Epi Class 9

Question 1

Confounding

Answer 1

distorts or hides a relationship

When two exposures are related and that makes it look like exposure A causes the disease when really it is exposure B that causes the disease.

Question 2

Effect modification

Answer 2

real effect is different in different populations

When different subpopulations with different biological responses are incorrectly grouped (means the RR or OR does not reflect the impact of effect modification)

Question 3

No 3rd Variable Effect

Answer 3

OR1 = OR2 = ORcrude (all equal)

Question 4

Types of Bias

Answer 4

Selection bias

Misclassification bias

Information bias

Question 5

Selection bias

Answer 5

error due to systematic differences between those selected for study and those not selected for study

Question 6

Misclassification bias

Answer 6

inaccuracies in methods of data acquisition may misclassify subjects

Question 7

Information bias

Answer 7

bias in the way that information is collected from study participants (recall bias, interviewer bias, non-response bias)

Question 8

Interaction

Answer 8

When the presence of two risk factors at the same time causes different outcomes than the presence of either one.

Can make both risk factors appear more risky or less risky than either really is.

Interaction can be additive or multiplicative

Question 9

Confounding test steps

Answer 9

1. Confirm that the potential confounder is associated with the exposure
2. Confirm that the potential confounder is associated with the outcome
3. Calculate crude OR between exposure and outcome
4. Stratify by the potential confounder and calculate OR (or RR) for each stratum

Question 10

Mantel-Haenszel (MH) analysis

Answer 10

creates a summary measure that is somewhere between OR1 and OR2 and adjusts for the sample size in each stratum

Question 11

Effect Modification test steps

Answer 11

1. Confirm that the potential effect modifier is associated with the exposure
2. Confirm that the potential effect modifier is associated with the outcome
3. Calculate crude OR between exposure and outcome
4. Stratify by the potential effect modifier and calculate OR (or RR) for each stratum

Question 12

The 3rd variable is an effect modifier if:

Answer 12

OR1 ≠ OR2 ≠ crude OR

Question 13

The 3rd variable is a confounder if:

Answer 13

1. Stratified ORs are equal: OR1 = OR2
   AND
2. Stratified ORs ≠ crude OR

Question 14

Confounding Summary

Answer 14

Third variable effect:
distorts or hides a relationship

Evidence:
OR1 = OR2 ≠ ORcrude

Results of Breslow-Day test for homogeneity:
p > 0.05
- the strata (OR1 and OR2) are not different

Reporting: ORadjusted = ORmh
- use stratified analysis or multiple regression to find ORmh

Question 15

Effect Modification Summary

Answer 15

Third variable effect:
Real effect is different in different populations

Evidence:
OR1 ≠ OR2 ≠ ORcrude (none equal)

Results of Breslow-Day test for homogeneity:
p < 0.05
- the strata (ORz and OR2) are different

Reporting:
Stratum-specific ORs: OR1 and OR2 listed separately

Question 16

No Third Variable Effect Summary

Answer 16

Evidence:
OR1 = OR2 = ORcrude (all equal)

Results of Breslow-Day test for homogeneity:
p ≥ 0.05
- the strata (OR1 and OR2) are the same

Reporting:
ORcrude

Question 17

4 Causal Relationships

Answer 17

1. Necessary and sufficient
2. Necessary but not sufficient
3. Sufficient but not necessary
4. Neither sufficient nor necessary

Question 18

Necessary and Sufficient Causation

Answer 18

Rarely found

Example: exposure to an infectious agent causes disease in everyone with the exposure

Question 19

Necessary but Not Sufficient Causation

Answer 19

Example: infectious agent must be contracted to get disease, but not everyone who is infected will become ill

Example: stages of carcinogenesis- each step is part of the causal pathway, but no one step is sufficient to cause cancer

Question 20

Sufficient but Not Necessary Causation

Answer 20

Individual exposures are rarely sufficient, but multiple exposures could lead to disease

Example; radiation and benzene both can cause leukemia but are not necessary exposures

Question 21

Neither Sufficient Nor Necessary Causation

Answer 21

Complex factors that contribute to chronic disease

Question 22

Temporal relationship

Answer 22

exposure before disease.

temporal = time

Question 23

Strength of association

Answer 23

OR, RR far from 1

Question 24

Dose-response relationship

Answer 24

more exposure = higher risk of disease

Question 25

Cessation of exposure

Answer 25

removing exposure reduces risk of disease

Question 26

Specificity of the association

Answer 26

one exposure = one disease

Question 27

How to reduce chance of bias

Answer 27

use large sample size to reduce chance of bias

Question 28

Biologic plausibility

Answer 28

makes biological sense.

shark/ice cream

Question 29

Replication of findings

Answer 29

other studies show the same thing

Question 30

Consistency with other knowledge

Answer 30

Corresponds to other information published by the field