Epidemiology Kept Simple Chapter 8: Association & Impact 4/20/2017 Epidemiology Kept Simple Chapter 8 Measures of Association & Potential Impact Epi Kept Simple

Chapter 8: Association & Impact 4/20/2017 Important Jargon Exposure (E)  an explanatory factor; any potential health determinant; the independent variable Disease (D)  the response; any health-related outcome; the dependent variable Measure of association (syn. measure of effect)  a statistic that quantifies the relationship between an exposure and a disease Measure of potential impact  a statistic that quantifies the potential impact of removing a hazardous exposure In epidemiology it is common to use the term exposure to denote any explanatory variable i.E we may speak of smoking as an exposure that causes lung cancer or advanced maternal age at pregnancy as an exposure that causes Down Syndrome (Prof. G. could you please help me understand the inactive lifestyle E+??)){We arbitrary define the risk factor as “exposure” to an inactive lifestyle. Then we compare the mortality rate in the exposed (inactive lifestyle) and nonexposed (active lifestyle) groups. I’ve added a third bullet to this effect.} Gerstman Chapter 8 Epi Kept Simple

Arithmetic (αριθμός) Comparisons Chapter 8: Association & Impact 4/20/2017 Arithmetic (αριθμός) Comparisons Measures of association are mathematical comparisons Mathematic comparisons can be done in absolute terms or relative terms Let us start with this ridiculously simple example: I have $2 You have $1 We compare the weight of a man of 100 kg to the weight of a woman of 50 kg. -Absolute comparisons are derived by subtraction and using (original units of measure kg) -{Relative comparisons are derived by division (the division cancels out units, making a unit-free comparison} "For the things of this world cannot be made known without a knowledge of mathematics."- Roger Bacon Gerstman Chapter 8 Epi Kept Simple

Chapter 8: Association & Impact 4/20/2017 Absolute Comparison In absolute terms, I have $2 – $1 = $1 more than you Note: the absolute comparison was made with subtraction It is as simple as that… We compare the weight of a man of 100 kg to the weight of a woman of 50 kg. -Absolute comparisons are derived by subtraction and using (original units of measure kg) -{Relative comparisons are derived by division (the division cancels out units, making a unit-free comparison} Gerstman Chapter 8 Epi Kept Simple

Chapter 8: Association & Impact 4/20/2017 Relative Comparison Recall that I have $2 and you have $1. In relative terms, I have $2 ÷ $1 = 2, or “twice as much as you” Note: relative comparison was made by division We compare the weight of a man of 100 kg to the weight of a woman of 50 kg. -Absolute comparisons are derived by subtraction and using (original units of measure kg) -{Relative comparisons are derived by division (the division cancels out units, making a unit-free comparison} Gerstman Chapter 8 Epi Kept Simple

Chapter 8: Association & Impact 4/20/2017 Applied to Risks Suppose, I am exposed to a risk factor and have a 2% risk of disease. You are not exposed and you have a 1% risk of the disease. Of course we are assuming we are the same in every way except for this risk factor. In absolute terms, I have 2% – 1% = 1% greater risk of the disease This is the risk difference We compare the weight of a man of 100 kg to the weight of a woman of 50 kg. -Absolute comparisons are derived by subtraction and using (original units of measure kg) -{Relative comparisons are derived by division (the division cancels out units, making a unit-free comparison} Gerstman Chapter 8 Epi Kept Simple

Chapter 8: Association & Impact 4/20/2017 Applied to Risks In relative terms I have 2% ÷ 1% = 2, or twice the risk This is the relative risk associated with the exposure We compare the weight of a man of 100 kg to the weight of a woman of 50 kg. -Absolute comparisons are derived by subtraction and using (original units of measure kg) -{Relative comparisons are derived by division (the division cancels out units, making a unit-free comparison} Gerstman Chapter 8 Epi Kept Simple

Chapter 8: Association & Impact 4/20/2017 Terminology For simplicity sake, the terms “risk” and “rate” will be applied to all incidence and prevalence measures. Let’s apply arithmetic to risks. These are the formulas. {The formulas are simple: RD is a subtraction and RR is a division. The key is to understand how we interpret the RR and the RD. They both quantify the relation between E and D, but they tell you something different about the association. Going through lots of examples in the book will help understand subtleties.} Gerstman Chapter 8 Epi Kept Simple

Chapter 8: Association & Impact 4/20/2017 Risk Difference Risk Difference (RD)  absolute effect associated with exposure where R1 ≡ risk in the exposed group R0 ≡ risk in the non-exposed group Let’s apply arithmetic to risks. These are the formulas. {The formulas are simple: RD is a subtraction and RR is a division. The key is to understand how we interpret the RR and the RD. They both quantify the relation between E and D, but they tell you something different about the association. Going through lots of examples in the book will help understand subtleties.} Interpretation: Excess risk in absolute terms Gerstman Chapter 8 Epi Kept Simple

Chapter 8: Association & Impact 4/20/2017 Relative Risk Relative Risk (RR)  relative effect associated with exposure or the “risk ratio” where R1 ≡ risk in the exposed group R0 ≡ risk in the non-exposed group Let’s apply arithmetic to risks. These are the formulas. {The formulas are simple: RD is a subtraction and RR is a division. The key is to understand how we interpret the RR and the RD. They both quantify the relation between E and D, but they tell you something different about the association. Going through lots of examples in the book will help understand subtleties.} Interpretation: excess risk in relative terms. Gerstman Chapter 8 Epi Kept Simple

