I work at a biotech that does intersecting research (predicting disease risk). We obsess about temporal variation at various time scales and the effects are quite real. We use multiple data planes (multi-omics) to evaluate temporal effects across diverse biology. Our goal is to ensure that our long-term predictions are minimally impacted by short-term fluctuations.
One of the "dirty secrets" in healthcare is similar issues with BP.<p>Things like posture, white-coat syndrome, having to pee, cuff placement, cuff size, arm position, muscularity, arm diameter, time sitting, and many other variables have a massive influence on blood pressure.<p>BP is kind of like weight - it should be taken at regular intervals during the day, at the same times, and averaged out over time to look at trends. "Snapshot" BP readings are most useful for things like hypertensive crisis, not ongoing BP management.<p>Unfortunately, we see a lot of people put on BP meds where other interventions may be more appropriate based on bad BP measurements.<p>I think there are a lot of things in healthcare like this, where our models are too simplistic and result in flawed understanding and consequently ineffective treatments.
That certainly breathes new life into old metaphors like "twilight years".<p>It sounds like the most immediate takeaway is that anyone analyzing this stuff needs to control for <i>when</i> measure individuals.
I mean epigenetic clocks are extremely unreliable and have enormous error bars. It is not surprising that they are easily influenced by additional variables.