Etiology (medicine)

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The etiology is concerned with the causes of the emergence of a disease . It is of great importance in medicine , clinical psychology and especially epidemiology .

The pathogenesis , however, refers more to the origin and development of diseases (see Pathology ). The expression etiopathogenesis represents a combination of both terms with a similar meaning ( ancient Greek γένεσις genesis : "origin, emergence").

Meaning of the term

The term is derived from αἰτία aitía , " cause ", and λόγος lógos , "reason, doctrine".

In medical parlance, the term etiology describes :

  • the study of the causes of the disease (as defined in general pathology, etiology .. i e p );
  • the totality of the factors that led to a given disease (in the clinical sense, etiopathogenesis in the sense of the word ).

In philosophy , especially in some ancient schools of philosophy, the term aitiology stands for the doctrine of causes in general. The adjective aetiological accordingly means quite generally: “the causes”, “the reason”, “the causal origin” or “the causal derivation” concerning or explanatory.

The three "Cs" of etiology

There are three basic methods of etiology, each with a different degree of certainty with which to find the cause of a disease or ailment. Knowing the “three Cs” can also help the patient not to lose his head in the event of a serious diagnosis, but to rethink his or her behavior rationally. This applies especially to the questions “What did I do wrong?” Or “Am I to blame for my suffering?”.

In general, the medical (and the scientific) research, works so that first a correlation (Correlatio) is detected. After more detailed investigations, one can - or not - find out whether there is a cause-and-consequence relationship (Contributio) . It is often the last step to find out a causal connection (causa) .


Causa ( Latin for "cause, cause of illness"): In the case of more frequent and better investigated medical phenomena , one can search for "causal" reasons for an illness. That is, if event A occurs, then event B must also occur. Examples are:

  • When smoking: Nicotine consumption always reduces the diameter of blood vessels and thus worsens the risk . a. the blood flow to the body tissue. This means that stopping nicotine consumption always results in improved blood flow.


With Contributio (Latin for "funding, contribution") there is still a strong connection in the sense of a cause-effect relationship, but this is no longer as strong as in the previous category. In general, if event A arrives, then event B meets frequently a factor than usual A. Contributes therefore to state B at .

  • Example: Not every smoker gets lung cancer , but smokers are more likely to get lung cancer than non-smokers. Quitting smoking means that all things being equal, the likelihood of developing lung cancer decreases.


The correlation ( Correlatio , Latin for "correlation, connection") is used for rare diseases as well as for diseases that have no clear or researched cause-consequence relationships. So as soon as you read something in a newspaper report about "A connection has been found between migraines and heart problems", one should think of the correlation. No one has yet been able to describe or prove whether migraines cause heart problems, heart problems cause migraines, or both depend on a third cause; it was only found that people with property A often also have property B and vice versa. The correlation does not differentiate between cause and consequence (effect).


  • The Japanese have the highest life expectancy of any person on earth. This does not mean that once you have Japanese citizenship or live in Japan, you will live longer or healthier. Nor can it be concluded that the Japanese way of life and diet are beneficial to health or that other ways of life and diet are detrimental to health. A genetic component is also conceivable, e.g. B. in that islanders are subject to a lower genetic mix than mainland residents.
  • People who pursue an intellectually challenging job between the ages of 20 and 50 are less likely to develop Alzheimer's disease . This is the fact at the correlation level. The interesting question now is:
    • Alzheimer's disease breaks out in adolescence and prevents the start of a mentally demanding activity or
    • A mentally demanding activity prevents Alzheimer's disease or
    • is there a third, previously unknown factor that contributes to both of these things?

