One of the most common topics of discussion on health and well-being forums comes from the way certain metrics are derived and used. For example, many people point to Body Mass Index (BMI) as a measure of the risk of cardio-vascular disease. In other discussions, VO2 Max, a measure of how efficient the body is at taking in and using oxygen, is a key indicator of cardiovascular fitness.
But sitting under the data that is actually collected lie algorithms – sophisticated calculations that use the data that is collected and use it to make estimates of other metrics. Let’s start with a look at VO2 Max as an example.
How does Apple calculate VO2 Max?
The Apple Watch uses data from the heart and motion sensors during an Outdoor Walk, Outdoor Run or Hiking workout in the Workout app. It also takes into account:
- Age
- Sex
- Weight
- Height
- Medications that might affect your heart rate
Apple’s VO2 Max measurement uses an algorithm that it is limited to providing estimates that range between 14 – 65 mL/kg/min. I assume that means that the closer to get to 65 1. mL/kg/min, the harder it will get to reach that number.
You can improve your VO2 max with exercise but Apple’s research says:
At baseline, genetic factors are believed to determine approximately 50 to 70 percent of the VO2 max differences observed between individuals and approximately 20 to 60 percent of the variation in VO2 max improvements in response to exercise training
Using Apple Watch to Estimate Cardio Fitness with VO2 max – May 2021
So, while you can change the result of the algorithm’s calculations through exercise, you can’t reduce your age, change your genetic sex or alter your height. Those unchangeable factors influence the outcome of the algorithm’s calculation.
Bathroom scales
I have a nifty set of bathroom scales that not only weighs me but also provides estimates of my percentage body fat, bone mass and basal metabolic rate (a measure of how much energy my body needs to sustain me).
These scales collect just two pieces of real data: my weight (which I presume is accurate) and electrical impedance as it sends a very weak electrical signal in one foot and receives it through the other. Yet, it uses those measurements, along with my height, age and whether I consider myself athletic or not to make estimates of a bunch of other metrics. There’s no way the scales actually measure all those things.
It uses a computer program, trained using data from studies, to make an educated guess.
The lesson to learn
It’s important to understand that the numbers that come from the algorithms that inform us about our health are not 100% accurate. But that doesn’t mean they aren’t helpful or useful.
The key, in my view, is to not focus on the absolute values but to work with trends. For example, if Apple Health reports that your V02 Max is improving, that’s good news. If your result improves, then that’s good news.
Many of us like to compare our progress and results with friends and peers. Two people can train in similar ways but end up with different results. Genetics are a significant factor and then there’s biological sex, age and other differences we can’t really do much about. So, consider the results of algorithms carefully and don’t get obsessed with comparisons.
Anthony is the founder of Australian Apple News. He is a long-time Apple user and former editor of Australian Macworld. He has contributed to many technology magazines and newspapers as well as appearing regularly on radio and occasionally on TV.