epidemiology kept simple chapter 8 measures of association & potential impact

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Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact

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Page 1: Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact

Epidemiology Kept Simple

Chapter 8

Measures of Association & Potential Impact

Page 2: Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact

Gerstman Chapter 8 2

Important Jargon• Exposure (E) an explanatory factor; any

potential health determinant; the independent variable

• Disease (D) the response; any health-related outcome; the dependent variable

• Measure of association (syn. measure of effect) a statistic that quantifies the relationship between an exposure and a disease

• Measure of potential impact a statistic that quantifies the potential impact of removing a hazardous exposure

Page 3: Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact

Gerstman Chapter 8 3

Arithmetic (αριθμός) Comparisons

• Measures of association are mathematical comparisons

• Mathematic comparisons can be done in absolute terms or relative terms

• Let us start with this ridiculously simple example:

• I have $2 • You have $1

"For the things of this world cannot be made known without a knowledge of mathematics."- Roger Bacon

Page 4: Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact

Gerstman Chapter 8 4

Absolute Comparison• In absolute terms, I

have $2 – $1 = $1 more than you

• Note: the absolute comparison was made with subtraction

It is as simple as that…

Page 5: Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact

Gerstman Chapter 8 5

Relative Comparison• Recall that I have $2 and

you have $1. • In relative terms,

I have $2 ÷ $1 = 2, or

“twice as much as you”• Note: relative comparison

was made by division

Page 6: Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact

Gerstman Chapter 8 6

• Suppose, I am exposed to a risk factor and have a 2% risk of disease.

• You are not exposed and you have a 1% risk of the disease.

Applied to Risks

• Of course we are assuming we are the same in every way except for this risk factor.

• In absolute terms, I have 2% – 1% = 1% greater risk of the disease

• This is the risk difference

Page 7: Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact

Gerstman Chapter 8 7

• In relative terms I have

2% ÷ 1% = 2, or twice the risk

• This is the relative risk associated with the exposure

Applied to Risks

Page 8: Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact

Gerstman Chapter 8 8

Terminology

For simplicity sake, the terms “risk” and “rate” will be applied to all incidence and prevalence measures.

Page 9: Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact

Gerstman Chapter 8 9

Risk DifferenceRisk Difference (RD) Risk Difference (RD) absolute absolute effect associated with exposureeffect associated with exposure

01 RRRD

where where

RR11 ≡ risk in the exposed group ≡ risk in the exposed group RR00 ≡≡ risk in the non-exposed grouprisk in the non-exposed group

Interpretation: Interpretation: ExcessExcess risk in absolute risk in absolute termsterms

Page 10: Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact

Gerstman Chapter 8 10

Relative RiskRelative Risk (RR) Relative Risk (RR) relative effect relative effect associated with exposure or the “risk associated with exposure or the “risk ratioratio””

0

1

R

RRR

where where

RR11 ≡ risk in the exposed group ≡ risk in the exposed group RR00 ≡≡ risk in the non-exposed grouprisk in the non-exposed group

Interpretation: excess risk in relative Interpretation: excess risk in relative termsterms..

Page 11: Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact

Gerstman Chapter 8 11

Example Fitness & Mortality (Blair et al., 1995)

• Is improved fitness associated with decreased mortality?

• Exposure ≡ improved fitness (1 = yes, 0 = no)

• Disease ≡ death(1 = yes, 0 = no)

• Mortality rate, group 1:R1 = 67.7 per 100,000 p-yrs

• Mortality rate, group 0:R0 = 122.0 per 100,000 p-yrs

Page 12: Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact

Gerstman Chapter 8 12

Example

Risk Difference

01 RRRD

The effect of the exposure (improved fitness) is to decrease mortality by 54.4 per 100,000 person-years

What is the effect of improved fitness on mortality in absolute terms?

yrs-p 100,000

0.122

yrs-p 100,000

7.67

yrs-p 100,000

4.54

Page 13: Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact

Gerstman Chapter 8 13

Example

Relative Risk

0

1

R

RRR

What is the effect of improved fitness on mortality in relative terms?

55.0yrs-p 100,000per 0.122

yrs-p 100,000per 7.67

The effect of the exposure is to cut the risk almost in half.

