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==Attributable risk among the exposed (ARe)==
 
==Attributable risk among the exposed (ARe)==
The attributable risk among the exposed (risk difference or excess risk) is the proportion of cases among exposed individuals that can be attributed to the exposure. It provides information about the absolute effects of the exposure [1].
+
The attributable risk among the exposed (risk difference or excess risk) is the proportion of cases among exposed individuals that can be attributed to the exposure. It provides information about the absolute effects of exposure<ref>Greenland S, Robins JM. Conceptual problems in the definition and interpretation of attributable fractions. Am J Epidemiol 1988;128:1185-97.</ref>.
 
   
 
   
 
===EXAMPLE: Reducing automobile related deaths===
 
===EXAMPLE: Reducing automobile related deaths===
Let us suppose that we are in charge of a prevention programme and that our goal is to reduce automobile-related deaths. However, we have a limited budget and we want to have the maximum impact on reducing deaths.
+
Let us suppose that we are in charge of a prevention program and that our goal is to reduce automobile-related deaths. However, we have a limited budget and want to have the maximum impact on reducing deaths.
  
 
We decide to conduct a cohort study of 10,000 drivers to examine risk factors for automobile-related deaths. We are particularly interested in factors like drunk driving and speeding since we believe interventions are feasible.
 
We decide to conduct a cohort study of 10,000 drivers to examine risk factors for automobile-related deaths. We are particularly interested in factors like drunk driving and speeding since we believe interventions are feasible.
  
We would like to quantify the disease burden (deaths) due to the exposure in each of the two groups (drunk drivers and speeding drivers). This means that in each exposed group we are aiming to measure how many of the deaths that occur are due to drunk driving and to speeding respectively.
+
We would like to quantify the disease burden (deaths) from exposure in both groups (drunk drivers and speeding drivers). This means that in each exposed group, we are aiming to measure how many deaths occur due to drunk driving and speeding, respectively.
  
 
First, we calculate the risk difference between the exposed and unexposed. This is known as the attributable risk among the exposed (ARe):
 
First, we calculate the risk difference between the exposed and unexposed. This is known as the attributable risk among the exposed (ARe):
  
[[2318.ARe.gif-550x0.png]]
+
[[File:2318.ARe.gif-550x0.png|400px|frameless|left]]
  
  
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We can also express attributable risk as the percentage of all deaths among the exposed that can be attributed to the exposure. .This is known as the attributable fraction among the exposed (AFe):
 
We can also express attributable risk as the percentage of all deaths among the exposed that can be attributed to the exposure. .This is known as the attributable fraction among the exposed (AFe):
  
[[1070.AFe-1.gif-550x0.png]]
+
[[File:1070.AFe-1.gif-550x0.png|400px|frameless|left]]
  
 
Ie = incidence among exposed
 
Ie = incidence among exposed
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==Attributable fraction in cohort studies==
 
==Attributable fraction in cohort studies==
 
In a cohort study, the attributable fraction among the exposed (AFe) is:
 
In a cohort study, the attributable fraction among the exposed (AFe) is:
 
+
[[File:1488.AFe-2.gif-550x0.png|400px|frameless|left]]
[[1488.AFe-2.gif-550x0.png]]
 
  
 
Ie = incidence among exposed
 
Ie = incidence among exposed
Line 59: Line 58:
 
RR = risk ratio
 
RR = risk ratio
  
In the example of speeding and drunk driving we therefore have:
+
In the example of speeding and drunk driving, we therefore have:
  
 
===Speeding===
 
===Speeding===
 +
[[File:0207.AFe-3.gif-550x0.png|400px|frameless|left]]
  
[[0207.AFe-3.gif-550x0.png]]
+
This means that (if speeding causes driving-related deaths) 80% of driving-related deaths among speeding drivers can be attributed to speeding. They could be avoided if speeding did not occur.
 
 
This means that (if speeding causes driving related deaths) 80% of driving related deaths among speeding drivers can be attributed to speeding. They could be avoided if speeding did not occur.
 
  
 
===Drunk driving===
 
===Drunk driving===
[[7343.AFe-4.gif-550x0.png]]
+
[[File:7343.AFe-4.gif-550x0.png|400px|frameless|left]]
  
This means that (if drunk driving causes driving related deaths) 91% of driving related deaths among drunk drivers can be attributed to drunk driving. They could be avoided if drunk driving did not occur.
+
This means that (if drunk driving causes driving-related deaths) 91% of driving-related deaths among drunk drivers can be attributed to drunk driving. They could be avoided if drunk driving did not occur.
  
These examples illustrate what happens if exposure increases risk of disease. If exposure prevents disease (e.g. vaccination), the attributable risk is often called the preventable fraction among the exposed (PFe).
+
These examples illustrate what happens if exposure increases the risk of disease. If exposure prevents disease (e.g. vaccination), the attributable risk is often called the preventable fraction among the exposed (PFe).
  