Bradford Hill Criteria

Austin Bradford Hill was an English statistician and epidemiologist who developed the Bradford Hill criteria for causality in medicine. He postulated the following nine criteria with which a suspected cause-effect relationship in medicine or epidemiology should be checked:

  1. Strength: A weak association between two phenomena does not mean that there is no causality between them. The fact that most people have meningococci in their nasal mucous membranes and yet very few people develop meningococcal meningitis does not disprove causality.
  2. Consistency: Consistent observations by different scientists at different risk populations using different methods increase the likelihood of a causal relationship.
  3. Specificity: Causality can be assumed if a specific population suffers from a disease that can only be explained in an unsatisfactory way so far. Another problem is that a disease can have many causes, and one cause (for example a certain carcinogenic substance) creates a variety of different cancers.
  4. Temporality: The effect must take place after the suspected cause has occurred - and if a delay between the cause and its development is expected, the effect must take place after this delay. Do factory workers have a higher risk of illness because they work in factories - or do they have a lower social status because of illnesses they have already suffered, so that they only have to work in a factory?
  5. Biological gradient: Greater exposure to a risk factor should lead to more frequent occurrences of the disease. The question here is often how exposure should be quantified - for example, do you count the number of days someone has smoked so far? Or the average number of cigarettes per day?
  6. Plausibility: A plausible mechanism between cause and effect is helpful, but not necessary. What is considered plausible today depends on today's biological knowledge. When statistical data was collected in the 18th century, it was found that chimney sweeps often contracted testicular cancer , no one could provide a plausible explanation for this on a chemical or molecular biological level.
  7. Consistency: A match between epidemiological data and results from the laboratory increases the certainty that there is a causality. As an example: tissue samples from the lungs of the deceased, on which pollutant concentrations are measured, are compared with the analysis of which substances a cigarette contains. These findings in turn are linked to completed questionnaires from smokers in which they explain their smoking habits.
  8. Experiment: Sometimes it is possible to test assumptions from epidemiological data experimentally, but this sometimes comes up against ethical limits. With an observed decrease in the number of illnesses after the abolition of a risk factor, important evidence of causality is provided.
  9. Analogy: The effect of similar active substances and risk factors should be taken into account. Finding that thalidomide harms the unborn child has led to the assumption that rubella infection during pregnancy does the same. The existence of a cause-and-effect relationship gives rise to a search for other causes that lead to a similar effect in a similar way.

These criteria were set out in The Environment and Disease: Association or Causation? set out. This publication is still one of the most cited scientific works today. However, Austin Bradford Hill refused to use his nine criteria as rigid rules. However, this list is also misunderstood and sometimes taught as a "checklist". According to Hill, these motto should serve to critically reconsider postulated causalities.

In the same publication, Hill criticized the blind belief in significance tests , because such tests can rule out a random error , but not systematic and methodological errors . But aetiological and epidemiological studies run the risk of suffering from the latter. Likewise, in the sense of the economist Hill, evidence of a causal relationship is insufficient to provide public health action. Cost and benefit analyzes are necessary for all those affected; Because the pure increase in life expectancy can, among other things, damage the quality of life, for example if you give up a beloved hobby, which brings with it an increased risk of accidents. For this purpose, if the costs are negligible and the expected benefits are relatively high, measures should also be carried out without statistically solid evidence of causality.


  • Urs Baumann, Meinrad Perrez (Ed.): Textbook Clinical Psychology. Psychotherapy: classification, diagnosis, etiology, intervention . 3rd completely revised edition. Huber, Bern a. a. 2005, ISBN 3-456-84241-4 .
  • Phillips & Goodman (2004): The missed lessons of Sir Austin Bradford Hill ( Review of the original 1965 paper and its relevance to epidemiology and medical etiology.)

Web links

Wiktionary: Etiology  - explanations of meanings, word origins, synonyms, translations

Individual evidence

  1. Work 'may ward off Alzheimer's' , BBC News.
  2. ^ Sir Austin Bradford Hill : The Environment and Disease: Association or Causation? In: Proceedings of the Royal Society of Medicine . tape 58 , no. 5 , 1965, pp. 295-300 , PMC 1898525 (free full text).
  3. ^ Carl V. Phillips & Karen J. Goodman: The missed lessons of Sir Austin Bradford Hill . In: Epidemiologic Perspectives & Innovations . tape 1 , no. 3 , 2004, p. 1–5 , doi : 10.1186 / 1742-5573-1-3 , PMC 524370 (free full text).