When comparing two or more populations with respect to a health outcome, it is temptiing to compare crude rates of disease, i.e., the number of disease events divided by the size of the population. The "crude rate" is the measure that was introduced in the module on Measures of Disease Frequency. However, comparisons of crude rates can be misleading because of confounding if the populations being compared have different distributions of other determinants of disease, such as age which has an important effect on many heatlh outcomes, such as mortality, heart disease, cancer, infectious diseases, and injury. As a result, differences in age can distort other comparisons between populations, and this distortion is called confounding. This module will focus on a technique called standardization that allows one to compute summary rates of health outcomes that are adjusted to take into account differences in confounding factors like age in order to provide a less distorted comparison.
The two closely related techniques are commonly used to compute "age-adjusted" summary rates that facilitate compartisons among population. Direct standardization applies a standard age distribution to the populations being compared in order to compute summary rates indicating how overall rates would have compared if the populations had had the same age distibution. This method is used when age-specific rates of disease are known for the populations being compared. In contrast, so-called indirect standardization applies a standard set of age-specific rates of disease to the populations being compared in order to compute the number of cases of disease that would be expected in a given population, based on its size and age-distribution.
After completing this module, the student will be able to:
- Explain what is meant by:
- Calculate standardized rates of disease or death for two populations using direct standardization and interpret the findings in words.
- Calculate standardized incidence ratio (SIR) and standardiized mortality rate (SMR) for a disease and describe its meaning.