Description
Book SynopsisEpidemiology Matters offers a new approach to understanding and identifying the causes of disease -- and with it, how to prevent disease and improve human health. Utilizing visual explanations and examples, this text provides an accessible, step-by-step introduction to the fundamentals of epidemiologic study, from design to analysis. Across fourteen chapters, Epidemiology Matters teaches the individual competencies that underlie the conduct of an epidemiologic study: identifying populations; measuring exposures and health indicators; taking a sample; estimating associations between exposures and health indicators; assessing evidence for causes working together; assessing internal and external validity of results. With its consequentialist approach -- designing epidemiologic studies that aim to inform our understanding, and therefore improve public health -- Epidemiology Matters is an introductory text for the next generation of students in medicine and public health.
Trade ReviewEpidemiology Matters makes a nice addition to the existing roster of introductory epidemiology texts. The authors provide a clear introduction to central epidemiologic concepts, including causality, internal validity, external validity, study design, and measures of association using a step-bystep approach. Their well-designed website provides useful supplementary materials... The book will be useful to students who take only one course in epidemiology, as well as to scholars who decide to pursue epidemiology in more depth. * American Journal of Epidemiology *
This is a unique addition to the ever-expanding library of introductory epidemiology books. The material is easily accessible to beginners, and the consequentialist approach brethes new life into the field.
Table of Contents1. An introduction ; 2. What is a population and what is population health? ; 3. What is an exposure, what is a disease, and how do we measure them? ; 4. What is a sample? ; 5. Watching a sample, counting cases ; 6. Are exposures associated with health indicators? ; 7. What is a cause? ; 8. Is the association causal, or are there alternative explanations? ; 9. How do non-causal associations arise? ; 10. How can we mitigate against non-causal associations in design and analysis? ; 11. When do causes work together? ; 12. Do the results matter beyond the study sample? ; 13. How do we identify disease early to minimize its consequences? ; 14. Conclusion: Epidemiology and what matters most
