Physiology Friday #128: Can Your "Sleep Age" Predict Your Lifespan?
Direct measures of sleep may have unique predictive power for healthspan and longevity.
Happy Physiology Friday.
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Quick finding of the week: Should you “cool it” with the post-workout ice bath? Cold-water immersion was found to reduce the ability of muscles to utilize dietary protein for muscle protein synthesis after resistance exercise and was shown to decrease muscle protein synthesis rates during a 2-week strength-training program in healthy adults.1
Poor sleep, short life?
Out of all of the cornerstones of health and longevity, sleep is probably the most important — with diet and exercise rounding out the top 3.
Sleep duration (how many hours of sleep you get each night) and sleep quality have been linked to a number of chronic diseases including cardiovascular disease, diabetes, cancer, and age-related cognitive decline, including dementia and Alzheimer’s disease.
It’s exciting to see that recently, a number of apps and health companies are placing a major emphasis on helping people improve their sleep habits using sleep tracking, while also providing tips, “hacks,” and protocols for healthy sleep.
A well-known sleep scientist and prominent science communicator named Matt Walker uses this phrase often: “The shorter your sleep, the shorter your life.”
While it may seem fatalistic, there may be some truth to this statement.
A new study published in the journal Nature Medicine2 used a deep learning model to estimate age using objective measures of sleep.
Sleep metrics were derived using polysomnography (PSG) — a non-invasive procedure in which brain signals, heart rhythm, and respiration are measured overnight during sleep using a variety of different sensors. PSG is the gold-standard measure of sleep duration and sleep quality.
A number of PSG-derived measures were used in the age-estimation calculation including: nighttime arousals (awakenings), apnea-hypopnea index (which correlates to sleep apnea), total sleep time, awakenings after sleep onset, and percentage of sleep spent in different sleep stages (stage 1-4 and REM sleep).
The model was able to calculate an individual’s “sleep age” within ~6 years of their actual (chronological) age.
The primary variable used in this study was the difference between the “sleep age” from the model and one’s chronological age — called the “age estimation error.” The age estimation error measures how much younger or older one’s “sleep age” is compared to their chronological age.
An older “sleep age” was associated with a significant increase in death from all causes and death from cardiovascular disease, and the risk increased the further one’s sleep age deviated from their chronological age.
For each 10-year difference between sleep age and someone’s actual age, the risk for all-cause mortality increased by 29%, and the risk for cardiovascular disease mortality increased by 40%.
An illustrative statistic highlights the major impact that “sleep age” has on life expectancy. For a 60-year-old subject, having a sleep age +10 years above chronological age decreased life expectancy by almost 9 years compared to having a sleep age -10 years below chronological age.
There’s a lot more to be concluded from this data than “sleep more and live longer.” Since PSG studies contain a wealth of information about brain, cardiovascular, and respiratory activity, any combination of sleep metrics and physiological variables that influence them could be proxies for health.
In other words, poor sleep may be a correlate of poor health rather than a direct cause. The reality is that the relationship is most likely bidirectional.
What are the actionable takeaways here? Obviously we are all trying to sleep as well as possible by any means necessary. Interestingly, in this study, one of the most powerful sleep variables related to “sleep age” was sleep fragmentation — defined as repetitive yet short interruptions in sleep. This would suggest that staying asleep and limiting nighttime awakenings should be an important focus.
Reducing awakenings at night may be accomplished by keeping a cool sleeping environment, sleeping in as dark a room as possible, and limiting food, caffeine, and alcohol intake prior to bedtime. It’s also probably pertinent to limit your water intake if it causes you to wake up during the night to urinate.
To end, I’ll rephrase the quote at the beginning of this post since it appears that: “The better your sleep, the better (and perhaps the longer) your life.”
Thanks for reading. See you next Friday.