I have noticed one unsurprising side effect of lowering BMI:
I have noticed a subjective, almost exponential, negative tolerance to cold. At a current BMI of 20 down from 22. It is much easier for me to feel chilled and I put on a jacket at temperatures I would have ignored before.
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Yes - fat is a very good insulator. When you’re eating few calories (i.e. CR, or CRON), and you have a low BMI, I’ve found I was almost always cold, so was always wearing an extra layer unless out in the sun on a summer’s day. But - I’d rather use a sweater for fleece for a few hours a day, than lug around a few extra pounds of fat all day, every day 
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I’ve been trying to figure out whether a high BMI is problematic solely due to fat, or if it’s still better to maintain a lower BMI range even when lean. I’m unsure about the right answer, but I’m curious about your thoughts on this study:
It concludes: "Indeed, adding waist circumference to the model in addition to ASMI eliminated the risk associated with higher BMI (Fig 6). "
I’m wondering if a BMI above 25 is safe, and possibly even desirable, provided that one maintains a waist circumference of around 84-85 cm. I determined this target based on waist-to-hip and waist-to-height studies, such as this one: Central fatness and risk of all cause mortality: systematic review and dose-response meta-analysis of 72 prospective cohort studies - PubMed
In fact the first study used an even more generous waist circumference threshold (90 cm). However, maintaining a narrower waist (say, 85 cm) while increasing BMI through muscle gain with intelligent nutrition and weight training is definitely doable.
So I have 2 hypotheses at this point:
- High BMI is bad regardless of whether it’s mostly fat or muscle, so it’s best to be on the lower end (e.g. 23-24) with a waist of ~85
- BMI is only bad if it’s mostly fat; otherwise it’s irrelevant. This would imply that it might be safe, or even desirable, to have a higher BMI (let’s say 25–27), as long as the waist circumference remains around 85 cm.
Recently, I’ve been leaning toward hypothesis #2, but I’m curious what you think!
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Correction. Here is the first study’s definition:
" Abdominal obesity was defined using National Cholesterol Education Program Adult Treatment Panel III cutpoints of 102 cm for men and 88 cm for women [29]."
So it’s even more generous than I thought! I’ve been personally targeting 84-85 WC as a man.
Also, given that WC is simply an imperfect proxy for body fat %, how about we propose a new control: “visible six pack + WC of X” where X can be based on 0.48–0.5 waist-to-height or ~0.8 waist-to-hip ratios for men. It’d be interesting to see what the all-cause mortality curve would look like with this control applied.
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People with a higher body-mass index are more likely to develop dementia, research finds.
Being classed as overweight rather than in the normal range increases the dementia risk by 16-33%.
Being classed as obese (an additional 14.5kg) adds the same amount of dementia risk again, making a total of up to 66%.
The study analysed data from 1.3 million adults in the US and Europe.
Full Open access Paper:
https://alz-journals.onlinelibrary.wiley.com/doi/10.1016/j.jalz.2017.09.016
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AnUser
#26
I think it’s bad whether it is muscle or fat to have high BMI, but there are waay worse things than to have a lot of muscle mass, it’s in fact probably very healthy and there is no issue at all.
To have a high BMI from muscle mass early in life is probably very healthy and wise, as there is an exponential decrease in muscle mass over time, which means when you start with high muscle mass you end up with high in older age as well.
It is also assosciated with a decreased risk of hip fractures to have higher BMI.
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AnUser
#27
True but most people who get down to BMI 18.5 will probably be skinny fat.
scta123
#28
Might be. But from my personal experience my lowest BMI was 19 just before surgery on my knee some 20+ years ago and my lean body mass was exactly the same as months later when my BMI was 25. And in my case it probably was the opposite.
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The masters paper controls for the effect of BMI independent of body shape factors. You can look at my discussion of the principal components in the original post. That means the conclusions on the hazards of BMI are independent of body shape (at least with the measurements in the NHANEs database, which are extensive). However, this means the principal components give a good indicator on how body shape effects long-term health.
So the two conclusions of the paper are
- BMI of 18.5-20 is possibly optimal, but BMI from <18.5 all the way to 25 are within error bars. So I think it’s fine, really. Also, maintaining a stable weight is good; time spent at a healthy BMI matters more than attaining that BMI at a particular test, and weight-loss due to disease states is not healthy, obviously.
- Modifiable factors of body shape can significantly affect within-BMI risk. Keep your body fat % low, muscle high (especially in your legs), and get your waist circumference as low as possible without sacrificing your health.
