A - Association Overview

Association

Introduction

The newspaper headline reads: "Childhood Obesity has been linked to Juvenile Onset Diabetes". This statement infers that the risk factor, obesity, is associated with the health condition, diabetes. Every overweight or obese person will not develop diabetes, but being obese increases a person's chance. Lessons in this module will help you understand association by explaining relationships between exposure and disease and distinguishing between confounding and associated variables.

Essential Questions

  • How do we determine if an exposure and disease are associated or independent?
  • How do you distinguish between confounding and associated variables?
  • What methods can we use to determine if two variables are independent or associated?

Key Terms

  1. Risk - A measure of how often an event occurs in a defined population in a defined period of time.
  2. Relative risk (risk ratio) - measures the magnitude of an association between an exposed and non-exposed group.
  3. Confounding - when an association is distorted because the exposure is correlated with another exposure that causes the outcome.
  4. Contingency table - A statistical table that shows the observed frequencies of data elements classified according to two variables, with the rows indicating one variable and the columns indicating the other variable.
  5. Odds ratio -the odds that an outcome will occur given a particular exposure, compared to the odds of the outcome occurring in the absence of that exposure.
  6. Risk factor - is a variable associated with an increased risk of disease or infection.
  7. Attributable risk - the difference in rate of a condition between an exposed population and an unexposed population.
  8. Exposure - Factors with which individuals come in contact.
  9. Inference - Process of predicting from what is observed in a sample to what is not observed in a population.

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