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  1. All, We've talked quite a bit around here lately about the optimal BMI for longevity, most notably in this thread about the Optimal Late-Life BMI for Longevity, and this one called Will Serious CR Beat a Healthy Obesity-Avoiding Diet & Lifestyle , and this one called Relationship between BMI and Disease, Longevity, and finally this one called Body Mass Index and All-Cause Mortality. In general, it appears (to my interpretation) that it doesn't pay to be very thin when it comes to longevity, and may in fact be counterproductive, particularly as someone gets into their senior years. Being average weight or even overweight does not appear to adversely impact longevity in older folks, in fact if anything the evidence points the other way - being a heavy senior appears associated with increased longevity. But what about cognitive health? It would be pretty tragic to live an especially long time, but lose your marbles along the way. Three recent studies that came across my radar shed some light on the issue of BMI and cognitive health. The first [1] looks pretty bad for chubby folks. It found being overweight was associated with a reduction in the volume of several important brain areas. The researchers did structural MRI scans of the brains of 203 relatively young men and women (mean age 32, range 18-50). They ranged in BMI from 18.5 to 46.4. They all self-reported being healthy, and were not receiving any pharmacological treatments. They processed the MRI scans to estimate cortical thickness and surface area, both globally and on a per-region basis. Overall they didn't find a correlation between any of the global brain anatomy measures and BMI: There was no association between BMI and global measures of average cortical thickness, total surface area or average LGI [Local gyrification index - a measure of how folded the cortex is. DP]. But in two brain areas there was a difference between obese folks and people who were either thin or simply overweight: Post-hoc contrasts revealed that while lean (BMI < 25) and overweight subjects (25 ≤ BMI < 30) did not significantly differ in the thickness of the right vmPFC or left LOC (p = 0.29 and p = 0.34, respectively), obese subjects (BMI ≥ 30) had significantly thinner cortices in these clusters, compared to both lean (p < 0.0001 in both clusters) and overweight subjects (p < 0.0001 in both clusters). The ventromedial prefrontal cortex (vmPFC) is at the front of the brain, above the eyebrows and is involved in executive function and decision-making. The LOC (lateral occipital cortex) is at the back of the brain, and is involved in vision processing and object recognition. The scatter plots for the cortical thickness in those two brain areas as a function of BMI look pretty scattered to me. It seems difficult to put too much stock in their results, especially below a BMI of 30, where the plots look pretty random, at least to my eyes: My dubiousness about the result is bolstered by the fact that this cortical thinning effect was discovered in post-hoc analysis. In other words, the researchers were fishing for differences in brain anatomy as a function of BMI, after the main effect they were looking for (cortical changes across the whole brain varying with BMI) didn't pan out. After undoubtedly looking at many regions, these two showed up with statistically significant variations as a function of BMI. There is always the danger with this sort of post-hoc approach of finding spurious correlations if you look hard enough at enough different variables. But other studies have found variations in the vmPFC related to obesity. In fact, these authors and others have speculated that the direction of causality may be reserved for the vmPFC. Rather than obesity causing brain shrinking in the vmPFC, having a smaller vmPFC may predispose someone to gaining weight. Why? Because the vmPFC is critical for good decision-making, and the thought is that a smaller vmPFC may result in poor impulse control, and therefore overeating and weight gain. In a separate new study by the same authors [2] (popular press coverage), this time looking at white matter (axons between brain areas) rather than grey matter (neuronal cell bodies and dendrites), the authors did find a more widespread difference between the brains of