Post on 15-Apr-2017
Second approach: “Classical” approach based on a priori criteria
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“Bias of the estimated effect of an exposure on an outcome due to the presence of a common cause of the exposure and the outcome” – Porta 2008
● A factor is a confounder if 3 criteria are met:● a) a confounder must be causally or noncausally
associated with the exposure in the source population (study base) being studied;
● b) a confounder must be a causal risk factor (or a surrogate measure of a cause) for the disease in the unexposed cohort; and
● c) a confounder must not be an intermediate cause (in other words, a confounder must not be an intermediate step in the causal pathway between the exposure and the disease)
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Exposure
E
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Disease (outcome)D
Confounder
C
Confounding Schematic
Szklo M, Nieto JF. Epidemiology: Beyond the basics. Aspen Publishers, Inc., 2000. Gordis L. Epidemiology. Philadelphia: WB Saunders, 4th Edition.
Exposure
EConfounder
C
Intermediate cause
Disease
D
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Exposure
E
ConfounderC
General idea: a confounder could be a ‘parent’ of the exposure, but should not be be a ‘daughter’ of the
exposure
Disease
D
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Example of schematic (from Gordis)
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Birth Order
E
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Down SyndromeD
Confounding factor: Maternal Age
C
Confounding Schematic
HRT use Heart disease
Association between HRT and heart disease
Confounding factor: SES
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Are confounding criteria met?
BRCA1 gene Breast cancer
Confounding factor:Age
x
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Are confounding criteria met?Should we adjust for age, when evaluating the association between a genetic factor and risk of breast cancer?
No!
Sex with multiple partners Cervical cancer
Confounding factor: HPV
Are confounding criteria met?
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Sex with multiple partners
HPV Cervical cancer
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What if this was the underlying causal mechanism?
Obesity Mortality
Are confounding criteria met?
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Confounding factor: Hypertension
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Obesity Hypertension Mortality
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What if this was the underlying causal mechanism?
Direct vs indirect effects
Obesity Hypertension Mortality
ObesityIndirect effect
Hypertension Mortality
Direct effect
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Direct effect is portion of the total effect that does not act via an intermediate cause 30
Indirect effect
Hernan MA, et al. Causal knowledge as a prerequisite for confounding evaluation: an
appl3ic3ation to birth defects epidemiology. Am J Epidemiol 2002;155(2):176-84.
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Simple causal graphs
DC E
Maternal age (C) can confound the association between multivitamin use (E) and the risk of certain
birth defects (D)
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Complex causal graphs
Hernan MA, et al. Causal knowledge as a prerequisite for confounding evaluation: an application to birth defects epidemiology. Am J Epidemiol 2002;155(2):176-84.
E DC
U
History of birth defects (C) may increase the chance of periconceptional vitamin intake (E). A genetic factor (U) could have been the cause of previous birth defects in the family, and could again cause birth defects in the current pregnancy
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Smoking
A
ECalcium
DBone
fractures
CBMI
supplementation
U
Physical
Activity
B
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Source: Hertz-Picciotto
More complicated causal graphs!
The ultimate complex causal graph!
36A PowerPoint diagram meant to portray the complexity of American strategy in Afghanistan!
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