The Impossibility of Comparison

The Impossibility of Comparison

‘Comparison is the thief of joy’

Theodore Roosevelt

It is almost human nature to compare ourselves to those around us. Some of it is done to inflate our self worth, when compared to those we perceive to be less ‘successful’ than us, and some done as a way to motivate ourselves.

Many times throughout my career, I have run into this phenomenon, and mostly to negative psychological impact on the individual performing the comparison. I have advised many of my clients to ‘stop comparing’ as if it were that easy. I have thought long and hard about how to logically defuse our want for comparison, and I believe it is through an appreciation of the scientific method that we can do this.

It is only through the understanding of what accurate comparison really is that we run into its’ logical impossibility. In high quality scientific studies (randomised controlled trials), in order to accurately compare an intervention strategy compared to another, we must control all the variables that could possibly influence the effectiveness of the said intervention.

Any variable that could influence the accurate measurement of an intervention is known as a ‘confounder.’ A confounder, owing its’ roots to statistics is defined as ‘a variable that influences both the dependent variable and independent variable, causing a spurious association.’ To provide a simplistic example, if we wanted to test whether walking 10000 steps a day versus no walking was effective in weight loss, we would need to ensure that calorie intake is controlled in both groups.

Failure to do this will lead to results that are not entirely accurate. If the ‘no walking’ group were all naturally in calorie deficits, whereas those who were walking were in calorie surpluses, then the conclusion that could be drawn is: no walking was more effective for weight loss than walking. However, if calorie intake was equal in both groups – you would see that those who walked more loss more weight.

What this simplistic example demonstrates is the importance of controlling confounders for the sake of accuracy.

Does this mean that as long as we control confounders, then we would be able to accurately compare? In theory, yes. However, that is on the assumption that we are already aware of all the variables that could influence the results – and that these can be controlled. Unfortunately, life just does not work that way. There are unknown variables that we cannot control. Not to mention there are variables that we know that can be difficult controlling.

In the context of health, it is erroneous for our clients to assume that any individual diet or workout is going to work for them ‘because it worked for someone else.’ Firstly, as similar as two individuals may present, they are not. Second, trying to ‘control’ the variables in someone’s life that may influence their health goal will have a ripple effect on other aspects of their life, not to mention the difficulty to do such a task in the first place.

Take this as an example, perhaps imaginary client ‘Danny’ (who is of Caucasian decent) has had success implementing a low carb diet that has helped with their weight loss. Danny then recommends this to his friend, Vu who is of South-East Asian descent. Vu adopts this approach, but finds it hard to adhere to because South-East Asian cuisine typically rich in carbohydrate dense foods like rice and noodles. Ultimately the method is unsustainable for Vu.

The diet in itself may have been successful if Vu was able to adhere to it, however variables such as culture and food preference played a strong role in its’ application.

If we extend this to a larger context, it is futile to compare the health progress of one individual to another, because we cannot possibly know all the variables that are influencing their health outcome. People are not scientific experiments, where age, sex, physical activity, medical history and personality traits can be matched near-perfectly.

Our inability to control all known variables, as well as the impossibility of controlling unknown variables can only lead us to the pragmatic conclusion of comparison – that it is logically impossible.