HLTH 207 Week 3 Asynchronous Work (ONE)

How are dichotomous exposure and outcomes organized?

2×2 tables

Which measure(s) of association can be calculated from the following table?

Rate-based measures of association

Which measure(s) of association can be calculated from the following table?

Risk/prevalence-based measures of association

Label the following table

1. Outcome (O+)

2. No outcome (O-)

3. Total

4. Exposed (E+)

5. A

6. C

7. N1 (A+C)

8. Unexposed (E-)

9. B

10. D

11. N0 (B+D)

12. Total

13. M1 (A+B)

14. M0 (C+D)

15. N

5 marginal totals of the 2×2 table

1. N

2. N1

3. N0

4. M1

5. M0

N (2×2 table)

total number of individuals in the study population

N1 (2×2 table)

total number of individuals exposed

N0 (2×2 table)

tota number of individuals who are unexposed

M1 (2×2 table)

total number of individuals with the outcome

M0 (2×2 table)

Total number of individuals without the outcome

A (2×2 table)

individuals who are exposed and have the outcome

B (2×2 table)

individuals who are unexposed and have the outcome

C (2×2 table)

individuals who are exposed and do not have the outcome

D (2×2 table)

individuals who are unexposed and do not have the outcome

Measures of association

derived by comparing measures of frequency for two groups

2 ways that measures of association are typically calculated

1. Taking the ratio of two measures of frequency

2. Taking the difference of two measures of frequency

Null value

the value that a measure of association takes on when there is no association between the exposure and outcome

What will the frequency of the outcome in the exposed and unexposed groups if there is no association between an exposure and outcome

The frequency of the outcome in the exposed group = frequency of the outcome in the unexposed group

Null value for all ratio measures of association

1

Null value for all difference measures of association

The null value for all difference measures of association is zero

Goal of calculating measures of association

Ultimately we will calculate a measure of association using our study data, and our goal is to determine whether it is different from its null value

What can we determine if our measures of association is significantly different from our null value?

This suggests that there is an association between exposure and outcome

Direction of a measure of association meaning

Refers to where it lies relate to its null value

Measure of association falls below the null meaning

Negative association - exposure is associated with a decreased outcome frequency

Measure of association falls above the null meaning

Positive association - exposure is associated with an increased outcome frequency

Magnitude of a measure of association meaning

Refers to the strength of association

What is teh global cutoff for classifying the strength of association?

There is no global cutoff

Whether an association is considered strong depends on the ___________________

research question

Risk ratio

a measure of the strength of the relative risk of an outcome between an exposed and unexposed group during a specific follow-up period

Risk ratio calculation

Risk in the exposed/risk in the unexposed = (A/N1)/(B/N0)

Risk difference

a measure of the absolute difference in the risk of an outcome between an exposed and unexposed group during a specified follow-up period

Risk difference calculation

Risk difference = risk in the exposed - risk in the unexposed = A/N1 - B/N0

Risk-based measures of association are appropriate for what 2 applications?

1. Some controlled trials

2. Some cohort studies

When might it not be appropriate to calculate risk-based measures

If follow-up is not uniform for all study participants

Interpretations of risk-based measures of association must include what information?

Information about hte length of the follow-up period

Prevalence ratio

a measure of the strength of the relative prevalence of an outcome between an exposed and unexposed group

Prevalence ratio calculation

Prevalence ratio = prevalence in the exposed/prevalence in the unexposed = (A/N1)/(B/N0)

Prevalence difference

a measure of the absolute difference in the prevalence of an outcome between an exposed and unexposed group

Prevalence difference calculation

Prevalence difference = prevalence in the exposed - prevalence in the unexposed = A/N1 - B/N0

Prevalence-based measures of association are appropriate for what application? Why?

Appropriate for the cross-sectional design since the observed outcomes are existing, rather than the newly-occurring

Exposure odds ratio (EOR)

the only measure of association that is appropriate to calculate for case-control studies

What measure does the EOR use?

The odds

EOR calculation

odds of exposure among the cases/odds of exposure among the controls = (A/B)/(C/D) = (AxD)/(BxC)

What must a table used to organize data to allow for calculating rates and rate-based measures of association incorporate?

Person-time

Label the following table

1. Outcome (+)

2. Person-time

3. Exposed (E+)

4. A

5. PT1

6. Unexposed (E-)

7. B

8. PT0

9. Total

10. M1 (A+B)

11. PT (PT1 +PT0)

PT1 (table)

total person-time contributed by all participants who were exposed

PT0 (table)

total person-time contributed by all participants who were unexposed

PT (table)

person-time contributed by the entire study population

Rate ratio

a measure of the strength of the relative risk of an outcome between an exposed and unexposed group

Rate ratio calculation

Rate ratio = rate in the exposed/rate in the unexposed = (A/PT1)/(B/PT0)

Rate difference

a measure of the absolute difference in the rate of an outcome between an exposed and unexposed group

Rate difference calculation

Rate difference = rate in the exposed - rate in the unexposed = A/PT1 - B/PT0

Do epidemiologic studies typically measure causation or association?

Association

How are measures of association related to causation?

A measure of association from an epidemiologic study may support or refute a study hypothesis of causation but a single epidemiologic study is unable to establish causation

Ideal scenario in epidemiologic study- is this possible? Why or why not?

• Ideally, we would observe the outcome for an individual when exposed and then observe the outcome for the same individual when unexposed, all else equal

• The ideal is impossible to observe because each individual has only one exposure status

Counterfactual

Unobservable (exposure status that did not actually occur) - hypothetical

Bradford Hill’s Criteria for Causation

guidelines for consideration when thinking about causal relationships, but should not be treated as a rigid checklist

9 guidelines of Bradford Hill’s Criteria for Causation

1. Strength

2. Consistency

3. Specificity

4. Temporality

5. Biological gradient/dose response

6. Biological plausibility

What is the only critical requirement for implying causation?

Temporality

Temporality

Requires that the exposure must occur before the outcome