What comes from what?

1
What comes from what?

• Measure of impact
• FETP India

2
Competency to be gained from this lecture

• Calculate an attributable fraction

3
Terminology

• Attributable fraction
• Etiologic fraction
• Attributable risk

Same thing
4
True or false?

• The relative risk of lung cancer among smokers is
  9
• Therefore, if nobody was smoking, the incidence
  of lung cancer would be divided by nine

? FalseMeasures of association are not measures
of impact It is not only the strength of
association that matters but also the proportion
of the population exposed to the risk factor.
5
True or false?

• 90 of patients with lung cancer are smokers
• Therefore, if nobody was smoking, the incidence
  of lung cancer would be reduced by 90

? False The proportion of a disease that may be
explained bya specific exposure does not depend
on the proportion of cases exposed. It also
depends upon the strength of the association
(90 of patients with lung cancer also eat masala
dosa)
6
Presentation of the data of an analytical study
in a 2 x 2 table
Ill Non ill Total Exposed a b ab Non
exposed c d cd Total ac bd abcd
7
Key areas

• Attributable fraction among exposed
• Attributable fraction in the population

8
Attributable fraction among exposed

• Proportion of disease that could be prevented if
  the risk factor was suppressed from among a
  population where 100 are exposed
• This does not make sense in the absence of
  causality

Attributable fraction among exposed
9
Concept of attributable fraction among exposed

• Lets see what is the risk of disease among
  exposed
• Of this risk, what is the proportion that is
  attributable to the exposure?
  

Attributable fraction among exposed
10
Attributable fraction among exposed From concept
to formula

• Estimate the risk among exposed (Denominator)
• Estimate the proportion of it that is
  attributable to the exposure (Numerator)
  

Attributable fraction among exposed
11
Attributable fraction among exposed Finding the
right formula

• Portion of the risk among exposed that is
  attributable to the exposure
• _________________Risk among exposed

Attributable fraction among exposed
12
The risk difference quantifies the excess of risk
among exposed in a cohort
Ill Non ill Total Exposed a b L1 Non
exposed c d L0 Total ac bd L1 L0
Risk difference R1- R0 (a/L1) - (c/L0)
Attributable fraction among exposed
13
Attributable fraction among exposed

• Risk difference
• _________________Risk among exposed

Attributable fraction among exposed
14
Attributable fraction among exposed in a cohort
study Conceptual formula
Ill Non ill Total Exposed a b L1 Non
exposed c d L0 Total ac bd L1 L0
AF e (R1-R0) /R1 (a/L1) - (c/L0) / (a/L1)
Attributable fraction among exposed
15
Attributable fraction among exposed Formula
used in calculations
AF e (R1-R0) /R1 RR-1 / RR
(Can be demonstrated)
Attributable fraction among exposed
16
Risk of leishmaniasis according to water bodies
within 25 metres of house, Chatrakhali, West
Bengal, 2004-6
Leishmaniasis Non ill Total Water
bodies 139 487 626 No water bodies 11 114 125 Tota
l 150 601 751
Relative risk (139/626) / (11/125) 22 / 9
2.5 AF e (2.5-1)/2.5 0.6 60(Try to
calculate using both formula)
Attributable fraction among exposed
17
The attributable fraction among exposed only
depends on the relative risk

• RR 1 AFe 0
• RR 2 AFe 1/2 50
• RR 3 AFe 2/3 66
• RR 4 AFe 3/4 75
• RR 5 AFe 4/5 80
• And so on with a plateau
  

Attributable fraction among exposed
18
Population attributable fraction among exposed
according to the relative risk
100.0
90.0
AFe
80.0
70.0
60.0
Attributable fraction among exposed
50.0
40.0
30.0
20.0
10.0
0.0
1
2
3
4
5
6
7
8
9
10
Relative risks
19
Case of a protective exposure Preventable
fraction among exposed
Ill Non ill Total Exposed a b L1 Non
exposed c d L0 Total ? ? L1 L0
PFe (R0-R1) /R0 1 - RR
Attributable fraction among exposed
20
Vaccine efficacy Preventable fraction among
exposed to a vaccine

