What comes from what? Measure of impact FETP India

What comes from what?

Measure of impact

FETP India

Competency to be gained from this lecture

Calculate an attributable fraction

Terminology

• Attributable fraction • Etiologic fraction• Attributable risk

Same thing

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.

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)

Ill Non ill Total

Exposed a b a+b

Non exposed c d c+d

Total a+c b+d a+b+c+d

Presentation of the data of an analytical study in a 2 x 2 table

Key areas

• Attributable fraction among exposed• Attributable fraction in the population

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

Concept of attributable fraction among exposed

• Let’s 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: 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: Finding the right formula

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

_________________

Risk among exposed

The risk difference quantifies the excess of risk among exposed in a

cohort

Risk difference = R1- R0 = (a/L1) - (c/L0)

Ill Non ill Total

Exposed a b L1

Non exposed c d L0

Total a+c b+d L1 + L0

Risk difference_________________

Risk among exposed

Ill Non ill Total

Exposed a b L1

Non exposed c d L0

Attributable fraction among exposed in

a cohort study: Conceptual formula

AF e = (R1-R0) /R1 = [(a/L1) - (c/L0)] / (a/L1)

Attributable fraction among exposed:

Formula used in calculations

AF e = (R1-R0) /R1 = RR-1 / RR

(Can be demonstrated)

Leishmaniasis Non ill Total

Water bodies 139 487 626

No water bodies 11 114 125

Total 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)

Risk of leishmaniasis according to water bodies within 25 metres of house, Chatrakhali, West Bengal,

2004-6

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

Population attributable fraction among exposed according to the

relative risk

100.0%

1 2 3 4 5 6 7 8 9 10

Relative risks

Ill Non ill Total

Exposed a b L1

Non exposed c d L0

Total ? ? L1 + L0

Case of a protective exposure: Preventable fraction among exposed

PFe = (R0-R1) /R0 = 1 - RR

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

Cases Controls Total

Exposed a b ?

Unexposed c d ?

Total C1 C0 C1+C0

Attributable fraction among exposed:

Case-control study

If rare disease: (OR - 1)/OR

Vaccine efficacy: 1 - OR Attributable fraction among exposed

S. typhus Controls Total

Sleeping in work clothes 66 13 79

Changing clothes to sleep 56 33 89

Total 122 46 168

Habits of sleeping in work clothes among scrub typhus cases and

controls, Darjeeling, West Bengal, India, 2005-6

Odds ratio = (66x33)/(56x13) =3.0AF e = (3-1)/3 = 66%

Number of hepatitis B vaccine doses received by HBsAg+ cases and

controls, Romania, 1997- 1998

HBsAg (+) HBsAg (-)Cases Controls

3 doses 3 25< 3 doses 4 2

OR= 0.06Vaccine efficacy = 1- OR = 94%

Key areas

• Attributable fraction among exposed• Attributable fraction in the population

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

Concept of attributable fraction in the population

• Let’s 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: 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: Finding the right formula

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

_________________

Risk in the population

Excess of risk in the population in a cohort

Excess of risk in the population = Rp- R0 = (a+c/L1+L0) - (c/L0)

Ill Non ill Total

Exposed a b L1

Non exposed c d L0

Excess of risk in the population_________________

Risk in the population

Ill Non ill Total

Exposed a b L1

Non exposed c d L0

Attributable fraction in the population in a cohort study:

Conceptual formula

AFp = (Rp-R0) /Rp

Attributable fraction in the population in a cohort study:Formula used in calculations

AFp = (Rp-R0) /Rp = P1x(RR-1/RR)

P1: Proportion of cases exposed

(Can be demonstrated)

Leishmaniasis Non ill Total

Water bodies 139 487 626

No water bodies 11 114 125

Total 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)

Risk of leishmaniasis according to water bodies within 25 metres of house, Chatrakhali, West Bengal,

2004-6

Incidence of gastro-enteritis according to food items consumed, wedding dinner, West Bengal, 2005

Incidence among those who ate

Incidence among those who did not eat

Ill Total % Ill Total % Cold drinks 153 186 82% 25 41 61% Salad 144 189 76% 34 38 89% Fish Fry 173 195 89% 5 32 16% Fish Curry 119 149 80% 59 78 76% Mutton 158 200 79% 20 27 74% Rosgulla 159 202 79% 19 25 76% Ice cream 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

* 87% of cases exposed, population attributable fraction: 38%

Attack rate of gastro-enteritis by food items, Coochbehar, West

Bengal, India, 2005Attack rate (%)

Relative risk

95% confidence

interval Ate Did not

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

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

• Depends upon the relative risk• Depends upon the proportion of cases

exposed• Can never exceed the proportion of

cases exposed

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%

Population attributable fraction according to the relative risk for

various level of exposure frequency among cases

100.0%

1 2 3 4 5 6 7 8 9 10

Relative risks

Pe 10%Pe 25%Pe 50%Pe 75%Pe 100% (AFe)

Cases Controls Total

Exposed a b ?

Unexposed c d ?

Total C1 C0 C1+C0

If rare disease: P1x [(OR - 1)/OR]

Attributable fraction in the population:

Case-control study

S. typhus Controls Total

Sleeping in work clothes 66 13 79

Changing clothes to sleep 56 33 89

Total 122 46 168

Sleeping in work clothes and scrub typhus, Darjeeling, West Bengal,

India, 2005-6

Odds ratio = (66x33)/(56x13) =3.0AF e = (3-1)/3 = 66%AF p = (66/122) x 66% = 54% x 66% = 36%

Characteristics of acute hepatitis B cases and controls, Karachi,

Pakistan, 2001

Exposure

Acute hepatitis B

(N=67)

Healthy controls(N=247) 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%

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)

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

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

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