Causality and hypothesis definition Flashcards
Types of studies inside epidemiology
o Descriptive studies - who, what, where, when
o Analytical studies - Why (study the cause)
o Predictive studies
Causality
The study of the causes that derive into a specific effect
Cause
An event, condition or characteristic which leads into an event
Risk factors
Characteristics that cause an increase in the probability of developing that effect (disease) but this does not necessarily mean that they are the cause of the disease
Characteristics of risk factors
o It is not a determining relationship
o They can be modifiable (diet, smoking, exercise…) or non modifiable (age, genetics, gender…)
o Important both the study of modifiable and non modifiable risk factors.
▪ Modifiable risk factors, if changed, can help reduce the probability of developing the disease. These types of risk factors are studied by preventive medicine
▪ If we study non modifiable factors, we will be able to define risk groups and offer a closer supervision, since these risk groups are more likely to end up in the ICU
Risk indicators or markers
Variables associated with the outcome but not the cause.
They are the indicator of risk but not the causal factor.
These indicators are used to know which people are of high risk
How is causality measured?
Through statistical association between the exposure and the outcome.
Statistical associations
Relationship between two variables which is greater than the relationships expected provided by chance
Statistical associations are not the same as causation
Problems of statistical association
o May be by chance
o May find that the variable I thought was the cause is in fact the consequence
o May be biased
o May be cofounded (cofounding is a type of bias)
Rothman’s model
There is not only one way of developing the disease (>1)
Causal mechanisms = set of minimal conditions that lead to the effect (causes put together)
▪ Pie charts: each sector = one component of the cause
▪ Contributing causes = each cause is responsible for a certain proportion of the disease
Sufficient cause
A cause that only needs one component to be able to form the effect
▪ The probability of developing the disease if you have the sufficient cause is 1 (100%)
▪ All exposed to the sufficient cause will develop the outcome
Necessary cause
A component that will be in all disease mechanisms
▪ The probability of exposure among causes is 1 (100%)
▪ None that is not exposed can develop the disease
(Tuberculosis only develops when exposed to the bacteria, but not all the exposed develop the disease)
Correlation - causation
Correlation does not imply causation
Review document