• Proportion of cases potentially avoided among
  vaccinated
• Proportion of the cases that would have occurred
  among vaccinated but that were avoided because of
  vaccination
• VE (ARNV - ARV) / ARNV

Attributable fraction among exposed
21
Attributable fraction among exposed
Case-control study
Cases Controls Total Exposed a b ? Unexposed c
d ? Total C1 C0 C1C0
If rare disease (OR - 1)/OR Vaccine efficacy 1
- OR
Attributable fraction among exposed
22
Habits of sleeping in work clothes among scrub
typhus cases and controls, Darjeeling, West
Bengal, India, 2005-6
S. typhus Controls Total Sleeping in work
clothes 66 13 79 Changing clothes to
sleep 56 33 89 Total 122 46 168
Odds ratio (66x33)/(56x13) 3.0 AF e (3-1)/3
66
Attributable fraction among exposed
23
Number of hepatitis B vaccine doses received by
HBsAg cases and controls, Romania, 1997- 1998

• HBsAg () HBsAg (-)
• Cases Controls
• 3 doses 3 25
• lt 3 doses 4 2
• 7 27

OR 0.06Vaccine efficacy 1- OR 94
Attributable fraction among exposed
24
Key areas

• Attributable fraction among exposed
• Attributable fraction in the population

25
Attributable fraction in the population

• Proportion of disease that could be prevented if
  the risk factor was suppressed in the population
  
• Does not make sense in the absence of causality

Attributable fraction in the population
26
Concept of attributable fraction in the
population

• Lets see what is the risk of disease in the
  population
• Of this risk, what is the proportion that is
  attributable to the exposure?
  

Attributable fraction in the population
27
Attributable fraction in the population From
concept to formula

• Estimate the risk in the population (Denominator)
• Estimate the proportion of it that is
  attributable to the exposure (Numerator)
  

Attributable fraction in the population
28
Attributable fraction in the population Finding
the right formula

• Portion of the risk in the population that is
  attributable to the exposure
• _________________Risk in the population

Attributable fraction in the population
29
Excess of risk in the population in a cohort
Ill Non ill Total Exposed a b L1 Non
exposed c d L0 Total ac bd L1 L0
Excess of risk in the population Rp- R0
(ac/L1L0) - (c/L0)
Attributable fraction in the population
30
Attributable fraction in the population

• Excess of risk in the population
• _________________Risk in the population

Attributable fraction in the population
31
Attributable fraction in the population in a
cohort study Conceptual formula
Ill Non ill Total Exposed a b L1 Non
exposed c d L0 Total ac bd L1 L0
AFp (Rp-R0) /Rp
Attributable fraction in the population
32
Attributable fraction in the population in a
cohort studyFormula used in calculations
AFp (Rp-R0) /Rp P1x(RR-1/RR) P1 Proportion
of cases exposed
(Can be demonstrated)
Attributable fraction in the population
33
Risk of leishmaniasis according to water bodies
within 25 metres of house, Chatrakhali, West
Bengal, 2004-6
Leishmaniasis Non ill Total Water
bodies 139 487 626 No water bodies 11 114 125 Tota
l 150 601 751
Relative risk (139/626) / (11/125) 22 / 9
2.5 AF e (2.5-1)/2.5 0.6 60 AF p
(139/150) x 60 93 x 60 56 (Try the two
formulas)
Attributable fraction in the population
34
Incidence of gastro-enteritis according to food
items consumed, wedding dinner, West Bengal, 2005
200
79
20
27
74





