Conditions Necessary for Confounding

There are three conditions that must be present for confounding to occur:

  1. The confounding factor must be associated with both the risk factor of interest and the outcome.
  2. The confounding factor must be distributed unequally among the groups being compared.
  3. A confounder cannot be an intermediary step in the causal pathway from the exposure of interest to the outcome of interest.

For example, it is known that modest alcohol consumption is associated with a decreased risk of coronary heart disease, and it is believed that one of the mechanisms by which alcohol causes a reduced risk is that alcohol raises blood levels of HDL, the so called "good cholesterol." Higher levels of HDL are known to be associated with a reduced risk of heart disease. Consequently it is believed that modest alcohol consumption raises HDL levels, and this, in turn, reduces coronary heart disease. In a situation like this HDL levels are not confounder of the association between alcohol and heart disease, because it is part of the mechanism by which alcohol produces this beneficial effect. If increased HDL is a consequence of alcohol consumption and part of the mechanism by which it lowers the risk of heart disease, then it is not a confounder..

A possible causal pathway in which alcohol consumption increases high density lipoproteins (HDL) and this, in turn, reduces the risk of heart disease

Not surprisingly, since most diseases have multiple contributing causes (risk factors), there are many possible confounders.

As a result, there may be many possible confounding factors that could influence an association. For example, in looking at the association between exercise and heart disease, other possible confounders might include age, diet, smoking status and a variety of other risk factors that might be unevenly distributed between the groups being compared.

Aside from their physical inactivity, sedentary subjects may be more likely to smoke, to have high blood pressure and diabetes, and to consume diets with a higher fat content; all of these factors would tend to increase the risk of coronary heart disease. On the other hand, subjects who go to a gym regularly (active) may be more likely to be males and perhaps more likely to have a family history of heart disease, i.e., factors that might increase the risk of active subjects. Consequently, there may be many confounders that can distort the estimate of association in one direction or another.





46 ± 1.4

59 ± 1.5

Dietary Fat %

29 ± 5.0

42 ± 7.0

Current Smokers









Family History of Heart Disease







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Domestic asbestos mining occurred in numerous states throughout most of the twentieth century. There are 60 former asbestos mines in the Eastern U.S. alone. The largest operations were in Arizona, North Carolina, Vermont and California.The men who worked in local asbestos mines were exposed to asbestos, which is a known risk for lung cancer.

It is well known that smoking is a risk factor for lung cancer. It is also known that miners tend to smoke more cigarettes because of the stress miners are exposed to, especially when working underground.

 If the following statement true or false?

Asbestos mining could be a confounder of the relationship between cigarette smoking and lung cancer.


Identifying Confounding

  1. A simple, direct way to determine whether a given risk factor caused confounding is to compare the estimated measure of association before and after adjusting for confounding. In other words, compute the measure of association both before and after adjusting for a potential confounding factor. If the difference between the two measures of association is 10% or more, then confounding was present. If it is less than 10%, then there was little, if any, confounding. How to do this will be addressed in greater detail below.
  2. Other investigators will determine whether a potential confounding variable is associated with the exposure of interest and whether it is associated with the outcome of interest. If there is a clinically meaningful relationship between an the variable and the risk factor and between the variable and the outcome (regardless of whether that relationship reaches statistical significance), the variable is regarded as a confounder.
  3. Still other investigators perform formal tests of hypothesis to assess whether the variable is associated with the exposure of interest and with the outcome.

Effects of Confounding

The magnitude confounding can be quantified by computing the percentage difference between the crude and adjusted measures of effect. There are two slightly different methods that investigators use to compute this, as illustrated below.

Percent difference is calculated by calculating the difference between the starting value and ending value and then dividing this by the starting value. Many investigators consider the crude measure of association to be the "starting value".

Other investigators consider the adjusted measure of association to be the starting value, because it is less confounded than the crude measure of association.

While the two methods above differ slightly, they generally produce similar results and provide a reasonable way of assessing the magnitude of confounding. Note also that confounding can be negative or positive in value.

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The risk of a smoker developing lung cancer was found to be 10 times higher than that of a non-smoker in Arizona. Since Arizona has over 103 naturally occuring asbestos sites and several mines, the researchers suspected asbestos mining was a confounder.

When the researchers adjusted for the confounding effect of working in the asbestos mines, they found that smokers were only 7 times more likely to develop lung cancer.

What was the magnitude of confounding in this study, and was the relationship between smoking and lung cancer truly confounded by asbestos mining exposure?