Relationship Between BMI and Disease, and Longevity

[Michael R]

Quoting a decent chunk from Wikipedia as background:

Quote

[Associations Between] Low BMI, high mortality

CR diets typically lead to reduced body weight, yet reduced weight can come from other causes and is not in itself necessarily healthy. In some studies, low body weight has been associated with increased mortality, particularly in late middle-aged or elderly subjects. Low body weight in the elderly can be caused by pathological conditions associated with aging and predisposing to higher mortality (such as cancer, chronic obstructive pulmonary disorder, or depression) or of the cachexia (wasting syndrome) and sarcopenia (loss of muscle mass, structure, and function). [smoking also lowers current body weight and long-term BMI trajectory, and of course also increases mortality risk -MR]. One of the more famous of such studies linked a body mass index (BMI) lower than 18 in women with increased mortality from noncancer, non−cardiovascular disease causes. The authors attempted to adjust for confounding factors (cigarette smoking, failure to exclude pre-existing disease); others argued that the adjustments were inadequate. ...

Such epidemiological studies of body weight are not about CR as used in anti-aging studies; they are not about caloric intake to begin with, as body weight is influenced by many factors other than energy intake. Moreover, "the quality of the diets consumed by the low-BMI individuals are difficult to assess, and may lack nutrients important to longevity." Typical low-calorie diets rarely provide the high nutrient intakes that are a necessary feature of an anti-aging calorie restriction diet. As well, "The lower-weight individuals in the studies are not CR because their caloric intake reflects their individual ad libitum set-points, and not a reduction from that set-point.^"

Indeed, simply eliminating people with any history of smoking from an analysis of BMI vs. future risk of death from any cause nearly eliminates the "J-shaped" elevation in mortality amongst people with low body mass indexes:

This was an especially powerful study, too, as it is a meta-analysis of 57 prospective epidemiological studies using individual patient data from over 900,000 subjects. The amazingly huge number of subjects makes it powerful, as is the fact that they used the actual, numerical data for each patient extracted from each study's raw data, than (for instance) pooling studies' "high" and "low" categories as is usually done; as the Cochrane Collaboration acknowledges, although most Cochrane analyses do not take the extra trouble to perform individual patient-data analysis, doing so "can improve the quality of data and the type of analyses that can be done and produce more reliable results (Stewart and Tierney 2002). For this reason they are considered to be a ‘gold standard’ of systematic review." Taking this trouble with the individual data from more than 900,000 people is an enormous scientific labor, and the investigators are to be congratulated.

Another important factor is the degenerative aging process itself. The National Institute on Aging's Baltimore Longitudinal Study of Aging (BLSA), the "most comprehensive and longest running longitudinal examination of human aging in the world," has reported that

Quote

Quote

Approximately 9 years before death, the rate of weight loss increased to an average of 0.39 kg/year (P < 0.001) for all-cause mortality. For cancer deaths, weight loss accelerated significantly 3 years before death, regardless of age group. For cardiovascular deaths, the best-fitting inflection point increased with age, from 5 years for participants aged 60–69 years to 9–10 years before death for those aged 80 years or older. Results suggest that weight loss in older persons may begin earlier than previously believed. The duration of weight loss for noncancer deaths suggests that even distal changes in energy balance may be linked to risk of death.((1); my emphasis)

Predicted weight (in kilograms) by time to death and age at death for male decedents from the Baltimore Longitudinal Study of Aging, Maryland, 1958–2005. Participants who died at A) age 60–69 years (n = 87), B) age 70–79 years (n = 211), C) age 80–89 years (n = 320), D) age ≥90 years (n = 182). Refer to the Statistical Analysis portion of the text for a description of the models.(1)

 

Nearly no epidemiological studies on body weight/BMI have even run for long enough to account for a 9 year trajectory of disease-related weight loss. Most such studies either fail to exclude any early deaths that are likely related to undiagnosed disease onset, or exclude no more than 3 years of such deaths (I have never seen more than 5 years excluded). Aging itself is linked to unintended weight loss, as this graph from the Framingham Heart Study (2) shows:

 

 ▲ = Females; ◻ = Males

What's more informative is that both men and women who go on to be long-lived have lifelong trajectories of lower body weight than normally-lived people:

(Males)

 

(Females)

▲ = Long-lived (survived to age 80 for males and age 83 for females); ◻ = medium-lived (i.e., individuals whose age at death was between the ages of 65 and 80 for males and 65 and 83 for females). Also from the Framinham Heart Study (2).

References

1: Alley DE, Metter EJ, Griswold ME, Harris TB, Simonsick EM, Longo DL, Ferrucci L. Changes in weight at the end of life: characterizing weight loss by time to death in a cohort study of older men. Am J Epidemiol. 2010 Sep 1;172(5):558-65. doi: 10.1093/aje/kwq168. Epub 2010 Aug 2. PubMed PMID: 20682520; PubMed Central PMCID: PMC3025636.

 

2: Yashin AI, Akushevich IV, Arbeev KG, Akushevich L, Ukraintseva SV, Kulminski A. Insights on aging and exceptional longevity from longitudinal data: novel findings from the Framingham Heart Study. Age (Dordr). 2006 Dec;28(4):363-374. PubMed PMID: 17895962; PubMed Central PMCID: PMC1994150.

 

3: Prospective Studies Collaboration, Whitlock G, Lewington S, Sherliker P, Clarke R, Emberson J, Halsey J, Qizilbash N, Collins R, Peto R. Body-mass index and cause-specific mortality in 900 000 adults: collaborative analyses of 57 prospective studies. Lancet. 2009 Mar 28;373(9669):1083-96. doi: 10.1016/S0140-6736(09)60318-4. Epub 2009 Mar 18. PubMed PMID: 19299006; PubMed Central PMCID: PMC2662372.

[Guest Scott McClatchey]

"Aging itself is linked to unintended weight loss, as this graph from the Framingham Heart Study (2) shows"

Michael,

     An alternative explanation for this graph is that those with high BMI die earlier. Or both may be true. Do you know of any study that addresses this?

Scott McClatchey
(remember me?)

[Taurus Londono]

...unsurprising that the bottom of that curve lies beyond the error bars...never ceases to be exasperating...

[Dean Pomerleau]

[Note: this post and the one below it were originally posted elsewhere, but have been moved to this thread as it is the more appropriate place for its content. - Dean]

 

As we've discussed in this thread, there are several confounders that are likely to make simply "being thin" very different from "practicing CR". Three of them with obvious health/longevity downsides are:

• Smokers are thinner than non-smokers
• People with latent chronic illnesses are thinner than healthy people
• Naturally thin people often eat crappy diets

Al Pater was kind enough to share with me this "oldie but goodie" [1] that may be the best study available that factors out these three confounders. The title itself gives you most of the background necessary to illustrate why this study is particularly relevant:

 

Body mass and 26 y risk of mortality among men who never smoked: a re-analysis among men from the Adventist Mortality Study

 

First off, Adventists are known for eating a relatively healthy diet, and for having lots of vegetarians and vegans compared to the general population. In fact, they've provided some of the best evidence that vegan/vegetarian/semi-vegetarian diets are associated with lower all-cause mortality than omnivorous diets [2].

 

Second, not many Adventists smoke, but (thankfully) they excluded even those few who ever have smoked from the analysis of this paper.

 

Third, they had a very long follow-up, up to 26 years. This was important, since they found that prior to 15 years, there was evidence that excess mortality in the thin group was due to latent, undiagnosed illness.

 

For their analysis, they divided the men into three groups based on their BMI at baseline: thin (BMI: 14.3-22.5, yikes - 14.3!), middle (22.6 - 27.4) and heavy (27.5 - 43.9). When they restricted the analysis to men who had been enrolled in the study for at least 15 years, they observed:

 

...a significant positive, linear relation between BMI and all-cause mortality was consistently found among middle-aged (30-54 y) and older (55-74 y) men.

 

In other words, the thin group had lower mortality than the middle and heavy groups at both age ranges. In the important older age range (55-74 yrs), the relative mortality rate (and 95% CI) for the three groups were thin 0.77 (0.61, 0.98), medium 1.0 (ref) and heavy 1.10 (0.89, 1.36). So not only did the thin guys do better than the overweight / obese guys, they did better than the normal-to-overweight guys as well. 

 

The benefits of being thin were particularly dramatic in both morality from cardiovascular disease and cancer, the two leading causes of death in this population. Here are the relative mortality rates (and 95% CI) for the three groups for two specific causes:

• Cardiovascular Disease: Thin 0.63 (0.46, 0.85)   middle 1.0 (ref)    heavy 1.13 (0.88, 1.47)
• Cancer:                           Thin 0.49 (0.25, 0.97)   middle 1.0 (ref)    heavy 0.98 (0.58, 1.65)

One possible caveat I considered - In the data reported, they didn't control for the variation between BMI groups in the number of non-meat eaters, which was in fact twice as common in the thin group as the heavy group. So vegan/vegetarianism may have been the cause of both the thinness and the reduced mortality. But they appear to have done additional analysis that found this was not the case:

 

In larger models, adjustment for potential confounders described above [which included meat-eating status] had little effect on the hazard ratios or trends in Table 1 [sic? - I think they meant Table 2, where the above reported stats come from].

