1. Epidemiology Kept Simple
Chapter 16
4/16/2017
Epidemiology Kept Simple
Chapter 16: From Association to Causation
Gerstman
Chapter 16
From Association to Causation

2. Cause
Causal inference  the process of deriving cause-and-effect conclusions by reasoning from knowledge and factual evidence
“Proof” is impossible in empirical sciences.
However, causal statements can be made strong, or even overwhelming
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3. Idea #1: Causal mechanisms essential
Told ya’
Proof of causal mechanisms is essential for effective public health intervention
Consider the case of miasmas and cholera (from Chapter 1)
“For want of knowledge, efforts which have been made to oppose [cholera] have often had contrary effect.” – John Snow
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4. Idea #2: Discovery of Preventive Measure May Predate Identification of Definitive Cause
What if we waited until the mechanism was known before employing citrus?
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5. §16.2 Surgeon General’s Report on Smoking
Epi data must be coupled with clinical, pathological, and experimental data
Epi data must consider multiple variables
Multiple studies must be considered
Statistical methods alone cannot establish proof
[Link to Surgeon General’s report]
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6. Hill’s Inferential Framework
Consistency
Specificity
Temporality
Biological gradient
Plausibility
Coherence
Experimentation
Analogy
A. Bradford Hill
(1897–1991)
* Hill, A. B. (1965). The environment and disease: association or causation? Proceedings of the Royal Society of Medicine, 58, full text
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7. Element 1: Strength
Stronger associations are less easily explained away by confounding than weak associations
Ratio measures (e.g., RR, OR) quantify the strength of an association
Example: An RR of 10 provides stronger evidence than an RR of 2
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8. Element 2: Consistency
Consistency ≡ similar conclusions from diverse methods of study in different populations under a variety of circumstances
Example: The association between smoking and lung cancer was supported by ecological, cohort, and case-control done by independent investigators on different continents
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9. Element 3: Specificity
Specificity ≡ the exposure is linked to a specific effect or mechanism
Example: Smoking is not specific for lung cancer (it causes many other ailments, as well)
Aristotle
(384 – 322 BCE)
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10. Temporality ≡ exposure precedes disease in time
Element 4: Temporality
Temporality ≡ exposure precedes disease in time
Mandatory, but not easy to prove. For example, is the relationship between lead consumption and encephalopathy this?
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11. or this?
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12. Element 5: Biological Gradient
Increases in exposure dose  dose-response in risk
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13. Element 6: Plausibility
Plausibility ≡ appearing worthy of belief
The mechanism must be plausible in the face of known biological facts
However, all that is plausible is not always true
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14. Element 7: Coherence
Coherence ≡ facts stick together to form a coherent whole.
Example: Epidemiologic, pharmacokinetic, laboratory, clinical, and biological data create a cohesive picture about smoking and lung cancer.
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15. Element 8: Experimentation
Experimental evidence supports observational evidence
Both in vitro and in vivo experimentation
Experimentation is not often possible in humans
Animal models of human disease can help establish causality
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16. Element 9: Analogy
Similarities among things that are otherwise different
Considered a weak form of evidence
Example: Before the HIV was discovered, epidemiologists noticed that AIDS and Hepatitis B had analogous risk groups, suggesting similar types of agents and transmission
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