Models of Disease Causation - Understanding Disease Processes and Prevention

1. بسم الله الرحمن الرحيم

2. Models of Disease Causation Dr. Salwa Tayel Family and Community Medicine Department King Saud University

3. Learning objectives: At the end of this lecture you (will) be able to: • Explain basic models of disease causation. • Identify purpose of studying the disease process.

4. Purpose of studying causal models • Studying how different factors can lead to ill health is important to generate knowledge to help prevent and control diseases. • Quote Hippocrates "To know the causes of a disease and to understand the use of the various methods by which the disease may be prevented amounts to the same thing as being able to cure the disease". Dr. Salwa Tayel Causation&Association

5. General Models of Causation • In epidemiology, there are several models of disease causation that help understand disease process. • The most widely applied models are: • The epidemiological triad (triangle), • the wheel, and • the web. And • The sufficient cause and component causes models (Rothman’s component causes model) Dr. Salwa Tayel Causation&Association

6. The epidemiologic triad Model • The epidemiologic triangle or triad is the traditional model of infectious disease causation. • It has three components: an external agent, a susceptible host, and environmental factors that interrelate in a variety of complex ways to produce disease in humans. • When we search for causal relationships, we must look at all three components and analyze their interactions to find practical and effective prevention and control measures. Dr. Salwa Tayel Causation&Association

7. The Epidemiologic Triad HOST AGENT ENVIRONMENT Dr. Salwa Tayel Causation&Association

8. Agent factors • Infectious agents: agent might be microorganism—virus, bacterium, parasite, or other microbes. e.g. polio, measles, malaria, tuberculosis Generally, these agents must be present for disease to occur. • Nutritive: excesses or deficiencies (Cholesterol, vitamins, proteins) • Chemical agents: (carbon monoxide, drugs, medications) • Physical agents (Ionizing radiation,…

9. Host factors • Host factors are intrinsic factors that influence an individual’s exposure, susceptibility, or response to a causative agent. • Host factors that affect a person’s risk of exposure to an agent: • e.g. Age, race, sex, socioeconomic status, and behaviors (smoking, drug abuse, lifestyle, sexual practices and eating habits) • Host factors which affect susceptibility &response to an agent: • Age, genetic composition, nutritional and immunologic status, anatomic structure, presence of disease or medications, and psychological makeup.

10. Environmental factors Environmental factors are extrinsic factors which affect the agent and the opportunity for exposure. Environmental factors include: • physical factors such as geology, climate,.. • biologic factors such as insects that transmit an agent; and • socioeconomic factors such as crowding, sanitation, and the availability of health services.

11. Malaria Agent Vector Environment Host Dr. Salwa Tayel Causation&Association

12. The epidemiologic triad Model Host: Intrinsic factors, genetic, physiologic factors, psychological factors, immunity Health or Illness ? Agent: Amount, infectivity, pathogenicity, virulence, chemical composition, cell reproduction Environment: Physical, biological, social Dr. Salwa Tayel Causation&Association

13. Other Models of causation • Web of Causation is devised to address chronic disease – can also be applied to communicable disease) due to multi-factorial nature of causation in many diseases Dr. Salwa Tayel Causation&Association

14. Web of Causation • There is no single cause • Causes of disease are interacting • Illustrates the interconnectedness of possible causes Dr. Salwa Tayel Causation&Association

15. Web of Causation social organization phenotype behaviour microbes Disease genes environment workplace Unknown factors RS Bhopal

16. Web of Causation - CHD stress medications genetic susceptibility smoking lipids Disease gender physical activity Unknown factors inflammation blood pressure RS Bhopal

17. Example of a Web of Causation Overcrowding Malnutrition Exposure to Mycobacterium Susceptible Host Infection Tuberculosis Tissue Invasion and Reaction Vaccination Genetic Dr. Salwa Tayel Causation&Association

18. The Wheel of Causation • The Wheel of Causation de-emphasizes the agent as the sole cause of disease, • It emphasizes the interplay of physical, biological and social environments. It also brings genetics into the mix. Dr. Salwa Tayel Causation&Association

19. The Wheel of Causation Social Environment Biological Environment Host (human) Genetic Core Physical Environment Dr. Salwa Tayel Causation&Association

20. The sufficient cause and component causes model Rothman’s component causes model

21. Necessary and sufficient causes • A necessary cause is a causal factor whose presence is required for the occurrence of the effect. If disease does not develop without the factor being present, then we term the causative factor “necessary”.Agent in Malaria: plasmodium Falciparum parasite is necessary factor ( always present) such as A in the previous slide. • Sufficient cause is a “minimum set of conditions, factors or events needed to produce a given outcome. Usually there’s no sufficient factor “rare”.> Rabies is both necessary and sufficient. • The factors or conditions that form a sufficient cause are called component causes. Dr. Salwa Tayel Causation&Association

22. Example • The tubercle bacillus is required to cause tuberculosis but, alone, does not always cause it, • so tubercle bacillus is a necessary, not a sufficient, cause. Dr. Salwa Tayel Causation&Association