 

Note: the three groups were defined based on BMI at baseline, 15-26 years prior to the mortality analysis, so there is no telling how their weight may have changed in the intervening years, and how that may have impacted mortality. But as we've seen, if they'd try to take into account post-baseline weight trajectory, they'd have run into the same weight-loss confounder quagmire discussed previously in this thread, so it's probably good they didn't try!

 

Finally, 55-74 years isn't that old - there could still be a disadvantage to being thin in very old age. This study was from 1998. It would be great if they'd do another follow-up, now that these men would be 17 years older if still alive!

 

--Dean

 

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[1] Int J Obes Relat Metab Disord. 1998 Jun;22(6):544-8.

Body mass and 26 y risk of mortality among men who never smoked: a re-analysis
among men from the Adventist Mortality Study.

Lindsted KD(1), Singh PN.

Author information:
(1)Center for Health Research, Loma Linda University, CA 92350, USA.

OBJECTIVE: To re-analyse the previously reported linear relation between
Quetelet's body mass index (BMI) and mortality, among men from the Adventist
Mortality Study after accounting for effects due to age at measurement of BMI,
smoking history and race.
DESIGN: Prospective cohort study. To specifically account for effects due to age
at measurement of BMI, smoking history and race, our methodology includes: 1,
computing hazard ratios for BMI quintiles from a proportional hazard regression,
with 'time on study' as the time variable, and age at baseline as a covariate; 2,
conducting separate analyses of middle-aged (age 30-54y) and older (age 55-74y)
men; and 3, restriction of the analyses to never-smoking, non-Hispanic white
males.
SUBJECTS: 5062 men (age: 30-74 y, BMI: 14-44 kg/m2) from the Adventist Mortality
Study.
MEASUREMENTS: Subjects reported data on anthropometric, demographic, medical,
dietary and lifestyle characteristics at baseline and were enrolled in mortality
surveillance during a 26y study period (1960-1985).
RESULTS: During the early years of follow-up (years 1-8, 9-14), we found some
evidence of excess risk among the leanest men that was probably due to the
effects of antecedent illness. During the later years of follow-up (years 15-26),
effects due to antecedent illness were not apparent and a significant positive,
linear relation between BMI and all-cause mortality was consistently found among
middle-aged (30-54 y) and older (55-74 y) men. Disease-specific analyses of the
later follow-up (years 15-26) revealed that the positive linear trends with
all-cause mortality, were primarily due to excess risk of cardiovascular disease
and cancer among the heavier men. Among older men, a significant inverse relation
between BMI and respiratory disease mortality risk was identified during later
follow-up (years 15-26), but this effect attenuated after restriction of the
analyses to men with no baseline history of respiratory disease.
CONCLUSIONS: The re-analysis confirms the findings of a positive, linear relation
between BMI and all-cause mortality, reported in the original study.

PMID: 9665675

 

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[2] JAMA Intern Med. 2013 Jul 8;173(13):1230-8. doi: 10.1001/jamainternmed.2013.6473.

Vegetarian dietary patterns and mortality in Adventist Health Study 2.

Orlich MJ(1), Singh PN, Sabaté J, Jaceldo-Siegl K, Fan J, Knutsen S, Beeson WL,
Fraser GE.

Author information:
(1)School of Public Health, Loma Linda University, Loma Linda, CA 92350, USA.
morlich@llu.edu

Comment in
JAMA Intern Med. 2014 Jan;174(1):168-9.
JAMA Intern Med. 2014 Jan;174(1):169.
JAMA Intern Med. 2013 Jul 8;173(13):1238-9.
Dtsch Med Wochenschr. 2013 Sep;138(39):1930.

IMPORTANCE: Some evidence suggests vegetarian dietary patterns may be associated
with reduced mortality, but the relationship is not well established.
OBJECTIVE: To evaluate the association between vegetarian dietary patterns and
mortality.
DESIGN: Prospective cohort study; mortality analysis by Cox proportional hazards
regression, controlling for important demographic and lifestyle confounders.
SETTING: Adventist Health Study 2 (AHS-2), a large North American cohort.
PARTICIPANTS: A total of 96,469 Seventh-day Adventist men and women recruited
between 2002 and 2007, from which an analytic sample of 73,308 participants
remained after exclusions.
EXPOSURES: Diet was assessed at baseline by a quantitative food frequency
questionnaire and categorized into 5 dietary patterns: nonvegetarian,
semi-vegetarian, pesco-vegetarian, lacto-ovo-vegetarian, and vegan.
MAIN OUTCOME AND MEASURE: The relationship between vegetarian dietary patterns
and all-cause and cause-specific mortality; deaths through 2009 were identified
from the National Death Index.
RESULTS: There were 2570 deaths among 73,308 participants during a mean follow-up
time of 5.79 years. The mortality rate was 6.05 (95% CI, 5.82-6.29) deaths per
1000 person-years. The adjusted hazard ratio (HR) for all-cause mortality in all
vegetarians combined vs nonvegetarians was 0.88 (95% CI, 0.80-0.97). The adjusted
HR for all-cause mortality in vegans was 0.85 (95% CI, 0.73-1.01); in
lacto-ovo-vegetarians, 0.91 (95% CI, 0.82-1.00); in pesco-vegetarians, 0.81 (95%
CI, 0.69-0.94); and in semi-vegetarians, 0.92 (95% CI, 0.75-1.13) compared with
nonvegetarians. Significant associations with vegetarian diets were detected for
cardiovascular mortality, noncardiovascular noncancer mortality, renal mortality,
and endocrine mortality. Associations in men were larger and more often
significant than were those in women.
CONCLUSIONS AND RELEVANCE: Vegetarian diets are associated with lower all-cause
mortality and with some reductions in cause-specific mortality. Results appeared
to be more robust in males. These favorable associations should be considered
carefully by those offering dietary guidance.

PMCID: PMC4191896
PMID: 23836264

Edited October 1, 2015 by Dean Pomerleau

[Dean Pomerleau]

Over on the Facebook Group, Mike Lustgarten posted a valid observation about my recent post to this thread analyzing the Adventist study (pmid: 9665675). The Facebook discussion format is too cumbersome and impoverished to really support such a discussion, so I'm moving it here.

 

Mike said:

Interesting post, Dean Pomerleau. Although all-cause mortality is significantly less in the low BMI group (14.3-22.5), you didn't include that deaths related from respiratory disease was significantly increased by 243%! So for someone with a low BMI, can this be further reduced? Fiber from whole grains is associated with reduced respiratory disease deaths...

https://michaellustgarten.wordpress.com/.../is-dietary.../

 

To which I responded: 

 

Mike, Of course I would never advise against eating more fiber!

But in men who were healthy at baseline (no prior history of respiratory illness), being thin wasn't associated with increased mortality from subsequent repiratory disease.

From the full text: "The significant inverse relation [between BMI and mortality] with respiratory disease mortality presented in Table 2, was attenuated after exclusion of men reporting history of respiratory illness (asthma, bronchitis, tuberculosis) at baseline (HR, years 15±26: 1.5, 1.0, 0.8; linear trend, P 0.15), and substantially attenuated (HR, years 15 26: 1.1, 1.0, 0.8; linear trend, P 0.31) after further exclusion of men reporting severe respiratory symptoms (coughing, shortness of breath, sore throat) or recent weight loss (>10 lbs up to five years before baseline)."

So as I said, being healthy and thin appears to be a good thing for reducing mortality in subsequent years.

 

To which Mike responded:

 

It may not be so simple to dismiss the increased respiratory mortality found in those with a low BMI. In this meta-analysis of 900,000 subjects, BMI < ~22 is associated with increased respiratory mortality risk!

 

http://www.thelancet.com/.../PIIS0140-6736(09.../fulltext... 

 

Mike is referring to this study [1]. a meta-analysis of BMI and cause-specific mortality among 900K adults. Mike correctly points out that in this population:

 

Below the range 22.5-25 kg/m(2), BMI was associated inversely with overall mortality, mainly because of
strong inverse associations with respiratory disease and lung cancer.

 

But Mike, once again this study is failing to sufficiently factor out the effects of pre-existing conditions and poor lifestyle choices. The lung cancer association with thinness is obviously not hard to explain - subjects may not have been smoking at baseline (as they authors claim to have factored that out), but they likely had smoked in the past, explaining both their thinness and later lung cancer. Which clearly points to my second, more germane observation.

