The Epidemiological Approach to Causation (PDF)

20.11.2024 Learning Objectives The Epidemiological By the end of this lecture, students should be able to; Approach to Causation...

20.11.2024 Learning Objectives The Epidemiological By the end of this lecture, students should be able to; Approach to Causation Distinguish between association and a causal relationship Define and state the important characteristics of a cause. Association – Causation Describe the historical development of disease causation theories, including the germ theory and the web of causation. State the criteria of causality: Hill’s Criteria including their limitations. Prof. Dr. Sebahat Dilek TORUN Distinguish between a risk factor and a cause. M.D. PhD Define necessary cause, sufficient cause and multifactorial cause Department of Public Health [email protected] Describe the key elements of the sufficient-component cause model. 20.11.2024 Sebahat Dilek Torun 5 6 Epidemiology Introduction Epidemiological principles stand on two basic assumptions: Epidemiology is the study (scientific, systematic, data-driven) I. Human disease does not occur at random of the distribution (frequency, pattern) and determinants (causes, II. The disease and the factors that cause and prevent risk factors) of health-related states and events (not just diseases) in disease can be identified through a systematic specified populations (patient is community, individuals viewed investigation of population. collectively), and the application of (since epidemiology is a discipline within public health) this study to the control of health problems. Determining the causal relationship between a disease and suspected risk factors is a part of epidemiological research. Sebahat Dilek Torun 7 8 SP 1  20.11.2024 Desctiptive Studies Objectives of Epidemiology Identify disease problem in community 1. To determine the frequency of disease in the population. 2. To identify the etiology / cause and the relevant risk Relate to environment & host factor factors of a disease. 3. To study the natural history and prognosis of disease. Suggest an etiological hypothesis 4. To evaluate both existing and newly developed preventive and therapeutic measures and modes of health care delivery. 5. To provide the foundation for developing public policy relating to Analytical & Experimental Studies environmental problems, genetic issues, and other considerations regarding disease prevention and health promotion. Test the hypothesis derived for observed RELATIONSHIP between suspected cause and disease Sebahat Dilek Torun 9 10 Introduction Risk Factors The Study Question : A condition, quality or attribute, the presence of which increases the – An epidemiologic investigation ⇒ etiology of disease chances of an individual to have, develop or be adversely affected by Study hypothesis : a disease process. – A specific statement regarding the relationship between two An attribute or exposure that is significantly associated with the variables: exposure and outcome (disease) development of a disease OR a determinant that can be modified An epidemiologic study ⇒ test the hypothesis of association between exposure and outcome. by intervention, thereby reducing the possibility of occurrence of If there is an association, the exposure is called a risk factor of the disease disease or other specified outcomes. A risk factor can be either: not necessarily the cause of a disease, but it – A predictor : such as employment in a specific industry or increases the likelihood that a person – A causal factor : such as exposure to benzene at work Sebahat Dilek Torun exposed to the factor will develop the disease 11 12 2  20.11.2024 Risk Factors Risk factors True or not ? Risk factors Modifiable Non-modifiable appropriate to intervention cannot be changed PRESENCE = disease will occur useful in the care of the individual E.g. age, sex, race family history and E.g. smoking, lack of physical activity,… genetic background,… ABSENCE = disease will not occur signals in alerting Sebahat Dilek Torun 13 15 Epidemiological methods are needed to Definitions of a “Cause ” identify risk factors and estimate the degree of risk. (e.g., case-control and cohort studies…) A cause is something that produces ‘an effect, result or consequence’ or ‘is responsible for an action or result, such as detection of risk factors a person, event or condition.’ = a start to prevention or intervention “reason” and “occasion.” For each risk factor determined, ask : – Can it can be reduced in a cost-effective way ? – Does its reduction will prevent or delay the unwanted outcome? Sebahat Dilek Torun 18 22 3  20.11.2024 Definitions of a “Cause ” Risk Factors vs Causes The term "risk factor" Epidemiology: used to indicate a factor that is associated with a given outcome. “ a cause of a disease is an event, condition or characteristic that preceded the disease onset and without which the disease Table : Risk Factors for Breast Cancer would not have occurred at all or would not have occurred until some later time.” (Rothman and Greenland) “something that makes a difference.”(Susser) Sebahat Dilek Torun Sebahat Dilek Torun 23 24 Causes of an automobile fatality… Key Characteristics of Causes The direct causes Essential attributes are: association, time order, directionality the speed of the car, Can be either a host or environmental factor (e.g. presence of hazardous road characteristics, conditions, actions of individuals, events, natural, social conditions, or economic phenomena) the time of day, May be positive (presence of a causative exposure induces disease) level of traffic, and or negative (lack of a preventive exposure induces disease) mental state of the driver. include active agents and static conditions. These factors are more proximate to “that which produces an effect, result, or consequence” than the breast cancer risk factors. Sebahat Dilek Torun Sebahat Dilek Torun From : Essentials of Epidemiology in Public Health 4th Ed [Ann Aschengrau] 2019 25 27 4  20.11.2024 Essential Attributes of True Causes (Susser) Association 1. Association: a relationship or a connection between a certain exposure and a – variation in a causal factor must result in a change in probability of certain outcome (disease) or health event. the outcome: if X changes, Y changes 2. Time order : The frequency of the disease differs based on the presence or – a cause must precede the effect; can be either proximate (e.g.; food absence of the exposure of interest. poisoning) or distant (e.g.; carcinogen) Measures of association : Relative Risk , Odds Ratio 3. Directionality: asymmetrical relationship b/w the cause and effect A cause must be associated with the outcome, but simply Exposure Outcome demonstrating an association is not enough for Causation ! Sebahat Dilek Torun Sebahat Dilek Torun 28 30 Why is it important to establish or exclude causality? Exposure and Outcome Association to understand the determinants of disease occurrence, “Is it real?” distribution and outcome Observed statistical association between a certain outcome and the hypothesized exposure may be: to identify links in the causal chain that can be intervened through general or specific intervention programmes 1. real association (causal or non-causal) to relate the output and impact of intervention programs to 2. a matter of chance their input, i.e. a causal evaluation. 3. result of bias 4. effect of confounding Sebahat Dilek Torun Sebahat Dilek Torun 32 33 5  20.11.2024 Types of Association YES = non-causal association Causal Non-causal Association Association p value ? Direct Indirect Interaction *Chance causal causal causal association association association *Counfounder exposure to lead *Bias → lead poisoning iodine deficiency *Based on ecological correlation → goitre → thyroid adenoma Sebahat Dilek Torun 34 37 Concept of Causation Germ Theory of Disease microorganisms demonstration! ✓ Proposed by Louis Pasteur and Robert Koch Disease agent → Human → Disease (one-to-one relationship) Theories untill the end of 18th century …. –Supernatural theory (Evil spirits ) ✓ Limitations … –Theory of humors by Greek and Indians TB ??? beta-haemolytic streptococci ??? –Theory of contagion (contact with the sick) –The miasmatic theory (Bad air/poisonous) Healthy carriers of typhoid ??? –Theory of spontaneous generation etc 38 39 6  20.11.2024 Theories of Multifactorial Causation (General Models of Causation) Epidemiological Triad Epidemiological (Ecological) Triad Physical Environment Environment Biological Environment Social Environment Web-of Causation Cultural Environment Wheel of Causation Agent Host Biological Intrinsic Characteristics (İmmunity) The sufficient cause and component causes models Socio-demographic Factors Chemical (Rothman’s component causes model) Physical Psycho-social Factors 40 41 surroundings and conditions Homeostatic Balance Advanced Model of external to the human or animal that cause or allow Epidemiologic Triad disease transmission H A A H Time : E E – incubation periods, Agent becomes more A H The proportion of – life expectancy of the pathogenic susceptibles in population host or the pathogen, increases and E H – duration of the course At equilibrium A of illness or condition. steady rate A H