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Neil Pearce, Wellington: Centre for Public Health Research, 2005, pp 130. ISBN 0-476-01236-8. An electronic copy in pdf form can be dounloaded for free from the web site http://publicHealth.Masseg.ac.uk
Neil Pearce’s new textbook provides an overview of major types of epidemiological study designs and their key strengths and weaknesses. At the start, Pearce emphasises that, compared with randomised controlled trials, observational studies require special attention to sources of bias, and the book’s content and organisation reflect this awareness. It is logically organised to explore study design types (incidence studies, prevalence studies, ecological studies), study design issues (precision, validity, effect modification), and the analysis and interpretation of results (causal inference). This format will help students to see the forest rather than the trees and to understand the relation between different epidemiological methods.
But Pearce himself poses a sensible question in his preface: “Who needs another introductory epidemiology text?” In response, Pearce maintains that his text is worthwhile because it is shorter than other texts, because it presents a variety of methods in a structured and systematic manner, and because the field of epidemiology is changing rapidly to tackle disease phenomena on a global scale. While the book succeeds admirably on the first two qualities, it falls short on providing a substantial foundation for epidemiology students to understand the need for new methods and theories for global public health. For example, chapter 1 highlights the need for a “problem based” approach to teaching epidemiology, but, apart from a handful of sidebar examples, the didactic approach of subsequent chapters fails to put this recommendation into practice.
Nevertheless, the book’s brevity and organisation make it accessible and practical both as an introductory textbook and as an introduction to epidemiology for those who want to read the epidemiology literature critically but not necessarily to practise it. Familiar mathematical equations are provided for calculating confidence intervals and χ2 values, although more for illustration than for application (unless the reader has already taken biostatistics). The one important omission is the lack of a glossary, which would have added to the book’s value as a user friendly reference tool.
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