From association to causation

Objectives of lecture: • what is the cause concept of Association and Causation • types of association • does association implies causation • what are the types of causal factors What are the Hill’s criteria for causation.

- Purpose of Epidemiology? - Basic Question in Analytic Epidemiology Exposure Disease

Research Questions/Hypotheses Is there an association between Exposure (E) & Disease (D)? Hypothesis: Do persons with exposure have higher levels of disease than persons without exposure?

Incidence Ratio per 100,000 Women Per Capita Supply of Fat Calories Figure 13-4. Correlation between dietary fat intake and breast cancer by country. USA 250 Switzerland Canada Fed. Repub. Of Germany 200 Italy Israel UK Denmark Sweden France New Zealand Australia 150 Norway Finland Yugoslavia Spain Incidence Ratio per 100,000 Women Poland 100 Romania Hong Kong Hungary 50 Japan Per Capita Supply of Fat Calories 600 800 1000 1200 1400 1600 Prentice RL, Kakar F, Hursting S, et al: Aspects of the rationale for the Women’s Health Trial. J Natl Cancer Inst 80:802-814, 1988.)

DOES CORRELATION IMPLY CAUSATION? Correlation: it indicates degree of association. Association…… Do both invoke causation?

Types of Association: A real association (causal) is present if we succeed in reducing the risk of disease by lowering the exposure level. Spurious associations refer to non-causal associations due to chance, bias, failure to control (confounding), etc. e.g; Neonatal deaths at Home vs hosp delivery,

Interpreting Associations - Causal and Non-Causal Non-Causal (due to confounding) Causal Characteristic Under Study Characteristic Under Study Factor X Disease Disease

Types of real association: A) Negative Association (Inverse Relationship): higher levels of the risk factor are protective against the outcome. e.g. regular physical exercise and ischemic heart diseases B) Positive Association: The magnitudes of both variables appear to move together up or down. e.g. hypertension and ischemic heart diseases

Pyramid of Associations Causal Non-causal Confounded Spurious / artefact Chance

Association : the rate of disease in a persons with a specific exposure. statistical dependence between two variables, • • A causal association is one in which a change in the frequency or quality of the exposure results in a corresponding change in the frequency of the disease or outcome of interest.

What is a Cause? Causative factor: An event, condition, or characteristic without which the disease would not have occurred. Causative factor:

One pragmatic definition of a cause of a disease is an exposure which produces a regular and predictable change in the risk of the disease.  

A good epidemiologic exposure variable should…. Have an impact on health Be measureable Differentiate populations Generate testable hypotheses Help to prevent or control disease

ASSOCIATION VS CAUSATION To decide whether exposure A causes disease B, we must first find out whether the two variables are associated?

Clinical observations Available data (Ecological or Cross-sectional Studies) Case-control studies Cohort studies Randomized trials (only used to confirm causation

Ecologic study of per capita smoking and lung cancer incidence Surgeon Alton Ochsner observed that almost all lung cancer patients were smokers Ecologic study of per capita smoking and lung cancer incidence Case-control study of lung cancer patients versus those without lung cancer 39 cohort studies ?

Types of causal pathway: 1. Direct causation (with out any intermediate step). 2. Indirect causation (a factor causes a disease, but only through an intermediate steps). - Which one is always present in human biology? disease factor Step 1 Step 2 factor disease

Causal Factors in general: Necessary cause: The cause must be present for the outcome to happen. Sufficient cause: If the cause is present the outcome must occur. Rare or Common? Isolation/inclusion

Types of causal factors 1. Necessary and sufficient Without factor, disease does not develop Its presence is sufficient to initiate disease

2. ‘necessary but not sufficient’: causative factor, and enabling factors required Each factor is necessary but not sufficient to cause the disease. e.g: initiator + promoter Factor A Disease Factor B Factor C Carcinogenesis

3. “Sufficient but not necessary’: the factor alone can produce the disease, but so can other factors that are acting alone. Factor A OR Factor B DISEASE OR Factor C

4.Neither sufficient nor necessary Factor A Factor B OR Factor C Factor D DISEASE OR Factor E Factor F

CAUSAL INFERENCE 1. DETERMINISTIC CAUSALITY: as in necessary and sufficient causes. AR%= ? 2. PROBABILISTIC CAUSALITY : the web of causation, or chain of causation Characteristics??

