Measures of Impact Lazareto, Menorca, Spain September 2011 L Petersen 1999, T Grein 2000-2004, M...

Post on 27-Mar-2015

218 views 1 download

Tags:

Transcript of Measures of Impact Lazareto, Menorca, Spain September 2011 L Petersen 1999, T Grein 2000-2004, M...

Measures of Impact

Lazareto, Menorca, SpainSeptember 2011

L Petersen 1999, T Grein 2000-2004, M Valenciano 2005-2007, P Stefanoff 2008, N Boxall 2009, F Burckhardt 2010, I Karagiannis 2011

2

Objectives

• To define measures of impact

• To calculate the attributable risk- among the exposed

- in the population

3

Scenario

• You are in charge of health promotion “Preventing automobile-related deaths”

• Limited budget best reduction of deaths

• Evidence: retrospective cohort study: “causes of automobile-related deaths”

4

Relative Risks

• Best reduction of deaths?

• Prevent drink & drive?

• Prevent speeding?

Relative Risk

Driving too fast 5

Driving while drunk 10.7

5

Relative Risks

0.0000050.000001

0.50.1

Risk (exposed) Risk (unexposed)

RR = 5.0

6

Measures of Impact

• Provide information about the public health impact of an exposure

• Contribution of an exposure to the frequency of disease

• Several concepts- Attributable risk (AR)

- Attributable risk among exposed (AR%)

- Attributable risk in the population (PAR)

- Preventable fraction among exposed (PF)

7

Attributable Risk (AR)(synonyms: Risk Difference)

• Quantifies disease burden in exposed group attributable to exposure in absolute terms

• AR = Re - Rne

• Answers:- what is the risk attributed to the exposure?

- what is the excess risk due to the exposure?

• Only use if causality “exposure > outcome”

8

Attributable Risk (AR)

• AR = Re - Rne

Outcome

a

c d

yes no

exposed

not exposed

b

Attributable Risk =

a

a+b

c

c+d

a+b

c+d

a

a+b

c

c+d-

Attributable Risk = Re – background risk

= Re

= Rne

9

Attributable Risk (AR)

Risk

0.01

0.05

Risk of death by speeding

Risk of death by driving speed limit

How high is the added risk of dying caused by the exposure “speeding“?

Added risk ?

exposure: speeding0.00

10

AR Speeding

AR (speeding) = 0.05 - 0.01 = 0.04 “speeding increases the risk of dying by 0.04. Four out of 100 speeding drivers will die in addition to normal (=background) death by driving because they drove too fast“.

11

AR Drunk driving

AR (drunk driving) = 0.15 - 0.01 = 0.14

“drunk driving increases the risk of dying by 0.14. Fourteen out of 100 drunk drivers die in addition to normal (background) death by driving because they were drunk while driving."

12

Summary so far

Measure Speeding Drunk driving

Relative Risk 5 10.7

Attributable Risk 0.04 0.14

13

Attributable Risk Percent (AR%)(synonyms: Attributable Fraction)

• Attributable risk expressed as a percentage of risk in exposed population

• Proportion of disease among the exposed which:

- can be attributed to the exposure

- could be prevented by eliminating the exposure

• AR% looks at exposed population, not total population

14

Attributable Risk Percent (AR%)

• Example speeding: What proportion of all speeding deaths (denominator) died because they drove too fast (numerator)?

deaths caused by speeding

deaths of all who drove too fastAR% = x 100

15

Attributable Risk Percent (AR%)

Risk (exposed) - Risk (not exposed)

Risk (exposed)x 100

RR > 1

AR% =

Risk (exposed) Risk (not exposed)

Risk (exposed) Risk (exposed)= - x 100

1

Relative Risk= 1 - x 100

RR - 1

RR= x 100

16

AR% Speeding drivers

AR% (speeding) = 80%“80% of all people who died while driving too fast, died because they drove too fast“.

17

AR% Drunk drivers

AR% (drunk driving) = 93%“93% of all people who died while being drunk, died because they were drunk“.

18

Summary so far

Measure Speeding Drunk driving

Relative Risk 5 10.7

Attributable Risk 0.04 0.14

Attributable Risk% 80% 93%

19

AR & AR% in Case-Control Studies

• No direct risk estimates in case-control study- AR (risk difference) and AR% calculation

IMPOSSIBLE!

Relative Risk - 1

Relative RiskAR% = x 100

20

AR & AR% in Case-Control Studies

• No direct risk estimates in case-control study- AR (risk difference) and AR% calculation

IMPOSSIBLE?

