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Association and causation

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dentistry

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Association and causation

  1. 1. Association and Causation Seminar:6/15 By Dr.B.S.Manoranjitha 2ndyear PG Dept. Of Public health dentistry MSRDC 1
  2. 2. Contents Introduction Approaches for studying disease etiology Approaches to etiology in human population Association and its types Types of causal pathways Types of causal relationships Evidence for a causal relationship Guidelines for judging whether an association is causal Conclusion 2
  3. 3. Introduction • Epidemiology aims at promotion of health by discovering the causes of diseases & ways to prevent and control. • Ascertainment of cause-effect relationships is one of the central and most difficult tasks of all scientific activities. • Epidemiological principles stand on two basic assumptions: 1. Human disease does not occur at random. 3
  4. 4. Introduction contd.. 2. The disease, its cause as well as preventive factors can be identified by a thorough investigation of population. • Hence, identification of causal relationship between a disease and suspected risk factors forms part of epidemiological research. 4
  5. 5. Approaches for studying disease etiology • Expose animals to risk factors such as carcinogens - lab Control the exposure dose Other environmental conditions and genetic factors Keep loss to follow-up to a minimum • Generalizability? • Cell culture or organ culture- in vitro. 5
  6. 6. Approaches to etiology in human population • Unplanned or natural experiments  People exposed to risk for non-study purposes  E.g. Exposure to atomic bomb radiation in Hiroshima and Nagasaki 1945  Occupational cohorts in specific industries Clinical observation Available data Case control studies Cohort studies Randomized trials 6
  7. 7. Approaches to etiology in human population contd.. • Conceptually, a two step process is followed in carrying out studies and evaluating evidence  Determining association or correlation between an exposure or characteristics and the risk of a disease • If association exist – determine whether the observed association is likely to be a causal one 7
  8. 8. Association • An association is said to exist between two variables when a change in one variable parallels or coincides with a change in another. This is also called ‘covariation’ or ‘correlation’. • Correlation indicates the degree of association between two variables 8
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  11. 11. Association contd.. • An association is said to be causal when it can be proved that a change in the independent variable (exposure) produces a change in the dependent variable (disease). • A causal relationship - exposure enters into the causation of disease. • Causation implies association, but association does not imply causation 11
  12. 12. Types of association Associations Non Causal Causal 12
  13. 13. Types of association contd.. • Real or spurious associations? • McMahon’s study: observed association of coffee consumption with risk of pancreatic cancer Coffee Drinking Pancreatic Cancer Causal association Coffee Drinking Smoking Pancreatic Cancer Non-causal association (due to confounding 13
  14. 14. • Distinction of association due to causal relationship and due confounding - really important - clinical and public health. • If the relationship is causal - succeed ↓ risk of pancreatic cancer if we lower coffee drinking. • But if its due to confounding, ↑ risk of pancreatic cancer is due to smoking. And changing the coffee drinking habit – no effect. Types of association contd.. 14
  15. 15. Types of Causal pathway 15
  16. 16. Types of causal relationships • Necessary and sufficient: Each factor is both necessary and sufficient for producing the disease. • Without that factor, the disease never develops( necessary) and in the presence of that factor, the disease always develops.( sufficient) • E.g. HIV virus and AIDS FACTOR A DISEASE 16
  17. 17. Types of causal relationships contd.. • Necessary but not sufficient • Each factor is necessary but not, in itself, sufficient to cause the disease .Thus, multiple factors are required, often in a specific temporal sequence. • E.g. Carcinogenesis- a multistage process involving both initiation and promotion. 17
  18. 18. • Sufficient but not necessary: The factor alone can produce the disease, so can other factors - acting alone • E.g. Either radiation or benzene exposure can each produce leukemia without the presence of the other. • However, cancer does not develop – everyone- experienced radiation or benzene exposure. Thus, criterion of sufficient is rarely met by a single factor. Types of causal relationships contd.. 18
  19. 19. • Neither sufficient nor necessary: • A factor by itself, is neither sufficient nor necessary to produce disease • More complex model, most accurately represents the causal relationships that operate in most chronic diseases. Types of causal relationships contd.. 19
  20. 20. Evidence for a causal relationship In 1840, Henle proposed postulates for causation - expanded by Koch in the 1880s. 1. The organism is always found with the disease. 2. The organism is not found with any other disease. 3. The organism, isolated from one who has the disease, and cultured through several generations, produces the disease (in experimental animals). 20
  21. 21. • Koch added that “Even when an infectious disease cannot be transmitted to animals, ‘regular’ and ‘exclusive’ presence of the organism proves a causal relationship.” • Postulates, though not perfect, useful - infectious diseases • Noninfectious diseases increasing importance - 20th century, • Strong evidence for non infectious diseases?? 21
  22. 22. Guidelines for Judging Whether an Association Is Causal- Bradford Hill (1964) 1. Temporal relationship 2. Strength of the association 3. Dose-response relationship 4. Replication of the findings 5. Biologic plausibility 6. Consideration of alternate explanations 7. Cessation of exposure 8. Consistency with other knowledge 9. Specificity of the association 22
  23. 23. Guidelines contd.. Temporal association • Causal attribute must precede the disease • E.g. Drinking contaminated water and occurrence of diarrhea • Length of interval between exposure and disease – important • E.g. Asbestos exposure takes 20 years to cause disease 23