R
osgulla
159
202
79
19
25
76







Ice cre
a
m
166
211
79
12
16
75







Pan
148
181
82
30
46
65








Relative risk 5.6, Attributable fraction among
exposed 82 Attributable fraction in the
population (173/178) x 82 80 The source
identified explains most cases
Attributable fraction in the population
35
Attack rate of gastro-enteritis by food items,
Coochbehar, West Bengal, India, 2005
Attack rate () Attack rate () Relative risk 95 confidence interval
Ate Did not eat Relative risk 95 confidence interval
Raw custard 90 51 1.8 1.3-2.4
Fruits 76 86 0.88 0.76-1.0
Sugar candy 75 88 0.85 0.74-1.0
Puffed rice 80 84 0.95 0.83-1.1
Seasoned rice 67 84 0.79 0.60-1.0
87 of cases exposed, population attributable
fraction 38
36
Additional investigations, gastroenteritis
outbreak, Coochbehar, West Bengal, India, 2005

• Raw custard not refrigerated contained raw milk,
  flour, sugar, honey, banana, clarified butter
• In addition to food items, all persons took a
  spoon of diluted raw milk, explaining
• High attack rate in persons unexposed to custard
• Low relative risk / attributable fraction for raw
  custard
• The attributable fraction in the population
  pointed to the fact the source of infection had
  two vehicles

37
Attributable fraction in the population

• Depends upon the relative risk
• Depends upon the proportion of cases exposed
• Can never exceed the proportion of cases exposed
  

Attributable fraction in the population
38
From the proportion of cases exposed to the
attributable fraction in the population

• 20 of cases exposed, OR very high
• Attributable fraction close to 20
• 100 of cases exposed, OR 1
• Attributable fraction 0

Attributable fraction in the population
39
Population attributable fraction according to the
relative risk for various level of exposure
frequency among cases
100.0
Pe 10
90.0
Pe 25
Pe 50
80.0
Pe 75
Pe 100 (AFe)
70.0
60.0
Population attributable fraction
50.0
40.0
30.0
20.0
10.0
0.0
1
2
3
4
5
6
7
8
9
10
Relative risks
40
Attributable fraction in the population
Case-control study
Cases Controls Total Exposed a b ? Unexposed c
d ? Total C1 C0 C1C0 If rare disease P1x (OR
- 1)/OR
Attributable fraction in the population
41
Sleeping in work clothes and scrub typhus,
Darjeeling, West Bengal, India, 2005-6
S. typhus Controls Total Sleeping in work
clothes 66 13 79 Changing clothes to
sleep 56 33 89 Total 122 46 168
Odds ratio (66x33)/(56x13) 3.0 AF e (3-1)/3
66 AF p (66/122) x 66 54 x 66 36
Attributable fraction in the population
42
Characteristics of acute hepatitis B cases and
controls, Karachi, Pakistan, 2001

Exposure Acute hepatitis B(N67) Healthy controls (N247) OR
Injection 43 (?) 68 (?) ?
Transfusion 2 (?) 1 (?) ?
Fraction attributable to injections (43/67) x
(4.7-1/4.7) 64 x 79 50 Fraction
attributable to transfusion (2/67) x (7.6-1/7.6)
3 x 87 2.5
Attributable fraction in the population
43
Risk assessment Rule of thumb

• 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 frankly elevated
  blood pressure (uncommon)
• More people acquire HCV from unsafe injection
  (common exposure, lower risk) than from unsafe
  blood (rare exposure, high risk)

Attributable fraction in the population
44
Measures of impact in population for protective
exposures

• If you want to know what was actually prevented
  by the prevention measure as used currently
• Calculate the fraction prevented in the
  population
• Proportion of the population USING the prevention
  measure x preventable fraction among exposed
• If you want to know how much could be prevented
  if the prevention measure was used in the whole
  population
• Consider failure to use the prevention measure
  as risk factor (1/RR or 1/OR)
• Calculate attributable fraction in the population
  of the failure to use the prevention measure
• Proportion of the population NOT USING the
  prevention measure x attributable fraction among
  exposed

45
Take home messages

• The attributable fraction among exposed
  translates the strength of association into an
  estimate of the proportion of cases attributable
  to the exposure among exposed
• The attributable fraction in the population
  translates the strength of association and the
  proportion of cases exposed into an estimate of
  the proportion of cases attributable to the
  exposure in the population

Attributable fraction in the population