing bias. This work highlights the importance of missing data in genetic linkage studies and presents ways to provide more accurate epidemiological information by correcting for missing data. The new resampling-based approach presented in this paper is also general enough to be applied to many types of missing-data problems involving complex datasets; such broader applications are a promising avenue for future research. / Applied Mathematics

Big data has enabled an entirely new approach to solving and understanding problems. With the popularity of social media, data is created by individuals. We believe that embedded in the big data of social media, like Twitter, is the documentation of self-reporting illness. Through analysis of keywords in tweets geo-tagged to Puerto Rico, we seek to model the outbreak of Chikungunya fever, with initial correlations of around 0.86. Collected tweets were then divided into categories and treated as independent variables for Lasso regression. Although we train on imperfect suspected numbers for the outbreak from the Pan-American Health Organization (PAHO), we analyze the coefficients to understand the social implications behind both social media disease reporting and awareness in Puerto Rico. We see different phases of Twitter volumes pre-, during and post-initial outbreak. News and government tweets decrease during subsequent outbreaks when we see a corresponding relative increase of self-reporting tweets. Especially when applied to epidemiology, big data isn't about finding the perfect answer, but instead, about discovering the underlying story. This thesis is about the story of a Chikungunya outbreak in Puerto Rico from the eyes of Twitter. / Applied Mathematics

The last decade witnessed the important scaled-up of malaria control interventions in sub-Saharan Africa (SSA). There is now renewed impetus to achieve the long-term goal of malaria elimination and reducing vectorial capacity of the Anopheles mosquito is a necessary first step towards this objective. Relying solely on the two pillars of malaria vector control (i.e., insecticide-treated nets and indoor residual spraying) will be insufficient to achieve elimination in much of SSA, however. Larval Source Management, and larviciding in particular, could play an important role in areas where breeding habitats are ‘few, fixed, and findable’ or where malaria vectors exhibit exophagic and exophilic behaviors, and in settings where insecticide resistance has emerged. Yet, only few contemporary studies have investigated the effectiveness of larviciding for malaria control despite historical success. Using the wealth of data from Dar es Salaam’s Urban Malaria Control Program (2004-2008), this dissertation will first assess the impact of a community-based larviciding program on prevalence of malaria infection in 15 urban wards of Dar es Salaam (Tanzania). The cost-effectiveness of this intervention will then be estimated from both a provider and a societal perspective. Finally, in a context of accelerated malaria control, the effect of reducing malaria transmission on disease-related behavior and knowledge will be examined. Results suggest that the larviciding intervention had a significant protective effect, decreasing by 21% the odds of being infected with malaria. Larviciding was found to be cost-effective for incidences as low as 40 infections per 1,000 individuals per year but the cost-effectiveness ratios were highly dependent on the assumed baseline malaria incidence rates. Such a successful intervention could also bring about further challenges to sustaining gains in reducing malaria transmission as the larviciding intervention was found to negatively affect bednet usage and knowledge of disease symptoms. Collectively, these results imply that larviciding should be considered as part of an Integrated Vector Management approach in SSA, if local eco-epidemiological conditions are suitable, and that there is a need to sustain behavioral change communication following successful vector control interventions.

Major cardiovascular risk factors have changed over the past 3-4 decades throughout the world. While adiposity and diabetes are rising worldwide, blood pressure and cholesterol are declining in high-income and even some middle-income countries, possibly due to improvements in diet or better diagnosis and treatment; the same risk factors have remained unchanged or even increased in low-income countries. To formulate effective prevention and health system policies, there is need to understand the implications of these diverse trends for cardiovascular diseases (CVDs). This dissertation focuses on quantifying the impact of multiple risk factors and preventive interventions on CVDs and their disparities at the population level. Answering this question requires information on how much of the effects of adiposity on CVDs are mediated through other metabolic risk factors (i.e. high blood pressure, high serum cholesterol and high blood glucose), which themselves have other determinants. The first paper quantifies the direct as well as the mediated effects of excess weight on coronary heart disease (CHD) and stroke through blood pressure, serum cholesterol and blood glucose. The analyses use data of 97 prospective cohorts with more than 1.8 million participants. This allows for assessing whether the extent of mediation is modified by geographical region, study period, and other characteristics of study populations. The second paper revisits the above question using causal inference models and further quantifies the role of inflammatory markers as potential mediators. The analyses use individual-level data from 9 prospective cohort studies that have high-quality measurements of metabolic and inflammatory biomarkers. The third paper uses national data sources in the United States (US) and estimates the distributions of 10-year risk of fatal CHD by race. It also assesses the effects of different population-wide and targeted interventions on CHD risk distributions and their disparities between blacks and whites. Our findings suggest that nearly half of excess risk for CHD and three-quarters of excess risk for stroke due to excess weight were mediated through three metabolic risk factors: blood pressure, cholesterol, and glucose. Inflammatory biomarkers had much smaller roles than the combination of metabolic risk factors. In the US, the distribution of 10-year CHD risk was shifted to the right among blacks compared to whites and had a heavier tail, leading to a substantially larger proportion of blacks in the high-risk group. A risk-based intervention that identifies and treats these individuals could substantially reduce both the overall risk of CHD and its racial disparities. These results together provide the quantitative evidence on the impact of cardiovascular risk factors and selected interventions on CVDs and their disparities.

Type 2 diabetes has reached epidemic proportions globally, and accumulating evidence suggests extremes of sleep duration increase risk. Diet may be an important mechanism, yet few studies examine prospective relationships of sleep duration and diet quality or whether diet explains associations of sleep duration with childhood obesity or diabetes in adults. In Chapter One, we report a moderate correlation between self-reported sleep duration and actigraphy in Sueño, the sleep ancillary study to the Hispanic Community Health Study/Study of Latinos. Chapter Two identifies associations of chronic insufficient sleep duration since infancy with lower diet quality in mid-childhood in Project Viva: children with the least favorable diet and sleep have the highest body mass index z-scores in mid-childhood, but diet does not explain associations with adiposity. In Chapter Three, adherence to healthful dietary patterns reduces risk of diabetes in the Women’s Health Initiative; high quality diets are protective in all groups, but race/ethnicity modifies associations. In Chapter Four, we find that changes in sleep duration, increases in particular , are associated with diabetes and concomitant changes in diet quality, physical activity and weight in the Nurses’ Health Study. Each of these studies contributes new knowledge: Sueño represents the largest sleep validation to date, the only validation among Hispanic/Latinos and allows researchers to better understand the information contained in (and the limitations of) self-reported measures of sleep duration within subgroups. In the Women’s Health Initiative, we address limitations of the current literature on dietary patterns by calculating four dietary indices within the same cohort, standardizing the scores for comparison and examining associations across racial/ethnic groups. Project Viva is the first study to examine the influence of chronic insufficient sleep on diet quality in childhood when health behaviors and dietary preferences are being formed. Finally, examining changes in sleep duration and changes in diet quality, physical activity and weight in the Nurses’ Health Study represents a novel way to leverage repeated assessments. Results of this dissertation may help build the case for policy and intervention efforts to prevent and treat obesity and diabetes, particularly those that seek to improve both sleep and diet. / Nutrition