 

As for the association between low BMI and respiratory disease mortality, one need look no further than the exclusion criteria the authors' employed:

 

To limit reverse causality, the first 5 years of follow-up were excluded, leaving 66 552 deaths of known cause during a mean of 8 (SD 6) further years

 

This is much too short an exclusion time (5 yr), and much too short a follow-up time (average of 13 years), since Michael Rae's analysis showed that at least 9 years of exclusion was needed, and the Adventist study under discussion observed specifically that the confounding effects of pre-existing respiratory conditions on the association between BMI and mortality were not washed out until subjects were followed for over 14 years post baseline.

 

So being thin but healthy at baseline appears overall beneficial for all-cause mortality, and not detrimental even for respiratory mortality, once subjects who are likely thin due to pre-existing respiratory conditions are excluded from the analysis for a sufficient period of time.

 

--Dean

 

---------

[1] Lancet. 2009 Mar 28;373(9669):1083-96. doi: 10.1016/S0140-6736(09)60318-4. Epub

2009 Mar 18.

Body-mass index and cause-specific mortality in 900 000 adults: collaborative
analyses of 57 prospective studies.

Prospective Studies Collaboration, Whitlock G, Lewington S, Sherliker P, Clarke
R, Emberson J, Halsey J, Qizilbash N, Collins R, Peto R.

BACKGROUND: The main associations of body-mass index (BMI) with overall and
cause-specific mortality can best be assessed by long-term prospective follow-up
of large numbers of people. The Prospective Studies Collaboration aimed to
investigate these associations by sharing data from many studies.
METHODS: Collaborative analyses were undertaken of baseline BMI versus mortality
in 57 prospective studies with 894 576 participants, mostly in western Europe and
North America (61% [n=541 452] male, mean recruitment age 46 [sD 11] years,
median recruitment year 1979 [iQR 1975-85], mean BMI 25 [sD 4] kg/m(2)). The
analyses were adjusted for age, sex, smoking status, and study. To limit reverse
causality, the first 5 years of follow-up were excluded, leaving 66 552 deaths of
known cause during a mean of 8 (SD 6) further years of follow-up (mean age at
death 67 [sD 10] years): 30 416 vascular; 2070 diabetic, renal or hepatic; 22 592
neoplastic; 3770 respiratory; 7704 other.
FINDINGS: In both sexes, mortality was lowest at about 22.5-25 kg/m(2). Above
this range, positive associations were recorded for several specific causes and
inverse associations for none, the absolute excess risks for higher BMI and
smoking were roughly additive, and each 5 kg/m(2) higher BMI was on average
associated with about 30% higher overall mortality (hazard ratio per 5 kg/m(2)

---

1.29 [95% CI 1.27-1.32]): 40% for vascular mortality (HR 1.41 [1.37-1.45]);
60-120% for diabetic, renal, and hepatic mortality (HRs 2.16 [1.89-2.46], 1.59
[1.27-1.99], and 1.82 [1.59-2.09], respectively); 10% for neoplastic mortality
(HR 1.10 [1.06-1.15]); and 20% for respiratory and for all other mortality (HRs
1.20 [1.07-1.34] and 1.20 [1.16-1.25], respectively). Below the range 22.5-25
kg/m(2), BMI was associated inversely with overall mortality, mainly because of
strong inverse associations with respiratory disease and lung cancer. These
inverse associations were much stronger for smokers than for non-smokers, despite
cigarette consumption per smoker varying little with BMI.
INTERPRETATION: Although other anthropometric measures (eg, waist circumference,
waist-to-hip ratio) could well add extra information to BMI, and BMI to them, BMI
is in itself a strong predictor of overall mortality both above and below the
apparent optimum of about 22.5-25 kg/m(2). The progressive excess mortality above
this range is due mainly to vascular disease and is probably largely causal. At
30-35 kg/m(2), median survival is reduced by 2-4 years; at 40-45 kg/m(2), it is
reduced by 8-10 years (which is comparable with the effects of smoking). The
definite excess mortality below 22.5 kg/m(2) is due mainly to smoking-related
diseases, and is not fully explained.

PMCID: PMC2662372
PMID: 19299006 Edited October 1, 2015 by Dean Pomerleau

[Dean Pomerleau]

All,

 

This new study [1] posted by Al Pater (thanks Al!) adds more to the evidence that being thin and even what the medical profession considers "underweight" does not necessarily mean an increase in mortality risk.

 

The researchers followed ~140K Korean men and women in the age range of 39-59 for 14 years, excluding the first 5 years of mortality data from their analysis to avoid reverse causality. Here is their main finding:

 

"Among never smokers, hazard ratios (HR) for underweight individuals [bMI < 18.5] were not significantly higher than those for normal-weight individuals (BMI=18·5-22·9 kg/m2): HR=0·87 (95 % CI 0·41, 1·84, P=0·72) for underweight men and HR=1·12 (95 % CI 0·76, 1·65, P=0·58) for underweight women."

 

Only in male current smokers did being underweight significantly increase mortality risk. Notice also that they used a lower than typical (in the US anyway) range for "normal" BMI of 18.5-22.9, rather than the usual 18.5-25.

 

On the other hand, the oldest subject by the end of the study would have been only 74, so this study says more about the benefits of being slim during middle age and early elderly years for avoiding early mortality, and doesn't say much about extending one's natural lifespan beyond the average of around 78-80.

 

--Dean

 

----

[1] weight and mortality.

Lee JY, Kim HC, Kim C, Park K, Ahn SV, Kang DR, Khaw KT, Willett WC, Suh I.

Public Health Nutr. 2015 Oct 15:1-6. [Epub ahead of print]

 

Abstract

 

OBJECTIVE:

 

According to most prospective studies, being underweight (BMI<18·5 kg/m2) is associated with significantly higher mortality than being of normal weight, especially among smokers. We aimed to explore in a generally lean population whether being underweight is significantly associated with increased all-cause mortality.

 

DESIGN:

 

Prospective cohort study.

 

SETTING:

 

Korea Medical Insurance Corporation study with 14 years of follow-up.

 

SUBJECTS:

 

After excluding deaths within the first 5 years of follow-up (1993-1997) to minimize reverse causation and excluding participants without information about smoking and health status, 94 133 men and 48 496 women aged 35-59 years in 1990 were included.

 

RESULTS:

 

We documented 5411 (5·7 %) deaths in men and 762 (1·6 %) in women. Among never smokers, hazard ratios (HR) for underweight individuals were not significantly higher than those for normal-weight individuals (BMI=18·5-22·9 kg/m2): HR=0·87 (95 % CI 0·41, 1·84, P=0·72) for underweight men and HR=1·12 (95 % CI 0·76, 1·65, P=0·58) for underweight women. Among ex-smokers, HR=0·86 (95 % CI 0·38, 1·93, P=0·72) for underweight men and HR=3·77 (95 % CI 0·42, 32·29, P=0·24) for underweight women. Among current smokers, HR=1·60 (95 % CI 1·28, 2·01, P<0·001) for underweight men and HR=2·07 (95 % CI 0·43, 9·94, P=0·36) for underweight women.

 

CONCLUSIONS:

 

The present study does not support that being underweight per se is associated with increased all-cause mortality in Korean men and women.

 

PMID: 26466868

[Dean Pomerleau]

As discussed above, this thread has focused mostly on the relationship between mid-life BMI and longevity. For a discussion of the optimal BMI in late-life for health and longevity, and in particularly the question of whether it is good to remain seriously CRed and rail thin into one's elder years, see this thread. 

 

--Dean

 

[nicholson]

Hi Dean:

 

Regarding your:

 

===========

 

As we've discussed in this thread, there are several confounders that are likely to make simply "being thin" very different from "practicing CR". Three of them with obvious health/longevity downsides are:

• Smokers are thinner than non-smokers
• People with latent chronic illnesses are thinner than healthy people
• Naturally thin people often eat crappy diets

===============

 

I think you might consider adding the following to your above list:
 

People who are 'effortlessly slim' (the "effortlessly" is important) must suffer from one of the following two phenomena:

 

A)  They have a 'poor appetite' which, it is intuitively obvious to me, is bad news of some sort.  Surely, thoroughly healthy people would be expected to have a 'very healthy appetite' would they not?  Or ......

 

B)  They have a very robust appetite, eat plenty, but are still slim.  Surely this must imply intestinal absorption problems?  And if they are not absorbing all the calories in transit, what other very important nutrients is their digestive tract also not absorbing?

 

I have observed previously that I have been quite struck by how many of my contemporaries who were unusually slim in their late teens and early 20s died before the rest of us.  And the same is true of the Wisconsin CR monkeys, so I am not imagining this.  

 

Rodney.

 

......... 