  24. 24. Strength Of The Association • Relationship between cause and disease - strong or weak. • With ↑ level of exposure to the risk factor an increase in incidence of the disease is found. • Strong associations - likely to be causal. • Weaker associations - undetected bias, confounding • But weaker association does not rule out causation. Guidelines contd.. 24
  25. 25. • Strength of association can be estimated by relative risk, odds ratio. Relative Risk = Incidence among Exposed Incidence among Non Exposed RR = 1 No association RR > 1 Positive association (possibly causal) RR < 1 Negative association (possibly protective)  It is direct measure of the strength of association. Guidelines contd.. 25
  26. 26. Odds Ratio Cases(with disease) Controls (without disease) H/O of exposure a b No H/O exposure c d Odds Ratio = OR = ad/bc Odds that a case was exposed Odds that a control was exposed Guidelines contd.. 26
  27. 27. • Which cases odds ratio is an estimate of relative risk?  The disease of interest should be a rare disease.  The “controls” should be “representative” of the same total population that gave rise to the “cases”. Guidelines contd.. 27
  28. 28. • As the dose of exposure ↑, the risk of disease also ↑ • If a dose-response relationship is present - strong evidence for a causal relationship. • However, absence of a dose-response relationship does not necessarily rule out a causal relationship. • Some cases in which a threshold may exist, no disease may develop - a threshold; above this level – disease. Dose-Response Relationship Guidelines contd.. 28
  29. 29. Replication of the findings • If relationship is causal- it should be consistent in different studies and in different populations, subgroups as well, unless clear reason to expect different results. Guidelines contd.. 29
  30. 30. Biologic Plausibility Of The Association • It refers to coherence with current body of basic knowledge. • Sometimes the lack of plausibility may simply be due to the lack of sufficient knowledge about the pathogenesis of a disease. 30 Guidelines contd..
  31. 31. Consideration of Alternate Explanations • Interprets an observed association - relationship is causal or is the result of confounding. • The extent to which the investigators have taken other possible explanations into account and ruled out such explanations are important considerations. Guidelines contd.. 31
  32. 32. Cessation of Exposure • If a factor is a cause of a disease, we would expect the risk of the disease to decline when exposure to the factor is reduced or eliminated. Provide supporting evidence. Guidelines contd.. 32
  33. 33. Cessation of Exposure contd.. • In few cases, pathogenic process - irreversibly initiated and disease occurrence determined by time the exposure is removed. E.g. Emphysema not reversed by cessation of smoking- progression is reduced. 33
  34. 34. Consistency with other knowledge • If relationship is causal- findings should be consistent with other data. Guidelines contd.. 34
  35. 35. Specificity of the association • Certain exposure is associated with only one disease • The weakest point of the guideline • Provides additional support for a causal inference. • Absence of specificity in no way negates a causal relationship Guidelines contd.. 35
  36. 36. Deriving causal inferences: Example • Till 1980’s major cause of peptic ulcer – life style related disease and smoking. • 1984 – Marshall and Warren – observed small curved bacteria in lower stomach of patients with gastritis and peptic ulcers. • Bacteria- cultivated from several biopsies. Organism present in almost all patients with gastric inflammation and peptic ulcer. 36
  37. 37. Assessment of the Evidence Suggesting Helicobacter pylori as a Causative Agent of Duodenal Ulcers 1. Temporal relationship. • About 11% of chronic gastritis patients → duodenal ulcers over a 10-year period. 2. Strength of the relationship. • H.pylori found - 90% of patients with duodenal ulcer. 3. Dose-response relationship. • Density of H. pylori per mm² of gastric mucosa - higher in duodenal ulcer patients. 37
  38. 38. Assessment of the Evidence contd.. 4. Replication of the findings • Many of the observations – H. pylori - replicated repeatedly. 5. Consideration of alternate explanations. • Smoking ↑ risk of duodenal ulcer – H. pylori infected patients but not a risk factor – H.pylori eradicated patients 38
  39. 39. 6. Biologic plausibility. • Earlier - difficult to envision bacterium infecting the stomach antrum causing ulcers in the duodenum, now recognized – H. pylori - binding sites on antral cells. • Induces mediators of inflammation. • Infected mucosa – weakened, susceptible to damaging effects of acid. Assessment of the Evidence contd.. 39
  40. 40. 7. Cessation of exposure. • Eradication - heals duodenal ulcers at the same rate as histamine receptor antagonists. • Long-term ulcer recurrence rates - zero after H.pylori was eradicated using triple-antimicrobial therapy,. Assessment of the Evidence contd.. 40
  41. 41. 8. Specificity of the association. • Prevalence of H.pylori in duodenal ulcers patients - 90% to 100%. 9. Consistency with other knowledge. • High prevalence of ulcer disease in latter part of 19th century, consistent with high prevalence of H pylori due to poor living conditions at the same period. Assessment of the Evidence contd.. 41
  42. 42. Conclusion • Apart from outbreak investigations, no single study is capable of establishing a causal relation. • Results from epidemiological studies are often used as inputs. • It is thus important for public health and policy makers to understand the fundamentals of causal inference. • Those decisions should be based on a careful consideration of the entire relevant scientific literature 46
  43. 43. References • Gordis L. Textbook of Epidemiology, 3rd Edition, Elsevier • WHO research methodology. Second edition. • Park K, Textbook of Preventive and Social medicine, 23rd edition, • R. Beaglehole & Bonita, Basic Epidemiology, 4th edition • AFMC WHO – Text book of Public Health and Community Medicine – Rajvir Balwar – 1st edition 47
  44. 44. • Raj Bhopal : Cause and effect: the epidemiological approach • Boffetta P. Causation in the Presence of Weak Associations. Crit Rev Food Sci Nutr. 2010 Dec; 50(s1) • Parascandola M, Weed DL. Causation in epidemiology. J Epidemiol Community Health 2001;55:905–12. 48
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