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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

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Confounding and Interaction


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    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

    3. 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

    4. 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

    5. 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.

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

    7. 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

    8. 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)

    9. 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

    10. 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?

    11. 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)

    12. 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)

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

    14. Nightlights

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

    16. Insert picture with nightlight off

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

    18. Night Light X Parental Myopia Child’s Myopia

    19. Insert picture with nightlight on again

    20. 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

    21. 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

    22. C causes E

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

    24. Non-causal relationship between C and E CAD

    25. 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)

    26. 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

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

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

    29. 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

    30. 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

    31. 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

    32. 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

    33. 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

    34. 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

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

    36. 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

    37. 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

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