Example Fitness & Mortality (Blair et al., 1995) Chapter 8: Association & Impact 4/20/2017 Example Fitness & Mortality (Blair et al., 1995) Is improved fitness associated with decreased mortality? Exposure ≡ improved fitness (1 = yes, 0 = no) Disease ≡ death (1 = yes, 0 = no) Mortality rate, group 1: R1 = 67.7 per 100,000 p-yrs Mortality rate, group 0: R0 = 122.0 per 100,000 p-yrs {See p. 159 for details.} Gerstman Chapter 8 Epi Kept Simple

Example Risk Difference Chapter 8: Association & Impact 4/20/2017 Example Risk Difference What is the effect of improved fitness on mortality in absolute terms? {See p. 159 for details.} The effect of the exposure (improved fitness) is to decrease mortality by 54.4 per 100,000 person-years Gerstman Chapter 8 Epi Kept Simple

Chapter 8: Association & Impact 4/20/2017 Example Relative Risk What is the effect of improved fitness on mortality in relative terms? {See p. 159 for details.} The effect of the exposure is to cut the risk almost in half. Gerstman Chapter 8 Epi Kept Simple

Designation of Exposure Chapter 8: Association & Impact 4/20/2017 Designation of Exposure Switching the designmation of “exposure” does not materially affect interpretations For example, if we had let “exposure” ≡ failure to improve fitness RR = R1 / R0 = 122.0 / 67.7 = 1.80 (1.8 times the risk in the exposed group (“almost double”) {See p. 159 for details.} Gerstman Chapter 8 Epi Kept Simple

2-by-2 Table Format Disease + Disease − Total Exposure + A1 B1 N1 For person-time data: let N1 ≡ person-time in group 1 and N0 ≡ person-time in group 0, and ignore cells B1 and B0 Gerstman Chapter 8

Fitness Data, table format Fitness Improved? Died Person-years Yes 25 -- 4054 No 32 2937 Rates per 10,000 person-years Gerstman Chapter 8

Food borne Outbreak Example Exposure ≡ eating a particular dish Disease ≡ gastroenteritis Disease + Disease − Total Exposure + 63 25 88 Exposure – 1 6 7 64 31 95 Gerstman Chapter 8

Food borne Outbreak Data Disease + Disease − Total Exposure + 63 25 88 Exposure – 1 6 7 64 31 95 Exposed group had 5 times the risk Gerstman Chapter 8

Chapter 8: Association & Impact 4/20/2017 Comparison of RR and RD RR  strength of effect RD  effect in absolute terms Rates (per 100000) of Lung CA & CHD assoc. w/smoking Smoker Nonsmoke RR RD LungCA 104 10 10.40 94 CHD 565 413 1.37 152 Smoking causes more heart disease even though the association between smoking a heart disease is weaker than the association between smoking an lung cancer. This is because heart disease is more common in the population. Smoking  Stronger effect for LungCA Smoking  Causes more CHD Gerstman Chapter 8 Epi Kept Simple

What do you do when you have multiple levels of exposure? Compare rates to least exposed “reference” group LungCA Rate (per 100,000 person-years) RR Non-smoker (0) 10 1.0 (ref.) Light smoker (1) 52 5.2 Mod. smoker (2) 106 10.6 Heavy sm. (3) 224 22.4 Gerstman Chapter 8

The Odds Ratio Similar to a RR, but based on odds rather than risks D+ Total E+ A1 B1 N1 E− A0 B0 N0 M1 M0 N When the disease is rare, interpret the same way you interpret a RR e.g. an OR of 1 means the risks are the same in the exposed and nonexposed groups “Cross-product ratio” Gerstman Chapter 8

Odds Ratio, Example Milunsky et al, 1989, Table 4 NTD = Neural Tube Defect Folic Acid+ 10 10,703 Folic Acid− 39 11,905 Exposed group had 0.29 times (about a quarter) the risk of the nonexposed group Gerstman Chapter 8

Measures of Potential Impact These measures predicted impact of removing a hazardous exposure from the population Two types Attributable fraction in exposed cases Attributable fraction in the population as a whole Gerstman Chapter 8

Attributable Fraction Exposed Cases (AFe) Proportion of exposed cases averted with elimination of the exposure Gerstman Chapter 8

Example: AFe RR of lung CA associated with moderate smoking is approx. 10.4. Therefore: Interpretation: 90.4% of lung cancer in moderate smokers would be averted if they had not smoked. Gerstman Chapter 8

Attributable Fraction, Population (AFp) Proportion of all cases averted with elimination of exposure from the population Gerstman Chapter 8

AFp equivalent formulas Gerstman Chapter 8

AFp for Cancer Mortality, Selected Exposures Doll & Peto, 1981 Miller, 1992 Tobacco 30% 29% Dietary 35% 20% Occupational 4% 9% Repro/Sexual 7% Sun/Radiation 3% 1% Alcohol 6% Pollution 2% - Medication Infection 10% Gerstman Chapter 8