 
We would then have the following:
 
We would then have the following:
 
+
[[File:2055.PFe-1.gif-550x0.png|400px|frameless|left]]
[[2055.PFe-1.gif-550x0.png]]
 
  
 
Ie = incidence among exposed
 
Ie = incidence among exposed
Line 83: Line 80:
  
 
RR = risk ratio
 
RR = risk ratio
 
 
  
 
Table. Vaccine effectiveness in the population of Anystate, 2010
 
Table. Vaccine effectiveness in the population of Anystate, 2010
Line 103: Line 98:
  
 
To calculate the preventable fraction:
 
To calculate the preventable fraction:
[[4861.PFe-1.gif-550x0.png]]
+
[[File:4861.PFe-1.gif-550x0.png|400px|frameless|left]]
 
 
[[1882.PFe-2b.GIF-550x0.png]]
 
  
 +
[[File:1882.PFe-2b.GIF-550x0.png|400px|frameless|left]]
  
  
Line 113: Line 107:
 
306,045 x (1.72/1,000) = 526 cases
 
306,045 x (1.72/1,000) = 526 cases
  
We have calculated that the vaccine was able to prevent 72% of these cases (the preventable fraction).
+
We have calculated that the vaccine prevented 72% of these cases (the preventable fraction).
  
The estimated number of cases that were prevented by the vaccination programme is therefore:
+
The estimated number of cases that were prevented by the vaccination program is therefore:
  
 
526 x 0.72 = 379 cases
 
526 x 0.72 = 379 cases
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==Attributable fraction in case-control studies==
 
==Attributable fraction in case-control studies==
[[4061.AFe-5.gif-550x0.png]]
+
[[File:4061.AFe-5.gif-550x0.png|400px|frameless|left]]
  
[[6428.PFe-3.gif-550x0.png]]
+
[[File:6428.PFe-3.gif-550x0.png|400px|frameless|left]]
  
 
AFe = attributable fraction among the exposed
 
AFe = attributable fraction among the exposed
Line 132: Line 126:
  
 
Two assumptions are made in substituting OR for RR:
 
Two assumptions are made in substituting OR for RR:
 +
* controls represent the general population
 +
* the prevalence of exposure is low<ref>Cole P, MacMahon B. Attributable risk percent in case-control studies. Br J Prev Soc Med 1971;25:242-4.</ref>.
  
that controls are representative of the general population
+
Methods are also available for calculating attributable fractions for matched case-control studies.<ref>Kuritz SJ, Landis JR. Attributable risk ratio estimation from matched-pairs case-control data. Am J Epidemiol 1987;125:324-8.</ref>
 
 
that the prevalence of exposure is low [2].
 
 
 
Methods are also available for calculating attributable fractions for matched case-control studies [3].
 
  
 
   
 
   
Line 168: Line 160:
  
 
=References =
 
=References =
1. Greenland S, Robins JM. Conceptual problems in the definition and interpretation of attributable fractions. Am J Epidemiol 1988;128:1185-97.
+
<references/>
2. Cole P, MacMahon B. Attributable risk percent in case-control studies. Br J Prev Soc Med 1971;25:242-4.
+
 
3. Kuritz SJ, Landis JR. Attributable risk ratio estimation from matched-pairs case-control data. Am J Epidemiol 1987;125:324-8.
+
 
 +
=credits=
 +
===FEM Editor 2007===
 +
* Meirion Evans
 +
===Original Authors===
 +
* Alain Moren
 +
* Marta Valenciano
 +
* Thomas Grein
 +
===FEM Contributors===
 +
* Lisa Lazareck
 +
* Meirion Evans
 +
 
 +
 
 +
[[Category:Measures of Disease Impact]]

Latest revision as of 21:06, 22 March 2023

Attributable risk among the exposed (ARe)

The attributable risk among the exposed (risk difference or excess risk) is the proportion of cases among exposed individuals that can be attributed to the exposure. It provides information about the absolute effects of exposure[1].

EXAMPLE: Reducing automobile related deaths

Let us suppose that we are in charge of a prevention program and that our goal is to reduce automobile-related deaths. However, we have a limited budget and want to have the maximum impact on reducing deaths.

We decide to conduct a cohort study of 10,000 drivers to examine risk factors for automobile-related deaths. We are particularly interested in factors like drunk driving and speeding since we believe interventions are feasible.

We would like to quantify the disease burden (deaths) from exposure in both groups (drunk drivers and speeding drivers). This means that in each exposed group, we are aiming to measure how many deaths occur due to drunk driving and speeding, respectively.

