disease-specific variables are expressed as their proportion of some attribute of the general population, and hence appear as the numerator of the fraction or percentage being calculated, general data about the population typically appearing in the denominator; hence the term "denominator data."
Denominator data is more important in policy making (e.g., predicting how many nurses will be needed in future decades, or how the prevalence of heart disease will increase as a population shifts to have more older people and fewer younger ones) than in clinical trials.
[1] Rates presented without respect to the relevant denominator data can be misleading, and are sometimes derided as floating numerators.
[4] This includes comparing national population estimates against the UN's, checking whether the provided data is internally consistent (e.g., if the reported number of pregnancies is higher or lower than the reported number of births), and if the trends in the population are steady.
[4] Denominator data can also be checked against surveys and external sources of information (e.g., to see whether the number of deaths reported by the government correlates with the number of coffins sold as reported by the coffin makers); when all sources agree, the data is more likely to be accurate.