Measures of Impact
18th EPIET/EUPHEM Introductory Course
September-October 2012
Lazareto, Menorca, Spain
Ioannis Karagiannis
Objectives
• To define measures of impact
• To calculate the attributable risk
- among the exposed
- in the population
• Eventually, make sense of stuff
2
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”
3
Relative Risks
Relative Risk
Driving too fast
5
Driving while drunk
11
• Best reduction of deaths?
• Prevent drink & drive?
• Prevent speeding?
4
Relative Risks
Risk (exposed)
Risk (unexposed)
0.000005
0.000001
0.5
0.1
RR = 5.0
5
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)
6
Attributable Risk (AR)
(synonyms: Risk Difference)
• Quantifies disease burden in exposed group
attributable to exposure in absolute terms
• AR = Re - Ru
• Answers:
- what is the risk attributed to the exposure?
- what is the excess risk due to the exposure?
• Only use if causality “exposure  outcome”
7
Attributable Risk (AR)
• AR = Re - Ru
Outcome
no
yes
exposed
a
b
a
a+b
= Re
a+b
not
exposed
c
d
c
c+d
= Ru
c+d
Attributable Risk =
a
a+b
-
c
c+d
Attributable Risk = Re – background risk
8
Attributable Risk (AR)
Risk
How high is the added risk of dying caused
by the exposure “speeding“?
0.05
Risk of death by
speeding
Added risk ?
Risk of death by
driving below the
speed limit
0.01
0.00
exposure: speeding
9
AR Speeding
Outcome
Speeding
Dead Alive
Yes
No
100
1900
Risk
2000
80
7920
8000
180
9820 10000
Risk
Ratio
Risk
Difference
5
0.04
0.05
0.01
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) because they drove
too fast“.
10
AR Drunk driving
Outcome
Drunk
Driving
Dead Alive
Yes
No
45
255
Risk
300
135
9565
9700
180
9820 10000
Risk
Ratio
Risk
Difference
11
0.14
0.15
0.01
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."
11
Summary so far
Measure
Relative Risk
Attributable Risk
Speeding
Drunk driving
5
0.04
11
0.14
12
Attributable Risk Percent (AR%)
(synonyms: Attributable Fraction)
• Attributable risk expressed as a percentage of
risk in the 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 the total population
13
Attributable Risk Percent (AR%)
• Example speeding: What proportion of all
speeding deaths (denominator) died because
they drove too fast (numerator)?
AR% =
deaths caused by speeding
deaths of all who drove too fast
x 100
14
Attributable Risk Percent (AR%)
RR > 1
Risk (exposed) - Risk (unexposed)
AR% =
=
=
Risk (exposed)
Risk (exposed)
Risk (exposed)
-
1
-
Risk (unexposed)
Risk (exposed)
1
x 100
x 100
x 100
Relative Risk
=
RR - 1
x 100
RR
15
AR% Speeding drivers
Outcome
Speeding
Dead Alive
Yes
100
1900
Risk
2000
AR%
0.05
0.05-0.01
= 80%
0.05
No
80
7920
8000
180
9820 10000
0.01
AR% (speeding) = 80%
“80% of all people who died while driving too fast, died because they
drove too fast“.
16
AR% Drunk drivers
Outcome
Drunk
Driving
Dead Alive
Yes
45
255
Risk
300
AR%
0.15
0.15-0.01
= 93%
0.15
No
135
9565
9700
180
9820 10000
0.01
AR% (drunk driving) = 93%
“93% of all people who died while being drunk, died because they were
drunk“.
17
Summary so far
Measure
Relative Risk
Attributable Risk
Attributable Risk%
Speeding
Drunk driving
5
0.04
80%
11
0.14
93%
18
AR & AR% in Case-Control Studies
AR% =
Relative Risk - 1
x 100
Relative Risk
• No direct risk estimates in case-control study
- AR (risk difference) and AR% calculation
IMPOSSIBLE!
19
AR & AR% in Case-Control Studies
AR% =
Relative Risk - 1
x 100
Relative Risk
• No direct risk estimates in case-control study
- AR (risk difference) and AR% calculation
IMPOSSIBLE?
