In previous articles we have focused on the potentials, principles, and pitfalls of meta-analysis of randomised controlled trials.1 2 3 4 5 Meta-analysis of observational data is, however, also becoming common. In a Medline search we identified 566 articles (excluding those published as letters) published in 1995 and indexed with the medical subject heading (MeSH) term “meta-analysis.” We randomly selected 100 of these articles and examined them further. Sixty articles reported on actual meta-analyses, and 40 were methodological papers, editorials, and traditional reviews (1). Among the meta-analyses, about half were based on observational studies, mainly cohort and case-control studies of medical interventions or aetiological associations.

The randomised controlled trial is the principal research design in the evaluation of medical interventions. However, aetiological hypotheses—for example, those relating common exposures to the occurrence of disease—cannot generally be tested in randomised experiments. Does breathing other people's tobacco smoke cause lung cancer, drinking coffee cause coronary heart disease, and eating a diet rich in saturated fat cause breast cancer? Studies of such “menaces of daily life”6 use observational designs or examine the presumed biological mechanisms in the laboratory. In these situations the risks involved are generally small, but once a large proportion of the population is exposed, the potential public health implications of these associations—if they are causal—can be striking.

Analyses of observational data also have a role in medical effectiveness research.7 The evidence available from clinical trials will rarely answer all the important questions. Most trials are conducted to establish efficacy and safety of a single agent in a specific clinical situation. Owing to the limited size of such trials, less common adverse effects of drugs may only be detected in case-control …