Causation Supplemental Summary - 2024-2025 PDF

CAUSATION First semester 2024-2025 Dr.Lama Rafieh,DDS,MPH. Week 8 Nature of cause Cause defined as “anything producing an effect or a result”. [Webster] In direct causation, A causes B without intermediate effects (very rare) In indirect causation,...

CAUSATION First semester 2024-2025 Dr.Lama Rafieh,DDS,MPH. Week 8 Nature of cause Cause defined as “anything producing an effect or a result”. [Webster] In direct causation, A causes B without intermediate effects (very rare) In indirect causation, A causes B, but with intermediate effects Primarily the cause or the causative factor must precede the outcome in time Rothman and Greenland (2005) have developed the idea of “multiple causation” They used the metaphor of a “causal pie” disease occurs only if a circle is completed by one or more component parts (e.g., a “pie” from a pie diagram) each of these “parts” or “pies” are cause for the disease. This concept indicates that it may be possible for a disease to occur by a combination of different factors in different conditions. Types of causes A necessary cause whose presence is required for the occurrence of the effect. Such a causal “pie” must be present; and the disease cannot occur in absence of this cause A sufficient cause is a complete causal mechanism that can be defined as a set of minimal conditions and events that inevitably produce disease. The term minimal implies that all the conditions or events are necessary. Each cause that contributes a pie to the circle under the sufficient cause model is a component cause.  Therefore, different component causes may contribute to disease causation, and it may be possible that for some diseases, there are no necessary causes even though several different sets of sufficient causes may exist. Some causes may be sufficient and not necessary, whereas some causes may be necessary, yet not sufficient. For example, although Mycobacterium tuberculosis is a necessary cause for tuberculosis, it is not sufficient because mere exposure to the organism will not produce disease; a component cause of compromised immunity is required. Together, these may be sufficient to cause the disease. Causal Inference It is common in scientific oral health literature to see most associations be interpreted as causal associations. Only if the association is considered to be true should the issue of potential causal association be explored. Hill’s Criteria: Nine criteria useful in establishing epidemiologic evidence of a causal relationship between a presumed cause and an effect: 1.Strength: The stronger the association, the stronger is the argument for potential causal association.(Strength of association means large relative risk) 2. Consistency: Has the association been repeatedly observed by different persons, in different places, circumstances, and times? (Consistency means repeatedly observed by different persons, in different places, circumstances, and times). 3. Specificity: If the association is limited to specific exposure and to a particular outcome, and there is no association between exposure and other diseases, then it is a strong argument in favor of causation.(specificity means that one cause leads to one outcome) 4. Temporality: The cause must precede the outcome. Hill’s Criteria: 5. Biological gradient: If the association is one which can reveal a biological gradient, or dose–response curve, then we should look most carefully for such evidence. dose-response relationship implies that the increase in exposure results in increased risk of disease. A stronger dose–response relationship strengthens the argument for causal association. 6. Plausibility: The association should be understandable in plausible terms. “It will be helpful if the causation we suspect is biologically plausible. (biological plausibility means that explanation of how the suspected factor under study is a causal, makes sense Remember, this depends upon the biological knowledge of the day.” Hill’s Criteria: 7. Coherence: “The cause-and-effect interpretation of our data should not seriously conflict with the generally known facts of the natural history and biology of the disease.”(coherence means that the causal conclusion should not contradict biological knowledge) 8. Experiment: “Occasionally it is possible to appeal to experimental, or semi-experimental, evidence.... Here the strongest support for the causation hypothesis may be revealed.”(provide experimental evidence ) 9. Analogy: “In some circumstances it would be fair to judge by analogy. (analogy means that cause & effect relationship already established for a similar exposure or disease) The hallmark of epidemiologic analysis is comparison The comparisons can be quantified by using such measures of association as risk ratios, rate ratios, and odds ratios. Risk Risk : is the probability of the occurrence of a disease or other health outcome of interest during a specified period. Measures of risk 1. Absolute measure of risk ( incidence rate , attack rate , prevelance rate ) 2.Relative Risk ( RR) 3.Attributable risk percentage (AR) Interpretuation RR=1 Risk of disease is the same in exposed and unexposed groups. Exposure is not associated with disease RR>1 Risk of disease is greater in exposed So exposure is a potential risk factor of getting disease RR 1 : means stronger association OR=1 : unrelated disease and exposure OR