So why use most correct stats as possible? Especially for women, your accuracy is all over the place for calorie burn. And calorie burn was probably the only reason you got the HRM, so why not have it as accurate as possible?
So Polar uses a BMR calc of stats as part of calculations for calorie burn.
So correcting any of those stats can improve what Polar estimates as your calorie burn. Because so many rely on that calorie estimate to tell them how many calories to eat back (very smart), more accuracy would probably be of benefit.
Which means if your estimated BMR based on body composition (Katch-McArdle formula) is different, or based on suppressed metabolism because of underfeeding it (NETting below BMR constantly), you could have a better estimate of calorie burn possible.
So probably the easiest method that doesn't require any self tests, would be adjusting your stats so Polar estimates with the same BMR you know is more accurate.
How to do it for body composition (Katch-McArdle BMR formula):
1 - Use the stats you entered into Polar (only sex, age, weight, height) here - http://www.gymgoal.com/dtool_bmr.html
________Note that BMR figure(that will not match MFP, which uses a slightly more accurate formula by Mifflin).
2 - Now get a decent estimate of your bodyfat% here - http://www.gymgoal.com/dtool_fat.html
________Use the Covert Bailey as accurate enough, and note it.
3 - Now take the BF% figure back to site in step 1 and use the optional % Body Fat stat.
________Note this more accurate estimate of your BMR based on your current Lean Body Mass (you are hoping this changes).
4 - Now remove the BF% stat, and adjust the age stat so the displayed BMR matches the estimate for BF% BMR.
________So that is the age of avg person with your BMR by Harris formula. That is what you enter into your Polar. When you drop 10 lbs, recalc your BF% and redo BMR calc based on it, to see if any need to change, hopefully you get younger biologically!
How to do it if your current daily goal has you NETting below your BMR on constant basis (per choice to lose weight slower):
1 - Get a decent estimate of what your BMR could be if fed (only sex, age, weight, height) - http://www.gymgoal.com/dtool_bmr.html
________This is not your true estimated BMR if netting below it for long enough to not be hungry anymore.
2 - Change the weight stat until the displayed BMR matches what you currently NET on constant basis (1200, 800, whatever).
________So that is the weight of avg person with your BMR running at full steam. That is what you enter into your Polar. When you drop 10 lbs or notice you are not netting so bad, recalc your BMR with what you are now netting constantly, or if you raise net goal at some point, hopefully you get heavier! Why not use age? You'd likely have to be 100 yrs old with metabolism that slow, but you can try it. Or change a little of both weight and age to show same slower BMR.
So the other reason for variance in the stats, is the MHR, and VO2max. Women again have big variance in true MHR, and resulting VO2max estimated from that.
And with the change to biological age above compared to chronological age, you may desire to adjust the MHR so the zones are correct, if that matters to you.
If you wish to get these as accurate as possible, here is a nice test to do if you have been exercising for a little while. With link if you are very aerobically fit for more serious test.
If you have not been exercising that long, submaximal step test for MHR estimate.
And for submaximal step test for VO2max, just use HRM for top bpm at end of test.
So hopefully by getting your more biological age down for both BMR and MHR compared to chronological age based on calculations, you can have better HRM calorie burn estimates, and hopefully you are eating those back to feed your workout so your body can improve and continue to give you great performance.
Oh, how did I come up with Polar is using BMR calc in their calorie estimates? Several online forums discussing. Tests people (and myself) did changing the values, doing exact same workout level for HR, and seeing the variance in estimate matches the variance in BMR changes.
Why could BMR calcs be that different? Because the BMR calcs are based on studies of people ALREADY at healthy weight, with avg LBM / BF ratios. If you have higher BF% at overweight compared to study partipants, then BMR is overestimated. At least with Katch BMR formula using LBM, while it was based on healthy weight subjects too, it will slightly underestimate at overweight, not as bad a deviation though.