Edited January 16, 2016 by nicholson

[Dean Pomerleau]

Admin Note: I've moved a bunch of posts on the topic of cold exposure and other mild stressors for health and longevity from this thread to a new one focused on the topic. Please follow this link to continue with that discussion. --Dean

[Dean Pomerleau]

Huh - that's funny. I didn't remember that the Cold Exposure thread that has dominated so much of my thought and time for the last four months, started here (see previous post above).

 

Anyway, a new mega-meta-analysis of BMI vs. mortality [1] just appeared in the BMJ, along with an editorial [2] about it and another new study of weight trajectory over a lifetime [3].

 

The results are [3] are intuitive and easy to explain, so I'll start there. They asked participants in the Nurses and Physicians Health Studies about their BMI at different points earlier in their life - e.g. whether they were thin or fat as a child, young adult etc. Then they correlated the people's lifetime weight trajectory with risk of mortality between ages 60 and 75. They found that people who had been thin all their life did the best. The thing I found most surprising was in male never-smokers how modest was the benefit of being thin all one's life. The never-smoker men who were always fat and either stayed constantly fat or got even fatter as they got older were only 20% more likely to die during the followup than never-smoker men where were always thin throughout their life. This is a much smaller disadvantage than was seen in women, where being heavy all one's life (and staying steady or getting heavier) in never-smokers was a veritable kiss-of-death (i.e. 64% higher mortality rate) compared with always-thin, never-smoker women.

 

Now on to [1]. What makes [1] remarkable was it's massive size:

 

The analysis of all participants included 228 cohort studies (198 risk estimates) with 3,744,722 deaths among 30,233,329 participants. The analysis of never smokers included 53 cohort studies (44 risk estimates) with 738,144 deaths and 9,976,077 participants. 

 

The ~10 million never-smokers they looked at was the most interesting and relevant population for most of us. What they found was in line with discussions earlier in this thread - namely that among the general population, and in studies that followed subjects for a relatively short period of time, it paid to be heavier. As we've discussed, this is likely due to reverse causality and latent disease - i.e. people are thin because they are already sick and don't know it yet, and are therefore more likely to die during followup. 

 

The most interesting result is summarized in this graph from [1], which shows mortality as a function of BMI among healthy, never-smokers in which the study followup was more than 20 years - to effectively eliminate early mortality due to latent diseases:

 

 

As you can see, the minimum morality rate was seen between a BMI and 20 and 22. There is a tiny J-shape to the curve, with a very modest uptick in mortality among people with BMI lower than 20, but it's pretty flat. It would almost certainly be even flatter down at that end if you factored out people who were malnourished due to eating a crappy diet in small amounts, and therefore died earlier than they otherwise would have if they'd stayed thin while eating a healthy diet like folks around here do.

 

--Dean

 

--------------

[1] BMJ. 2016 May 4;353:i2156. doi: 10.1136/bmj.i2156.

 

BMI and all cause mortality: systematic review and non-linear dose-response

meta-analysis of 230 cohort studies with 3.74 million deaths among 30.3 million

participants.

 

Aune D(1), Sen A(2), Prasad M(3), Norat T(4), Janszky I(2), Tonstad S(3),

Romundstad P(2), Vatten LJ(2).

 

Free full text: http://www.bmj.com/content/353/bmj.i2156

 

OBJECTIVE:  To conduct a systematic review and meta-analysis of cohort studies of

body mass index (BMI) and the risk of all cause mortality, and to clarify the

shape and the nadir of the dose-response curve, and the influence on the results 

of confounding from smoking, weight loss associated with disease, and preclinical

disease.

DATA SOURCES:  PubMed and Embase databases searched up to 23 September 2015.

STUDY SELECTION:  Cohort studies that reported adjusted risk estimates for at

least three categories of BMI in relation to all cause mortality.

DATA SYNTHESIS:  Summary relative risks were calculated with random effects

models. Non-linear associations were explored with fractional polynomial models.

RESULTS:  230 cohort studies (207 publications) were included. The analysis of

never smokers included 53 cohort studies (44 risk estimates) with >738 144 deaths

and >9 976 077 participants. The analysis of all participants included 228 cohort

studies (198 risk estimates) with >3 744 722 deaths among 30 233 329

participants. The summary relative risk for a 5 unit increment in BMI was 1.18

(95% confidence interval 1.15 to 1.21; I(2)=95%, n=44) among never smokers, 1.21 

(1.18 to 1.25; I(2)=93%, n=25) among healthy never smokers, 1.27 (1.21 to 1.33;

I(2)=89%, n=11) among healthy never smokers with exclusion of early follow-up,

and 1.05 (1.04 to 1.07; I(2)=97%, n=198) among all participants. There was a J

shaped dose-response relation in never smokers (Pnon-linearity <0.001), and the

lowest risk was observed at BMI 23-24 in never smokers, 22-23 in healthy never

smokers, and 20-22 in studies of never smokers with ≥20 years' follow-up. In

contrast there was a U shaped association between BMI and mortality in analyses

with a greater potential for bias including all participants, current, former, or

ever smokers, and in studies with a short duration of follow-up (<5 years or <10 

years), or with moderate study quality scores.

CONCLUSION:  Overweight and obesity is associated with increased risk of all

cause mortality and the nadir of the curve was observed at BMI 23-24 among never 

smokers, 22-23 among healthy never smokers, and 20-22 with longer durations of

follow-up. The increased risk of mortality observed in underweight people could

at least partly be caused by residual confounding from prediagnostic disease.

Lack of exclusion of ever smokers, people with prevalent and preclinical disease,

and early follow-up could bias the results towards a more U shaped association.

 

PMID: 27146380

 

--------

[2] BMJ. 2016 May 4;353:i2433. doi: 10.1136/bmj.i2433.

 

Body mass index and mortality: understanding the patterns and paradoxes.

 

Wild SH(1), Byrne CD(2).

 

Free full text: http://www.bmj.com/content/353/bmj.i2433

 

PMID: 27146663

 

-----------

[3] BMJ. 2016 May 4;353:i2195. doi: 10.1136/bmj.i2195.

 

Trajectory of body shape in early and middle life and all cause and cause

specific mortality: results from two prospective US cohort studies.

 

Song M(1), Hu FB(2), Wu K(3), Must A(4), Chan AT(5), Willett WC(2), Giovannucci

EL(2).

 

Free full text: http://www.bmj.com/content/353/bmj.i2195

 

OBJECTIVE:  To assess body shape trajectories in early and middle life in

relation to risk of mortality.

DESIGN:  Prospective cohort study.

SETTING:  Nurses' Health Study and Health Professionals Follow-up Study.

POPULATION:  80 266 women and 36 622 men who recalled their body shape at ages 5,

10, 20, 30, and 40 years and provided body mass index at age 50, followed from

age 60 over a median of 15-16 years for death.

MAIN OUTCOME MEASURES:  All cause and cause specific mortality.

RESULTS:  Using a group based modeling approach, five distinct trajectories of

body shape from age 5 to 50 were identified: lean-stable, lean-moderate increase,

lean-marked increase, medium-stable/increase, and heavy-stable/increase. The

lean-stable group was used as the reference. Among never smokers, the

multivariable adjusted hazard ratio for death from any cause was 1.08 (95%

confidence interval 1.02 to 1.14) for women and 0.95 (0.88 to 1.03) for men in

the lean-moderate increase group, 1.43 (1.33 to 1.54) for women and 1.11 (1.02 to

1.20) for men in the lean-marked increase group, 1.04 (0.97 to 1.12) for women

and 1.01 (0.94 to 1.09) for men in the medium-stable/increase group, and 1.64

(1.49 to 1.81) for women and 1.19 (1.08 to 1.32) for men in the

heavy-stable/increase group. For cause specific mortality, participants in the

heavy-stable/increase group had the highest risk, with a hazard ratio among never

smokers of 2.30 (1.88 to 2.81) in women and 1.45 (1.23 to 1.72) in men for

cardiovascular disease, 1.37 (1.14 to 1.65) in women and 1.07 (0.89 to 1.30) in

men for cancer, and 1.59 (1.38 to 1.82) in women and 1.10 (0.95 to 1.29) in men

for other causes. The trajectory-mortality association was generally weaker among

ever smokers than among never smokers (for all cause mortality: P for interaction

<0.001 in women and 0.06 in men). When participants were classified jointly

according to trajectories and history of type 2 diabetes, the increased risk of

death associated with heavier body shape trajectories was more pronounced among

participants with type 2 diabetes than those without diabetes, and those in the

heavy-stable/increase trajectory and with a history of diabetes had the highest

risk of death.

CONCLUSIONS:  Using the trajectory approach, we found that heavy body shape from 

age 5 up to 50, especially the increase in middle life, was associated with

higher mortality. In contrast, people who maintained a stably lean body shape had

the lowest mortality. These results indicate the importance of weight management 

across the lifespan.

