confounding .ppt Fakultas Kesehatan Masyarakat

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1. Confounding - S2 1
CONFOUNDING
Department of Epidemiology
Faculty of Public Health
Airlangga University

2. Confounding - S2 2
Confounding ……….
is an important problem for health and
medical researchers whenever they
conduct studies to assess a relationship
between an exposure (E) and some
health outcome or disease of interest
(D).

3. Confounding - S2 3
Confounding ……….
is a type of bias that may occur when
we fail to take into account other
variables, like age, gender, or smoking
status, in attempting to assess an E 
D relationship.

4. Confounding - S2 4
Confounding……. is a form of bias that
concerns how a measure of effect may
change in value depending on whether
variables other than the exposure variable
are controlled in the analysis
Definition…..

5. Confounding - S2 5
Confounding …..adalah distorsi dari efek suatu
faktor yang disebabkan adanya faktor lain
yang juga berpengaruh terhadap kejadian yang
diteliti.
Confounding terjadi akibat perbedaan distribusi
variabel yang diduga sebagai confounding
(PCV) dalam kelompok yang dibandingkan.
Definisi………

6. Confounding - S2 6
X
A B
(X confounding)
A X B
(X intervening)
Causal Model

7. Confounding - S2 7
Smoking CHD
PCV
(drinking coffee)
Example…..

8. Confounding - S2 8
Is the same with interaction /
effect modification ?
•Confounding and interaction are different
concepts
•Interaction consider what happens after we
control for another variable
•Interaction is present if the estimate of the
measure of association differs at different
levels of a variable being controlled

9. Confounding - S2 9
Continued…..
-When assessing confounding and
interaction in the same study, it is possible
to find one with or without the other
-In the presence of strong interaction, the
assessment of confounding may be
irrelevant or misleading

10. Confounding - S2 10
A confounder………
-must be a risk factor
-cannot be an intervening variable
-must be associated with the exposure in the
source population
Data-based criterion…….
-adjusted estimate ≠ crude analysis
Criteria Confounding…….

11. Confounding - S2 11
Controlling confounding means doing
something to make comparison fair:
–Exclude people who have the risk factor
(“restriction”)
–Matching
–Stratified analysis (adjustment, standardization)
–Mathematical modeling (e.g., regression)
Control of Confounding

12. Confounding - S2 12
1.Interpreting data requires assumptions
about causal relations (including what
factors are potential confounders).
Confounding – key concepts

13. Confounding - S2 13
2.If exposed people and unexposed
people differ on factors that affect
disease incidence, then those factors
may confound (distort) the observed
relation between exposure and disease
(i.e., actual confounding).
Confounding – key concepts

14. Confounding - S2 14
3.We can control confounding by study
design if we can make the exposed and
unexposed groups similar in respect to all
disease determinants, though matching or
randomized assignment of exposure.
Confounding – key concepts

15. Confounding - S2 15
4.We can control confounding in the
analysis if we can stratify the data by
disease determinants that are not
themselves caused by the exposure
(i.e., not causal intermediates).
Confounding – key concepts

16. Confounding - S2 16
Thank you………