• If odds ratio approximates relative risk, then

Relative Risk - 1

Relative RiskAR% = x 100

Odds Ratio - 1

Odds RatioAR% = x 100

21

Population Attributable Risk (PAR%)

• Proportion of cases in the total population attributable to the exposure

• Proportion of disease in the total population that could be prevented if we could eliminate the risk factor

• Determine exposures relevant to public health in community

• Only use if causality “exposure > outcome”

22

Population Attributable Risk (PAR%)

• Example speeding: What proportion of all people who died (denominator) died because they drove too fast (numerator)?

deaths caused by speeding

total deathsPAR% = x 100

23

Population Attributable Risk (PAR%)

Risk (total pop) - Risk (not exposed)

Risk (total pop)x 100PAR% =

p (RR - 1)

p (RR - 1) +1x 100PAR% =

p = proportion of population exposed

PAR% = p(cases) x AR%

p(cases) = proportion of cases exposed

24

PAR% Speeding

Risk (total) - Risk (not exposed)

Risk(total)PAR% = = = 0.44

0.018 - 0.01

0.018

= 44%

risk in total population

risk in unexposed

25

PAR% Speeding

100

80 7920

2000

8000

10000

dead alive

180 9820

speeding

notspeeding

1900

Risk

100/2000 = 0.05

80/8000 = 0.01

Attributable Risk (AR) = 0.05 - 0.01 = 0.04

AR

Risk(exposed)AR% = x 100 = (0.04/0.05) x 100 = 80%

p(cases) = % cases exposed = 100/180 = 0.55

PAR% = pc x AR% = 0.55 x 80% = 44%

26

PAR% Drunk driving

Risk (total) - Risk (not exposed)

Risk(total)PAR% = = = 0.22

0.018 - 0.014

0.018

= 22%

risk in total population

risk in unexposed

27

Summary

Measure Speeding Drunk driving

Relative Risk 5 10.7

Attributable Risk 0.04 0.14

Attributable Risk% 80% 93%

Pop. attributable risk% 44% 22%

% drivers with risk factor in population

20% 3%

• Best reduction of deaths?

• Prevent drinking or speeding?

28

PAR% in Case-Control Studies

• proportion of controls exposed ≈ proportion of population exposed

PAR% =Pcontrols – (OR – 1)

x 100Pcontrols (OR – 1) + 1Pcontrols = Proportion of controls exposed

PAR% = Pcases ( OR – 1 ) x 100OR

Where Pcases = proportion cases exposed

29

Summary

Measure Meaning Question answered

RR, OR Strength of association (between exposure > outcome)

Is the exposure associated with the risk of getting ill/ the outcome?

AR Excess risk of exposed (in absolute terms)

What is the difference in risk between exposed and not exposed?

AR% Proportion of risk of exposed attributed to exposure, potential prevention of exposed

What proportion of those who are exposed and ill is likely due to the exposure?

PAR% Proportion of risk of population attributed to exposure, potential prevention of population,

Public Health relevance

What proportion of those who are ill in the population is likely due to the exposure?

30

Preventable fraction (PF)

• Exposure associated with decreased risk

• Where RR < 1, exposure is protective

• Proportion of cases that would have occurred if exposure hadn’t happened

Vaccination!

31

• RR < 1 = protective exposure (protective factor)

• Proportion of cases that were prevented because of exposure

Risk (not exposed) - Risk (exposed)

Risk (not exposed)

Preventable fraction (PF)

PF =

Risk (not exposed) Risk (exposed)

Risk (not exposed) Risk (not exposed)PF = -

32

• RR < 1 = protective exposure (protective factor)

• Proportion of cases that were prevented because of exposure

Risk (not exposed) - Risk (exposed)

Risk (not exposed)

Preventable fraction (PF)

PF =

PF = 1 - Relative Risk

Risk (not exposed) Risk (exposed)

Risk (not exposed) Risk (not exposed)PF = -

33

Preventable Fraction (PF)Vaccine efficacy

  Pop. CasesCases

/100,000

Vaccinated 200,000 100 50

Unvaccinated 300,000 600 200

Total 500,000

Risk (not exposed) - Risk (exposed)

Risk (not exposed)PF =

PF = 600/300,000 - 100/200,000

600/300,000= 0.75

34

Preventable Fraction (PF)Vaccine efficacy

• How many people would have been ill without the vaccine?

• 200/100,000 cases of unvaccinated

• In population of 200,000 we expect 400 cases

• Only 100 cases occurred; 300 cases were prevented (by vaccine)

• 300/400 = 75% of hypothetical cases were prevented

Thank you