Concise Epidemiologic Principle and Concepts - Second Edition: Study Design, Conduct and Application

We often conceive epidemiology in either simplistic or complex terms, and neither of these is accurate. To illustrate this, the complexities in epidemiology could be achieved by considering a study to determine the correlation between serum lipid profile as total cholesterol, HDL, LDL, triglyceride, and total body fatness or obesity measured by BMI in children. Two laboratories measured serum lipid profiles, and one observed a correlation with BMI, while the other did not. Which is the reliable finding? To address this question, one needs to examine the context of blood drawing since fasting blood level may provide a better indicator of serum lipid. Epidemiologic studies could be easily derailed given the inability to identify and address possible confounding. Therefore, understanding the principles and concepts used in epidemiologic studies designed and conducted to answer clinical research questions facilitates e accurate and reliable findings in these areas. Another similar example in a health fair setting involves geography and health, termed health-o-graphy. The risk of dying in one zip code A was 59.5 per 100,000, and in the other zip code B was 35.4 per 100,000. There is a common sense and non-epidemiologic tendency to conclude that there is an increased risk of dying in zip code A. To arrive at such inference, one must first find out the age distribution of these two zip codes since advancing age is associated with increased mortality. Indeed, zip code A is comparable to the United States population while, zip code B is the Mexican population. These two examples are indicative of the need to understand epidemiologic concepts such as confounding by age or effect measure modification prior to undertaking clinical research.

This textbook describes the basics of research in medical and clinical settings, as well as the concepts and application of epidemiologic designs in research. Design transcends statistical techniques, and no matter how sophisticated statistical modeling, errors of design/sampling cannot be corrected. The author of this textbook has presented a complex field in a very simplified and reader-friendly manner with the intent that such a presentation will facilitate the understanding of the design process and epidemiologic thinking in clinical research. Additionally, this book provides a very basic explanation of how to examine the data collected for research conduct for the possibility of confounders and how to address such confounders, thus disentangling such effects for reliable and valid inference.

Research is presented as an exercise around measurement, with measurement error inevitable in its conduct, hence the inherent uncertainties of all findings in clinical and medical research. Concise Epidemiologic Principles and Concepts (Second Edition) for Clinicians covers research conceptualization, namely research objectives, questions, hypothesis, design, implementation, data collection, analysis, results, and interpretation. While the primary focus of epidemiology is to assess the relationship between exposure (risk or predisposing factor) and outcome (disease or health-related event), the causal association is presented in a simplified manner, including the role of quantitative evidence synthesis (QES) in causal inference. Epidemiology has evolved over the past three decades, resulting in several fields being developed. This text presents, in brief, the perspectives and future of epidemiology in the era of the molecular basis of medicine, “3Ts,” and systems science, as well as Epigenomic Epidemiology.

Epidemiologic evidence is more reliable if conceptualized and conducted within the context of translational, transdisciplinary, and team science. With molecular epidemiology, we are better equipped with tools to identify molecular biologic indicators of risk as well as biologic alterations in the early stages of disease, and with 3 Ts and systems science, we are more capable of providing accurate and reliable inference on causality and outcomes research. Further, the author argues that unless sampling error and confounding are identified and addressed, clinical research findings will remain largely inconsistent, implying an inconsequential epidemiologic approach.

Appropriate knowledge of research conceptualization, design, and statistical inference is essential for conducting clinical and biomedical research. This knowledge is acquired through the understanding of epidemiologic/observational (non-experimental) and experimental designs and the choice of the appropriate test statistic for statistical inference. However, regardless of how sophisticated the statistical technique employed for statistical inference is, study conceptualization and design are the building blocks of valid scientific evidence. Since clinical research is performed to improve patients’ care, it remains relevant to assess not only the statistical significance but the clinical and biologic importance of the findings, for clinical decision-making in the care of an individual patient. Therefore, the aim of this book is to provide clinicians, biomedical researchers, graduate students in research methodology, students of public health, and all those involved in clinical/biomedical research with a simplified but concise overview of the principles and practice of epidemiology. In addition, the author stresses common flaws in the conduct, analysis, and interpretation of epidemiologic studies.

Valid and reliable scientific research is that which considers the following elements in arriving at the truth from the data, namely biological relevance, clinical importance, and statistical stability and precision (statistical inference based on the p-value and the 90, 95, and 99 percent confidence interval). The interpretation of results of new research must rely on factual association or effect and the alternative explanation, namely systematic error, random error (precision), confounding, and effect measure modifier. Therefore, unless these perspectives are disentangled, the results from any given research cannot be considered reliable. However, even with this disentanglement, all study findings remain inconclusive with some degree of uncertainty.

