Ha
Most come from rich families. Swimming. Tennis. Gymnastics. Every winter sport. Most come from rich families.
Ask Chat GPT, it says most are financially strained and the majority don't have long term wealth after the Olympics. AI is slop, but seeing as you go to the slop bucket, you should be fine with a slop bucket answer. I will not spam the slide with screen shots, but I did attach two just for you (as the slop bucket is known to be inconsistent).
You didn’t ask a question. You stated something you wanted backed up because it is the lifestyle you have chosen. Lots have chimed in that you’re not looking at the data objectively.
I did not ask a question. I would not come to Rokslide for health information any more than a master plumber would for plumbing information. I was sharing information to help others and I stated as much.
Your a1c should not be explained off because you run long distances. Neither should your weight above the line for normal. You’re not special. Those numbers are still warning signs on the dashboard.
Specificity of Hb A1c for prediabetes is around 60-80%. Any good clinician will not hang their hat on that if it doesn't fit the picture and will seek further testing.
Did you know, you can have prediabetes at Hb A1c below the 5.6% cut point? Testing choices are about compromise between specificity, sensitivity, and practicality. Population level trade offs are tailored for the mean and not the tails.
BMI is widely acknowledged to have flaws within the medical community. Saying a high BMI is bad when reliably assessed fat mass is in the healthy range is laughable. It is equally laughable to call a healthy weight BMI good when fat mass is well above the healthy range. Again, mean vs tails.
Good clinicians know the mean, and they also know they will see people in the tails and care is individualized.
Put differently, just like a good hunter knows when it is time to pull out the glass and take a closer look at the "rock" or "snow patch", a good clinician knows when it is time to look closer.