1. Causation Learning Objectives
To be able to discuss Different Theories of causation
Causation in Infectious vs. Chronic Disease
Modern view of causation
Original file -

2. Jay M. Fleisher MS, Ph.D.
Associate Professor, Nova Southeastern University
Studied at:
Columbia University School of Public Health MS Epidemiology
NYU Ph.D. Environmental Epidemiology/Biostatistics

3. Causation Two types of medical research
Bench work
Epidemiology
Bench work usually describes the underlying biology of disease
Epidemiology either tests the results of bench work on human populations or provides input to the biomedical scientist on what we still do not know
1. Bench or laboratory Science usually can control the environment the experiment is taking place in
- Control for diet, and environment Animal is in
2. Epidemiology cannot directly control for a human subjects environment
- Therefore Epi uses certain methods to study illness among populations and attempts to control for differences in the individual study subjects “environment”
- We do this using a combination of Methods of Study design and Statistical analyses

4. What does the term “ Causal” really mean?

5. Example #1 - HIV and AIDS
Epidemiology identifies new disease caused by defect in immune system
Bench science identifies the infectious agent
Epidemiological studies confirm that agent causes disease in humans
Causation is proven
1. Not everyone exposed to HIV seroconverts
2. Among health care workers, less that 1% of those exposed via needle sticks seroconvert
3. Why? WE DO NOT KNOW ALL THE REASONS
4. THEREFORE OUR KNOWLEDGE OF CAUSATION OF EVEN AIDS IS INCOMPLETE

6. Example #2 - What Causes an MI
Epidemiological studies combined with laboratory study identify risk factors
Cigarette smoking
Cholesterol
Elevated blood pressure
Stress
Family history
Obesity
Etc
Which of the above contribute the most risk
What are the relationships between risk factors
1. What is the ‘Cause” of an MI

7. Therefore: The issue of causation is not as simple as it first appears
Thus, the need for a unifying concept of causation

8. A Unifying Model of Causal Relationships

9. The 2 Components: Sufficient Cause Necessary Cause
precedes the disease
if the cause is present, the disease always occurs
Necessary Cause
if the cause is absent, the disease cannot occur
1. Using these 2 components of Causation, we can produce a unified frame work of causation that will encompass all Disease Processes

10. The 4 Models of Causal Relationships

11. 1. Necessary and Sufficient*
Only Factor A
Disease
1. If the Factor is Present, the Disease will Always Occur
2. Without the factor, the Disease NEVER develops
3. Most infectious diseases will not cause illness in everyone, and not all heavy smokers develop Lung Ca
3. Almost never exists in Medicine Except for certain types of genetic illness like Sickle cell Anemia, Downs Syndrome, and perhaps HIV -> AIDS
Sickle Cell Anemia
Genetic factors
* RARELY OCCUR

12. 2. Necessary but Not Sufficient
Factor A +
Factor B
Disease
1. Each factor necessary but not in itself sufficient to cause the illness in itself , all are necessary to cause disease, but individually, none are sufficient to cause the disease
2. Each Risk factor alone Cannot Cause Disease
2. Thus multiple factors are required often in a specified temporal sequence
3. EX: Carcinogenesis -> +
Factor C

13. 2. Necessary but Not Sufficient - Example
Initiation +
Latent Period
Cancer
1.Carcinogenesis is considered to be a multistage process involving Initiation and promotion
-Promoter damages the cell in some way
- theory of many hits to cell in order to produce the first Ca cell could comprise the Latent Period
Finally last hit on cell is the Promoter that turns cell into a Ca cell +
Promoter

14. 3. Sufficient but Not Necessary
Factor A
Factor B
Disease
1. In this model each risk factor Sufficient to cause disease, but not all risk factors necessary in disease causation ( If Factor C is absent, disease can still occur)
1. In this Model each risk factor can produce the illness without the other factors being present
2. Unlike the Concept of Necessary and Sufficient Model, the disease CAN develop without a specific Necessary cause
3. However, not really Sufficient because other co-factors either known or unknown are in the causal process
Factor C

15. 3. Sufficient but Not Necessary - Example
Ionizing Radiation or
Benzene
Leukemia
1. In this Model each risk factor can produce the illness without the other factors being present
2. If exposed to enough Radiation, other 2 Risk factors not necessary to cause the illness
Ionizing Radiation, Benzene exposure and possibly Electromagnetic fields can each cause Leukemia independently of each other
However, other co – factors in causal process e.e., not all exposed to benzene will get Leukemia or
Electromagnetic
Fields?

