Well, I have now read the second of the two papers. I think I know what has been done. They have done an enormous data collection for the period from 1st Jan to 1st May. They have found out how many people there are with a diagnosis of diabetes, what their age is, what their BMI is, their latest HbA1c and a couple of other factors. They have done this using input from GP records using NHS number to identify individuals. They have then looked at death stats for the same period looking for death certificates where COVID is referred to as a contributor to the death. The NHS number provides the link to the diabetes data.
They have then entered the data into a statistical package which looks at all the data and looks for the effect of each of the factors as separate entities. It does this by calculating a hazard ratio for each factor ( HbA1c, BMI ethnicity, etc) which says something about the additional risk of being in a particular category. This hazard ratio increases with age, HbA1c, and generally with BMI although are higher for anorexic levels of BMI.
So far so good. The next thing I have to work out is what the hazard ratio means and what the risks are being compared to. I would expect the comparisons to be to people without a diabetes diagnosis but on a first read, I cannot see how that can have been done. Also, the raw data shows an expected increase in death rate with age but not for HbA1c or BMI, that only comes out in the statistical analysis. I need to get comfortable with that and the conclusions you can draw.
Might run out of steam on this one.