 

PMID: 27146280 

[TomBAvoider]

Not everyone is on the same page, still. Disparate results are being reported, still. A sweet spot of BMI of 27 is still being hailed. Most intriguingly, it appears that deaths for obese people fell dramatically over the last few decades - in other words, we have the longest lived overweight/obese people ever; perhaps a testimony to how well modern medicine can treat diseases of obesity, compared to decades past. New study published 05/10/2016:

 

http://jama.jamanetwork.com/article.aspx?articleid=2520627

 

Original Investigation | May 10, 2016

Change in Body Mass Index Associated With Lowest Mortality in Denmark, 1976-2013

Shoaib Afzal, MD, PhD1,2,3,4; Anne Tybjærg-Hansen, MD, DMSc1,2,3,4,5; Gorm B. Jensen, MD, DMSc5; Børge G. Nordestgaard, MD, DMSc1,2,3,5

 

JAMA. 2016;315(18):1989-1996. doi:10.1001/jama.2016.4666.

 

ABSTRACT

 

Importance  

 

Research has shown a U-shaped pattern in the association of body mass index (BMI) with mortality. Although average BMI has increased over time in most countries, the prevalence of cardiovascular risk factors may also be decreasing among obese individuals over time. Thus, the BMI associated with lowest all-cause mortality may have changed.

 

Objective  

 

To determine whether the BMI value that is associated with the lowest all-cause mortality has increased in the general population over a period of 3 decades.

 

Design, Setting, and Participants  

 

Three cohorts from the same general population enrolled at different times: the Copenhagen City Heart Study in 1976-1978 (n = 13 704) and 1991-1994 (n = 9482) and the Copenhagen General Population Study in 2003-2013 (n = 97 362). All participants were followed up from inclusion in the studies to November 2014, emigration, or death, whichever came first.

 

Exposures  

 

For observational studies, BMI was modeled using splines and in categories defined by the World Health Organization. Body mass index was calculated as weight in kilograms divided by height in meters squared.

 

Main Outcomes and Measures  

 

Main outcome was all-cause mortality and secondary outcomes were cause-specific mortality.

 

Results  

 

The number of deaths during follow-up was 10 624 in the 1976-1978 cohort (78% cumulative mortality; mortality rate [MR], 30/1000 person-years [95% CI, 20-46]), 5025 in the 1991-1994 cohort (53%; MR, 16/1000 person-years [95% CI, 9-30]), and 5580 in the 2003-2013 cohort (6%; MR, 4/1000 person-years [95% CI, 1-10]). Except for cancer mortality, the association of BMI with all-cause, cardiovascular, and other mortality was curvilinear (U-shaped). The BMI value that was associated with the lowest all-cause mortality was 23.7 (95% CI, 23.4-24.3) in the 1976-1978 cohort, 24.6 (95% CI, 24.0-26.3) in the 1991-1994 cohort, and 27.0 (95% CI, 26.5-27.6) in the 2003-2013 cohort. The corresponding BMI estimates for cardiovascular mortality were 23.2 (95% CI, 22.6-23.7), 24.0 (95% CI, 23.4-25.0), and 26.4 (95% CI, 24.1-27.4), respectively, and for other mortality, 24.1 (95% CI, 23.5-25.9), 26.8 (95% CI, 26.1-27.9), and 27.8 (95% CI, 27.1-29.6), respectively. The multivariable-adjusted hazard ratios for all-cause mortality for BMI of 30 or more vs BMI of 18.5 to 24.9 were 1.31 (95% CI, 1.23-1.39; MR, 46/1000 person-years [95% CI, 32-66] vs 28/1000 person-years [95% CI, 18-45]) in the 1976-1978 cohort, 1.13 (95% CI, 1.04-1.22; MR, 28/1000 person-years [95% CI, 17-47] vs 15/1000 person-years [95% CI, 7-31]) in the 1991-1994 cohort, and 0.99 (95% CI, 0.92-1.07; MR, 5/1000 person-years [95% CI, 2-12] vs 4/1000 person-years [95% CI, 1-11]) in the 2003-2013 cohort.

 

Conclusions and Relevance  

 

Among 3 Danish cohorts, the BMI associated with the lowest all-cause mortality increased by 3.3 from cohorts enrolled from 1976-1978 through 2003-2013. Further investigation is needed to understand the reason for this change and its implications.

 

There are also pop writeups:

 

http://health.usnews.com/health-care/articles/2016-05-10/obesity-may-i-not-i-take-years-off-your-life-study

 

http://www.npr.org/sections/health-shots/2016/05/10/477376914/does-putting-on-a-few-pounds-help-you-cheat-death

 

"So being fatter, at least a bit, may be healthier.

"I was surprised as a scientist to see how clear the result was," Borge Nordestgaard, a clinical professor and chief physician at Copenhagen University Hospital and senior author of the study, told Shots.

So he and his colleagues sliced and diced the data to see what could account for the shift. They looked at age, sex, smoking, cancer and heart disease. The most relevant was the decline in smoking since the 1970s. But when they looked at the mortality rates in nonsmokers who had never had cancer or heart disease, it also became associated with a higher BMI over time."

 

 

[Dean Pomerleau]

Tom,

 

Thanks for posting this new study of BMI and mortality [1]. One request - when you post a new study please go to Pubmed and do a search on the title to include the study's pubmed number, so people in the future can easily search to see if this study has ever been mentioned in any of our discussions.

 

Having read the full text (although not the supplemental material, which is behind a paywall I can't seem to get past with sci-hub.cc. If anyone can send that to me I'd appreciate it - as the authors seem to have buried an awful lot of interesting stuff in there), I can say it is an interesting paper. But I think it is another case of the media misinterpreting or being misled, and perhaps even the researchers not thinking clearly about the explanation for their own results. I was disappointed how thin was the discussion section in general, and how shallow was the section in the discussion about limitations of the study. Below I'll attempt to give several potential explanations for the counterintuitive results, which I'll summarize first.

 

What they found was that from an all-cause mortality perspective (as well as the other major causes, including CVD) it was better to be very thin (BMI ~18!) back in the late 1970s and 1980s, but these days you're least likely to die if you're much chubbier, with a BMI around 26! How's that for a headline grabber!? In the old days it was good to be thin, but now you're better off chubby!

 

From the full text:

 

 

Analyses restricted to never-smokers without a history of cardiovascular

disease or cancer showed different patterns in the

3 time periods, from an almost linearly increasing risk of all-cause

mortality with increasing BMI in the 1976-1978 cohort

to a U-shaped pattern in the 2003-2013 cohort (BMI associated

with the lowest mortality, 26.1)... The BMI associated with

the lowest mortality in the 1976-1978 cohort was the lowest

BMI value on the plot, that is, approximately 18, as the

association was linear...

Now that's indeed a striking result. If you were part of a group from the late 70s, you were least likely to die during followup if you were rail-thin, with a BMI around 18. But the group followed more recently (starting between 2003 and 2013),you were least likely to die during followup if you were overweight, with a BMI ~26.

 

What could explain such a large shift in the most longevous weight / BMI over such relatively short period of time, particularly in light of the fact that so many other studies and meta-analyses (discussed above) have shown the optimal BMI to be much lower than 26?

 

There are a couple plausible, yet rather mundane, potential explanations that the authors considered and that may have contributed, but I think the most logical explanation relies on implications from the "damage" model of aging, so I think Michael (and Aubrey) will be pleased, both from the data which vindicates them, and (hopefully) from my explanation for it.

 

First, the mundane possible answers:

• Better medicine - improved diagnosis, prevention and treatment for diseases of aging

For all the criticism we heap on the medical establishment's focus on treating symptoms rather than preventing the diseases of aging, things really have come quite a ways since the late 70s. I'm not saying I'm advocating these as a first line of defense, but widespread use of statins, stents etc for CVD, and drugs like metformin to slow the progression of diabetes really have helped people with diseases of aging live longer, and in some instances, healthier lives, despite their bad habits including overweight / obesity and a poor diet. Since the main preventable health problems are conditions associated with being overweight/obese, that's where the focus (and money) has gone, and that's where improvements have been made. So to some extent, chubby people may have benefitted disproportionately from medical advances, allowing them to remain (relatively) healthy despite the disadvantage their extra weight would otherwise pose. The authors speak to this possibility:

A potential explanation for the secular trend [i.e. fatter people

having lower relative mortality today than in yesteryear - DP]

may be that while improved treatment for cardiovascular

risk factors or complicating diseases has reduced mortality

in all weight classes, the effects may have been greater

at higher BMI levels than at lower BMI levels.[ref] Because obesity

is a causal risk factor for hypertension, diabetes, cardiovascular

disease, and dyslipidemia [ref] obese individuals may

have had a higher selective decrease in mortality,...

possibly suggesting a period effect related to changes in

clinical practice, such as improved treatments...