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Alex
#30
With respect, you look fantastic. I cannot imagine you are unhealthy as you do not look overly thin at all.
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Alex
#31
Another problem I have had with losing a lot of pounds is that sitting on hard surfaces is not nearly so comfortable!
But as with insulation, it is a small price to pay.
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Ulf
#32
Waist circumference as low as possible for me means BMI at 20.
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blsm
#33
Thank you so much sir. It can be tricky to be objective about ourselves so I find honest input from others useful. I’m excited to do a dexa scan soon because although my BMI is technically borderline (fluctuates between 18.1-18.6) the mirror tells a different story and I really think my body composition is perfectly fine/healthy for me.
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What do you all think about this conclusion?
“For this purpose, we derived an optimal value of BMI of 24 for males (26 for females) and optimal value of WHtR of 0.5 for males (0.46 for females).” from this study?
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Apologies, here is the right study:
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Ulf
#36
The analysis by Amelia1917 of the BMI paper is superb. I just big to differ in one detail. From her conclusion: “BMI of 18.5-20 is possibly optimal, but BMI from <18.5 all the way to 25 are within error bars”.
I would replace “possibly optimal” with “probably significantly superior”. It it true that the differences between the BMI ranges all the way to 25 are within error bars, but only barely. Estimating crudely from the graph in figure 5, I get an HR hazard ratio of all-cause mortality of 0.95 to 1.4 of the BMI 20 to 25 compared to 18.5 to 20, with HR of 1.2 falling in the middle.
A statistical curve will show a fat belly and thin tails. It should only be a 5 to max 10 % chance that HR falls in the 0.95 / 1.05 range i.e. BMI 20 - 25 being roughly equal in health outcome to 18.5 - 20. The bulk of the statistical probability will be in the HR 1.1 to 1.3 range i.e. 10 - 30 % higher all cause mortality for the 20 to 25 range compared to 18.5 - 20 being likely. . For me that is a significant difference.
This is a very crude calculation without any mathematial equation! My course in statistics from college days is rusty to say the least. Is there anyone who can put the bars of the right-hand part of figure 5 into an equation?
Amelia1917, might you have access to the underlying data? E.g. having the exact midpoint figure of HR that I guess to be 1.2 would help. As would knowing the exact figures of the upper and lower extremes of each bar.
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This is not surprising. This is a result of the body slowing down its metabolism to conserve energy. This is seen in animals on CR and humans that cut calories very low. It has less to do with body fat being insulating and more to do with thyroid hormones dropping due to low leptin levels. A good example of this is that if you fast for a few days. You will most likely notice that you feel colder one day into the fast even though you obviously can’t lose much body fat in that time. However leptin levels can temporarily drop almost 50% with short term fasting and that will lower heat production.
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Here in Hong Kong, when it goes below 70 degrees the locals break out the winter coats. I still go around in short sleeved shirts. Now when it breaks below 60, I wear a light jacket and the locals dress as if it were going to snow. The local population has a very very low BMI average.
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Asians need a lower bmi than Caucasians on average.
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Neo
#40
Causality of fat mass index (FMI) on longevity seem to be linear and not U or J curve shaped in a person who avoids risk factors:
Findings
Linear MR analyses indicated a positive association between genetically predicted fat mass and all-cause mortality (HR 1.10, 95 % CI 1.08–1.12, P < 0.001). The association between FMI and all-cause mortality was manifested as J-shaped (HRs across FMI categories: 1.04, 1.00, 1.07, 1.21, 1.54), which was significantly modified by the number of low-risk lifestyle factors (P for interaction<0.001). When evaluating individual lifestyle factors, we observed a nonlinear relationship between FMI and all-cause mortality among participants who had high-risk lifestyle factors, while a linear relationship was observed among participants who had low-risk lifestyle factors, especially for those with adequate physical activity (HRs across FMI categories: 0.95, 1.00, 1.05, 1.17, 1.44) and who never smoked (0.96, 1.00, 1.03, 1.14, 1.51).
Interpretation
Genetically determined fat mass is causally and linearly associated with mortality. The J-shape association between anthropometric FMI and mortality is caused by high-risk lifestyle factors.
Association between fat mass and mortality: analysis of Mendelian randomization and lifestyle modification - ScienceDirect
@amelia1917 @AlexKChen has this paper been discussed in the CR(ON) community?
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