Maybe Your Sleep Tracking is Killing You?
The Lure of the Measurable
Last week I found the death clock.
It’s a tool for telling you when you’ll die. For the memento mori crowd, it gives you a way to estimate roughly how many weeks of scrolling Twitter you might have left.
You should play around with it if you haven’t already. One of the biggest aspects that stands out is what happens if you go from drinking Daily to Never. It increased my life expectancy from 73 years to 88 years.
I’m not sure how they’re getting those numbers. It doesn’t sound quite right. A single drink of beer every day and a bottle of wine every day are both drinking “Daily.” And will a little sip of Bud every day shave 15 years off your life?
But I do think it highlights one challenge we run into with thinking about a healthy lifestyle and choosing health interventions for our lives: the lure of the measurable.
The Death Clock only uses a few pieces of data:
Aside from how optimistic or pessimistic your outlook is, these are all straightforward and easily measured.
But do they acurately capture what goes into lifespan? Let’s imagine two people:
Abe has never smoked, never drank. He works out for 60-90 minutes daily and considers himself optimistic. He is the perfect death-clock-optimizor.
But he lives alone. He spends all day, aside from exercising, in front of a screen, either doing work he doesn’t care about or watching TV. He has no family nearby. He has no friends he can confide in. He only gets a smattering of sunshine in a week. His water isn’t filtered, his air is polluted, he sleeps with the TV running in the background. No hobbies. No sense of purpose. He’s only optimistic because he thinks he’s going to be rich someday by slaving away at this unfulfilling job.
Obviously, this is not a good life. But by simple death clock measurements, it’s an ideal one. Abe may live to the ripe old age of 88, but I kinda doubt it. I suspect he dies sad and alone in front of the TV two years after retirement when he realized it was all a waste.
Compare that to Ben. He has a glass of wine every night or two, usually surrounded by friends when they’re sharing a dinner. He works a few hours a day on something he’s passionate about, then goofs off outside playings sports or spending time with his family. He’s not as lean as he could be, his BMI is 27, but he generally eats cleanly. He might indulge in a cigarette or cigar every week or two. He lives in a mountain town with fresh water, air, and no serious noise pollution. He sleeps like a baby. He sold his TV years ago.
By death clock measurements, Ben is going to live noticeably shorter than Abe. About a decade shorter.
Do we believe that? I don’t. And this isn’t an issue with Death Clock. They seem to be using some of the best data we have access to. The issue is how much we rely on measurable data for making decisions.
In Man’s Search for Meaning, Frankl argues that their sense of purpose distinguished the concentration camp prisoners who survived from those who didn’t. It’s hard to prove, but some Japanese research on Ikigai seems to agree. A strong sense of purpose is a major factor in your lifespan and health span.
But it’s not easy to measure. It doesn’t fit into a ring on your apple watch. And when it can’t be measured, it’s easy to forget how important it is. Some of the most important factors in a happy and healthy life may be the things we cannot measure. But those soft and fuzzy values get pushed to the periphery in a world of wearables and controlled studies.
We can even run into less extreme versions of the problem simply based on which quantifiable metrics we can and cannot measure. I heard a version of this recently on the Peter Attia podcast; basically, LDL particle count is clearly a risk factor for coronary artery disease, but there’s another half of the equation we can’t easily measure: how narrow your arteries are. If you live a sedentary life, you have smaller coronary arteries that are easier to clog. If you do extensive cardiovascular exercise, your arteries get bigger and are harder to clog. Could someone with a high VO2 max override the risk from having high LDL? I don’t think we know, but it’s an interesting question worth exploring.
Maybe some populations have always had “high cholesterol,” but it didn’t matter because we spent most of the day moving. And that question matters since research does seem to suggest that people with low cholesterol also have higher all-cause mortality. So maybe increasing cardio is better than taking a statin? I don’t know, but why would we assume the best solution to a problem is the one we can most easily measure?
I see people run into the marketing version of this problem all the time, too: they’re too focused on the metrics they can measure instead of the ones they cannot. They copy the quantifiable things of a successful creator and then wonder why they don’t have the same success, but it’s because success often comes from the things they cannot easily measure.
And then we get into really weird territory around placebo effects. Maybe your resting heart rate is fine, and you’re perfectly healthy, but your Oura scores are making you feel unhealthy. Thinking you’re unhealthy, even when you’re not, is a big deal. It can kill you. So perhaps you’d be better off not tracking your data and just seeing how you feel? I noticed I felt like I was sleeping much better once I stopped tracking my heart rate and HRV.
Anyway, I have an impossible time believing that someone who can run marathons and deadlift 3x their body weight and has a glass of wine a few times a week is going to die sooner than someone who is skinny, lonely, and sober. But that’s what our crude tools might suggest. So don’t get too carried away by the tools. Science is just one form of knowledge.
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Richard Hamming had a good bit on this in The Art of Doing Science and Engineering:
"Of the things you can choose to measure some are hard, firm measurements, such as height and weight, while some are soft, such as social attitudes. There is always a tendency to grab the hard, firm measurement, though it may be quite irrelevant as compared to the soft one, which in the long run may be much more relevant to your goals. Accuracy of measurement tends to get confused with relevance of measurement, much more than most people believe. That a measurement is accurate, reproducible, and easy to make does not mean it should be done; instead, a much poorer one which is more closely related to your goals may be much preferable. For example, in school it is easy to measure training and hard to measure education, and hence you tend to see on final exams an emphasis on the training part and a great neglect of the education part."
The idea of a poorer measurement nonetheless being the better one is so compelling and I feel like it applies here -- like "happiness" is much harder to measure than sleep but it might be the better metric anyway.
I recently purchased a “smart watch” mainly for running really as my old one broke.
But this one gives me a whole new level of stats. I now know my blood oxygen concentration at any point in the last two weeks. Great but I don’t have a clue what it means or whether I’m about to die.
The other thing it gives you is a sleep score. Last night I felt like I had a great sleep. 7 hrs 30 mins and didn’t wake up at all. But I only got a score of 75. Urghhh. Not enough REM sleep apparently.
So yeah, I get you point. Great article. Thanks.