E E Environmental changes the cause of an organism that that favor the agent Environmental changes that alter host disease harbours the disease susceptibility 43 44 7  20.11.2024 Web of Causation Web of causation for Myocardial Infarction (MI) Aging and Changes in life style Stress other factors Ideally suited in the study of non- Lack of Physical Emotional Plenty of food Smoking communicable diseases (NCDs) intake exercise disturbances where the disease agent is often not known, but is the outcome of Obesity Hypertension interaction of multiple factors. Increased cathecolamines Considers Hyperlipidemia trombotic Changes in walls of arteries tendency – all the predisposing factors of any type and Coronary atheosclerosis Coronary Occlusion – their complex interrelationship with each other. Myocardial Ischemia Myocardial Infarction 47 49 Wheel of Causation Environmental The sizes of the different components of the wheel depend component upon specific disease entities. Disease visualized in form of wheel. Genetic A hub representing the host component The core representing the genetic Host component The surrounding peripheral portion representing the environment : - Social - Biological - Physical 50 51 8  20.11.2024 Sufficient - Component Cause Model (Rothman) provides a practical view of causation which also has a sound theoretical basis. has similarities to the "web of causation" theory more developed in the sense that it simultaneously provides a general model for the conditions necessary to cause (and prevent) disease in a single individual and for the epidemiological study of the causes of disease among groups of individuals. Sebahat Dilek Torun 53 54 Under this model a disease can be caused by any completed "pie," Sufficient cause : which is itself comprised of component causes of the disease under combination of factors that will inevitably produce a disease outcome investigation. (Causal pie) Causes which are present in every "pie" are called "necessary" “minimum” set of conditions, factors or events needed to produce a causes, causes which are the only component of a "pie" are called given outcome. "sufficient" causes, and causes which are neither necessary nor Usually there’s no one sufficient factor “rare”. sufficient are called "component" causes. Component causes : factors or conditions that contribute towards the disease outcome/ form a sufficient cause (Pieces of the pie) – not sufficient to cause disease on its own Necessary cause - causal factor whose presence is required for the occurrence of the effect. (disease does not develop without the presence of the Sebahat Dilek Torun causatve factor) Sebahat Dilek Torun 55 56 9  20.11.2024 Sufficient Cause for AIDS Sufficient-Component Cause Model to TB pie chart representing the sufficient cause model for AIDS Sebahat Dilek Torun (I) Sebahat Dilek Torun 57 59 (II) (III) Exposure to TB necessary, but not solely sufficient component. Sebahat Dilek Torun Sebahat Dilek Torun 60 61 10  20.11.2024 Rothman’s Component Causes and Causal Pies Model Sebahat Dilek Torun a disease with three sufficient causes 63 64 Features of the Sufficient-Component Cause Model Features of the Sufficient-Component Cause Model A cause is not a single component, but a minimal set of A component cause that must be present in every sufficient conditions or events that inevitably produces the outcome cause of a given outcome is referred to as a necessary cause Each component in a sufficient cause is called a component The completion of a sufficient cause is synonymous with the cause. biologic occurrence of the outcome – The outcome will not occur by that pathway if any one of e.g. natural progression from HIV infection to an AIDS diagnosis the components is missing (blocked or prevented) The components of a sufficient cause do not need to act – it is not necessary to identify all of the component causes in order to prevent the disease outcome simultaneously; they can act at different times. e.g. action of causal components of breast cancer spans nearly a There may be a number of sufficient causes for a given disease woman’s entire lifetime or outcome Sebahat Dilek Torun Sebahat Dilek Torun 66 67 11  20.11.2024 Types of Causal Relationships Necessary and Sufficient a factor is both necessary and sufficient for producing the disease Without that factor, the disease never develops (necessary), in the presence of that factor, the disease always develops (sufficient) If a relationship is causal, four types of causal relationships are possible: rarely if ever occurs 1. Necessary and Sufficient 2. Necessary, but not Sufficient 3. Sufficient, but