I'm not sure why the authors don't mention this, but this explanation may be particularly relevant for Denmark (where the study took place), which has been making steady improvements in their healthcare system since the 1970s [2]. Unlike the US, people in Denmark now seem to think their healthcare system has improved in the last several decades and is now working pretty well [3]!

• Healthier Lifestyles - More exercise, less smoking, better diet

Perhaps despite getting fatter, people are also exercising more, smoking less (which naturally leads to weight gain), and perhaps even eating a better diet these days relative to the 70s and 80s. The first two were clearly the case in this study. Relative to the 1976-78 cohort, subjects in the 2003-2013 cohort exercised twice as much, were over three times less likely to smoke, and had lower cholesterol despite a higher BMI - probably resulting from a combination of diet and statins. Again these improvements might preferentially benefit those with a higher BMI more than slim folks. The authors acknowledge this possible explanation as well:

[C]ohorts recruited at later periods have an increase in the BMI associated

with the lowest mortality, possibly suggesting ... improved... general public

health status, such as decreased smoking or increased physical activity.

• Latent Illnesses - Thin and more likely to die - especially as a result of smoking

​ Now we come to a possible explanation that we've been talking about quite a bit in this thread - latent / nascent diseases resulting in subjects being thin at time of enrollment in the study and dying relatively soon. The 2003-2013 cohort were followed for an average of only 4.5 years, while the 1976-78 cohort had an average followup of 20 years. As we've seen in previous studies discussed in this thread, it seems to take far longer than 4.5 years, in fact sometimes up to 2 decades, for the apparent disadvantage of being thin at the start of the study to be overcome. The authors acknowledge this possibility, but suggest that it wasn't much of a factor, largely based on data underlying this graph:

What it shows is that for the 1976-78 cohort, the optimal BMI for all participants (including the 64% who were smokers at the start of the study...) remained relatively flat, and (they claim) the same was true of the few years the 2003-2013 cohort has been followed. But if you ask me it looks like the later/latter cohort is definitely trending downward (i.e. lower BMI getting better with time), although admittedly the effect is relatively modest.

They really should have thrown out all the ever-smokers from the entire analysis. The fact that the smoking rate dropped from nearly 2/3rds in the 1976-78 time frame to less than 1/5th in the 2003-2013 not only makes comparison between the cohorts very difficult, it also indicates a hugely important societal trend that will impact both weight and mortality within a cohort as well.

In short, this hypothesis says the Danes have shifted from dying early (and being thin) as a result of a high rate of smoking in the 70s and 80s, to being fat non-smokers today. In the first few years of followup (i.e. in the 2003-2013 cohort), this provides a lifespan benefit - smoking is really bad for you, so being a fat non-smoker is advantageous from a mortality perspective, especially in the short term, since obesity-related morbidity/mortality takes many years to develop. But as you can see from the graph above, as followup time in the 2003-2013 cohort increases, there is a definite downward trend in the optimal BMI, as the deleterious effects of being overweight/obese start to rear their ugly head.

So do the effects of smoking, latent diseases and the slow progression of obesity-related health problems explain all of the so-called "obesity paradox" - why there is surprisingly little penalty for being chubby, especially in the early years of a study?

 

I'm beginning to think not, and I'm surprised I haven't seem more people talk about the following idea - especially Michael, Aubrey and Co, since it relates to their "damage" model of how aging works - as we've discussed in this thread.

 

Here is the idea in a nutshell:

 

First of all, notice that there are two (competing) factors in play when it comes to mortality:

• How likely you are to be struck with an illness or disease.
• How likely you are to die once you are struck with an illness or disease.

My contention is that thin folks (especially thin folks in the general population who don't take care of themselves particularly well) are at a strong disadvantage when it comes to #2 - i.e. thin folks are more "fragile" (i.e. likely to succumb to any particular illness or disease) than stockier folks, who are more robust. Early in a longitudinal study, when the deleterious effects of being fat haven't had time yet to wreak havoc on the fat participants' health, it is relatively rare for anyone in the cohort to get seriously ill, to the point of (near) death. This can be seen in the mortality statistics of [1], in which a whopping 78% of folks in the 1976-78 cohort had died by the end of the study, while only 6% of the 2003-2013 cohort had died. In the few who do happen to get seriously ill in the early years of followup, it is the thin ones who are more fragile and therefore more likely to die.

 

In other words, the thin folks start out with a survival disadvantage relative to the fatties, independent of any latent/nascent disease or increased cancer or CVD due to smoking. As we've seen in the CR & Immunity thread, there is evidence that even a nutritionally adequate CR diet can compromise rodent immune systems relative to AL feeding, so that once they get sick, the thin CR rodents are more likely to die. This fragility disadvantage of being skinny could be expected to be even more significant in humans eating a standard, crappy western diet...

 

So due to their fragility, skinny folks start out at a mortality disadvantage early in a study when few participants get seriously ill. They must therefore subsequently claw their way out of that hole over time. How do they do that? By beating out the fatties in #1 above - i.e. the likelihood of being struck by an illness or disease. In short, according to Michael et al's theory of aging, thin folks are accumulating less damage (from systemic inflammation, etc.) than the fatties with each passing year. Over time, the fatties risk of getting struck by a serious illness/disease climbs to the point where their robustness advantage (which itself will fall over time as they abuse their bodies...) won't be enough to compensate, and they'll start dying at a higher rate than the fragile thin folks, who won't get sick as frequently.

 

In other words, by 15 or 20 years into a longitudinal study, the disadvantage the thin folks had at the beginning (due to fragility) will have turned into a survival advantage since they'll have accumulated less life-shortening damage through the years.

 

Here is an analogy, to drive the point home.

 

Imagine there are two types of glassware in a lab, flasks (left) and test tubes (right):

 

 

As you may have guessed, the flasks represent the chubby folks and the test tubes represent the thin folks in this analogy.

 

Lab technicians carry both types of glassware around the lab using a test tube clamp, like the one below - which are spring loaded so as to apply constant pressure, regardless of what they are carrying:

 

At the start, because the flasks are bigger, they weigh more and are (statistically) a bit more likely to be dropped by these constant-tension clamps than the lighter test tubes. But the clamps are pretty strong, and the flange at the top of both types of glassware make it rare that either get dropped. And when they do, the larger surface area at the bottom of the flasks make them less likely to break (more robust) than the fragile test tubes. So at the beginning, drops are rare, and when they happen it's the fragile test tubes that are more likely to break (i.e. die).

 

But over time, something interesting happens. Because of the bulging shape, it's harder to clean the insides of the flasks relative to the test tubes. As a result "gunk" starts to build up on the bottom and especially along the sloping sides of the flasks, while the tests tubes inner walls remain squeaky clean (see where I'm going with this? ☺). As a result, the flasks gain mass (accumulate damage). After a while, the constant pressure of the clamp isn't enough to securely grip the fattening flasks. As a result, flasks started getting dropped (become ill) more frequently than test tubes. And that added mass from the built-up gunk inside them increases the force with which they hit the floor, so they are no longer more robust than the test tubes. Instead the flasks become just as likely, or eventually even more likely, to break when they hit the floor (die when they get sick).

 

In short, the flasks will have a survival advantage relative to the test tubes early in the experiment, but will eventually start to break (die) more frequently as gunk builds up inside them and so they get more frequently dropped (fall prey to illness or disease).

 

This sort of interplay between fragility and damage accumulation seems like a more plausible explanation (than latent disease or smoking-related early mortality) for why thin folks start out at a mortality disadvantage, and why it takes so long for thin folks to gain a survival advantage in longitudinal studies of BMI vs. mortality.

 

Michael, if you are out there, I'd love to hear your thoughts on this idea. I'm sure I'm not the first to think of it.

 

--Dean

 

Update: Sigh..., even a quality publication like Scientific American doesn't seem to get it...

 

-----------

[1] JAMA. 2016 May 10;315(18):1989-1996. doi: 10.1001/jama.2016.4666.

Change in Body Mass Index Associated With Lowest Mortality in Denmark, 1976-2013.

 

Afzal S(1), Tybjærg-Hansen A(1), Jensen GB(2), Nordestgaard BG(1).

 

Full text: http://sci-hub.cc/10.1001/jama.2016.4666

 

Importance: Research has shown a U-shaped pattern in the association of body mass

index (BMI) with mortality. Although average BMI has increased over time in most

countries, the prevalence of cardiovascular risk factors may also be decreasing

among obese individuals over time. Thus, the BMI associated with lowest all-cause

mortality may have changed.

Objective: To determine whether the BMI value that is associated with the lowest

all-cause mortality has increased in the general population over a period of 3

decades.

Design, Setting, and Participants: Three cohorts from the same general population

enrolled at different times: the Copenhagen City Heart Study in 1976-1978

(n = 13 704) and 1991-1994 (n = 9482) and the Copenhagen General Population Study

in 2003-2013 (n = 97 362). All participants were followed up from inclusion in

the studies to November 2014, emigration, or death, whichever came first.