16. 4. Neither Sufficient Nor Necessary
Factor A +
Factor B
and/or +
Disease
Factor C
Factor D
and/or
1. Illustrative of most of today’s Chronic diseases
2. Risk Factors combine in ways we know little about to produce disease
3. Therefore, No single factor will cause the disease by itself ( None are Sufficient Causes), and not all are necessary for the disease to Occur ( only a few can cause disease) +
Factor E
Factor F

17. 4. Neither Sufficient Nor Necessary - Example
Smoking +
Cholesterol
and/or + MI
HBP
Fam. History
and/or
1. Which combination of Risk factors will cause an MI
2. Doesn’t have to be all of these risk factors
3. We just don’t know
4. If we look at the risk factors, none are sufficient by themselves, and not all are needed ( thus not all are necessary) +
Stress
Obesity

18. Therefore:
Concept of Necessary vs. Sufficient Causes provides a theoretical framework for causation of all disease
How do we actually assess whether a Risk Factor is indeed Causal

19. Criteria for Assessing Causation
Temporal relationship
Exposure precedes the disease
Strength of the Association
Measured by the Relative Risk ( either the Rate Ratio or the Odds Ratio)
Dose-response Relationship
As the dose of exposure increases the risk of disease also increases
Example: Cigarette Smoking and Lung Ca
Replication of the Findings
Results replicated in other studies
Biologic plausibility
Does the association fit with what we know about the underlying biology
Sometimes we know little or nothing about the undelieing biology ( “Black Box” epidemiology
Consistency
Alternative explanation eliminated
Cessation effects
Specificity of the Association
Dose-response
1. Temporal relationship: Exposure to Risk factor occurred before Illness onset
2. Biological Plausibility - Sometimes we know, sometimes we don’t
3. The relationship is verified by repeated studies
4. Alternate Explaination Eliminated: Hard to prove a negative
5. Cessation Effect: Risk Drops in absence of exposure to the risk factor
6. Strength of Association: usually measured via relative Risk.. Higher the relative Risk, more likely Causal
7. Specificity of the Association: Specific Exposure Associated with only 1 disease - throw back to Infectious disease theory - Not generally applicable as Shown by previous discussion of Frame Work of Causation
8. Dose response strong evidence for Causal relationship

20. Criteria for Assessing Causation
Biologic plausibility
Does the association fit with what we know about the underlying biology
Sometimes we know little or nothing about the underlying biology ( “Black Box” epidemiology)
Example – Asbestosis and Lung Ca.. Only have theory of mechanism
Consideration of Alternate Explanations
If knowledge exists, rule out or make sure studies took into account
Cessation of Exposure
If exposure is reduced or eliminated Risk will decline
Example Ex-Smokers
Specificity of the Association
A specific agent is associated with only 1 disease
OK for infectious agents but falls apart with many Risk Factors for Chronic Illness
Example: Cigarette Smoking associated with several diseases
1. Temporal relationship: Exposure to Risk factor occurred before Illness onset
2. Biological Plausibility - Sometimes we know, sometimes we don’t
3. The relationship is verified by repeated studies
4. Alternate Explaination Eliminated: Hard to prove a negative
5. Cessation Effect: Risk Drops in absence of exposure to the risk factor
6. Strength of Association: usually measured via relative Risk.. Higher the relative Risk, more likely Causal
7. Specificity of the Association: Specific Exposure Associated with only 1 disease - throw back to Infectious disease theory - Not generally applicable as Shown by previous discussion of Frame Work of Causation
8. Dose response strong evidence for Causal relationship

21. Relevant Web Sites