obese/overweight people and thin people. This time they scanned the brains of over 500 people aged 20 to 87. Basically, when it came to white matter volume, the brains of overweight (avg BMI 27.1) or obese (avg BMI 33.5) folks looked about 10 years older than the lean (normal weight) folks (avg BMI 22.7). Here are the curves for white matter volume as a function of age: As you can see, everyone's white matter volume declines past age 40, but the overweight/obese folks appear to never reach the same peak volume as the normal weight folks and start to decline earlier than the normal weight folks as well. As a result, past middle age the overweight/obese folks' brains looked about 10 years older than the thin folks in terms of white matter volume. The impact of BMI on white matter volume appeared to be independent of exercise, income or education. Interestingly, the authors also found that "a previous diagnosis of elevated cholesterol" was associated with reduced white matter volume, independent of age and BMI. But perhaps most surprisingly, despite the reduced white matter volume in obese/overweight folks relative to lean folks, they saw no difference in cognitive scores (on the Cattell test - "used to capture fluid intelligence by measuring abstract reasoning ability") between the chubby and the lean folks: The authors say: Although previous studies have linked white matter integrity, processing speed and fluid intelligence (Kievit et al., 2016) our results suggest that BMI does not additional influence the age and brain structure relationship with cognition. In other words, despite having less white matter, the heavier folks didn't suffer any faster cognitive decline than the thin folks, at least as measured by this test of "fluid intelligence" in a snapshot of people at various ages. The authors again point to the possibility of reverse causality (less white matter → weight gain), but it seems harder to argue in this case, where the white matter shrinkage/deficit was global rather than confined to decision-making parts of the brain like they saw in [1]. Despite minor doubts about the arrow of causality, and despite a lack of cognitive deficits in the heavier folks, it seems to me like a no-brainer to prefer potentially preserving white matter by staying lean (avg BMI ~23) relative to becoming overweight (BMI >25) or obese (BMI > 30). So these two studies (weakly) suggest it's better to be lean than overweight/obese for brain health. But what about the other end of the scale? That's where study [3] comes in. In this one, a different set of researchers did PET brain imaging on 280 healthy older people (mean age 73, range 62-90) with normal cognitive function. More on demographics: Subjects were roughly average for the American population in terms of prevalence for antihypertensive use (58%) and statin use (44%), but had less diabetes mellitus type 2 (9%) and active smoking (4%).d Here was the distribution of BMIs: Body-Mass Index 26.9 (16–41) - Underweight (BMI <18.5) 2.5% (n=7) - Normal (BMI 18.5–24.9) 31.8% (n = 89) - Overweight (BMI 25–29.9) 41.4% (n = 116) - Obese (BMI >30) 24.3% (n = 68) What they did was correlate BMI with PiB retention, which is a surrogate for brain amyloid concentration, an early marker for increased risk of cognitive impairment / alzheimer disease. What they found that was being on the thin end of the BMI spectrum (i.e. < 25) was associated with an increased PiB retention, i.e. increased risk of future cognitive decline. This association was seen across the board, but was only significant in APOE4 carriers (i.e. those with a genetic tendency to develop cognitive impairment / alzheimer's disease). Here are the scatter plots of data from APOE4 carriers (green) and non-carriers (blue): As you can see, once again there was a pretty wide scatter, and the blue points have only a very modest downward slope (i.e. reduced risk of cognitive decline) with increasing BMI. In short, it appears if you know you are an APOE4 carrier (or if you don't know that you aren't an APOE4 carrier) it looks like it may be a good idea to avoid being thin late in life. But once again it is hard to know if being thin causes cognitive decline in APOE4 carriers, or that being an APOE4 carrier causes weight loss later in life. When taken together, the upshot of these three studies of BMI & cognitive health seems to point to a similar conclusion as we've seen for BMI & longevity. Namely that a middle-of-the-road BMI (i.e. 23-25) in one's elder years appears associated with the maximum chance of keeping one's marbles intact with age. --Dean ------------ [1] Int J Obes (Lond). 