"Distinguishing Association from Causation: A Backgrounder for Journalists"
Writing for the American Council on Science and Health , Kathleen Meister offers sound advice for medical and science writers. Available in PDF , here's the executive summary :
• Scientific studies that show an association between a factor and a health effect do not necessarily imply that the factor causes the health effect. Many such studies are preliminary reports that cannot justify any valid claim of causation without considerable additional research, experimentation, and replication.
• Randomized trials are studies in which human volunteers are randomly assigned to receive either the agent being studied or an inactive placebo, usually under double-blind conditions (where neither the participants nor the investigators know which substance each individual is receiving), and their health is then monitored for a period of time. This type of study can provide strong evidence for a causal effect, especially if its findings are replicated by other studies. Such trials, however, are often impossible for ethical, practical, or financial reasons. When they can be conducted, the use of low doses and brief durations of exposure may limit the applicability of their findings.
• The findings of animal experiments may not be directly applicable to the human situation because of genetic, anatomic, and physiologic differences between species and/or because of the use of unrealistically high doses.
• In vitro experiments are useful for defining and isolating biologic mechanisms but are not directly applicable to humans.
• Observational epidemiologic studies are studies in human populations in which researchers collect data on people's exposures to various agents and relate these data to the occurrence of diseases or other health effects among the study participants. The findings from studies of this type are directly applicable to humans, but the associations detected in such studies are not necessarily causal.
• Useful, time-tested criteria for determining whether an association is causal include:
- Temporality. For an association to be causal, the cause must precede the effect. - Strength. Scientists can be more confident in the causality of strong associations than weak ones. - Dose-response. Responses that increase in frequency as exposure increases are more convincingly supportive of causality than those that do not show this pattern. - Consistency. Relationships that are repeatedly observed by different investigators, in different places, circumstances, and times, are more likely to be causal. - Biological plausbility. Associations that are consistent with the scientific understanding of the biology of the disease or health effect under investigation are more likely to be causal.
• New research results need to be interpreted in the context of related previous research. The quality of new studies should also be assessed. Those that include appropriate statistical analysis and that have been published in peer-reviewed journals carry greater weight than those that lack statistical analysis and/or have been announced in other ways.
• Claims of causation should never be made lightly. Premature or poorly justified claims of causation can mislead people into thinking that something they are exposed to is endangering their health, when this may not be true, or that a useless or even dangerous product may produce desirable health effects.
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