23. Rothman’s Component Causes and Causal Pies Model • Rothman's model has emphasised that the causes of disease comprise a collection of factors. • These factors represent pieces of a pie, the whole pie (combinations of factors) are the sufficient causes for a disease. • It shows that a disease may have more that one sufficient cause, with each sufficient cause being composed of several factors. Dr. Salwa Tayel Causation&Association

24. Rothman’sComponent Causes and Causal Pies • The factors represented by the pieces of the pie in this model are called component causes. • Each single component cause is rarely a sufficient cause by itself, But may be necessary cause. • Control of the disease could be achieved by removing one of the components in each "pie" and if there were a factor common to all "pies“ (necessary cause) the disease would be eliminated by removing that alone. Dr. Salwa Tayel Causation&Association

25. Exercise If a particular disease is caused by any of the three sufficient causes in the diagram. which components, if any, are a necessary cause? (Circle ALL that apply.) A. A B. B C. C D. D E. E F. F G. None

26. Causal pies representing all sufficient causes of a particular disease

27. Exercise • Some of the risk factors for heart disease are smoking, hypertension, obesity, diabetes, high cholesterol, inactivity, stress, and type A personality. - Are these risk factors necessary causes, sufficient causes, or component causes? none of them is necessary or sufficient, but each 1 of them is a component factor. Dr. SalwaTayelCausation&Association

28. Causation and Association • Causation - implies that there is a true mechanism that leads from exposure to disease • Epidemiology does not determine the cause of a disease in a given individual • Instead, we determine the relationship or association between a given exposure and frequency of disease in populations. Dr. Salwa Tayel Causation&Association

29. Association vs. Causation • Association is an identifiable relationship between an exposure and disease • Association implies that exposure might cause disease • Finding an association does not make it causal • We infer (assume) causation based upon the association and several other criteria. Dr. Salwa Tayel Causation&Association

30. Epidemiological criteria (guidelines) for causality • An association rarely reflects a causal relationship but it may. • Criteria for causality provide a way of reaching judgements on the likelihood of an association being causal. Dr. Salwa Tayel Causation&Association

31. Hill’s Criteria for Causal Relation • Strength of association • Consistency of findings • Specificity of association • Temporal sequence • Biological gradient (dose-response) • Biological plausibility • Coherence with established facts • Experimental evidence Dr. Salwa Tayel Causation&Association

32. Strength of association association • Does exposure to the cause change disease incidence? • The strength of the association is measured by the relative risk. • The stronger the association, the higher the likelihood of a causal relationship. • Strong associations are less likely to be caused by chance or bias Dr. Salwa Tayel Causation&Association

33. Consistency of findings • Consistency refers to the repeated observation of an association in different populations under different circumstances. • Causality is more likely when the association is repeated by other investigations conducted by different persons in different places, circumstances and time-frames, and using different research designs. Dr. Salwa Tayel Causation&Association

34. Specificity of association • It means that an exposure leads to a single or characteristic effect, or affects people with a specific susceptibility • easier to support causation when associations are specific, but • this may not always be the case • as many exposures cause multiple diseases • This is more feasible in infectious diseases than in non-infectious diseases, which can result from different risk agents. Dr. Salwa Tayel Causation&Association

35. Temporal sequence (temporality) • Did the cause precede the effect? • Temporality refers to the necessity that the cause must precede the disease in time. • This is the only absolutely essential criterion.  • It is easier to establish temporality in experimental and cohort studies than in case-control and cross-sectional studies. Dr. Salwa Tayel Causation&Association

36. Biological gradient • Does the disease incidence vary with the level of exposure? (dose-response relationship) • Changes in exposure are related to a trend in relative risk • A dose-response relationship (if present) can increase the likelihood of a causal association. Dr. Salwa Tayel Causation&Association

37. Biological gradient Dr. Salwa Tayel Causation&Association

38. Biological plausibility • Is there a logical mechanism by which the supposed cause can induce the effect? • Findings should not disagree with established understanding of biological processes. Dr. Salwa Tayel Causation&Association

39. Coherence • Coherence implies that a cause-and-effect interpretation for an association • does not conflict with what is known of the natural history and biology of the disease Dr. Salwa Tayel Causation&Association

40. Experimental evidence • It refers to evidence from laboratory experiments on animal or to evidence from human experiments • Causal understanding can be greatly advanced by laboratory and experimental observations. Dr. Salwa Tayel Causation&Association

41. Judging the causal basis of the association • No single study is sufficient for causal inference • It is always necessary to consider multiple alternate explanations before making conclusions about the causal relationship between any two items under investigation.  • Causal inference is not a simple process • consider weight of evidence • requires judgment and interpretation Dr. Salwa Tayel Causation&Association

42. Weigh up weaknesses in data and alternative explanations Weigh up quality of science and results of applying causal frameworks Figure 5.12 The scales of causal judgement Dr. Salwa Tayel Causation&Association

43. Pyramid of Associations Causal Non-causal Confounded Spurious / artefact Chance RS Bhopal

44. The End Thank You Website http://faculty.ksu.edu.sa/73234/default.aspx salwatayel@hotmail.com