The use of an adjusted odds ratio to estimate an adjusted relative
risk appropriate for studies of rare outcomes, however,
may be misleading when the outcome is common. The overestimation
may inappropriately affect clinical decision-making
or policy development. Additionally, overestimation of the
importance of a risk factor may lead to unintentional errors in
the economic analysis of potential intervention programs or
treatments. Options exist to obtain unbiased estimates of relative
risks in studies of common outcomes. Two methods that
have widely available user-friendly software and often are
statistically appropriate (e.g., fit the data) include stratified
analysis and log-binomial modeling.