epidemiology and causation

Henle-Koch postulates

they demanded the following criteria to be met before an agent could be considered the cause of a disease:

• It has to be present in every case of the disease.

• It has to be isolated and grown in pure culture.

• It has to cause specific disease, when inoculated into a susceptible animal and can then be recovered from the animal and identified.

pros of henl-koch postulates

first set of criteria used to provide a generally accepted framework for identifying causes of disease. brought some order and discipline to the study of infectious diseases

cons of henle-koch postulates

had some basic assumptions which were often impossible to fulfill. They require that a disease has to have only one cause and so have difficulty dealing with multiple factors, multiple effects of single causes, carrier states, non-agent

factors (such age, breed) and they are not applicable to non-infectious diseases.

Evans unified concept of causation

generally accepted for identifying cause-effect relationships

• The proportion of individuals with the disease should be higher in those exposed to the putative cause than in those not exposed.

• The exposure to the putative cause should be more common in cases than in those without the disease, when other risk factors are constant.

• The number of new cases should be significantly higher in those exposed to the putative cause than in those not exposed, as shown in prospective studies.

• Temporally, the disease should follow exposure to the putative cause.

• A measurable spectrum of host responses, from mild to severe, should follow exposure to the putative cause along a logical biological gradient

• The host response should appear (or increase in magnitude) regularly following exposure to the putative cause. This pattern should not occur in those not exposed.

• Experimental reproduction of the disease should occur with greater frequency in animals exposed to the putative cause than in those not exposed (this exposure may be

deliberate (volunteers) experimentally induced in the lab or demonstrated in a controlled regulation of natural exposure).

• Elimination of the putative cause should result in a lower incidence of the disease.

• Preventing or modifying the host response should decrease or eliminate the expression of disease.

• The relationship should be biologically and epidemiologically plausible

cons of evan’s rules of unified concept of causation

Some of Evan’s rules require the association between the hypothesised causal factors and the disease in question to be statistically significant.

epidemiological concept of causation

A cause of a disease is an event, condition, or characteristic which plays an essential role in producing an occurrence of the disease. Knowledge and complex thinking about cause-and effect relationships underlies epidemiological investigation (as well therapeutic manoeuvres in clinical medicine).

the process by which an exposure, event, or characteristic (such as a pathogen, behavior, or environmental factor) directly results in the onset of a disease or health outcome

An observed statistical association between a risk factor and a disease does not automatically prove causation because of potential chance, bias, or confoundin

proximate causation

answers the "how" question by explaining the immediate biological, physiological, or environmental mechanisms that directly trigger a disease or health outcome

ultimate causation

answers the "why" or "how come" questions by explaining the deep evolutionary history, genetic adaptations, ecological pressures, or upstream socio-economic structures that shaped why a population or species is vulnerable to that condition in the first place

association vs causation

• Association ≠ Cause

• “a state in which two attributes occur together

either more or less often than expected by chance.”

• Statistics identifies ASSOCIATIONS

• Identification of CAUSATION requires complex

thinking

role of chance

Two things can appear related just due to chance

confounding

happens when a third, extraneous factor (a confounder) distorts the true association between an exposure and a health outcome

In confounding, a hidden third factor (Z) drives both X and Y. In reverse causation, only X and Y are involved, and the arrow points in the opposite direction.

reverse causation

situation where a researcher or observer assumes that variable X causes variable Y, when the true direction of the relationship is actually backward—meaning Y causes X, or both influence each other in a feedback loop.

ex: A study might observe that people with low levels of physical activity are more likely to develop dementia, leading to the assumption that inactivity causes dementia. In reality, early-stage (prodromal) dementia develops silently for years, causing people to become physically inactive before they are officially diagnosed.