2016 Jul;40(7):1177-82. doi: 10.1038/ijo.2016.42. Epub 2016 Mar 22. Increased body mass index is associated with specific regional alterations in brain structure. Medic N(1,)(2), Ziauddeen H(1,)(2,)(3), Ersche KD(1), Farooqi IS(2), Bullmore ET(1,)(4), Nathan PJ(1,)(5), Ronan L(1), Fletcher PC(1,)(2,)(3). Author information: (1)Department of Psychiatry, University of Cambridge, Cambridge, UK. (2)Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK. (3)Cambridgeshire and Peterborough NHS Foundation Trust, University of Cambridge, Cambridge, UK. (4)Medicines Discovery and Development, GlaxoSmithKline, Clinical Unit Cambridge, Cambridge, UK. (5)School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia. Full text: http://sci-hub.cc/10.1038/ijo.2016.42 BACKGROUND: Although obesity is associated with structural changes in brain grey matter, findings have been inconsistent and the precise nature of these changes is unclear. Inconsistencies may partly be due to the use of different volumetric morphometry methods, and the inclusion of participants with comorbidities that exert independent effects on brain structure. The latter concern is particularly critical when sample sizes are modest. The purpose of the current study was to examine the relationship between cortical grey matter and body mass index (BMI), in healthy participants, excluding confounding comorbidities and using a large sample size. SUBJECTS: A total of 202 self-reported healthy volunteers were studied using surface-based morphometry, which permits the measurement of cortical thickness, surface area and cortical folding, independent of each other. RESULTS: Although increasing BMI was not associated with global cortical changes, a more precise, region-based analysis revealed significant thinning of the cortex in two areas: left lateral occipital cortex (LOC) and right ventromedial prefrontal cortex (vmPFC). An analogous region-based analysis failed to find an association between BMI and regional surface area or folding. Participants' age was also found to be negatively associated with cortical thickness of several brain regions; however, there was no overlap between the age- and BMI-related effects on cortical thinning. CONCLUSIONS: Our data suggest that the key effect of increasing BMI on cortical grey matter is a focal thinning in the left LOC and right vmPFC. Consistent implications of the latter region in reward valuation, and goal control of decision and action suggest a possible shift in these processes with increasing BMI. DOI: 10.1038/ijo.2016.42 PMCID: PMC4936515 [Available on 2017-01-01] PMID: 27089992 ------------ [2] Neurobiology of Aging (2016), Obesity associated with increased brain-age from mid-life Ronan, L., Alexander-Bloch, A.F, Wagstyl, K., Farooqi, S., Brayne, C., Tyler, L.K, Cam-CAN, Fletcher, P.C, Free full text: http://www.neurobiologyofaging.org/article/S0197-4580(16)30140-3/pdf Abstract Common mechanisms in aging and obesity are hypothesized to increase susceptibility to neurodegeneration, however direct evidence in support of this hypothesis is lacking. We therefore performed a cross-sectional analysis of MRI-based brain structure on a population-based cohort of healthy adults. Study participants were originally part of the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) and included 527 individuals aged 20 – 87 years. Cortical reconstruction techniques were used to generate measures of whole brain cerebral white matter volume, cortical thickness and surface area. Results indicated that cerebral white matter volume in overweight and obese individuals was associated with a greater degree of atrophy, with maximal effects in middle-age corresponding to an estimated increase of brain-age of 10 years. There were no similar BMI-related changes in cortical parameters. This study suggests that at a population level, obesity may increase the risk of neurodegeneration. Keywords obesity; white matter volume; structural MRI; population-based PMID: Not available doi: 10.1016/j.neurobiolaging.2016.07.010. ----------- [3] J Alzheimers Dis. 2016 