Lecture 8 :Confounding

1. Lecture 8 :Confounding 

2. Learning outcomes Identify confounding in research studies Describe ways to overcome confounding

3. Confounder Derived from Latin � to pour together� A variable that is an independent determinant of the outcome of interest and is unequally distributed among the exposed and non-exposed

4. Confounding occurs when the measurement of the effect of an exposure (study factor) is distorted because of the association of exposure with other factor(s) that influence the outcome under study. presence of confounding ? �mixing of effect� of the study factor (exposure) with that of another factor(s) ? overestimate or underestimate of the true association between exposure and outcome

5. Example

6. 3 Criteria To Be A Confounder is a variable that is associated with the exposure and independent of that exposure, it is an independent risk factor for the outcome is NOT an intermediate step in the causal chain between the exposure and outcome (an intervening variable) If removed � the association between exposure and outcome changes

7. Confounder Independent risk factor for the disease/outcome If removed ? change in association between exposure and outcome/disease Is not an intervening variable (ie not on the causal pathway)

8. Examples Independent risk factor? If removed ? ? change in association Intervening variable?

9. Examples Independent risk factor? If removed ? ? change in association Intervening variable?

10. Examples Independent risk factor? If removed ? ? change in association Intervening variable?

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16. Assessing effect of confounder Evaluate its presence or absence Identify the direction Quantify the magnitude of effect

17. Evaluating the presence of a confounder Variable is an independent risk factor for the outcome If suspected confounding variable is removed the association between the exposure and the outcome changes Variable is not an intervening variable

18. Testing for Confounding Obtain a crude outcome measure (crude death rate, crude birth rate, overall odds ratio or relative risk) Repeat the outcome measure controlling for the variable (age-adjusted rate, gender- specific odds ratio or relative risk) Compare the two measures; the estimate of the two measures will be different if the variable is a confounder

19. Do calcium supplements prevent osteoporosis?

20. Magnitude of confounder�s effect Magnitude of specific association between the confounder and the exposure Magnitude of specific association between the confounder and the outcome

21. Direction of confounder�s effect Depends on the nature of the interrelationships among the exposure, confounder and outcome The direction of confounder�s effect may be either positive or negative

22. Positive Confounding This refers to the situation in which the effect of the confounding factor is to produce an observed estimate of the association between exposure and disease that is more extreme ie enhances the effect, overestimates the effect ? more positive or more negative than the true association

23. Positive Confounding

24. Negative Confounding Where the confounding factor leads to an underestimation of the effect of the exposure on outcome ie downgrades the effect ? less positive or less negative than the true association

25. Reducing the effect of confounders In the design and conduct of the study by: Randomisation Restriction (Allow only those into the study who fit into a narrow band of a potentially confounding variable) Matching (Match cases and controls on the basis of the potential confounding variables � especially age and gender)

26. Reducing the effect of confounders Matching (continued): Cases and controls can be individually matched for one or more variables, or they can be group matched Matching is expensive and requires specific analytic techniques Overmatching or unnecessary matching may mask findings In the analysis of data Stratification Adjustment � Statistical modeling � eg Multiple Linear Regression, Logistic Regression, Proportional Hazards Model