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1
Epidemiologic Measures
of Association
Lt Col Ayon Gupta
Assistant Professor
Dept of Community Medicine , AFMC
2
Epidemiologic Measures of Association
Session Objectives
By the end of session students should be able to:
Compute & Interpret Relative risk (RR)
& Odds ratio (OR) as a measure of
association between exposure and
Disease
 Understand when OR approximates
RR
3
Definitions
Association
 A statistical relationship between two or
more variables
Risk
 Probability conditional or unconditional of
the occurrence of some event in time
 Probability of an individual developing a
disease or change in health status over a fixed
time interval, conditional on the individual
not dying during the same time period
Absolute risk
4
Association between exposure &
Disease
 Question:
Is there an excess risk associated with a
given exposure?
 Objective:
To determine whether certain exposure is
associated with a given disease
 Methodology:
Use one of the epidemiologic study designs
Cohort
Case-control
5
Cohort Study
 Assess the cumulative incidence (CIE+) of
disease in an exposed group (absolute Risk)
Assess the cumulative incidence (CIE-) of disease
in unexposed group (absolute Risk)
e.g. Coronary Heart Disease (CHD) Risk among Smokers
1-year risk of CHD among smokers (CIE+)*
CHD
Yes No Total
Smokers 84 2916 3000
CIE+ = 84/3000 = 28/1000/yr (1-risk of CHD among smokers)
Cont.
6
CHD Risk among non-smokers
 1-year risk of CHD among non-smokers (CIE-
)
CHD
Yes No
 Non-smokers 87 4913 5000
CIE-= 87/5000=17.4/1000/yr (1-yr risk of
CHD among non-smokers) Cont.
7
Assessment of Excess Risk (Two methods)
a. Ratio
RR (Ratio of two risks; Risk Ratio; Relative Risk)
CIE+ / CIE- = 28/17.4 = 1.6
Interpretation of RR
Smokers were 1.6 times as likely to develop CHD as were
non-smokers
b. Difference
Difference of two risks (Risk Difference)*
CIE+- CIE- = 28.0  17.4 = 10.6
8
OR (Odds Ratio, Relative Odds)
 In case-control study (CCS), we cannot calculate
the CI or IR,
therefore, cannot calculate the RR directly
 OR as a measure of association between
exposure & disease is
used when data are collected in case-control
study
 OR can be obtained however, from a cohort as
well as a
case-control study and can be used instead of
RR.
9
OR in case-control and
cohort studies
 Cohort study
Ratio of the proportion of exposed subjects who
developed the disease to the proportion of non-
exposed subjects who developed the disease
 Case-control study
Ratio of the proportion of cases who were
exposed to the proportion of controls who were
non-exposed
10
Odds Ratio
 Odds are ratio of two probabilities
i.e. Probability that event occurs / 1-Probability
that event does not occur
 Odds refer to single entity
 If an event has the probability P,
then the odds of the same event are
P/1-P
11
Derivation of OR in Cohort study
P D
+|E
+ = (exposed developed the disease) = a/(a+b)
P D
-|E
+ = (exposed did not develop the disease) = b/(a+b)
Odds of developing disease among exposed =
D+|E+/1-P D-|E+ = a/(a+b)
b/(a+b) = a/b
P D
+|E
- = (non-exposed developed the disease) = c/(c + d)
P D
-|E
- = (non-exposed did not develop the disease)= d/(c + d)
Odds of developing disease among non-exposed =
= PD+|E
-/1-P D+|E
- = c/(c+d)
d/(c + d) = c/d
Odds ratio a/b : c/d = ad/bc
12
OR in case-control study
 In case-control study RR cannot be
calculated directly to determine the
association between exposure and disease.
 Dont know the risk of disease among
exposed and un-exposed since we start
recruiting cases and controls.
 Can use OR as measure of association
between exposure and disease in a case
control study.
