A high pressure is a good predictor for someone being unhealthy. On the other hand statins that reduce blood pressure don't provide the returns that people hoped for.

Goodhard's law applies very much.

Before dying with a heart attack Seth Roberts had a year where he improvement on the score that's the best predictor for heart attacks, while most people don't improve on the score as they age.

Using metrics like BMI and WHR seems to me very primitive. We should have no problem running a 3D scan of the whole body. I would estimate that obesitey[3D scan + complex algorithm] is a much better metric than obesity[BMI], obseity[WHR] or obesitey[BMI/WHR].

That's to be further improved by not only going for the visible light spectrum but adding infrared to get information about temperature. And you can follow it up by giving the person a west with hundreds of electrodes and measuring the conductance.

The tricoder xprice is also interesting.

As quantified self devices get cheaper it will also be possible to use their data to develop new metrics. A nursing home could decide to give every member a device that tracks heart rate 24/7. After a few years time the can give the data to some university bioinformatics folks who try to get good prediction algorithms.

Can we construct a whole host of other, similar numbers, like "math skills" and thus measure the impact of education and aging?

Math skills can mean multiple things to different people. Some people take it to mean the ability to calculate 34*61 in a short amount of time and without mistakes. Other people take it to mean doing mathematical proofs.