The normative values aren't handed down from God, or some definite evidence of health. Instead, they were the typical range (mean ± 3SD, percentiles, etc) from a sample of healthy people, possibly matched for demographics (e.g., sex).
Suppose we set each range so that it contains 99/100 healthy people. It would only take about 70 independent tests before you have a 50:50 chance of being outside that range on one of them--and that's assuming you're an exact match for the reference population.
There's also error in the measurements themselves. Some of it is errors in the actual procedure or preparation: cross-contamination between samples, dust blows into the well, etc. However, many of the tests are stochastic too. Some measure binding between stuff in your blood (e.g., antibodies) and a "probe" that's designed to detect them. This usually works, but non-specific binding can cause false positives (the probe binds something that is similar to, but not quite the same as, the target). Other conditions can cause false negatives. The "front line" screenings are usually meant to be cheap, fast, and biased towards false positives.
You might be interested in a fairly common statistics question about screening. Suppose you had a test that is 99% reliable: 99% of sick people test positive; 99% of healthy people test negative. The disease itself is somewhat rare--only 1% of people have it. If you test positive, what are the odds you're actually sick? The answer[0] will explain why we don't test or scan people for tons of rare diseases, even with very reliable (and free) tests.
The normative values aren't handed down from God, or some definite evidence of health. Instead, they were the typical range (mean ± 3SD, percentiles, etc) from a sample of healthy people, possibly matched for demographics (e.g., sex). Suppose we set each range so that it contains 99/100 healthy people. It would only take about 70 independent tests before you have a 50:50 chance of being outside that range on one of them--and that's assuming you're an exact match for the reference population.
There's also error in the measurements themselves. Some of it is errors in the actual procedure or preparation: cross-contamination between samples, dust blows into the well, etc. However, many of the tests are stochastic too. Some measure binding between stuff in your blood (e.g., antibodies) and a "probe" that's designed to detect them. This usually works, but non-specific binding can cause false positives (the probe binds something that is similar to, but not quite the same as, the target). Other conditions can cause false negatives. The "front line" screenings are usually meant to be cheap, fast, and biased towards false positives.
You might be interested in a fairly common statistics question about screening. Suppose you had a test that is 99% reliable: 99% of sick people test positive; 99% of healthy people test negative. The disease itself is somewhat rare--only 1% of people have it. If you test positive, what are the odds you're actually sick? The answer[0] will explain why we don't test or scan people for tons of rare diseases, even with very reliable (and free) tests.
[0] ʎʇɟᴉɟ-ʎʇɟᴉɟ