From a Professional’s Perspective
It is important that fitness professionals working in the outdoor fitness market understand the difference between relative risk and absolute risk. This is important for a number of reasons:
- So you have an understanding of the difference between the two terms;
- So you can converse, confidently and professionally, with health and fitness professionals; e.g. with General Practitioners (GPs) engaged in exercise referral; and/or
- So you can accurately convey any risk(s) with your clients.
From an Individual’s Perspective
Knowing that exercising regularly can decrease your disease or injury risk is important, but you probably want to know just how much exercising regularly can lower your risk. Understanding the terms relative risk and absolute risk can help you better understand your own risk.
What is Relative Risk?
- Relative risk is the number that tells you how much something you do, such as maintaining a healthy weight, can change your risk compared to your risk if you are very overweight.
- Relative risk can be expressed as a percentage decrease or a percentage increase.
- If something you do or take does not change your risk, then the relative risk reduction is 0% (no difference).
- If something you do or take lowers your risk by 30% compared to someone who doesn’t take the same step, then that action reduces your relative risk by 30%.
- If something you do triples your risk, then your relative risk increases 300%.
- The same absolute risk can be expressed in different ways.
- For example, say you have a 1 in 10 risk of developing a certain disease in your life.
- This can also be said to be a 10% risk, or a 0.1 risk – depending if you use percentages or decimals.
What is Absolute Risk?
- Absolute risk is the size of your own risk.
- Absolute risk reduction is the number of percentage points your own risk goes down if you do something protective, such as stop drinking alcohol.
- The size of your absolute risk reduction depends on what your risk is to begin with.
Relative Risk and Absolute Risk in Context
In clinical situations, risk may be summarised using two different measures: relative risk (RR) or absolute (sometimes called attributable) risk (AR). When describing the effect of a risk factor, such as a high level of serum cholesterol in relation to coronary heart disease (CHD), RR is the ratio of the risk of disease in one group (i.e. CHD among those with high serum cholesterol) to that in another (i.e. CHD in those with low serum cholesterol); AR is the difference between the risks of disease in the two populations and defines the absolute magnitude of the risk.
However, RR is preferred in aetiological research, is more frequently reported in medical literature as well as in the popular press and is commonly used in clinical encounters.
If the underlying risk of disease is known, RR can be converted to AR (Malenka & Baron, 1989; Laupacis et al, 1988; Benichou & Gail, 1990). The two measures are logically equivalent and, in this sense, presentation of either should lead to the same decision (if information about the underlying risk of disease is presented). However, the literature on perception of risks suggests this might not be true (Tversky & Kahneman, 1974; Elstein, 1976). When treatment efficacy is expressed in relative terms, larger percentages result than when the same treatment is discussed in absolute terms. For example, suppose a medication reduces the risk of an adverse outcome from 0.05 to 0.025. In relative terms it reduces the risk by 50%, while in absolute terms it reduces the risk by 2.5%. Thus, the presentation of RR may magnify the perception of efficacy.
Some medical and fitness professionals also utilise hazard ratios to convey risk. If you would like to learn about hazard ratios then look here.
Malenka, D.J. & Baron, J,A. (1989) Cholesterol and Coronary Heart Disease: The Importance of Patient-specific Attributable Risk. Archives of Internal Medicine. 148, pp.2247-2252.
Laupacis, A., Sackett, D.L. & Roberts, R.S. (1988) An Assessment of Clinically Useful Measures of the Consequences of Treatment. New England Journal of Medicine. 318, pp.1728-1733.
Benichou, J. & Gail, M.H. (1990) Estimates of Absolute Cause-specific Risk in Cohort Studies. Biometrics. 46, pp.813-826.
Tversky, A. & Kahneman, D. (1974) Judgement under Uncertainty: Heuristics and Biases. Science. 185, pp.1124-1131.
Elstein, A.S. (1976) Clinical Judgment: Psychological Research and Medical Practice. Science. 194, pp.696-700.
- Framing (brainad.wordpress.com)