This book presents a comprehensive guide on how to conduct clinical and medical research—mainly research question formulation, study implementation, hypothesis testing using appropriate test statistics to analyze the data, and results interpretation. In so doing, it attempts to illustrate the basic concepts used in study conceptualization, epidemiologic design, and appropriate test statistics for statistical inference from the data. Therefore, though statistical inference is emphasized throughout the presentation in this text, equal emphasis is placed on clinical relevance or importance and biological relevance in the interpretation of the study results.

Specifically, this book describes in basic terms and concepts how to conduct clinical and medical research using epidemiologic designs. The author presents epidemiology as the main profession in the trans-disciplinary approach to the understanding of complex ecologic models of disease and health. Clinicians, even those without preliminary or infantile knowledge of epidemiologic designs, could benefit immensely from what, when, where, who, and how studies are conceptualized, data collected as planned with the scale of measurement of the outcome and independent variables, data edited, cleaned and processed prior to analysis, appropriate analysis based on statistical assumptions and rationale, results tabulation for scientific appraisal, results interpretation and inference. Unlike most epidemiologic texts, this is the first book that attempts to simplify complex epidemiologic methods for users of epidemiologic research, namely clinicians and allied health researchers. Additionally, it is rare to find a book with integrates of basic research methodology into epidemiologic designs. Finally, research innovation and the current challenges of epidemiology are presented in this book to reflect the currency of the materials and the approach, as well as the responses to the challenges of epidemiology today namely, epigenomic epidemiology in environmental and gene interaction disease determinants.

Epidemiology Conceptualized - Epidemiologic investigation and practice are as old as the history of modern medicine. It dates back to Hippocrates (circa 2,400 years ago). In recommending the appropriate practice of medicine, Hippocrates appealed to the physicians’ ability to understand the role of environmental factors in predisposition to disease and health in the community. During the Middle Ages and the Renaissance, epidemiologic principles continued to influence the practice of medicine, as demonstrated in De Morbis Artificum (1713) by Ramazinni and the works on scrotal cancer in relation to chimney sweeps by Percival Pott in 1775. With the works of John Snow, a British physician (1854), on cholera mortality in London, the era of scientific epidemiology began. By examining the distribution/pattern of mortality and cholera in London, Snow postulated that cholera was caused by contaminated water.

  Epidemiology Today – Epigenomic Epidemiology

There are several definitions of epidemiology, but a practical definition is necessary for the understanding of this science and art. Epidemiology is the basic science of public health. The objective of this profession is to assess the distribution and determinants of disease, disabilities, injuries, natural disasters (tsunamis, hurricanes, tornados, and earthquakes), and health- related events at the population level. Epidemiologic investigation or research focuses on a specific population. The basic issue is to assess the groups of people at higher risk: women, children, men, pregnant women, teenagers, whites, African Americans, Hispanics, Asians, poor, affluent, gay, lesbians, married, single, older individuals, etc. Epidemiology also examines how the frequency of the disease or the event of interest changes over time. In addition, epidemiology examines the variation of the disease of interest from place to place. Simply, descriptive epidemiology attempts to address the distribution of disease with respect to “who,” “when,” and “where.” For example, cancer epidemiologists attempt to describe the occurrence of prostate cancer by observing the differences in populations by age, socioeconomic status, occupation, geographic locale, race/ethnicity, etc.

Epidemiology also attempts to address the association between the disease and exposure. For example, why are some men at high risk for prostate cancer? Does race/ethnicity increase the risk for prostate cancer? Simply, is the association causal or spurious? This process involves the effort to determine whether a factor (exposure) is associated with the disease (outcome). In the example of prostate cancer, such exposure includes a high-fat diet, race/ethnicity, advancing age, pesticides, family history of prostate cancer, and so on. Whether or not the association is factual or a result of chance remains the focus of epidemiologic research. The questions to be raised are as follows: Is prostate cancer associated with pesticides? Does pesticide cause prostate cancer?

Epidemiology often goes beyond disease-exposure association or relationship to establish a causal association. In this process of causal inference, it depends on certain criteria, one of which is the strength or magnitude of association, leading to the recommendation of preventive measures. However, complete knowledge of the causal mechanism is not necessary prior to preventive measures for disease control. Further, findings from epidemiologic research facilitate the prioritization of health issues and the development and implementation of intervention programs for disease control and health promotion.

Epidemiology today reflects the application of gene and environment interaction in disease causation, morbidity, prognosis, survival, and mortality in subpopulation health outcomes. The knowledge and understanding of subpopulation differentials in DNA methylation of specific genes and histone modification allows for the application of abnormal transcriptomes, impaired gene expression, protein synthesis dysfunctionality, and abnormal cellular functionality.