13
OR in case-control Study
Probability of case being exposed = Pcase
Probability of case being non-exposed =1-Pcase
Odds of case being exposed = Pcase/1- Pcase
Probability of control being exposed = Pcontrol
Probability of case being non-exposed =1-Pcontrol
Odds of control being exposed = Pcontrol/ 1-Pcontrol
14
Derivation of OR in case-control Study
Probability of being exposed among cases = a /(a + c)
Probability of being non-exposed among cases) = c /(a + c)
Odds of being exposed among cases = a/c
Probability of being exposed among controls = b/(b + d)
Probability of being unexposed among controls = d/(b + d)
Odds of being exposed among controls = b/d
OR = ad/bc
15
 Past surgery HCV status
HCV+ HCV-
 Yes 59 168
 No 54 48
損 113 216
Example
OR in case-control Study
16
Odds of Past surgery among HCV+
P1 (Surgery among HCV+) = 59/113
1-P1 (No surgery among HCV+) = 54/113
Odds of surgery among HCV+ ) = 59/54 = 1.09
Odds of Past surgery among HCV-
P2 (Surgery among HCV-) = 168/216
1-P2 (No surgery among HCV-) = 48/216
Odds of surgery among HCV- = 168/48 = 3.5
OR = 3.50/1.09 = 3.21
17
When is the OR a good estimate of RR?
 In CCS, only OR can be calculated as measure of
association
 In Cohort study, either RR or OR is a valid measure of
association
 When a RR can be calculated from case control study?
*When exposure prevalence among studied cases
in similar and nearly similar to that of disease
subjects in the population from which cases are
taken.
*Prevalence of exposure among studied controls
is similar to that of non-diseased population from
cases were drawn.
*Rare disease (CI < 0.1)
18
Matched case-control study
 Matching: In a matched case-control
study each case is matched to a control
according to variables that are known to
be related to disease risk i.e. age, sex, race
 Data are analyzed in terms of case-
control pairs rather than for individual
subjects
 Four types of case-control
combinations are possible in regard to
exposure history.
19
 Concordant pairs are ignored since they
dont contribute in calculation of effect
estimate (i.e. OR)
 Disconcordant pairs of cases and controls
are used to calculate the matched OR.
 Matched OR = Ratio of discordant pairs
= b /c
i.e. # of pairs in which cases exposed / # of
pairs in which controls were exposed
20
Example:
Risk factors for brain tumors in children.
Hypothesis = children with higher birth
weights are at increased risk for certain
childhood cancers.
Cases = Children with brain tumors
Controls = Normal children
Exposure = Birth weight > 8 lbs.
21
8 18
7 38
8 + 1b
Cases <8 1b
Total
26
45
15 56 71
8+ 1b <8 1b
Total
Normal Controls
Odds Ratio 18/7 = 2.57
2 = 4.00; P = 0.046
Interpretation the is same as before
Example

More Related Content

measures of association.pptx

  • 1. 1 Epidemiologic Measures of Association Lt Col Ayon Gupta Assistant Professor Dept of Community Medicine , AFMC
  • 2. 2 Epidemiologic Measures of Association Session Objectives By the end of session students should be able to: Compute & Interpret Relative risk (RR) & Odds ratio (OR) as a measure of association between exposure and Disease Understand when OR approximates RR
  • 3. 3 Definitions Association A statistical relationship between two or more variables Risk Probability conditional or unconditional of the occurrence of some event in time Probability of an individual developing a disease or change in health status over a fixed time interval, conditional on the individual not dying during the same time period Absolute risk
  • 4. 4 Association between exposure & Disease Question: Is there an excess risk associated with a given exposure? Objective: To determine whether certain exposure is associated with a given disease Methodology: Use one of the epidemiologic study designs Cohort Case-control
  • 5. 5 Cohort Study Assess the cumulative incidence (CIE+) of disease in an exposed group (absolute Risk) Assess the cumulative incidence (CIE-) of disease in unexposed group (absolute Risk) e.g. Coronary Heart Disease (CHD) Risk among Smokers 1-year risk of CHD among smokers (CIE+)* CHD Yes No Total Smokers 84 2916 3000 CIE+ = 84/3000 = 28/1000/yr (1-risk of CHD among smokers) Cont.
  • 6. 6 CHD Risk among non-smokers 1-year risk of CHD among non-smokers (CIE- ) CHD Yes No Non-smokers 87 4913 5000 CIE-= 87/5000=17.4/1000/yr (1-yr risk of CHD among non-smokers) Cont.
  • 7. 7 Assessment of Excess Risk (Two methods) a. Ratio RR (Ratio of two risks; Risk Ratio; Relative Risk) CIE+ / CIE- = 28/17.4 = 1.6 Interpretation of RR Smokers were 1.6 times as likely to develop CHD as were non-smokers b. Difference Difference of two risks (Risk Difference)* CIE+- CIE- = 28.0 17.4 = 10.6
  • 8. 8 OR (Odds Ratio, Relative Odds) In case-control study (CCS), we cannot calculate the CI or IR, therefore, cannot calculate the RR directly OR as a measure of association between exposure & disease is used when data are collected in case-control study OR can be obtained however, from a cohort as well as a case-control study and can be used instead of RR.
