Often called “the cornerstone” of public health, epidemiology is the study of the distribution and determinants of diseases, health conditions, or events among populations and the application of that study to control health problems. By applying the concepts learned in this course to current public health problems and issues, students will understand the practice of epidemiology as it relates to real life and makes for a better appreciation of public health programs and policies. This course explores public health issues like cardiovascular and infectious diseases – both locally and globally – through the lens of epidemiology.

From the lesson

Measures of Association

This module introduces measures of association and confidence intervals.

Clinical Associate Professor Department of Epidemiology, UNC Gillings School of Global Public Health

Dr. Lorraine Alexander

Clinical Associate Professor, Director of Distance Learning (North Carolina Institute for Public Health) Department of Epidemiology, UNC Gillings School of Global Public Health

[MUSIC]

Now so far we've covered both the

definition and calculations for Measures of Association.

Next, let's learn how to correctly interpret the measures of association.

Once you've learned these, you might

actually find yourself critiquing news reports

or discussions in the news that

are incorrectly using the measures of association.

After you have reviewed this segment you should be

able to do the items listed in the learning objectives.

These include interpreting the measures of

association, and recognizing which measures of

disease occurrence or frequency, and association

are commonly used with different study designs.

How do I know if an exposure has a positive

or negative effect on the disease that I'm interested in?

Or how do you know if the exposure doesn't have

any effect at all?

Here are the guidelines for relative measures of association i.e.,

ratios.

If the risk rate is equal to one then there

is no association between exposure and the disease or health outcome.

If the risk ratio or rate ratio is greater than one then the risk

in the exposed or rate in the exposed is greater than in the unexposed.

If the risk ratio or rate ratio is

less than one, then the risk in the exposed is lower than the unexposed.

For absolute measures of association, i.e.,

differences, if the risk difference is equal

to zero, then there is no association, i.e.,

the risk is the same in the both groups.

If the risk difference is greater than zero, then the

risk in the exposed is greater than in the unexposed.

And if the risk difference is less than zero, then the risk in the exposed is less

than in the unexposed.

Note that the null value for differences is zero

while for the ratios the null value is one.

Let's preface the topic of which measures of association

are commonly found with different types of study design by

first noting that all the measures of association we

have covered can be estimated in the cohort study design.

However, some of the other study designs

are not able to directly calculate risks and rates as you can in the cohort.

So, here is a table illustrating the measures of association

that can be commonly used for different types of study designs.

Note that prevalence and odds ratios and

differences are more commonly found with cross-sectional and

case-control studies, while risk and rate ratios and

differences are more commonly used with cohort studies.

Risks and rate ratios cannot be directly

calculated from case control and cross sectional studies.

This concludes the segment on interpreting measures of association.

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