The application of epidemiologic research study principles to a variety of research settings

Over the last 3 years the research I was involved in could for the most part be classified in terms of epidemiologic research design. This thesis does not discuss the intricacies of carrying out an epidemiologic study but rather describes the different applications of epidemiologic study designs including the advantages and disadvantages of each. With the ever-growing amount of literature, it is essential to understand the benefits and limitations of each type of study for clinical decision-making and for selecting the appropriate design when attempting to answer research questions. This thesis concludes by giving examples of different studies performed by the author that exemplify specific studies discussed in the introduction

PUBH 8133 – Advanced Epidemiology

An in-depth integration of advanced epidemiology concepts designed to reinforce epidemiological principles, as well as build a foundation for epidemiologic research in public health practice. Specific course content includes theory, methods, and applications for epidemiologic studies including random and systematic error, confounding, counterfactuals, causal inference, effect modification, internal and external validity and advanced study design. Emphasis will also be placed on choosing and performing appropriate analytic techniques necessary for biostatistical inference, including estimation and interpretation of effect measures

Causation in Occupational Disease: Balancing Epidemiology, Law and Manufacturer Conduct

Drs. Lynch & Henefin examine evolution of disease causation theory and its impact on public health, as well as how these relate to the courtroom admissibility of expert opinion evidence

Methodological challenges when carrying out research on CKD and AKI using routine electronic health records.

Research regarding chronic kidney disease (CKD) and acute kidney injury (AKI) using routinely collected data presents particular challenges. The availability, consistency, and quality of renal data in electronic health records has changed over time with developments in policy, practice incentives, clinical knowledge, and associated guideline changes. Epidemiologic research may be affected by patchy data resulting in an unrepresentative sample, selection bias, misclassification, and confounding by factors associated with testing for and recognition of reduced kidney function. We systematically explore the issues that may arise in study design and interpretation when using routine data sources for CKD and AKI research. First, we discuss how access to health care and management of patients with CKD may have an impact on defining the target population for epidemiologic study. We then consider how testing and recognition of CKD and AKI may lead to biases and how to potentially mitigate against these. Illustrative examples from our own research within the UK are used to clarify key points. Any research using routine renal data has to consider the local clinical context to achieve meaningful interpretation of the study findings

Chicano/Mexican Culture as a Rational Instrument in the Human Sciences

The use of culture as an analytical category by social scientists presents an opportunity to examine how professional discursive formations are used to make empirical assertions. The social fact of culture is neither uniform nor unitary. Traditionally, culture has been thought of as a product of disciplinary research, not necessarily a variable for empirical study. When culture is used as a tool or instrument of scientific methodology, it loses its fluid nature as a disciplinary discourse. In this essay, I examine the specific discussion of the epidemiologic health paradox that states that the Chicano/Mexican immigrant culture serves as a protective factor against many maladies that afflict other U.S. populations. Since the 1970s, this discussion of culture as a protective factor provides an interesting exposition of the uses of culture by empirical scholars

East African HIV care: depression and HIV outcomes.

Importance:Depression is a common co-morbidity for people living with HIV (PLWH) and is associated with elevated plasma HIV RNA levels. While depression correlates with deficits in antiretroviral (ARV) adherence, little data exist to inform the relationship between depression and HIV vial load more broadly. Objective:To examine the relationship between depression and viral load in the African Cohort Study (AFRICOS) independently of ARV adherence. Design:PLWH in Kenya, Uganda and Tanzania underwent screening for depression using the Center for Epidemiologic Studies Depression Scale (CESD) upon enrollment at AFRICOS HIV care sites. Setting:AFRICOS is an ongoing prospective longitudinal cohort study enrolling HIV-infected adults at HIV care centers including sites in Kenya, Tanzania and Uganda. These sites are administered by President's Emergency Plan For AIDS Relief programs. Participants:HIV+ individuals were eligible if they were at least 18 years old, receiving HIV care at the enrolling clinic and consented to data and specimen collection. Main outcome measure:CESD. Results:Among 2307 participants, 18-25% met the CESD threshold for depression. Depression was associated with decreased ARV adherence (OR 0.59, p =  0.01). Higher scores on three CESD items were significantly associated with 209-282% higher viral load, independently of ARV adherence among participants on ARVs ⩾6 months. Conclusions:PLWH had high prevalence of depression on the CESD. Diverse depression symptoms were independently associated with increases in viral load, underscoring the need for comprehensive treatment of depression

Emerging Challenges and Opportunities in Infectious Disease Epidemiology.

Much of the intellectual tradition of modern epidemiology stems from efforts to understand and combat chronic diseases persisting through the 20th century epidemiologic transition of countries such as the United States and United Kingdom. After decades of relative obscurity, infectious disease epidemiology has undergone an intellectual rebirth in recent years amid increasing recognition of the threat posed by both new and familiar pathogens. Here, we review the emerging coalescence of infectious disease epidemiology around a core set of study designs and statistical methods bearing little resemblance to the chronic disease epidemiology toolkit. We offer our outlook on challenges and opportunities facing the field, including the integration of novel molecular and digital information sources into disease surveillance, the assimilation of such data into models of pathogen spread, and the increasing contribution of models to public health practice. We next consider emerging paradigms in causal inference for infectious diseases, ranging from approaches to evaluating vaccines and antimicrobial therapies to the task of ascribing clinical syndromes to etiologic microorganisms, an age-old problem transformed by our increasing ability to characterize human-associated microbiota. These areas represent an increasingly important component of epidemiology training programs for future generations of researchers and practitioners

Role of a plausible nuisance contributor in the declining obesity-mortality risks over time.

CONTEXT: Recent analyses of epidemiological data including the National Health and Nutrition Examination Survey (NHANES) have suggested that the harmful effects of obesity may have decreased over calendar time. The shifting BMI distribution over time coupled with the application of fixed broad BMI categories in these analyses could be a plausible nuisance contributor to this observed change in the obesity-associated mortality over calendar time. OBJECTIVE: To evaluate the extent to which observed temporal changes in the obesity-mortality association may be due to a shifting population distribution for body mass index (BMI), coupled with analyses based on static, broad BMI categories. DESIGN, SETTING, AND PARTICIPANTS: Simulations were conducted using data from NHANES I and III linked with mortality data. Data from NHANES I were used to fit a true model treating BMI as a continuous variable. Coefficients estimated from this model were used to simulate mortality for participants in NHANES III. Hence, the population-level association between BMI and mortality in NHANES III was fixed to be identical to the association estimated in NHANES I. Hazard ratios (HRs) for obesity categories based on BMI for NHANES III with simulated mortality data were compared to the corresponding estimated HRs from NHANES I. MAIN OUTCOME MEASURES: Change in hazard ratios for simulated data in NHANES III compared to observed estimates from NHANES I. RESULTS: On average, hazard ratios for NHANES III based on simulated mortality data were 29.3% lower than the estimates from NHANES I using observed mortality follow-up. This reduction accounted for roughly three-fourths of the apparent decrease in the obesity-mortality association observed in a previous analysis of these data. CONCLUSIONS: Some of the apparent diminution of the association between obesity and mortality may be an artifact of treating BMI as a categorical variable