Confounding and Interaction

1. Confounding and Interaction • Definition and classification of bias • Confounding: one of the central problems in epidemiology • What is it? What does it do? • What kind of variables act as confounders? • Which variables to consider as confounders? • Methods to prevent or manage confounding • Randomization • Restriction • Matching • Stratification

2. Bias in Epidemiologic Studies • The goal of any study is to find the truth • Ways of missing the truth (getting the wrong answer): • Bias • Any systematic error that results in incorrect estimate of: • measure of disease (exposure) occurrence in a descriptive study • measure of association (between exposure and disease) in an analytic study • Chance • Random error • type I • type II

4. Classification Schemes for “Ways of Getting the Wrong Answer” • Szklo and Nieto • Bias • Selection Bias • Information/Measurement Bias • Confounding • Chance • Other Common Approach • Bias • Selection Bias • Information/Measurement Bias • Confounding Bias • Chance

5. Smoking, Matches, and Lung Cancer • A tobacco company researcher believes that cigarette smoke is not a cause of lung cancer but that exposure to matches is the cause. • He conducts a large case-control study to test this hypothesis

6. Smoking, Matches, and Lung Cancer • Your colleague has located 1000 cases of lung cancer from a population-based registry, of whom 820 carry matches. • Among 1000 reference (control) patients (selected randomly from the population and found to have normal chest x-rays), 340 carry matches. • Quantitate the relationship between matches and lung cancer in your colleague’s data.

7. Matches and Lung cancer • Exposure odds ratio = (820/180) / (340/660) = disease odds ratio • OR = 8.8 • 95% CI (7.2, 10.9)

8. Smoking, Matches, and Lung Cancer • You decide to look at the relationship between matches and lung cancer in the smokers separately from the non-smokers. • You find that among the 1000 cases, 900 are smokers and 810 (OF THE 900) carry matches. • Among the 1000 reference patients, 300 are smokers and 270 (OF THE 300) carry matches. • Draw the necessary stratified tables and calculate the relevant measure of association

9. Smoking, Matches, and Lung Cancer Crude OR crude Stratified Smokers Non-Smokers OR CF+ = ORsmokers OR CF- = ORnon-smokers • ORcrude = 8.8 (7.2, 10.9) • ORsmokers = 1.0 (0.6, 1.5) • ORnon-smoker = 1.0 (0.5, 2.0)

10. Confounding: Smoking, Matches, and Lung Cancer • In the relationship between matches and lung cancer, smoking is a ________ factor or a ______________ • Smoking _______ the relationship between matches and lung cancer • Illustrates how confounding can create an apparent effect even when there is no actual true effect

11. Smoking, Matches, and Lung Cancer • To be complete, you also decide to examine the relationship between smoking and lung cancer. • What tables should you construct to do this?

12. Smoking, Matches, and Lung Cancer Crude OR crude Stratified Matches Present Matches Absent OR CF+ = ORmatches OR CF+ = OR no matches • ORcrude = 21.0 (16.4, 26.9) • ORmatches = 21.0 (10.7, 41.3) • ORno matches = 21.0 (13.1, 33.6)

13. Confounding: Smoking, Matches, and Lung Cancer • What is the effect of matches on the relationship between smoking and lung cancer? • Illustrates one important component in the requirements of a ____________________ (aka a _______________ factor)

14. Confounding: Examples of Magnitude and Direction Crude RR crude Potential Confounder Absent Stratified Potential Confounder Present RR CF+ RR CF-

15. Nightlights

16. Nightlights and Myopia • Quinn et al. Nature 1999 • Prevalence Ratio =

17. Insert picture with nightlight off

18. Nightlights and Myopia: • Two subsequent studies found no association • Zadnik et al. and Gwiazda et al. Nature, 2000

19. Night Light X Parental Myopia Child’s Myopia

20. Insert picture with nightlight on again

21. What kind of variables act as confounders? • Properties of a True Confounder • A true confounder (C) must be associated with: • the exposure (E) in question and • the disease (D) under study Confounder D

22. Properties of a True Confounder Refined Properties: Association with Exposure • A confounding variable can be either the cause of, the result of, or simply associated in a non-causal manner with the exposure in question Confounder D

23. C causes E

24. Poverty E causes C ? [access to care] Poor Diet Mortality

25. Non-causal relationship between C and E CAD

26. Properties of a True Confounder Refined Properties: Association with Exposure • A confounding variable must be associated with the exposure in question independent of its association with the disease in question. • It must be associated with the exposure not simply through its association with the disease (i.e. must be associated with the exposure among the non-diseased)

27. Properties of a True Confounder Refined Properties:Association with Disease • A confounding variable must be associated with the disease. • It need not be a “cause” of disease; it may merely be a marker for (i.e. associated with) a cause Confounder D

28. IDU Hep B and C virus ? C causes D Cirrhosis

29. Unknown biologic factor(s) C as a marker for D

30. Properties of a True Confounder Refined Properties: Association with Disease • A confounding variable must be associated with the disease independent of its association with the exposure in question • i.e. must be associated with the disease among the unexposed

31. When Planning a Study, Which Factors Should be Considered as Potential Confounders? • Any factor for which prior evidence indicates it is a confounder and • In newer research areas: • factors known to be associated with both the exposure and disease under study and • factors known to be associated with the disease and which may be associated with exposure • When in doubt, plan on taking ALL potential confounders into account • i.e. measure all potential confounders unless you may regret it later

32. What is NOT a Confounder? • A variable that is an intermediate step in the causal path between exposure and disease is not a confounding variable. E factor This is not confounding D

33. Intermediaries are NOT Confounders • A variable that is an intermediate step in the causal path between exposure and disease is not a confounding variable. • Is HCV associated with transfusion? • With cirrhosis? • Is HCV a confounder in the relationship between transfusion and cirrhosis? Transfusion pre-1988 HCV Cirrhosis

34. Transfusion, HCV and Cirrhosis Crude RR crude Stratified HCV Present HCV Absent RR CF+ = RRHCV RR CF+ = RR no HCV • RRcrude = 1.5 (1.3 to 1.7) • RRHCV = 1.0 • RRno HCV = 1.0

35. EtOH and CAD • Is HDL associated with EtOH? • With CAD? • When evaluating the relationship between EtOH and CAD, is HDL a confounder or an intermediary? EtOH HDL HDL CAD

36. EtOH and CAD • If there is only one pathway in question, then HDL is an intermediary variable. EtOH HDL CAD

37. EtOH and CAD • If interest is in a pathway other than through HDL, then HDL is a confounder • Here, HDL is extraneous to pathway under study • Confounding factors are extraneous factors • Hence, classification of HDL depends upon the conceptual pathway under investigation EtOH ? HDL vasospasm CAD

38. What is NOT a Confounder? • Variables that are the RESULT of the disease, regardless of their association with the exposure are NOT confounders Confounder D

39. Smoking Cough ? Cough is not a confounder. Do not adjust for it! Lung CA