Page 14: Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact

Gerstman Chapter 8 14

Designation of Exposure• Switching the designmation of

“exposure” does not materially affect interpretations

• For example, if we had let “exposure” ≡ failure to improve fitness

• RR = R1 / R0 = 122.0 / 67.7 = 1.80 (1.8 times the risk in the

exposed group (“almost double”)

Page 15: Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact

Gerstman Chapter 8 15

2-by-2 Table FormatDisease + Disease − Total

Exposure + A1 B1 N1

Exposure – A0 B0 N0

Total M1 M0 N

For person-time data: let N1 ≡ person-time in group 1 and N0 ≡ person-time in group 0, and ignore cells B1 and B0

1

11 N

AR

0

00 N

AR

Page 16: Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact

Gerstman Chapter 8 16

Fitness Data, table formatFitness Improved?

Died Person-years

Yes 25 -- 4054

No 32 -- 2937

67.61000,104054

25

1

11

N

AR

95.108000,102937

32

0

00

N

AR

Rates per 10,000 person-years

Page 17: Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact

Gerstman Chapter 8 17

Food borne Outbreak Example

Disease + Disease − Total

Exposure + 63 25 88

Exposure –

1 6 7

Total 64 31 95

7159.088

63

1

11 N

AR 1429.0

7

1

0

00 N

AR

Exposure ≡ eating a particular dishDisease ≡ gastroenteritis

Page 18: Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact

Gerstman Chapter 8 18

Food borne Outbreak Data

71

8863

0

1 R

RRR

1429.0

7159.0 01.5

Exposed group had 5 times the risk

Disease + Disease − Total

Exposure + 63 25 88

Exposure – 1 6 7

Total 64 31 95

Page 19: Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact

Gerstman Chapter 8 20

What do you do when you have multiple levels of exposure?

Compare rates to least exposed “reference” group

LungCA Rate (per 100,000 person-years)

RR

Non-smoker (0) 10 1.0 (ref.)

Light smoker (1) 52 5.2

Mod. smoker (2) 106 10.6

Heavy sm. (3) 224 22.4

2.501

25

0

11

R

RRR 6.10

01

106

0

22 R

RRR

Page 20: Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact

Gerstman Chapter 8 21

The Odds Ratio

• When the disease is rare, interpret the same way you interpret a RR

• e.g. an OR of 1 means the risks are the same in the exposed and nonexposed groups

D+ D− Total

E+ A1 B1 N1

E− A0 B0 N0

Total M1 M0 N

01

01

00

11

AB

BA

BA

BAOR

“Cross-product ratio”

Similar to a RR, but based on odds rather than risks

Page 21: Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact

Gerstman Chapter 8 22

Odds Ratio, ExampleMilunsky et al, 1989, Table 4

NTD = Neural Tube DefectNTD+ NTD−

Folic Acid+ 10 10,703

Folic Acid− 39 11,905

01

01

AB

BAOR

Exposed group had 0.29 times (about a quarter) the risk of the nonexposed group

39703,10

905,1110

29.0

Page 22: Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact

Gerstman Chapter 8 23

Measures of Potential Impact

• These measures predicted impact of removing a hazardous exposure from the population

• Two types– Attributable fraction in

exposed cases– Attributable fraction in

the population as a whole

Page 23: Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact

Gerstman Chapter 8 24

Attributable Fraction Exposed Cases (AFe)

RR

RRAFe

1 :formula Equivalent

1

01 :formula alDefinitionR

RRAFe

Proportion of exposed cases averted with elimination of the exposure

Page 24: Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact

Gerstman Chapter 8 25

Example: AFe

RR of lung CA associated with moderate smoking is approx. 10.4. Therefore:

RR

RRAFe

1

Interpretation: 90.4% of lung cancer in moderate smokers would be averted if they had not smoked.

904.4.10

14.10

Page 25: Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact

Gerstman Chapter 8 26

Attributable Fraction, Population (AFp)

population nonexposedin rate

rate overall

where

:formula alDefinition

0

0

R

R

R

RRAFp

Proportion of all cases averted with elimination of exposure from the population

Page 26: Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact

Gerstman Chapter 8 27

AFp equivalent formulas

populationin exposure of prevalence where

)1(1

)1(

e

e

ep

p

RRp

RRpAF

exposed are that cases of proportion where

c

cep

p

pAFAF

Page 27: Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact

Gerstman Chapter 8 28

AFp for Cancer Mortality, Selected Exposures

Exposure Doll & Peto, 1981 Miller, 1992

Tobacco 30% 29%

Dietary 35% 20%

Occupational 4% 9%

Repro/Sexual 7% 7%

Sun/Radiation 3% 1%

Alcohol 3% 6%

Pollution 2% -

Medication 1% 2%

Infection 10% -