Epidemiology Kept Simple

1. Epidemiology Kept Simple Chapter 16: From Association to Causation Chapter 16

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 Chapter 16

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 Chapter 16

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? Chapter 16

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 studiesmust be considered • Statistical methodsalone cannot establish proof [Link to Surgeon General’s report] Chapter 16

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, 295-300. full text Chapter 16

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 Chapter 16

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 Chapter 16

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) Chapter 16

10. 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? Chapter 16

11. or this? Chapter 16

12. Element 5: Biological Gradient Increases in exposure dose  dose-response in risk Chapter 16

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 Chapter 16

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. Chapter 16

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 Chapter 16

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 Chapter 16