Jun 18;53(3):1097-105. doi: 10.3233/JAD-150987. Lower Late-Life Body-Mass Index is Associated with Higher Cortical Amyloid Burden in Clinically Normal Elderly. Hsu DC(1,)(2,)(3), Mormino EC(4), Schultz AP(4), Amariglio RE(4,)(2), Donovan NJ(1,)(2,)(5), Rentz DM(4,)(2,)(5), Johnson KA(4,)(6,)(2), Sperling RA(4,)(2), Marshall GA(4,)(2); Harvard Aging Brain Study. Author information: (1)Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. (2)Department of Neurology, Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. (3)Department of Psychiatry, Mercy Medical Group, Sacramento, CA, USA. (4)Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. (5)Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. (6)Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. Full text: available on request BACKGROUND: Lower body-mass index (BMI) in late life has been associated with an increased risk of dementia, and weight loss has been associated with more rapid decline in Alzheimer's disease (AD) dementia. OBJECTIVE: To explore the association between BMI and cortical amyloid burden in clinically normal (CN) elderly at risk for AD dementia. METHODS: Cross-sectional analyses were completed using baseline data from the Harvard Aging Brain Study, consisting of 280 community-dwelling CN older adults aged 62-90. Assessments included medical histories and physical exam, Pittsburgh compound B (PiB) positron emission tomography (PET) amyloid imaging, and apolipoprotein E ɛ4 (APOE4) genotyping. For the primary analysis, a general linear regression model was used to evaluate the association of BMI with PiB retention. Covariates included age, sex, years of education, and APOE4 carrier status. Secondary analyses were performed for BMI subdivisions (normal, overweight, obese), APOE4 carriers, and BMI×APOE4 interaction. RESULTS: In the primary analysis, greater PiB retention was associated with lower BMI (β  =  -0.14, p = 0.02). In the secondary analyses, APOE4 carrier status (β= -0.27, p = 0.02) and normal BMI (β= -0.25, p = 0.01), as opposed to overweight or obese BMI, were associated with greater PiB retention. The BMI×APOE4 interaction was also significant (β= -0.14, p = 0.04). CONCLUSIONS: This finding offers new insight into the role of BMI at the preclinical stage of AD, wherein lower BMI late in life is associated with greater cortical amyloid burden. Future studies are needed to elucidate the mechanism behind this association, especially in those with lower BMI who are APOE4 carriers. DOI: 10.3233/JAD-150987 PMCID: PMC4976009 PMID: 27340843
  2. Al posted a new study [1], that appears to me to support the theory I've been promulgating for a while that what's important for health and longevity is the quality of one's diet and lifestyle, rather than the quantity of calories one eats. The study followed over 90,000 postmenopausal women for about 13 years to see how the baseline quality of their diet (as quantified by 4 popular dietary quality metrics) impacted subsequent mortality. The dietary quality metrics were designed to gauge how well the women adhered to commonly-accepted 'good' dietary patterns, like following a Mediterranean Diet, or a DASH-like diet. All four shared much in common (emphasize fruits & vegetables, whole grains, avoid red & processed meat, etc.), and fortunately all four resulted in similar outcomes in this study, so I'll collapse all four in my brief discussion of the results below into a single notion of a "good diet". What they found was the women who had the best diet (i.e. were in the highest quintile of 'good diet' score relative to lowest quintile) had about a 20-25% lower risk of dying during the 13 year follow-up period. They also had a lower BMI (25-26 vs. 28-29) although weren't especially slim, and the exercised more than the women who ate the crappiest diet, although the researchers attempted to factor out BMI, exercise, and calories (see next point) from their statistical analysis to focus on the link between diet quality and mortality. On average the women who were eating the best diet and hence were healthier & longer-lived didn't report eating any fewer calories than the women eating the crappiest diet (although as we know food frequency questionnaires are fraught with difficulties...), they were just eating healthy foods rather than unhealthy ones. In short, this is yet one more study showing that dramatic improvements in health/longevity, on par with what we hope to achieve via CR, seem to be attainable by following a healthy obesity-avoiding diet & lifestyle, but without calorie restriction. --Dean -------- [1] Comparing indices of diet quality with chronic disease mortality risk in postmenopausal women in the Women's Health Initiative Observational Study: evidence to inform national dietary guidance. George SM, Ballard-Barbash R, Manson JE, Reedy J, Shikany JM, Subar AF, Tinker LF, Vitolins M, Neuhouser ML. Am J Epidemiol. 