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Confounding bias versus Effects Modification

7K views 9 replies 6 participants last post by  qirkergaard 
#1 ·
Hi everybody

Can you please explain the difference between confounding bias and effect modification! I didn't get the explanation from UW

thank you
 
#3 ·
Confounding factor is a specific variable that is associated with both the effect and the outcome. Example---When studying the effects of smoking and esophageal cancer, ALCOHOLISM is a confounding factor since patients who smoke tends to drink and drinking is a risk factor of esophageal cancer.

Effect modification is when effect of exposure on disease differs in strata groups of the population. e.g. tetracycline causes discoloration in children but not in adult.
 
#4 ·
Confounding factor is a specific variable that is associated with both the effect and the outcome. Example---When studying the effects of smoking and esophageal cancer, ALCOHOLISM is a confounding factor since patients who smoke tends to drink and drinking is a risk factor of esophageal cancer.

Effect modification is when effect of exposure on disease differs in strata groups of the population. e.g. tetracycline causes discoloration in children but not in adult.
This is a pretty short (2 pages) article explaining the diff. between them:
http://courses.washington.edu/b570/handouts/confounding.pdf

and here you´ll find a lot of examples (Stanford U)
www.stanford.edu/~kcobb/hrp261/lecture2.ppt
Thank you so much for the replay and the great explanation; things are more clear now
 
#6 ·
Confounding:
Confounding occurs when a factor other than the one you are studying is associated both with the disease and the factor you are studying.

Imagine you are studying the association between an exposure and a disease, for example between drinking coffee and heart disease, and want to decide whether it is a causal association.

Hypothesis = coffee drinking increases the risk of lung cancer

- For example, if drinking coffee is associated with smoking (perhaps people who drink coffee also tend to smoke) the smoking forms a confounding variable because we know that it independently affects heart disease. The result is that there appears to be an association between coffee drinking and heart disease when, in reality, this may be occurring just because the people who drink coffee also smoke, and it is their smoking (not the coffee drinking) which actually causes the heart disease.

Effect modification or interaction: occurs when the effect measure depends on the level of another factor or = when our chosen summary of association differs in different strata.

"The relative risk of ischemic stroke for non-whites compared with whites is about 2 for those aged 35 to 64 years and about 1 for those 65 years of age and above"

Here we have 2 strata (levels):
1.- "young 35-64y/o" = RR of ischemic stroke for non-whites compared with whites is 2
2.- "old >64" y/o" = RR of ischemic stroke for non-whites compared with whites is 1

This is an example of modification of the effect of race by age.
 
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