First, we calculate the risk difference between the exposed and unexposed. This is known as the attributable risk among the exposed (ARe):

2318.ARe.gif-550x0.png


The study gives the following results:

Table. Risk of death from speeding or drunk driving, Anystate, 2010 Speeding

Speeding Total drivers No. of deaths Risk of death  Attributable risk (exposed)
Yes 2,000 100 50 50 - 10 = 40/1,000
No 8,000 80 10
Drunk driving Total drivers No. of deaths Risk of death per 1,000 Attributable risk (exposed)
Yes 300 45 150 150 - 14 = 136/1,000
No 9,700 135 14

We can also express attributable risk as the percentage of all deaths among the exposed that can be attributed to the exposure. .This is known as the attributable fraction among the exposed (AFe):

1070.AFe-1.gif-550x0.png

Ie = incidence among exposed

Iu = incidence among unexposed

If the risk factor is causal, then the attributable fraction among the exposed corresponds to the proportion of disease among the exposed that can:

  • be attributed to the exposure
  • be avoided by eliminating the exposure.


Attributable fraction in cohort studies

In a cohort study, the attributable fraction among the exposed (AFe) is:

1488.AFe-2.gif-550x0.png

Ie = incidence among exposed

Iu = incidence among unexposed

RR = risk ratio

In the example of speeding and drunk driving, we therefore have:

Speeding

0207.AFe-3.gif-550x0.png

This means that (if speeding causes driving-related deaths) 80% of driving-related deaths among speeding drivers can be attributed to speeding. They could be avoided if speeding did not occur.

Drunk driving

7343.AFe-4.gif-550x0.png

This means that (if drunk driving causes driving-related deaths) 91% of driving-related deaths among drunk drivers can be attributed to drunk driving. They could be avoided if drunk driving did not occur.

These examples illustrate what happens if exposure increases the risk of disease. If exposure prevents disease (e.g. vaccination), the attributable risk is often called the preventable fraction among the exposed (PFe).

We would then have the following:

2055.PFe-1.gif-550x0.png

Ie = incidence among exposed

Iu = incidence among unexposed

RR = risk ratio

Table. Vaccine effectiveness in the population of Anystate, 2010

No. of cases Cases per 1,000 Risk ratio (RR)
Population
Vaccinated 306,045 150 0.49 0.28
Unvaccinated 298,655 515 1.72 Reference
Total 604,700 665 1.1


To calculate the preventable fraction:

4861.PFe-1.gif-550x0.png
1882.PFe-2b.GIF-550x0.png


The expected number of cases among the vaccinated population, if they were unvaccinated, is:

306,045 x (1.72/1,000) = 526 cases

We have calculated that the vaccine prevented 72% of these cases (the preventable fraction).

The estimated number of cases that were prevented by the vaccination program is therefore:

526 x 0.72 = 379 cases


Attributable fraction in case-control studies

4061.AFe-5.gif-550x0.png
6428.PFe-3.gif-550x0.png

AFe = attributable fraction among the exposed

PFe = preventable fraction among the exposed

OR = odds ratio

Two assumptions are made in substituting OR for RR:

  • controls represent the general population
  • the prevalence of exposure is low[2].

Methods are also available for calculating attributable fractions for matched case-control studies.[3]


Synopsis

Attributable risk among the exposed (ARe)

  • The number of cases (amount of disease) among the exposed that can be attributed to the exposure
  • What is the risk among the exposed that is due to the exposure?
  • This is calculated as the absolute difference between risk in the exposed and risk in the unexposed
  • It assumes that the causal effect is entirely due to the risk factor

Synonyms:

  • Attributable risk (exposed)
  • Attributable benefit (exposed)
  • Risk difference / Excess risk
  • Rate difference / Excess rate
  • Absolute risk reduction

Attributable fraction among the exposed (AFe)

  • The proportion of cases (percentage of disease) among the exposed that can be attributed to the exposure
  • Attributable risk expressed as a proportion of the risk in the exposed
  • What is the proportion of disease among the exposed that:
    • can be attributed to the exposure?
    • can be prevented if the exposure is eliminated?

Synonyms:

  • Attributable fraction (exposed)
  • Attributable proportion / Attributable risk percent (exposed)
  • Aetiological fraction / Preventable fraction (exposed)
  • Relative risk reduction

References

  1. Greenland S, Robins JM. Conceptual problems in the definition and interpretation of attributable fractions. Am J Epidemiol 1988;128:1185-97.
  2. Cole P, MacMahon B. Attributable risk percent in case-control studies. Br J Prev Soc Med 1971;25:242-4.
  3. Kuritz SJ, Landis JR. Attributable risk ratio estimation from matched-pairs case-control data. Am J Epidemiol 1987;125:324-8.


credits

FEM Editor 2007

  • Meirion Evans

Original Authors

  • Alain Moren
  • Marta Valenciano
  • Thomas Grein

FEM Contributors

  • Lisa Lazareck
  • Meirion Evans

Contributors