• Part 1 - Measures of Disease Frequency
• Part 2 - Measuring Association Between Exposures & Health Outcomes

# Introduction

For centuries, knowledge about the cause of disease and how to treat or prevent it was limited because it was based mostly on anecdotal evidence. Significant advances occurred when the strategy for studying disease shifted to looking at groups of people and using a numeric approach to make critical comparisons.

Link to video transcript in a Word file

Key Questions:

How do we measure the frequency of health outcomes?
How can I estimate the burden of disease in a population?
How do we design studies to determine whether an exposure is associated (linked) to a disease?
How can I estimate the risk of developing an adverse health outcome?
How do we detect associations?
How can I present basic information about exposure and outcome from a sample?

# Learning Objectives

Part 1 - Measures of Disease Frequency

After successfully completing this section, you will be able to:

• Define, calculate and interpret measures of disease frequency: prevalence, risk (cumulative incidence) and incidence rate
• Explain the interrelationship among prevalence, incidence, and average duration of disease (i.e. P = IR x D). Be able to calculate the average duration of disease, given the prevalence and incidence rate.
• Calculate measures of frequency from raw data
• Explain what is meant by "person-time" and be able to calculate person-time and incidence rates

Part 2 - Measuring Association Between Exposures & Health Outcomes

After completing this section, you will be able to:

• Explain the design strategies and data obtained from prospective and retrospective cohort studies, intervention studies (clinical trials), and case-control studies
• Organize data from retrospective cohort studies, intervention studies (clinical trials), and case-control studies into a "2x2" contingency table
• Define and calculate prevalence ratio and prevalence difference; risk ratio and risk difference; rate ratio and rate difference
• Explain absolute and relative measures of association in words to scientific and lay audiences