Web of Causation Disease social organization phenotype behaviour microbes Disease genes environment Unknown factors workplace

genetic susceptibility Web of Causation - CHD stress medications genetic susceptibility smoking lipids CHD gender physical activity Unknown factors inflammation blood pressure

An attempt to discover WHICH THE CAUSE, OR whether TWO VARIABLES are associated, WE NEED: EPIDEMIOLOGICAL STUDIES, to?? Statistics, to?   Does Statistical analysis alone can constitute proof of a causal relationship? NO

MAKING CAUSAL INFERENCES The use of Hill’s causal criteria in making inferences from data.

Hill’s criteria for judging whether an association is causal Consideration of alternate explanations Reversibility of exposure Specificity of the association Study design Temporal relationship Strength of association Dose response relationship Consistency of the findings Biologic plausibility and Coherence with other knowledge

Temporal Sequence It means? The length of exposure is also important, Which study designs?

STRENGTH Is the association strong? Heavy smoking with lung cancer, Heavy smoking with CHD. The stronger the association the more likely it is to be truly causal. WHY?? small associations can be causal?

dose-response relationship relative risk increases with higher exposure dose. Years of exposure? Not necessary. Why? … threshold effect… unascertained exposure level … irrelevant to all exposures.

Consistency of Findings of Effect Does mean exact replication? Look for consistent findings across different populations in differing circumstances with different study designs Relationships that are demonstrated in multiple studies are more likely to be causal. Why? Smoking with lung cancer. contraceptives and breast cancer.

Plausibility and Coherence (ie., biologic credibility) • existence of biologic or social mechanistic model to explain the association e.g. Trinitrate → headache Fitness . • does it a provision?

EXAMPLE: Serological marker of hepatitis B infection is associated with elevated rates of liver cancer. Is supported by viral genome in many liver cancers. So… Hepatitis B infection is a true cause of liver cancer

By contrast, Reserpine was thought to be a cause of breast cancer. But, no supporting biological mechanism. Subsequent larger studies (no consistancy). So .. Causation not true.  

Consideration of alternate explanations - review of literatures for analogue. - depend on depth of knowledge.

Reversibility (cessation of exposure) : Removal of the exposure leads to decreased risk of outcome. e.g. . stop smoking leads to decreased risk of CHD. HOWEVER, in certain cases, the damage may be irreversible.

Specificity of the Association Is it a Provision? - H. Pylori? - smoking & lung cancer?

Study design : All of the study designs are important. The best evidence comes from?. Example: Smoking cessation programs result in lower lung cancer rates.

To put the studies in order according to power: Ability to " prove causation Type of study Strong Randomized controlled trial strong Other intervention study Moderate prospective cohort moderate Retrospective cohort Case-control Poor Cross-sectional study Ecological Very Poor Parametric study

Judging Causality Weigh quality Weigh weaknesses of science and results of causal models Weigh weaknesses in data and other explanations

Framework for the Interpretation of an Epidemiologic Study I Framework for the Interpretation of an Epidemiologic Study I. Is there a valid statistical association? • Due to chance? • Due to bias? • Due to confounding? II. Can this valid statistical association be judged to be one of cause and effect? • Is there a strong association? • Is there consistency with other studies? • Is the time sequence compatible? • Is there biologic credibility to the hypothesis? • Is there evidence of a dose-response relationship?

Why was it relatively easy to determine that smoking was a cause of lung cancer? Measurable. Used to classify persons accordingly. Lung cancer incidence in smokers is much greater than in nonsmokers.

Why will it be relatively hard to determine if community air pollution is a cause of lung cancer?