This document discusses the relationship between association and causation in epidemiology. It explains that while association means two things occur together, causation requires proving a causal relationship. Several types of association are described, including spurious, indirect, and direct associations. Criteria for determining when an associative relationship is likely causal are provided, including temporal relationship, strength, specificity, consistency, biological plausibility, and coherence of the association. Overall, the document aims to clarify the difference between association and causation and how causation can be established in epidemiological research.

1. IN THE NAME OF ALLAH
Association and causation

2. INTRODUCTION
(JUST TO REFRESH UR MEMORY )
• Descriptive study: it like a detective who want to solve mysteries by identifying the case
(which is the disease problem ) and try to connect between evidence which are here host
,agent and environmental factors

3. LINKING:

4. ANALYTICAL AND EXPERIMENTAL STUDY
• Its just like a scientist who want to prove the hypothesis by observing and they always
asking themselves:
• Is there is any association between CAUSE and DISEASE
They test the hypothesis. And those are known
as EPIDEMIOLOGISTS
Anyway ….. from this
bold word our lesson
comes

5. • In this world many diseases has more than 1 etiology either cause or risk factor i.e.
Multifactorial and this makes it difficult to relate the cause with the disease. U CANT POINT
FINGER on a cause and say THAT’S IT.
• The more association between causes and disease, the more investigation we need, to find
the cause

6. THE MORE ASSOCIATIONS
The more investigation
To detangle the web of causation (solve it)

7. • Association is not always causation
• Association means there is relationship between stuffs, but it doesn’t have to be a cause.
They occur frequently together .
• That’s why the epidemiologist 1st state that
• There association between A and B
• Then
• Oh yes the association is likely to be a cause That’s mean A almost the cause of B

8. BUT…. HOW TO KNOW WHICH ONE IS MORE
ASSOCIATED THAN THE OTHER???
• That’s by something called CORRILATION
• It’s the degree of association between two characters
• It is measured by the correlation coefficient which range from -1.0 to 1.0

9. • lakin alcorrelation la tastatee3 an tatnabaa bssb almarad
• Lanaho bbasata lays kol ma yata3arad laho gabl almarad bldarora ykon sabab laho
• Wa lanaha la tagees alrisk
• Correlation cannot be used to invoke causation because the sequence of exposure
preceding disease cannot be assumed to have occur and it don’t measure risks
Which one ???!!!!

10. IMPORTANT SENTENCE
• Causation implies Correlation BUT correlation does not imply causation.
• Alsabab ya3ni wogod 3alaga walakin laysa kol 3alaga stkon sababyah

11. TYPES OF ASSOCIATION:
• A- spurious association:
• Spurious= not real
• That’s mean the association between disease and cause is not real.
• This is due to selection bias
• Eg: more perinatal mortality in mothers that give birth at hospital than at home

12. • B- indirect association :
• Simple example: Sahar is a friend with Salma, and Salma is Hanaa, so Hanaa is Sahar’s
friend too but indirectly. The common friend is Salma.
• So the association is due to the presence of another factor which is common to both,
known as CONFOUNDING factor.
• E.g. of confounding factors:
• Age, sex, social class

13. • Eg of indirect association: hint: remember salt(which usually contain iodine) and sugar.
1. Altitude and endemic goiter confounding factor is iodine deficiency.
2. Glucose and CHD ,confounding factor is cigarette smoking(it increase the # of cups
of coffee and amount of sugar u consume)!!!!

14. 3. Colera and water supply confounding factor is vibrio bacteria……. And so on

15. • C- Direct association:
1. One to one causal relationship
2. Multifactorial causation.

16. • One to one causal relationship
• Change in A is followed by change in B.
• When A is present B must result.
• Eg Measles.
• But its not always that simple as some causes can cause more than 1 disease like strept.

17. • Multifactorial causation:
• Either the causes are acting:
1. Independently
2. Or cumulatively
pollution
smoking Lung cancer
asbistos

18. WHEN WE CAN SAY THAT THIS ASSOCIATION IS
LIKELY TO BE CAUSATION??
• We have certain criteria that should be present:
• Temporal association (irtibat zamani)
• Strength of association
• Specificity of association
• Consistency of association(thabat alrabit)
• Biological plausibility(magbola 3lmyaan)
• Coherence of association

19. • Temporal association :
• The exposure to putative cause must precede temporarily the onset of the disease
• Its more obvious in acute disease more than in chronic disease

20. • Strength of association:
• Remember we have experimental data and analytical data
• When there is no experimental data the strength of association will depend on
• relative risk,
• dose response relationship,
• duration and response relationship
• Otherwise by cessation experiment

21. • Specificity of the association:
• It’s the most difficult to occur for 2 reasons:
• Single cause or factor can give rise to more than 1 disease
• Most diseases are due to multiple factors
• Specificity supports causation but lack of specificity does not eliminate it.
It supports the idea of one to one

22. • An example of this: in the same manner of the previous slide:
• Not everyone who smokes develops cancer
• Not every one who develop cancer has smoke

23. • Consistency of the association : means that if u did the experiment or the
research 10000000000000 times u will get the same result even if u did it each time by
different method

24. • Biological plausibility:
• Ya3ni anaho yagib an yakoon alrabit (assotiation) ma3goolan min alna7yah al3lmyah
altybyah mwafig lilshorot.

25. • Coherence of the association:
• Acually I didn’t know how to explain this
• ANY IDEAS???

26. • Finally I hope my presentation has
achieve the goal
• Don’t forget to pray for me
• Gooooooooood luck
• Walaa Yousif Ali