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
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 DISEASEThey test the hypothesis. And those are knownas EPIDEMIOLOGISTSAnyway ….. from thisbold word our lessoncomes
• 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
THE MORE ASSOCIATIONS The more investigation To detangle the web of causation (solve it)
• 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
BUT…. HOW TO KNOW WHICH ONE IS MOREASSOCIATED 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
correlation • risks - - •• 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 ???!!!!
IMPORTANT SENTENCE• Causation implies Correlation BUT correlation does not imply causation. •
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
• 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
• 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)!!!!
3. Colera and water supply confounding factor is vibrio bacteria……. And so on
• C- Direct association: 1. One to one causal relationship 2. Multifactorial causation.
• 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.
• Multifactorial causation:• Either the causes are acting:1. Independently2. Or cumulatively pollution smoking Lung cancer asbistos
WHEN WE CAN SAY THAT THIS ASSOCIATION ISLIKELY TO BE CAUSATION??• We have certain criteria that should be present: • Temporal association ( ) • Strength of association • Specificity of association • Consistency of association( ) • Biological plausibility( ) • Coherence of association
• 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
• 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
• 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
• 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
• 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