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  1. Day 5 Teach Epidemiology Professional Development Workshop Centers for Disease Control and PreventionGlobal Health Odyssey MuseumTom Harkin Global Communications Center June 8-12, 2009

  2. Teach Epidemiology Teach Epidemiology

  3. Teach Epidemiology Welcome to Web Sites Teach Epidemiology

  4. Teach Epidemiology Teach Epidemiology Teach Epidemiology

  5. Teach Epidemiology Welcome to Teach Epidemiology Teach Epidemiology

  6. Time Check 9:15 AM

  7. Teach Epidemiology Teach Epidemiology

  8. Teaching Epidemiology Group 5 Teach Epidemiology

  9. Teach Epidemiology 9 Teach Epidemiology

  10. Enduring Epidemiological Understandings 10 Teach Epidemiology

  11. Scenario 1 - Guilt by Association Wendy Mark

  12. Association Cause X Mark Empty Beer Bottles Cause Scenario 1- Guilt By Association Not Observed Wendy Observed

  13. Definition Confounding A situation in which an association between a given exposure and an outcome is observed as a result of the influence of a third unobserved factor, called a confounder.

  14. Review Confounding A situation in which an association between a given exposure (Mark) and an outcome (empty bottles) is observed as a result of the influence of a third unobserved factor, called a confounder (Wendy) Obviously we should have spoken to Wendy.

  15. Association Cause X Cause Lung Cancer Match-Carrying Review - Diagram of Confounding Confounder Not Observed Smoking Observed

  16. Epi Teams

  17. Association Cause X Cause Coffee Cancer 1 Confounding Confounder Not Observed Observed

  18. Association Cause X Cause Low Birth Weight Babies Drinking Alcohol during Pregnancy 2 Confounding Confounder Not Observed Observed

  19. Association Cause X Cause Eating Pretzels Auto Accidents 3 Confounding Confounder Not Observed Observed

  20. Association Cause X Cause Watching TV Acne 4 Confounding Confounder Not Observed Observed

  21. Association Cause X Cause Playing Volleyball Skin Cancer 5 Confounding Confounder Not Observed Observed

  22. Association Cause X Cause Driving Motorcycles Hepatitis C 6 Confounding Confounder Not Observed Observed

  23. Association Cause X Cause Playing Baseball Oral Cancer 7 Confounding Confounder Not Observed Observed

  24. Association Cause X Cause Skin Cancer Sand 8 Confounding Confounder Not Observed Observed

  25. Association Cause X Cause Eating Ice Cream Drowning 9 Confounding Confounder Not Observed Observed

  26. Scenario 2

  27. Had Bedsores 9% 824 79 745 No Bedsores 3% 8,576 8,290 286 Scenario Died Not Died Total Risks Relative Risk a b X 3 c d 90 Individuals with bedsores are 3 times more likely to die than those without bedsores.

  28. Cause Scenario 2 “If we can keep our patients from getting bedsores, then we can go a long way towards preventing hospital deaths.” “The study establishes a clear progression beginning with patients getting bed sores and ending with death.” Getting bedsores Death

  29. Confounding Is cause the only possible association between the two? 1. Cause 2. Chance 3. Bias 4. Reverse Time Order 5. Confounding

  30. Association Cause X Bedsores Deaths Cause Scenario 2 Not Observed ? Observed

  31. Not Observed Not Observed Wendy ? Association Association Cause Cause Observed Observed X X Bedsores Mark Broken Beer Bottles Death Cause Cause Scenarios Scenario 1 Scenario 2

  32. Association Cause X Bedsores Death Cause Scenario 2 Confounder Not Observed ? Observed

  33. Association Cause X Bedsores Death Cause Scenario 2 Brainstorm Not Observed ? Severity of Medical Condition Observed

  34. Definition Stratification A procedure which creates strata based on categories of the suspected confounding variable and examines the exposure-disease association within each stratum (subgroups).

  35. Stratification

  36. Had Bedsores 51.9% 106 55 51 No Bedsores 50.0% 19 5 5 Scenario 2 Stratified Patients with High Medical Severity Died Not Died Total Risks Relative Risk a b x1 c d 90 There is no association!!

  37. Had Bedsores 3.3% 718 24 694 No Bedsores 3.3% 8,566 281 8,285 Scenario 2 Stratified Patients with Low Medical Severity Died Not Died Total Risks Relative Risk a b x1 c d 90 There is no association!!

  38. High Severity 51.7% 116 60 56 Low Severity 3.2% 9,284 305 8,979 Scenario 2 Adjusted All Patients Based on Severity of Illness ONLY Died Not Died Total Risks Relative Risk a b x16 c d 90 The high relative risk show that severity of illness is a CONFOUNDER.

  39. Scenario 2 Summary – Relative Risk of Death

  40. Severity of Illness

  41. Group Practice

  42. Confounding Is the association due to confounding? 1. Cause 2. Chance Bias 3. 4. Reverse Time Order Confounding 5.

  43. Enduring Epidemiological Understandings 43 Teach Epidemiology

  44. Enduring Epidemiological Understandings Knowledge that “… is connected and organized, and … ‘conditionalized’ to specify the context in which it is applicable.” National Research Council , Learning and Understanding Teach Epidemiology

  45. Time Check 10:00 AM

  46. Teach Epidemiology Teach Epidemiology

  47. Teaching Epidemiology Group 6 Teach Epidemiology

  48. TYPES OF BIAS Using the definitions of the types of bias given, match the following phrases with the appropriate bias.

  49. Name the Bias • epidemiologist asks specific questions to case Information Bias

  50. Name the Bias • better memory recall Recall Bias