1. Chapter 4: Causation in Epidemiologic Investigation & Research Dr. Sri Kolluri 1

2. Causation and Causal Relationships in Epidemiology How to determine the cause of disease? ▫Examination of a causal relationship  Sufficient Cause: a cause that precedes the disease and if present, the disease will ALWAYS occur  Example: Genetic abnormalities: presence of an extra 21 st chromosome = down’s Syndrome  Necessary Cause: a cause that preceded the disease and if present, the disease MAY occur  Example: Typhoid Mary carried typhus but exhibited no symptoms, yet was able to spread the disease to others.  Carriers of diseases 2

3. More… Risk Factor: Is an exposure, behavior, or attribute that if present and active increases the probability of a disease in a group of people who have the risk factor. ▫Example: Heavy tobacco use among men is a risk factor for increased risk of lung cancer 3

4. And Yet Even More… Causal/Non-causal Associations: Are the associations between the disease/death and the presumed cause of that episode. ▫One must investigate associations in order to correctly determine that there is actually a viable cause and effect in play in terms of an epidemiological episode. 4

5. Associations… Statistically Significant Association: ▫This is when the difference between the control and case is large enough to matter or be unlikely or likely to have caused the disease  Unlikely is defined as likely to occur no more than one time in twenty potential opportunities ▫May be determined to be indirect or directly the cause. In order to make this determination, one must look at presence/absence of certain factors 5

6. Types of Association 1) Direct Causal Association occurs when the factor exerts an effect without other intermediary factors being present. ▫Example: a diagnosis of rabies in a person who has been bitten by a dog certified as rabid is made after a ten day quarantine and lab examination. If +ve test result then dog bite is the direct cause. 6

7. Types of Association 2) Indirect Causal Association occurs when one factor influences one or more factors that are directly or indirectly causal. ▫Example: A rural non-mobile African village is located 30 miles from the nearest medical facility.  Although the geographic location of the facility does not cause disease or death, the fact that no-one can get to the facility in time may cause death or prolonged illness and disease syndromes to occur. 7

8. Q) What caused the effect? A woman presents to the local ER with the complaint of head pain. This symptom was noted 3 hrs after falling off a stepstool in the kitchen and bumping her head. After radiographs are taken, a sub-scapular hematoma (i.e. bruise under the scalp) is noted. What is the direct cause of the effect? What is the indirect cause of the effect? 8

9. Answers to the Question Direct cause of the effect = bumping the head ▫The physical striking of the head caused the bruise. It is reasonable to assume that anytime you strike your head, there is going to be some form of bruising Indirect cause of the effect = falling off the stepstool ▫One can fall off of a stepstool without hitting ones head, also one can hit ones head without falling off a stepstool, the stepstool is an indirect cause to the effect and may or may not be present. 9

10. How to Determine Cause and Effect? Investigate statistical association ▫Please refer to pp. 68: Box 4-2: Statistical Association and Causality Investigation of Temporal Relationships ▫Proving that the cause happened before the effect, examination of time factor Elimination of all known alternative, reasonable explanations ▫The practice of R/O = rule out 10

11. Pitfalls to Causal Research There are many things that can slow or interfere with validating research into cause and effect 1) Bias: Most dangerous pitfall as it is a deviation or distortion of data or interpretation that goes in one particular direction.  Many times this is caused by the researcher or the subjects unknowingly influencing the outcome of the research  Many types of bias, refer to pp.69 Box 4-3 11

12. Pitfalls of Causal Research..contd. 2) Random Error: Something that happens randomly and unexpectedly for no reason, and shows up as unexpected highs or lows in the statistical analysis 3) Confounding: Confusion of two or more variables in such a way as to not to be able to separate out which is which, causing the data to be discarded 12

13. More Pitfalls of Causal Research 3) Synergism: an interaction of two variables that produces an effect that is greater together then than the separate effect of the variables 4) Effect Modification: Appearance of an unexpected third variable which affects the performance of the two accounted for variables 13

14. Question Is it possible for a causal effect to increase the risk for more than one disease process? 14

15. Answer YES 15

16. Any Questions? 16

17. Chapter 5 Common Research Designs of Epidemiology 17

18. Question What is the purpose of research design? 18

19. Purpose of Research Design is.. To generate a workable hypothesis To test the hypothesis To identify variables that may cause an effect to happen for the disease being studied To identify risk factors for the disease To minimize previously mentioned research pitfalls from occurring (i.e. bias, confounding, etc.) 19

20. Research Design Generating Hypothesis ▫Cross sectional surveys (interviews) ▫Cross sectional ecological surveys (behavior) ▫Longitudinal ecologic studies (on-going surveillance) 20

21. Research Design Testing of Hypothesis: 1) Cohort Studies: studies involving a clearly identified group of people/individuals  Ex: 30 men between the ages of 45-70 residing in Philadelphia identified for PSA testing  Ex: African American women tested for sickle cell anemia  Ex: White tailed deer captured for collection of Ixodes ticks to assess the presence of Lyme Disease 21

22. Types of Cohort Studies Prospective Cohort Studies: ▫The identification of a group of people/individuals on whom baseline (initial) data is collected after which the same data is collected over a long period of time  Ex: Framingham Heart Study – a study that has been on-going since 1950.  Can be expensive and time-consuming. 22

23. Types of Cohort Studies Retrospective Cohort Studies ▫Choosing a group of people in which something has already occurred and reviewing what their lives were like after the event. Ex: Study of people exposed to radiation after Chernobyl incident in Russia and looking at:  Their rate of carcinogenic developments post-exposure  Their death rates and causes  Their reproductive ability post-exposure 23

24. More Hypothesis Testing 2) Case-Control Studies ▫One group is given a drug for a condition the other is given a placebo. The group given the drug is the case group, the group given the placebo is the control group. The results of the administration of the drug/placebo is studied and compared. 24

25. Experimental Design # 1 Types of design that are used for testing hypothesis ▫Randomized Controlled Clinical Trials (therapeutic in nature)  Patients are assigned randomly to either the case group or the control group  This type of study is considered the “gold standard” for experimental design  May be single or double blind study (blind studies means the researcher and/or the patients are ignorant of which group they are in so as to avoid bias. 25

26. Experimental Design # 2 Randomized Controlled Field Trials (preventive in nature) ▫Consists of both a case and control group ▫Recipients of placebo or a drug that is designed to prevent something (i.e. vaccine) 26

27. Quiz Time What are some advantages to these two methods of experimental design? What are some disadvantages to these two methods of experimental design? 27

28. And Finally… Techniques for Data Summary: ▫Meta-analysis: Summation of the data obtained ▫Decision Analysis: Summation of data and illustration of how it can be used to change policy or clinical methodologies currently in place. ▫Cost Effective Analysis: Summation of data and illustration of financial gains/losses to be obtained by the new information. 28

29. The End QUESTIONS? 29