• If odds ratio approximates relative risk, then
AR% =
Odds Ratio - 1
x 100
Odds Ratio
20
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
• Determines exposures relevant to public
health in community
• Only use if causality “exposure  outcome”
21
Population Attributable Risk (PAR%)
• Example speeding: What proportion of all
people who died (denominator) died because
they drove too fast (numerator)?
PAR% =
deaths caused by speeding
total deaths in the population
x 100
22
Population Attributable Risk (PAR%)
Risk (total pop) - Risk (unexposed)
PAR% =
Risk (total pop)
x 100
p (RR - 1)
PAR% =
x 100
p (RR - 1) +1
p = proportion of population exposed
PAR% = p(cases) x AR%
p(cases) = proportion of cases exposed
23
PAR(%) according to the relative risk
for various level of exposure frequency
among cases
100.0%
Pe 10%
Pe 25%
Pe 50%
Pe 75%
Pe 100% (AFe)
Population attributable fraction
90.0%
80.0%
70.0%
60.0%
50.0%
40.0%
30.0%
20.0%
10.0%
0.0%
1
2
3
4
5
6
Relative risks
7
8
9
10
PAR% Speeding
Outcome
Speeding
Dead Alive
Risk
Yes
100
1900
2000
0.050
No
80
7920
8000
0.010 risk in unexposed
180
9820 10000
0.018 risk in total population
Risk (total) - Risk (not exposed) 0.018 - 0.01
=
PAR% =
= 0.44
Risk(total)
0.018
= 44% 25
PAR% Speeding
dead alive
Risk
speeding
100
1900
2000
100/2000 = 0.05
not
speeding
80
7920
8000
80/8000 = 0.01
180
9820
10000
Attributable Risk (AR) = 0.05 - 0.01 = 0.04
AR% =
AR
Risk(exposed)
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
Outcome
Drunk
Driving
Dead Alive
PAR% =
Risk
Yes
45
255
300
0.150
No
135
9565
9700
0.014 risk in unexposed
180
9820 10000
0.018 risk in total population
Risk (total) - Risk (unexposed)
Risk(total)
0.018 - 0.014
=
= 0.22
0.018
= 22% 27
Summary
Measure
Speeding
Drunk driving
Relative Risk
Attributable Risk
Attributable Risk%
Pop. attributable risk%
% drivers with risk
factor in population
5
0.04
80%
44%
20%
11
0.14
93%
22%
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)
Pcontrols (OR – 1) + 1
x 100
Pcontrols = Proportion of controls exposed
PAR% = Pcases
(
OR – 1
OR
)
x 100
Where Pcases = proportion cases exposed
29
Summary
Measure
Meaning
Question answered
RR, OR
Strength of association
(between exposure and
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,
What proportion of those who are ill in
the population is likely due to the
exposure?
Public Health relevance
30
Take-home message
• There is more death and disability from
frequent exposure to lower risks than to rare
exposures to higher risks
• Examples:
 More people die from marginally elevated blood
pressure (common) than from seriously elevated
blood pressure (uncommon)
 More people acquire HCV from unsafe injection
(common exposure, lower risk) than from unsafe
blood products (rare exposure, high risk)
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 been present
32
Preventable fraction (PF)
• RR < 1  protective exposure (protective
factor)
• Proportion of cases that were prevented
because of the exposure
PF =
PF =
Risk (unexposed) - Risk (exposed)
Risk (unexposed)
Risk (unexposed)
Risk (unexposed)
-
Risk (exposed)
Risk (unexposed)
PF = 1 - Relative Risk
33
Preventable Fraction (PF)
Vaccine efficacy
Pop.
Cases
Cases
/100,000
Vaccinated
200,000
100
50
Unvaccinated
300,000
600
200
Total
500,000
PF =
PF =
Risk (unexposed) - Risk (exposed)
Risk (unexposed)
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
35
True or false?
• The relative risk of lung cancer and smoking is 9
• Therefore, if nobody smoked, the incidence of lung
cancer would be nine times lower than it currently is
 False
Measures of association are not measures of impact.
The prevalence of smoking in the population also matters!
True or false?
• 90% of patients with lung cancer are smokers
• Therefore, if nobody smoked, the incidence of lung
cancer would be reduced by 90%
 False
The proportion of a disease that may be explained by a specific
exposure does not depend on the proportion of cases exposed. It also
depends on the strength of the association (90% of patients with lung
cancer also eat fresh salad for lunch every day)
Thank you 