Epidemiology: .

by Moyses Szklo, F. Javier Nieto

Overview

Written for those who are familiar with the basic strategies of analytic epidemiology, Epidemiology: Beyond the Basics takes readers through a more rigorous discussion of key epidemiologic concepts and methods such as study design, measures of association, research assessment, and more. With real-life examples throughout, the book avoids complex statistical formulations and is an invaluable resource for intermediate students and practicing epidemiologists who wish to expand their knowledge of epidemiology and its role in the medical and public health sciences. The Fourth Edition offers updated examples and new exercises in each chapter as well as many new discussions of topics such as: prevalence ratios vs. odds ratios; inverse probability weighting as a technique for correcting for selection bias; regression to the mean as a source of confounding (Glymour bias); mediation analysis; correction for competing causes in multivariate analysis; the extension of the Cox model for the analysis of nested case-control studies; multilevel analysis; translational epidemiology and much more. This edition also offers an updated package of instructor materials including instructor’s manual, PowerPoint lecture slides, and a test bank. © 2019 | 578 pages

Product Details

ISBN-13:	9781284116595
Publisher:	Jones & Bartlett Learning
Publication date:	05/02/2018
Pages:	578
Product dimensions:	6.90(w) x 8.90(h) x 1.00(d)

About the Author

Moyses Szklo, MD, DrPH, is a Professor of Epidemiology at the Johns Hopkins Bloomberg School of Public Health and is Director of its Chronic Disease Epidemiology Program. His current research focuses on risk factors for subclinical and clinical atherosclerosis. He is also Editor in Chief of the American Journal of Epidemiology.

F. Javier Nieto, MD, PhD, is Helfaer Professor of Public Health, and Professor and Chair at the Department of Population Health Sciences at the University of Wisconsin School of Medicine and Public Health. His current research focuses on emerging risk factors for ischemic heart disease, particularly chronic infections and sleep disorders.

Table of Contents

Part 1 Introduction
Chapter 1 Basic Study Designs in Analytical Epidemiology
Part 2 Measures of Disease Occurrence and Association
Chapter 2 Measuring Disease Occurrence
Chapter 3 Measuring Associations Between Exposures and Outcomes
Part 3 Threats to Validity and Issue s of Interpretation
Chapter 4 Understanding Lack of Validity: Bias
Chapter 5 Identifying Noncausal Associations: Confounding
Chapter 6 Defining and Assessing Heterogeneity of Effects: Interaction
Part 4 Dealing with Threats to Validity
Chapter 7 Stratification and Adjustment: Multivariate Analysis in Epidemiology
Chapter 8 Quality Assurance and Control
Part 5 Issue s of Reporting and Application of Epidemiologic Results
Chapter 9 Communicating Results of Epidemiologic Studies
Chapter 10 Epidemiologic Issue s in the Interface with Public Health Policy
Appendix A Standard Errors, Confidence Intervals, and Hypothesis Testing For Selected Measures of Risk and Measures of Association
Appendix B Test for Trend (Dose Responses)
Appendix C Test of Homogeneity of Stratified Estimates (Test for Interaction)
Appendix D Quality Assurance and Quality Control Procedures Manual for Blood Pressure Measurement and Blood/Urine Collection in the ARIC Study
Appendix E Calculation of the Intraclass Correlation Coefficient
Appendix F Exercises-Answers

Editorial Reviews

This text is a sophisticated treatment of the issues that arise and methods that are employed when epidemiologists seek to measure disease risk and to investigate the complex determinants of risk. The purpose is to serve as an intermediate text, a bridge between the basics and the specialized texts that focus on specific methods or research designs. The real contribution is that the authors integrate and unify the treatment of these methods and their interpretation from the perspective of experienced epidemiologists, not merely data analysts. They present the full range of issues in this book in a way that is accessible to all, yet they avoid oversimplification. The audience for this gap-filling book is diverse, spanning the range from students enrolled in a second course in epidemiology, to practitioners who may use the book as a reference, to teachers of epidemiology. The book fills a niche in the field of epidemiology texts because it represents a unified presentation of advanced concepts in measurement of risk and association within the context of the principal study designs. The concepts of bias, confounding, and interaction are addressed in depth, as is their impact on study validity and causative reasoning. The treatment of the impact of time, including age, secular trend, and cohort effects is excellent, as is the discussion of stratification and regression-based modeling in accounting for confounding and effect modification. I only wish the authors had included a chapter on screening and prevention. Although this book is likely to be a standard addition to the library of most students and practitioners in the field of epidemiology, its clarity and richness of content makeit attractive to any health professional. This book fills a unique niche and therefore has little direct competition. The books that overlap somewhat include Kahn and Sempos's Statistical Methods in Epidemiology (Monographs in Epidemiology and Biostatistics, Vol. 12), (Oxford Univ Press 1989) and Selvin's Statistical Analysis of Epidemiologic Data (Monographs in Epidemiology and Biostatistics, Vol. 25) (Oxford Univ Press, 1996). However, these are more descriptions of methods and thus lack the rich discussion of the role of these methods and the issues they address in the broader context of epidemiological reasoning.

Robert McCarter

This intermediate-level text explores key epidemiologic concepts and basic methods in more depth than basic texts. Moyses and Nieto (epidemilogy, Johns Hopkins School of Hygiene and Public Health) present nine chapters that discuss cohort and nested case-control studies, birth cohort analysis, ecological studies, cumulative incidence, measures of association, confounding, interaction, reliability and validity measure, forms of bias, and other topics. Complex concepts such as confounding, interactions, and statistical modeling are illustrated with graphics, diagrams, and examples. Annotation c. Book News, Inc., Portland, OR (booknews.com)

Booknews

Reviewer: Robert McCarter, ScD (University of Maryland at Baltimore School of Medicine)
Description: This text is a sophisticated treatment of the issues that arise and methods that are employed when epidemiologists seek to measure disease risk and to investigate the complex determinants of risk.
Purpose: The purpose is to serve as an intermediate text, a bridge between the basics and the specialized texts that focus on specific methods or research designs. The real contribution is that the authors integrate and unify the treatment of these methods and their interpretation from the perspective of experienced epidemiologists, not merely data analysts. They present the full range of issues in this book in a way that is accessible to all, yet they avoid oversimplification.
Audience: The audience for this gap-filling book is diverse, spanning the range from students enrolled in a second course in epidemiology, to practitioners who may use the book as a reference, to teachers of epidemiology.
Features: The book fills a niche in the field of epidemiology texts because it represents a unified presentation of advanced concepts in measurement of risk and association within the context of the principal study designs. The concepts of bias, confounding, and interaction are addressed in depth, as is their impact on study validity and causative reasoning. The treatment of the impact of time, including age, secular trend, and cohort effects is excellent, as is the discussion of stratification and regression-based modeling in accounting for confounding and effect modification. I only wish the authors had included a chapter on screening and prevention.
Assessment: Although this book is likely to be a standard addition to the library of most students and practitioners in the field of epidemiology, its clarity and richness of content make it attractive to any health professional. This book fills a unique niche and therefore has little direct competition. The books that overlap somewhat include Kahn and Sempos's Statistical Methods in Epidemiology (Monographs in Epidemiology and Biostatistics, Vol. 12), (Oxford Univ Press 1989) and Selvin's Statistical Analysis of Epidemiologic Data (Monographs in Epidemiology and Biostatistics, Vol. 25) (Oxford Univ Press, 1996). However, these are more descriptions of methods and thus lack the rich discussion of the role of these methods and the issues they address in the broader context of epidemiological reasoning.

Doody's Review Service