This module explores measures of association that are used to compare groups of different people, groups across different places, or one group over time. Age-standardized data is often required when making such comparisons. The module therefore also provides an explanation of when standardization of public health data is important and how to age-standardize data. It concludes by providing details on more complex measures of potential impact, including population attributable fraction and excess mortality. Completing this module will improve your knowledge of the importance of comparing groups in epidemiology, as this helps to identify populations most affected by poor health. The population attributable fraction is then used to estimate the reduction in disease due to the removal of harmful exposures or the implementation of beneficial public health interventions.
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