2014 Sep 15;180(6):616-25. doi: 10.1093/aje/kwu173. Epub 2014 Jul 17. PMID: 25035143 Free PMC Article http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4157698/ http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4157698/pdf/kwu173.pdf Abstract Poor diet quality is thought to be a leading risk factor for years of life lost. We examined how scores on 4 commonly used diet quality indices-the Healthy Eating Index 2010 (HEI), the Alternative Healthy Eating Index 2010 (AHEI), the Alternate Mediterranean Diet (aMED), and the Dietary Approaches to Stop Hypertension (DASH)-are related to the risks of death from all causes, cardiovascular disease (CVD), and cancer among postmenopausal women. Our prospective cohort study included 63,805 participants in the Women's Health Initiative Observational Study (from 1993-2010) who completed a food frequency questionnaire at enrollment. Cox proportional hazards models were fit using person-years as the underlying time metric. We estimated multivariate hazard ratios and 95% confidence intervals for death associated with increasing quintiles of diet quality index scores. During 12.9 years of follow-up, 5,692 deaths occurred, including 1,483 from CVD and 2,384 from cancer. Across indices and after adjustment for multiple covariates, having better diet quality (as assessed by HEI, AHEI, aMED, and DASH scores) was associated with statistically significant 18%-26% lower all-cause and CVD mortality risk. Higher HEI, aMED, and DASH (but not AHEI) scores were associated with a statistically significant 20%-23% lower risk of cancer death. These results suggest that postmenopausal women consuming a diet in line with a priori diet quality indices have a lower risk of death from chronic disease. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US. KEYWORDS: diet; diet quality indices; mortality risk; postmenopausal women; prospective cohort study
  3. Dean Pomerleau

    The Waiter’s Weight Matters...

    All I can say is that people are zombies when it comes to food choices... From [1]: Diners ordered significantly more items when served by heavy wait staff with high body mass indexes (BMI; p < .001) compared with wait staff with low body mass indexes. Specifically, they were four times as likely to order desserts (p < .01),... In this popular press article on the study, the author says: “A fun, happy, heavy waiter, might lead a diner to say ‘What the heck’ and to cut loose a little.” --Dean ------------- [1] The Waiter’s Weight - Does a Server’s BMI Relate to How Much Food Diners Order? Tim Döring1 Brian Wansink2⇑ 1Friedrich Schiller University Jena, Germany 2Cornell University, Ithaca, NY, USA Brian Wansink, Cornell University, 475 Warren Hall, Ithaca, NY 14853-7801, USA. Email: fblsubmissions@cornell.edu http://eab.sagepub.com/content/early/2015/10/29/0013916515621108.abstract Abstract Does the weight of a server have an influence on how much food diners order in the high-involvement environment of a restaurant? If people are paying for a full meal, this has implications for consumers, restaurants, and public health. To investigate this, 497 interactions between diners and servers were observed in 60 different full-service restaurants. Diners ordered significantly more items when served by heavy wait staff with high body mass indexes (BMI; p < .001) compared with wait staff with low body mass indexes. Specifically, they were four times as likely to order desserts (p < .01), and they ordered 17.65% more alcoholic drinks (p < .01). These findings provide valuable evidence in recent lawsuits against weight discrimination, and it suggests to consumers who decide what they will and will not order at a restaurant—such as a salad appetizer, no dessert, and one drink—than to decide when the waiter arrives.
