If you search the internet looking for weight loss calculators and equations, you’ll be bombarded by a plethora of tools to calculate such interesting facts as:
- Your Basal Metabolic Rate (BMR), or how many calories you burn each day if you were to sleep for 24 hours straight
- Your body fat percentage
- Your energy expenditure when you exercise (how many calories you burn)
- Your predicted strength
- How much muscle you can gain
- Your body mass index, or BMI
…and so on.
But just how accurate are these equations?
To understand the reliability of such weight loss orientated calculations, you must first understand how these equations are derived. Having studied science at university, I had to scrutinise numerous papers that determined such equations as have been listed above.
These equations are determined empirically. In other words, they are derived based on the results of an experiment. How this is most commonly accomplished is as follows:
- A researcher (or group of researchers) will conduct an experiment.
- They collect the results.
- Using the data that has been collected, they will develop an equation that satisfies this data with a line of best fit.
To illustrate this concept, assume that the following data is collected in regards to a simple money orientated experiment where the researches compared the amount of money invested to the return on investment (ROI) with 5 different people:
| $ Invested |
ROI $
|
| $250 |
$23 |
| $500 |
$49 |
| $1000 |
$100 |
| $2000 |
$213 |
| $5000 |
$550 |
Looking at these numbers, the approximate ROI is equal to about a tenth of the amount of money invested. So equation for the line of best fit would be something similar to:
$ROI = $ Invested / 10
Of course, the line of best fit will be slightly different to this equation because I don’t currently have any software that will accurately calculate the line of best fit based on this data 
So, using this simple example, you can see that the actual equation is accurate for only one set of data – where $1000 was invested. All the other four sets of data do not produce accurate results.
Similarly with experiments pertaining to weight loss and body composition, this is often the case. More often than not, almost all (if not all) of the data does not fit perfectly on this line of best fit. So the equation is hardly ever 100% accurate for the group of people participating in that experiment.
In such an experiment, this equation is often the average of all the usable results that were collected. The equation is also subject to any errors that may have been incurred as a result of a poorly designed experiment, or even just acceptable inaccuracies such as human error, equipment error etc.
Applying this information to your weight loss endeavours, it is important to understand that equations that have been derived from experimental data are average values only. In all likelihood, they are never going to be accurate predictors of what you are measuring.
So why is it that these equations are based on average results and therefore are not necessarily accurate for your body? A couple of key reasons:
- Humans vary widely in their genetic make-up, lifestyle, body composition etc. There are millions of chemical reactions occurring simultaneously within your body. With so many variables at hand, it is impossible with our technology today to derive an accurate equation to predict the likes of body composition, energy expenditure, calorie consumption etc. Hence an average of a group of results is utilised.
- Average values eliminate extreme values and will show a general trend. Thus the degree of inaccuracy is lessened.
The weight loss equations and calculators widely available should therefore be utilised as a guide. They will not predict with any degree of certainty how much weight you will lose, or how many calories you should consume to accomplish a particular goal. They can often be useful as a starting point and then you can measure your results moving forward. If your results do not equal your expectations, you will then have to reconsider what you are doing and make the necessary adaptations to your approach.
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