...The fact that many of the (very optimistically estimated) number of those who were added to O-Care rolls did not want or feel they needed it should be considered as well.
I personally know several people who were able to get insurance under Obamacare but didn't have it before. Not one says that they "did not want or feel they needed" insurance. What they say is, "Thank God, this is saving my life."
However, even if what you said was true: what you are implying is that there is a body of people who previously were saying "I don't want or need insurance, because if I get sick I'll go to a hospital that is legally is not allowed to turn me away, and the taxpayers will pay for it," -and they are now paying for their own health care. That's a win for the taxpayers.
In other cases, such as ones I am very familiar with, previously covered spouses were forced to move to their own plan if their work provider had coverage available. This means that although a new health care subscriber can now be counted, that person was already covered
That's not the way the number of uninsured is counted. That would count as a wash: neither an addition nor a reduction to the number of uninsured.
... More often than not, it is the large urban populations that shift state's support bias to liberal, and it is those same urban areas that hold the most desperate and dependent populations of the truly underprivileged.
Sorry, the belief that poverty is an urban phenomenon is another myth. It's a myth that's pervasive among liberals and conservatives, but simply not true. There are actually more poor and underprivileged people in rural America. You're right about urban areas being liberal and rural conservative, but wrong about being able to attribute that to "dependent populations of truly underprivileged": the greatest use of food stamps, as a percentage of population, in poor rural areas, not urban areas.
.... Its not that hard to play with numbers to make any point you want.
But you don't have to do that, because it's even easier to simply say "Those numbers don't support my political bias, so they are wrong."