  4. Dean Pomerleau

    Optimal Late-Life BMI for Longevity

    Mike Lustgarten has penned an interesting blog post in which he looks at data from several sources, including these two meta-analyses [1][2]. Study [1] found the optimal BMI for adults in general (median age 58), was pretty flat and optimal between BMI of 19-25. Here is the graph: But [2] found in older adults (65+) the optimal BMI was much higher: As we've discussed here, this late-life "obesity paradox" might be a result of latent disease making people thin and more likely to die. Or it could simply be that heavier people have more metabolic reserves, which is important to enable the elderly to weather the "slings and arrows" of aging / decrepitude (e.g. falls & fractures, hospitalization, sarcopenia, loss of appetite, etc.) But the most interesting graphic from Mike's post is this one, in which Mike looked through a bunch of references (see his blog post for the list of references) and apparently did his own meta-analysis of the average BMI of centenarians (thanks Mike!): As you can see, most centenarians have a BMI between 19 and 24. He concludes: Centenarians have a BMI between 19.3-24.4 kg/m2. Shouldn’t that be the BMI reference range for those interested in living past 100? On the CR Society Facebook Group discussion of Mike's blog post, I question his rationale for this statement, saying: To play devil's advocate, it seems like the only way to answer [the question of the optimal BMI for living past 100] is to see if [the centenarians] have maintained that BMI from a much younger age, or have only gotten that thin as a results of sarcopenia and other unintended weight loss. Or maybe they've gained weight relative to their younger selves. There just isn't enough information to know what is optimal based on late-life BMI in the extremely old. I further suggest something we've discussed before (in the thread mentioned above): The optimal strategy may be to remain thin until one's elderly years to gain the benefits of CR, then put on weight to serve as a metabolic reserves when adverse events are likely to require them in old age. --Dean ------- [1] Berrington de Gonzalez A, Hartge P, Cerhan JR, Flint AJ, Hannan L, MacInnis RJ, Moore SC, Tobias GS, Anton-Culver H, Freeman LB, Beeson WL, Clipp SL, English DR, Folsom AR, Freedman DM, Giles G, Hakansson N, Henderson KD, Hoffman-Bolton J, Hoppin JA, Koenig KL, Lee IM, Linet MS, Park Y, Pocobelli G, Schatzkin A, Sesso HD, Weiderpass E, Willcox BJ, Wolk A, Zeleniuch-Jacquotte A, Willett WC, Thun MJ. Body-mass index and mortality among 1.46 million white adults. N Engl J Med. 2010 Dec 2;363(23):2211-9. doi: 10.1056/NEJMoa1000367. Erratum in: N Engl J Med. 2011 Sep 1;365(9):869. ---- [2] Winter JE, MacInnis RJ, Wattanapenpaiboon N, Nowson CA. BMI and all-cause mortality in older adults: a meta-analysis. Am J Clin Nutr. 2014 Apr;99(4):875-90.
  5. All, Al Pater posted a study [1] that compared the effects on biomarkers of health for various types of vegetarian diets vs. omnivores in a group of Taiwanese men and women of all ages. The study divided subjects into four groups: vegan, lacto-vegetarians, ovo-lacto-vegetarians, and omnivores, as ascertained via a 26 element food frequency questionnaire, and explicit questions about how they self-classify their diet. They matched each of the 10,000 vegetarians in the study with five omnivores of the same age and sex. Here are the main findings comparing all the vegetarians as a group against the omnivores: With adjustment for age, sex, physical activities, alcohol consumption and education, vegetarians had significantly lower abnormalities [i.e. values in the unhealthy range as defined by health authorities - DP] in WC [Waist Circumference], BMI, SBP [systolic BP] DBP [Diastolic BP], FBG [Fasting Blood Glucose],TC [Total Cholesterol] and LDL as well as in TC:HDL ratios, with OR ranging from 0·37 to 0·90, but higher abnormality in HDL [i.e. low HDL] (OR ranged from 1·17 to 1·52), when compared with non-vegetarians cross-sectionally. <snip> Overall, we observed lower values for WC, BMI, SBP, DBP, FBG, TC, HDL and LDL, along with lower TC:HDL ratios, in vegetarians compared with non-vegetarians, which replicated the findings of previous Taiwanese studies(9,22,23). Except for [lower] HDL and [higher] TAG [triglycerides] values in lacto-ovo-vegetarians [only], the vegetarian diets showed significant beneficial effects on metabolic traits, which may be partly due to the lower BMI of vegetarians. <snip> With additional adjustment for BMI (Table 3), the beneficial effects for blood pressure and blood glucose were partly attenuated, whereas the effect on lipids remained consistent. <snip> Lacto-ovo-vegetarians appeared to eat more carbohydrates and fructose, which could be one of the main causes for TAG elevation in this group. <snip> Whether the lower HDL in vegetarians can be regarded as a risk factor may require further study, as vegetarians generally had better TC:HDL ratios. In addition, previous studies have found that low HDL due to reduced fat intake was not associated with poor cardiovascular health(25,26). Strangely, they apparently didn't ask the subject about smoking habits, and therefore didn't control for it. