EPIDEMIOLOGIE Attribution of risk relative risk absolute risk difference attributable risk fractions Risk/rate • Measures the strengths of association between the risk factor and disease • Incidence rate or Risk in exposed (r1) • Incidence rate or Risk in unexposed (r0) Relative measures of effect (relative risk) We have 2 groups of individuals: • An exposed group (group with risk factor of interest) and unexposed group (without such factor of interest) • We are interested in comparing the amount of disease (mortality or other health outcome) in the exposed group to that in the unexposed group Risk ratio •we calculate the risk ratio (RR) as: RR=r1/r0 Risk difference • the absolute difference between two risks (or rates) RD = r1 – r0 Relative risk Example: cohort study of oral contraceptive use and heart attack Myocardial infarction Yes No Total OC use Yes 25 400 425 No 75 1500 1575 Total 100 1900 2000 Risk (exposed) = 25/425=0.059 Risk (unexposed) = 75/1575=0.048 Relative risk = 0.059/0.048 = 1.23 • Alternative measure of risk Odds ratio The odds of disease is the number of cases divided by the number of non-cases Cases Odds = ------------ Non cases Odds ratio (OR) is ratio of odds of disease among exposed (oddsexp) and odds of disease among unexposed (oddsunexp) OR= oddsexp/ oddsunexp We can calculate • Odds (exposed) Oexp=25/400 • Odds (unexposed) Ounexp=75/1500 • Odds ratio OR = Oexp / Ounexp = 1.25 Myocardial infarction Yes No Total OC use Yes 25 400 425 No 75 1500 1575 Total 100 1900 2000 Odds ratio as an approximation to the risk ratio • For a rare disease, odds ratio is approximately equal to the risk ratio (because denumerators are very similar) • For a common conditions, OR overestimates the true RR Absolute risk difference (attributable risk) Risk ratio •we calculate the risk ratio (RR) as: RR=r1/r0 Risk difference • the absolute difference between two risks (or rates) RD = r1 – r0 Example: cohort study of oral contraceptive use and heart attack Myocardial infarction Yes No Total OC use Yes 25 400 425 No 75 1500 1575 Total 100 1900 2000 Risk (exposed) = 25/425=0.059 Risk (unexposed) = 75/1575=0.048 Risk difference = 0.059 - 0.048 = 0.011 = 1.1% Interpretation • Risk difference = 1.1% (=1.1/100 persons) • Women using OC had 1.1% higher risk of heart attack than women not using OC • If we compare 100 women on OC vs. 100 not using OC, there will be 1.1 more heart attack in the OC group. Attributable risk fraction (ARF, AR%) (risk difference %, etiological fraction) Proportion of disease among exposed that is attributable to the exposure AR 0.059-0.048 AR% = -------------------------------- = ----------------------- = 0.19 = 19% Incidence in exposed 0.059 Interpretation: If OC cause heart attack, about 19% of heart attacks among women using OC can be - attributed to their OC use. - eliminated if they did not use OC Measures of population impact • Population attributable risk (PAR) is the absolute difference between the risk (or rate) in the whole population and the risk or rate in the unexposed group PAR = r – r0 Example: cohort study of oral contraceptive use and heart attack Myocardial infarction Yes No Total OC use Yes 25 400 425 No 75 1500 1575 Total 100 1900 2000 Risk (exposed) = 25/425=0.059 Risk (unexposed) = 75/1575=0.048 Risk (whole population) = 100/2000 = 0.05 PAR = 0.050 - 0.048 = 0.002 = 0.2% = 2/1000 PAR interpretation • If OC use were stopped, the excess annual risk of heart attack in ALL women would be reduced by 2/1000. • Please note: 2/1000 = 200/100,000 = 2,000/1,000,000 • Not negligible! Population attributable risk fraction (PARF or PAR%) • It is a measure of the proportion of all cases in the study population (exposed and unexposed) that may be attributed to the exposure, on the assumption of a causal association • It is also called the aetiologic fraction, the percentage population attributable risk or the attributable fraction • If r is rate in the total population PAR = r – r0 PAF = PAR/r PAF = (r-r0)/r Example: cohort study of oral contraceptive use and heart attack Myocardial infarction Yes No Total OC use Yes 25 400 425 No 75 1500 1575 Total 100 1900 2000 Risk (exposed) = 25/425=0.059 Risk (unexposed) = 75/1575=0.048 Risk (whole population) = 100/2000 = 0.05 PARF = (0.050-0.048)/0.05 = 0.002/0.05 = 0.04 =4% PARF interpretation • If OC use were stopped, the excess annual risk of heart attack in ALL women would be reduced by 4%. • Please note: 4% of a common disease can be a large number of events • Not negligible! Alternative formula for PARF p (RR – 1) PARF = ------------------------------------ p (RR -1) + 1 Example: lung cancer and smoking - Prevalence of smoking = 30% - RR ~10 0.3(10-1) 0.3x9 2.7 PARF = -------------------- = -------------------- = -------------- = 0.73 = 73% 0.3(10-1)+1 0.3x9+1 3.7 73% of all lung cancers in the population could be prevented if smoking is eliminated Measure of effect Use of the measure How to interpret results Risk Difference (AR, PAR, AR%, PARF) Public Health Interested in excess disease burden due to factor (“Attributable risk”) Important for prevention action Close to 0 = little effect Large difference = large effect Risk Ratio Epidemiology Causation “This factor doubles the risk of the disease” Close to 1 = little effect Large ratio = large effect Close to 0 = large effect!Odds Ratio As for Risk Ratio “This factor doubles the odds of the disease” Only possibility (case-control study) More advanced statistical methods (logistic regression)