not Necessary 4. Neither Sufficient nor Necessary Gordis Epidemiology Sebahat Dilek Torun 68 69 Necessary, but Not Sufficient Sufficient but Not Necessary each factor is necessary, but not in itself, sufficient to cause the disease the factor alone can produce the disease but so can other multiple factors are required, often in a specific temporal sequence factors that are acting alone – Carcinogenesis - a promoter e.g. either radiation exposure or benzene exposure – Tuberculosis -tubercle bacillus → leukemia without the presence of the other – noncardia gastric adenocarcinoma - Helicobacter pylori the criterion of sufficient is rarely met by a single factor Sebahat Dilek Torun Sebahat Dilek Torun 70 71 12  20.11.2024 Neither Sufficient Nor Necessary a factor by itself is neither sufficient nor necessary to produce disease more complex model, which probably most accurately represents the Guidelines for Judging Whether causal relationships that operate in most chronic diseases. an Association Is Causal Sebahat Dilek Torun Sebahat Dilek Torun 72 75 Criteria for Causal Association Temporality 1964- Surgeon General Report 1965- Hill’s Criteria Presence of causal attribute must precede the disease or unfavorable 1. Consistency 1. Strength of association outcome in time is absolutely essential. 2. Strength 2. Consistency Exposure to the factor must have occurred before the disease developed - Dose-response 3. Specificity Length of interval between exposure and disease very important 3. Specificity 4. Temporality If the disease develops in a period of time too soon after exposure, 5. Dose-response the causal relationship ??? 4. Temporality 6. Biological plausibility 5. Coherence 7. Coherence Lack of temporality rules out causality !!! 8. Experimental evidence 9. Analogy Sebahat Dilek Torun Sebahat Dilek Torun 76 78 13  20.11.2024 Temporality : Mandatory, but not easy to prove ! Strength of association E.g. is the relationship between lead consumption and encephalopathy this? Ratio measures (e.g., RR, OR) quantify the strength of an association. With increasing level of exposure to the risk factor an increase in incidence of the disease is found causal relationships more likely to demonstrate strong associations than non-causal, but; – weak associations should not be taken as an indication of non-causality. – a strong association alone is not an indicative of causality Sebahat Dilek Torun Sebahat Dilek Torun 79 80 Consistency Specificity ▪ Reproducibility of results in various populations and situations A one-to-one relationship between the cause and effect. ▪ generally used to rule out other explanations of outcome development e.g.certain pathogens are necessary to produce a specific disease. ▪ the greater the consistency, the more likely a causal association. ▪ Lack of consistency does not rule out a causal association as some Invalid in a number of instances causal agents are causal only in the presence of other co-factors. – Not everyone who smokes develop Lung Cancer, – Not everyone who develops cancer has smoked. – smoking does not lead only to lung carcinogenesis but to a numerous of other clinical disorders Lack of specificity does not rule out causation. Sebahat Dilek Torun Sebahat Dilek Torun 81 82 14  20.11.2024 Dose-Response Relationship Coherence of the Association As the dose of exposure increases, the association coherent with the risk of disease also increases. known facts of relevant origins: If present → strong evidence for a causal relationship. Epidemiologic, pharmacokinetic, laboratory, clinical, and biological Absence does not necessarily rule out a data create a cohesive picture causal relationship about smoking and lung cancer – a threshold may exist, no disease may develop up to a certain level of exposure Fig. Male and Female differences in trends of lung cancer deaths is coherent with recent adoption of cigarette smoking by women Sebahat Dilek Torun Sebahat Dilek Torun 83 84 Experimental Evidence Consideration of Alternate Explanations Experimental evidence supports observational evidence In judging whether a reported association is causal, the extent Both in vitro and in vivo experimentation to which the investigators have taken other possible Experimentation is not often possible in humans explanations into account and the extent to which they have Animal models of human disease can help establish causality ruled out such explanations are important considerations. Sebahat Dilek Torun Sebahat Dilek Torun 86 91 15  20.11.2024 Any Contributions or Questions ? Thank you for your patience and attention Sebahat Dilek Torun Sebahat Dilek Torun 92 93 16