[R] Image processing in R for BMI calculation

Sorkin, John j@ork|n @end|ng |rom @om@um@ry|@nd@edu
Tue Mar 2 01:25:00 CET 2021


Heinz,

I can't tell you how much I appreciated your email. I firmly believe that the rules and norms of the R-help mailing list need to be respected and followed. Nevertheless, I feared that if the comments were left unquestioned people who are not familiar with BMI, its strengths weakness, and its history, might assume from the comments that the metric is worthless, and that all studies that have used it are by extension worthless. It is for this reason, and because I thought it important the people understand that the exponent of 2 in the denominator is not a arbitrary value, but rather a value with a reason that I replied. 

I hope that the larger list community will forgive the liberty I have taken with the listerver's norms. I also hope that none of the people who were part of the email chain were personally offended by my comments.

John




John David Sorkin M.D., Ph.D.
Professor of Medicine
Chief, Biostatistics and Informatics
University of Maryland School of Medicine Division of Gerontology and Geriatric Medicine
Baltimore VA Medical Center
10 North Greene Street
GRECC (BT/18/GR)
Baltimore, MD 21201-1524
(Phone) 410-605-7119
(Fax) 410-605-7913 (Please call phone number above prior to faxing)



________________________________________
From: Heinz Tuechler <tuechler using gmx.at>
Sent: Monday, March 1, 2021 6:26 PM
To: Sorkin, John; Jim Lemon; Richard O'Keefe; T. A. Milne via R-help; Abby Spurdle
Subject: Re: [R] Image processing in R for BMI calculation

Dear All,

since Bert Gunter correctly stated that the discussion is off topic, I
answer to you only.
In my view John and Abby made very reasonable comments, while
particularly the link
https://nam11.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.npr.org%2Ftemplates%2Fstory%2Fstory.php%3FstoryId%3D106268439&data=04%7C01%7Cjsorkin%40som.umaryland.edu%7Cd5d29291516a4b5c84d408d8dd096c00%7C717009a620de461a88940312a395cac9%7C0%7C0%7C637502379829397742%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=MKCnjEzFyRmCrO6Efxo0s%2BTJ4cV%2B3m1FPy61MPwptE8%3D&reserved=0
mentioned in the note of T. Arthur Milne seems remarkably superficial -
maybe it's just a joke?

Some examples:
"Moreover, it ignores waist size, which is a clear indicator of obesity
level." Without reference to hip?

"Because the majority of people today (and in Quetelet's time) lead
fairly sedentary lives ..." 200 years ago?

"Because the BMI is a single number between 1 and 100 (like a
percentage) ..." Try to imagine a BMI of 1, or of 100. The BMI will be
between 1 and 100, but 1 to 100 will not be its range.

"It suggests there are distinct categories of underweight, ideal,
overweight and obese, with sharp boundaries that hinge on a decimal
place." Why should categories be implied by the BMI itself?

"It is embarrassing for one of the most scientifically, technologically
and medicinally advanced nations in the world ..." That's true, at least
for my eyes. When I visited the USA, I had the impression that in many
cases you don't need a measure at all.

best regards,

Heinz

Sorkin, John wrote/hat geschrieben on/am 01.03.2021 22:42:
> Colleagues,
>
> BMI has is failures, but it has demonstrated utility. BMI predicts multiple outcome measures including cardiovascular disease and mortality. Don't through out a useful metric because it is not the perfect metric.
>
> As to why BMI is computed as weight/height^2, it can be shown that dividing height by the square of weight decreases the correlation between weight and height. The optimum exponent (i.e. the power that most effectively minimizes the correlation between weight and height) is not the same in men and women and it differs by race. In general an exponent of 2.0 is best for men; for women an exponent of 2.2 is a bit better than 2.0.
>
> In any event, don't let the perfect get in the way of the good.
>
> John
>
>
> John David Sorkin M.D., Ph.D.
> Professor of Medicine
> Chief, Biostatistics and Informatics
> University of Maryland School of Medicine Division of Gerontology and Geriatric Medicine
> Baltimore VA Medical Center
> 10 North Greene Street
> GRECC (BT/18/GR)
> Baltimore, MD 21201-1524
> (Phone) 410-605-7119
> (Fax) 410-605-7913 (Please call phone number above prior to faxing)
>
>
>
> ________________________________________
> From: R-help <r-help-bounces using r-project.org> on behalf of Jim Lemon <drjimlemon using gmail.com>
> Sent: Monday, March 1, 2021 4:23 PM
> To: Richard O'Keefe; r-help mailing list
> Subject: Re: [R] Image processing in R for BMI calculation
>
> I must agree with the criticism of BMI as a diagnostic index. It is
> easy to tell if a person is - ahem - wide and not very high with a
> single glance. These elementary parameters can easily be deduced from
> an image of said person. However, it does not convey that essential
> ratio of muscle to - ahem - adipose tissue that is the stated reason
> for its prominence. I suggest an older, but more valid, index that was
> used in the identification of witches. Simply tie the person's hands
> behind their back and throw him or her into the deep end of the pool.
> Time to drowning is the response variable and I am certain that those
> now chastised for their adipose tissue will vastly prefer it.
>
> Jim
>
> On Mon, Mar 1, 2021 at 10:24 PM Richard O'Keefe <raoknz using gmail.com> wrote:
>>
>> "Body Mass Index" is a rather bizarre thing:
>> body.mass.in.kg / height.in.m^2
>> I have never been able to find any biological
>> or physical meaning for this.  Yet clinicians
>> are solemnly advised to measure the weight to
>> the nearest 0.1kg and the height to the
>> nearest 0.1cm.
>>
>> How do you propose to determine the weight from
>> a single image?  Even an R package cannot perform magic.
>>
>>
>> On Mon, 1 Mar 2021 at 05:39, Paul Bernal <paulbernal07 using gmail.com> wrote:
>>
>>> Hello everyone,
>>>
>>> Does anyone know about any package for image processing, for example, to
>>> calculate body mass index pased on a picture, silouette or image.
>>>
>>> Any guidance will be greatly appreciated.
>>>
>>> Best regards,
>>>
>>> Paul
>>>



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