Exposures: For observational studies, BMI was modeled using splines and in

categories defined by the World Health Organization. Body mass index was

calculated as weight in kilograms divided by height in meters squared.

Main Outcomes and Measures: Main outcome was all-cause mortality and secondary

outcomes were cause-specific mortality.

Results: The number of deaths during follow-up was 10 624 in the 1976-1978 cohort

(78% cumulative mortality; mortality rate [MR], 30/1000 person-years [95% CI,

20-46]), 5025 in the 1991-1994 cohort (53%; MR, 16/1000 person-years [95% CI,

9-30]), and 5580 in the 2003-2013 cohort (6%; MR, 4/1000 person-years [95% CI,

1-10]). Except for cancer mortality, the association of BMI with all-cause,

cardiovascular, and other mortality was curvilinear (U-shaped). The BMI value

that was associated with the lowest all-cause mortality was 23.7 (95% CI,

23.4-24.3) in the 1976-1978 cohort, 24.6 (95% CI, 24.0-26.3) in the 1991-1994

cohort, and 27.0 (95% CI, 26.5-27.6) in the 2003-2013 cohort. The corresponding

BMI estimates for cardiovascular mortality were 23.2 (95% CI, 22.6-23.7), 24.0

(95% CI, 23.4-25.0), and 26.4 (95% CI, 24.1-27.4), respectively, and for other

mortality, 24.1 (95% CI, 23.5-25.9), 26.8 (95% CI, 26.1-27.9), and 27.8 (95% CI,

27.1-29.6), respectively. The multivariable-adjusted hazard ratios for all-cause

mortality for BMI of 30 or more vs BMI of 18.5 to 24.9 were 1.31 (95% CI,

1.23-1.39; MR, 46/1000 person-years [95% CI, 32-66] vs 28/1000 person-years [95%

CI, 18-45]) in the 1976-1978 cohort, 1.13 (95% CI, 1.04-1.22; MR, 28/1000

person-years [95% CI, 17-47] vs 15/1000 person-years [95% CI, 7-31]) in the

1991-1994 cohort, and 0.99 (95% CI, 0.92-1.07; MR, 5/1000 person-years [95% CI,

2-12] vs 4/1000 person-years [95% CI, 1-11]) in the 2003-2013 cohort.

Conclusions and Relevance: Among 3 Danish cohorts, the BMI associated with the

lowest all-cause mortality increased by 3.3 from cohorts enrolled from 1976-1978

through 2003-2013. Further investigation is needed to understand the reason for

this change and its implications.

 

PMID: 27163987

 

--------------

[2] Health Econ. 2005 Sep;14(Suppl 1):S41-57.

 

The Danish health care system: evolution--not revolution--in a decentralized

system.

 

Pedersen KM(1), Christiansen T, Bech M.

 

Author information:

(1)Institute of Public Health, Health Economics, University of Southern Denmark,

Denmark. kmp@sam.sdu.dk

 

The Danish health care system has undergone gradual changes, but not radical

reforms, from 1970 until 2004. Theoretically, the development can be viewed from

the perspective of fiscal federalism, decentralization, and incentives embodied

in reimbursement systems. Furthermore, path dependence and incrementalism have

characterized the system. The Danish health care system is decentralized

politically, financially, and operationally. The counties are responsible for

health care, and finance it out of county income and property taxes along with

block grants from the state. Hospitals are publicly owned while general

practitioners are private entrepreneurs working on contract with the counties.

Hospital services and GP and specialist services are free, while there are

co-payments for drugs, adult dental care, physiotherapy and the like. Co-payments

make up close to 19% of total health expenditures. The system has been

characterized by expenditure control, reasonable positive development in

productivity, and a high degree of patient and citizen satisfaction despite

waiting lists. Free choice of hospital was introduced more than 10 years ago. It

has recently been expanded so that after waiting 2 months for treatments like

elective surgery at public hospitals, citizens can choose either private

hospitals or go abroad with full payment from public funds. The thinking behind

decentralization gradually has been eroded for a number of reasons. This has led

to a reform that will be effective as of January 2007. The number of counties

will be reduced, but the new regions retain responsibility for health care. A

national earmarked health tax will be introduced so that the regions will receive

revenues from state block grants and municipal co-payment, for instance an amount

per hospitalization.

 

Copyright © 2005 John Wiley & Sons, Ltd.

 

PMID: 16170792

 

---------

[3] http://fall09hpm101denmark.providence.wikispaces.net/History+and+Satisfaction+of+Denmark%27s+Health+Care

[Dean Pomerleau]

All,

 

Mike Lustgarten and I had a long discussion about this paper, and the idea of "one size does (Mike) or doesn't (me) fit all" when it comes to biomarkers like BMI, WBC etc.

 

For anyone with a Facebook account, here is the permalink to our discussion, which I think was very respectful (as online chat session go...) and informative.

 

--Dean

[Dean Pomerleau]

Al Pater filled my request for the supplemental material for this latest BMI and mortality study (PMID 27163987) - thanks Al!

 

I'm glad he did. It contains a really compelling graph of the relationship between BMI and all-cause mortality for healthy never-smokers from the 1976-78 cohort:

 

 

 

Look at how linear that graph is, and how mortality risk appears to still be trending downward below a BMI of 18. Read that and weep fat apologists!

 

--Dean

[Gordo]

That is a refreshing different perspective from most studies.  How many 18 BMI subjects from 1976-1978 were included in the study?  I'd be curious to know how/why they were so thin.  What comes to mind is the "constitutionally lean" discussed over in the cold exposure thread.  Just wondering if perhaps BAT is involved more so than "CR Practice" per se...

 

... really compelling graph of the relationship between BMI and all-cause mortality for healthy never-smokers from the 1976-78 cohort:

 

Look at how linear that graph is, and how mortality risk appears to still be trending downward below a BMI of 18. Read that and weep fat apologists!

 

--Dean

[Dean Pomerleau]

Gordo,

 

How many 18 BMI subjects from 1976-1978 were included in the study?

 

There were 296 participants in the 76-78 cohort that had a BMI of less than 18.5. This represents only about 4% of the 7044 total participants in that cohort. 

 

--Dean

[Michael R]

Another Reminder that BMI is a Shitty Measure of Anthropometry
Another problem with the BMI epidemiology is that it poorly captures the actual anthropometry of individuals: is this BMI 23 person lean and fit, or is s/he loaded with visceral fat related to South Asian heritage? Is this BMI 27.5 person bearing fat inside and out, or is he Lebron James?

This study is one of several to instead look at measures of (or more directly linked to) body fat than simple body weight, and one of the few that does so while also having genuinely long-term followup (eliminating the problem of the long period of weight loss preceding death from diseases of aging) and looking at true never-smokers (rather than ex-). Lo and behold, less and less fat is good, all the way down:

Quote

The aim of our study was to examine the associations of body composition (assessed by five different measures) with incident CVD outcomes in healthy individuals.

A total of 296 535 participants (57.8% women) of white European descent without CVD at baseline from the UK biobank were included. [This is a bonus: the UK Biobank has the lifelong health records of volunteers via their National Health Service, rather than relying on self-report or limited insurance data in people who may have switched insurers -MR]. ...

Low BMI (≤18.5 kg m⁻²) was associated with higher incidence of CVD and the lowest CVD risk was exhibited at BMI of 22–23 kg m⁻² beyond which the risk of CVD increased. This J-shaped association attenuated substantially in subgroup analyses, when we excluded participants with comorbidities. In contrast, the associations for the remaining adiposity measures were more linear; 1 SD increase in waist circumference was associated with a hazard ratio of 1.16 [95% confidence interval (CI) 1.13–1.19] for women and 1.10 (95% CI 1.08–1.13) for men with similar magnitude of associations for 1 SD increase in waist-to-hip ratio, waist-to-height ratio, and percentage body fat mass.

Conclusion

Increasing adiposity has a detrimental association with CVD health in middle-aged men and women. The association of BMI with CVD appears more susceptible to confounding due to pre-existing comorbidities when compared with other adiposity measures. Any public misconception of a potential ‘protective’ effect of fat on CVD risk should be challenged.

... and here are the data for men for BMI in lifelong nonsmokers and in people without pre-existing comorbidities:

 

References
1: Iliodromiti S, Celis-Morales CA, Lyall DM, Anderson J, Gray SR, Mackay DF, Nelson SM, Welsh P, Pell JP, Gill JMR, Sattar N. The impact of confounding on the associations of different adiposity measures with the incidence of cardiovascular disease: a cohort study of 296 535 adults of white European descent. Eur Heart J. 2018 May 1;39(17):1514-1520. doi: 10.1093/eurheartj/ehy057. PubMed PMID: 29718151; PubMed Central PMCID: PMC5930252.

https://academic.oup.com/eurheartj/article/39/17/1514/4937957

[mccoy]

What surprises me in the above study is that the popular wisdom that too little fat in women is deleterious seems to be contradicted. Even extremely low fat quantities like 5% display a lesser CVD HR.