  • 9. 9 OR in case-control and cohort studies Cohort study Ratio of the proportion of exposed subjects who developed the disease to the proportion of non- exposed subjects who developed the disease Case-control study Ratio of the proportion of cases who were exposed to the proportion of controls who were non-exposed
  • 10. 10 Odds Ratio Odds are ratio of two probabilities i.e. Probability that event occurs / 1-Probability that event does not occur Odds refer to single entity If an event has the probability P, then the odds of the same event are P/1-P
  • 11. 11 Derivation of OR in Cohort study P D +|E + = (exposed developed the disease) = a/(a+b) P D -|E + = (exposed did not develop the disease) = b/(a+b) Odds of developing disease among exposed = D+|E+/1-P D-|E+ = a/(a+b) b/(a+b) = a/b P D +|E - = (non-exposed developed the disease) = c/(c + d) P D -|E - = (non-exposed did not develop the disease)= d/(c + d) Odds of developing disease among non-exposed = = PD+|E -/1-P D+|E - = c/(c+d) d/(c + d) = c/d Odds ratio a/b : c/d = ad/bc
  • 12. 12 OR in case-control study In case-control study RR cannot be calculated directly to determine the association between exposure and disease. Dont know the risk of disease among exposed and un-exposed since we start recruiting cases and controls. Can use OR as measure of association between exposure and disease in a case control study.
  • 13. 13 OR in case-control Study Probability of case being exposed = Pcase Probability of case being non-exposed =1-Pcase Odds of case being exposed = Pcase/1- Pcase Probability of control being exposed = Pcontrol Probability of case being non-exposed =1-Pcontrol Odds of control being exposed = Pcontrol/ 1-Pcontrol
  • 14. 14 Derivation of OR in case-control Study Probability of being exposed among cases = a /(a + c) Probability of being non-exposed among cases) = c /(a + c) Odds of being exposed among cases = a/c Probability of being exposed among controls = b/(b + d) Probability of being unexposed among controls = d/(b + d) Odds of being exposed among controls = b/d OR = ad/bc
  • 15. 15 Past surgery HCV status HCV+ HCV- Yes 59 168 No 54 48 損 113 216 Example OR in case-control Study
  • 16. 16 Odds of Past surgery among HCV+ P1 (Surgery among HCV+) = 59/113 1-P1 (No surgery among HCV+) = 54/113 Odds of surgery among HCV+ ) = 59/54 = 1.09 Odds of Past surgery among HCV- P2 (Surgery among HCV-) = 168/216 1-P2 (No surgery among HCV-) = 48/216 Odds of surgery among HCV- = 168/48 = 3.5 OR = 3.50/1.09 = 3.21
  • 17. 17 When is the OR a good estimate of RR? In CCS, only OR can be calculated as measure of association In Cohort study, either RR or OR is a valid measure of association When a RR can be calculated from case control study? *When exposure prevalence among studied cases in similar and nearly similar to that of disease subjects in the population from which cases are taken. *Prevalence of exposure among studied controls is similar to that of non-diseased population from cases were drawn. *Rare disease (CI < 0.1)
  • 18. 18 Matched case-control study Matching: In a matched case-control study each case is matched to a control according to variables that are known to be related to disease risk i.e. age, sex, race Data are analyzed in terms of case- control pairs rather than for individual subjects Four types of case-control combinations are possible in regard to exposure history.
  • 19. 19 Concordant pairs are ignored since they dont contribute in calculation of effect estimate (i.e. OR) Disconcordant pairs of cases and controls are used to calculate the matched OR. Matched OR = Ratio of discordant pairs = b /c i.e. # of pairs in which cases exposed / # of pairs in which controls were exposed
  • 20. 20 Example: Risk factors for brain tumors in children. Hypothesis = children with higher birth weights are at increased risk for certain childhood cancers. Cases = Children with brain tumors Controls = Normal children Exposure = Birth weight > 8 lbs.
  • 21. 21 8 18 7 38 8 + 1b Cases <8 1b Total 26 45 15 56 71 8+ 1b <8 1b Total Normal Controls Odds Ratio 18/7 = 2.57 2 = 4.00; P = 0.046 Interpretation the is same as before Example