Lecture 14.

Question 1

Is Knowledge of the complete pathway of a dis-ease a prerequisite for introducing preventive measures?

Answer 1

No.

Question 2

Must All Bradford Hill criteria be fulfilled to determine causality?

Answer 2

No. They act as a guide

Question 3

what are the benefits of the population health framework?

Answer 3

Provide the maximum benefit for the largest number of
people, at the same time reducing inequities in the distribution
of health and wellbeing

Question 4

An important role of epidemiology is to

Answer 4

seek the cause of “dis-ease”

Epidemiology does not determine the cause of a disease in a given individual

Instead, it determines the relationship or association between a given exposure and dis-ease outcome in populations

Question 5

does a preventative action need to be taken after a cause has been identified?

Answer 5

No. Can be taken before the cause is identified( eg cholera & scurvy)

Question 6

James Lind’s experiment is

Answer 6

an example of early RCT

attempted to find the cure for scurvy amongst sailors( citrus fruit)

Question 7

Can causality be proven in human studies?

Answer 7

Often no, because of ethical reasons. ( especially when trying to prove if something causes a bad outcome(disease death) and it is known to be harmful. )

Question 8

Bradford Hill Framework

Answer 8

Aid to determining a causal relationship

1. Temporality
2. Strength of association
3. Consistency of association
4. Biological gradient (dose-response)
5. Biological plausibility of association
6. Specificity of association
7. Reversibility

Question 8

Bradford Hill Framework

Answer 8

1. Temporality
2. Strength of association
3. Consistency of association
4. Biological gradient (dose-response)
5. Biological plausibility of association
6. Specificity of association
7. Reversibility

Question 9

Temporality

Answer 9

• First the cause then the disease

- Essential to establish a causal relation

Question 10

Strength of association

Answer 10

• The stronger an association, the more likely to be causal in absence of known
  biases (selection, information, and confounding)

Question 11

Consistency of association

Answer 11

• Replication of the findings by different
  investigators, at different times, in
  different places, with different methods

Multiple studies have
shown similar results

Question 12

Biological gradient (dose-response)

Answer 12

• Incremental change in disease rates in
  conjunction with corresponding changes in exposure

Question 13

Biological plausibility of association

Answer 13

• Does the association make sense biologically?

Chemicals in tobacco that are known
to promote cancers (carcinogens)

Question 14

Specificity of association

Answer 14

A cause leads to a single effect or an effect
has a single cause
 However, health issues have multiple, interacting causes and many outcomes share causes

Question 15

Reversibility

Answer 15

The demonstration that under controlled conditions changing the exposure causes a change in the outcome

Question 16

sufficient cause

Answer 16

• The whole pie
• A minimum set of conditions without any one
of which the disease would not occur
• Not usually a single factor, often several
• A disease may have several sufficient causes
(several pies can produce the same disease)

Question 17

Component cause

Answer 17

• Each factor or slice is a component cause
• A factor that contributes towards dis-ease
causation, but is not sufficient to cause dis-ease on
it’s own
• Component causes “interact” to produce disease

Question 18

Necessary cause

Answer 18

• A factor (or component cause) that must be present if a specific dis-ease is to occur.
• A component cause will be a necessary cause for some diseases

Question 19

The problems with the causal pie model:

Answer 19

• Fails to capture dose-response relations as a continuum
• Assumes that all causes are deterministic
• A causes B means that whenever A occurs, B occurs

Question 20

Probabilistic concept of causation

Answer 20

• A cause increases the probability (or chance) that its effect will occur
e.g., smoking increases the probability of lung cancer
• Does not exclude necessary and sufficient causes
• Probability of an effect/outcome occurring
• A sufficient cause raises the probability to 1
• A necessary cause raises that probability from 0
• Each component cause contributes toward the probability
from 0 to 1.
• Fits well with public health goals of epidemiology (considers
environmental factors, group-level effects)

Question 21

Counterfactual definition of causation

Answer 21

• States that the presence or absence of the cause
“makes a difference” in the outcome (or probability of the outcome)
• Whereas the necessary, sufficient, component, and probabilistic definitions clarify what kind of difference it makes
• Is consistent with both deterministic and probabilistic phenomena

Question 22

what is population health important?

Answer 22

• Targets factors that could avoid premature mortality

- Most effective at improving health of populations rather than individuals