These are not physiological amounts though, so I wonder about the sample. Undernourished, anorexic individuals? Female bodybuilders on contest day?

 

Edited October 22, 2018 by mccoy

[kpfleger]

Great find Michael---thanks for sharing.

All cause mortality would be nice instead of just CVD. Is there a price in terms of increased diabetes or dementia, or increased death from infectious diseases?

[Dean Pomerleau]

Reviving this classic thread to post a new video by Dr. Greger on the optimal BMI. He says that the weight of evidence suggests a BMI of 20-21 is ideal for health and longevity. He shows this graph illustrating how risk of diabetes goes up pretty linearly starting at a BMI of 21 or less:

The source of the graph above is this Luigi Fontana paper [1]. Here is the full figure from Luigi's paper showing how risk of various diseases goes up in both women (top row) and men (bottom row) with both increasing BMI (left column) and weight gain during adulthood (right column):

Here is Dr. Greger's video:

--Dean

[mccoy]

I remain a little skeptical, a RR = 2 of T2D for a BMI of 22 in women...  But right now I have no time to read the paper.

Edited January 6, 2021 by mccoy

[mccoy]

This graph is originally from Willet et al., 1999, Fontana just cites it. The abstract is very concise, almost useless. The full article is not available. We have no guarantees that the article followed the methods outlined by Fontana himself to avoid reverse causation and other spurious correlations. It is probably a prospective cohort study, prone to various biases and errors. We have no description about the control population. Unfortunately, the graph by itself does not say much, other that, according to data we don't know and of which there is no public access, very thin women of unknown habits and health conditions have been taken as a reference (control population). Taking as control population a subgroup with such uncommon characteristics rises some doubts as to the purpose of the study. It says that very skinny women have much less T2D than normoweight women. But what's the prevalence of T2D in that very skinny subgroup? I imagine very, very, low. So the 2-3fold increase in more normal women would not be significant at all in absolute terms, maybe within the range of statistical error. I greatly respect Fontana as a researcher, but of course he wants to prove something in his article, and whatever information helps him to prove that, is useful to the purpose. Maybe it's useless in daily life?

Guidelines for Healthy Weight

List of authors.

• Walter C. Willett, M.D., Dr.P.H., 
• William H. Dietz, M.D., Ph.D., 
• and Graham A. Colditz, M.D., Dr.P.H.

 

• Article
• Figures/Media

Excess body fat is a cause of cardiovascular diseases, several important cancers, and numerous other medical conditions¹ and is a growing problem in many countries. In the United States, for example, the age-adjusted prevalence of obesity increased by approximately 30 percent from 1980 to 1994.² In this review we consider the assessment of body fat and the definition of a healthy body weight for an adult. We also discuss how clinicians can use this information in caring for patients. Because overt obesity has undisputed adverse consequences for health, our focus is on lesser degrees of adiposity, the consequences of which . . .

Edited January 8, 2021 by mccoy

[Dean Pomerleau]

Mccoy,

You give up too easily. Both the paper you reference (i.e. the one referenced by Fontana) and the one before that in the chain [1] (i.e. the real original paper where the data comes from) is available via sci-hub. 

It found that mortality increased with BMI, particularly among younger age groups. Here is the most interesting graph from the paper:

Note the error bars are pretty large relative to the effect size (particularly for men who were much fewer in number in the study) and the effects aren't very large until you get somewhere in the range of BMI 26-29. Also this paper focused on all-cause mortality and CVD mortality - it doesn't break out the diabetes risk, which must have been done as part of subsequent sub-analysis (or perhaps in the supplemental material). Deaths within only the first year were excluded (as was anyone with a history of smoking) and the list confounders adjusted for seem rather limited.

--Dean

--------------

[1] 

1. N Engl J Med. 1998 Jan 1;338(1):1-7. doi: 10.1056/NEJM199801013380101.

The effect of age on the association between body-mass index and mortality.

Stevens J(1), Cai J, Pamuk ER, Williamson DF, Thun MJ, Wood JL.

Author information:
(1)Department of Nutrition, School of Public Health, University of North 
Carolina, Chapel Hill 27599-7400, USA.

Comment in
    N Engl J Med. 1998 Jan 1;338(1):52-4.
    N Engl J Med. 1998 Apr 16;338(16):1156; author reply 1158.
    N Engl J Med. 1998 Apr 16;338(16):1158.
    N Engl J Med. 1998 Apr 16;338(16):1158-9; author reply 1159.
    N Engl J Med. 1998 Apr 16;338(16):1159.
    N Engl J Med. 1998 Apr 16;338(16):1159.
    N Engl J Med. 1999 Oct 7;341(15):1140-1.

BACKGROUND: The effect of age on optimal body weight is controversial, and few 
studies have had adequate numbers of subjects to analyze mortality as a function 
of body-mass index across age groups.
METHODS: We studied mortality over 12 years among white men and women who 
participated in the American Cancer Society's Cancer Prevention Study I (from 
1960 through 1972). The 62,116 men and 262,019 women included in this analysis 
had never smoked cigarettes, had no history of heart disease, stroke, or cancer 
(other than skin cancer) at base line in 1959-1960, and had no history of recent 
unintentional weight loss. The date and cause of death for subjects who died 
were determined from death certificates. The associations between body-mass 
index (defined as the weight in kilograms divided by the square of the height in 
meters) and mortality were examined for six age groups in analyses in which we 
adjusted for age, educational level, physical activity, and alcohol consumption.
RESULTS: Greater body-mass index was associated with higher mortality from all 
causes and from cardiovascular disease in men and women up to 75 years of age. 
However, the relative risk associated with greater body-mass index declined with 
age. For example, for mortality from cardiovascular disease, the relative risk 
associated with an increment of 1 in the body-mass index was 1.10 (95 percent 
confidence interval, 1.04 to 1.16) for 30-to-44-year-old men and 1.03 (95 
percent confidence interval, 1.02 to 1.05) for 65-to-74-year-old men. For women, 
the corresponding relative risk estimates were 1.08 (95 percent confidence 
interval, 1.05 to 1.11) and 1.02 (95 percent confidence interval, 1.02 to 1.03).
CONCLUSIONS: Excess body weight increases the risk of death from any cause and 
from cardiovascular disease in adults between 30 and 74 years of age. The 
relative risk associated with greater body weight is higher among younger 
subjects.

DOI: 10.1056/NEJM199801013380101
PMID: 9414324 [Indexed for MEDLINE]

[mccoy]

Dean, it's true that I have no more much patience, one effect of aging perhaps. On the other side, here in Europe it's becoming increasingly difficult to find open sci-hub sites. Also, when I answered I had really no time for a detailed research.

Anyway, I can find no logical objections in the plots you posted. They are referred to all-cause mortality, they carry error bars and they do not display outlying values, so the explanation is straightforward, as you say. My reading of the plots is that there is a significant, but not a very substantial increase of all-cause mortality, and that depends on age classes. From BMI 27-32 in younger people, from BMI 27-29 up to 74 years, then there really appears not to be a definitely increased mortality for higher BMIs. Such a conclusion is logically more satisfactory. There is usually a trend of increased all-cause mortality with increasing BMI, but it has often large error bars and the RR becomes substantial at higher BMIs. One possible objection is that the control group, especially in women, is thin, it does not appear to exhibit normal or ideal weight, and this ideal or normal weight attributed to the control group should be logically explained anyhow.

My previous objection was with the data on T2D, where  that steep uptrending line in women constitutes an absolute anomaly which must be explained in detail, eventually confirmed or denied, and surely offering some comments about it, explaining above all why very thin women have been chosen as a control group.

 

[Ron Put]

Overall mortality, especially among hospital patients, may give undue emphasis on the known benefits of heft in cases of serious infections. In other words, an obese person may die earlier than a fit, thin person in general, but may fight off a severe infection better.

This would be especially true in older populations, whose immune systems, including T-cell activation, are generally weakened.

'The Obesity Paradox:' When Obese Patients Fare Better Than Healthy Ones

Researchers gave several possible explanations for this obesity paradox. First, the fat mobilized from excess fatty tissue during critical illness provides energy more efficiently than nutrients given to patients, thus preventing lean tissue wasting. Second, similar to what defends the body from infectious diseases in the first study, low-grade inflammation provides a protective response. Lastly is what researchers call "a paradox within a paradox." Obese people have higher muscle-quality corrected for muscle thickness.

"Obesity and overweight are associated with an increased risk of death in the general population, but in specific disease conditions, a decrease in mortality has been reported," the study states. "The 'obesity paradox' of critical illness refers to better survival with a higher body mass index."