Who needs another introductory epidemiology text? Certainly, there are many introductory epidemiology books currently in print, and many of them are excellent. Nevertheless, there are four reasons why I believe that this new text is justified.

Firstly, it is much shorter than most introductory texts, many of which contain more material than is required for a short introductory course. This is a short introduction to epidemiology, and is not intended to be comprehensive. Secondly, I have endeavoured to show clearly how the different basic epidemiologic methods fit together in a logical and systematic manner.

For example, I attempt to show how the different possible study designs relate to each other, and how they are different approaches to a common task. Similarly, I attempt to show how the different study design issues (confounding and other types of bias) relate to each other, and how the principles and methods of data analysis are consistent across different study designs and data types. Thirdly, in this context, rather than attempt a comprehensive review of available methods (e.g. multiple methods for estimating confidence intervals for the summary risk ratio), I have attempted to select only one standard method for each application, which is reasonably robust and accurate, and which is consistent and coherent with the other methods presented in the text

Contents
1. Introduction 9
Germs and miasmas 10
Risk factor epidemiology 11
Epidemiology in the 21st century 12
PART 1: STUDY DESIGN OPTIONS
2. Incidence studies 21
Incidence studies 22
Incidence case-control studies 28
3. Prevalence studies 33
Prevalence studies 33
Prevalence case-control studies 38
4. More complex study designs 41
Other axes of classification 41
Continuous outcome measures 42
Ecologic and multilevel studies 47
PART 2: STUDY DESIGN ISSUES
5. Precision 59
Basic statistics 60
Study size and power 61
6. Validity 67
Confounding 67
Selection bias 73
Information bias 74
7. Effect modification 83
Concepts of interaction 83
Additive and multiplicative models 88
Joint effects 89
PART 3: CONDUCTING A STUDY
8. Measurement of exposure and health status 95
Exposure 95
Health status 102

9. Cohort studies 109
Defining the source population and risk period 109
Measuring exposure 112
Follow-up 113
10. Case-control studies 117
Defining the source population and risk period 117
Selection of cases 118
Selection of controls 119
Measuring exposure 122
11. Prevalence studies 125
Defining the source population 125
Measuring health status 126
Measuring exposure 128
PART 4: ANALYSIS AND INTERPRETATION OF STUDIES
12. Data analysis 133
Basic principles 133
Basic analyses 136
Controlling for confounding 140
13. Interpretation 145
Appraisal of a single study 145
Appraisal of all of the available evidence 148