For example - our skin is constantly covered in bacteria and molds, surely sunlight impacts these.
So while there is a decent bit of established evidence from more extreme environments that Vitamin D is important, there's only now really been enough research covering whether a supplement is necessary for people who can source it through "normal" pathways.
We aren’t even scratching the surface of how contra-evidentiary the instructions to the general population (since elites didn’t follow them) were.
Population level statistics has lead to a large number of algorithms that have been proven wrong for medical conditions.
BMI, dietary cholesterol, vitamin D, etc...
Auto differentiation is an incredible tool, but I don't see how it will truly be a 'miracle' like vitamin D, which in hindsight is clearly over fitting combined with a correlation that wasn't acausal connection.
ML is extremely powerful, but not for individuals for the same reason statistics is great for populations but not individual.
This is the 'common sense' problem that both fields struggle with and need to correct for. Ethical problems with empirical testing in humans complicating the problem when applying ML or statistics to medical problems complicates that too.
Personalized intake recommendations.
Comprehensive health assessments from various health sources (labs, wearables, etc).
Monitoring vitamin trends through health assessments w/ time & overall wellness.
Reading and applying latest research/clinical trials to all the above.
The title that I see is "How Much Vitamin D Do You Need to Stay Healthy?".
Also, it's against the guidelines:
> please use the original title, unless it is misleading or linkbait; don't editorialize.
It does a bunch of other things too. Like specific things. That can be and have been shown to be beneficial in the right contexts for the right people.
So what purpose do these kinds of articles serve?
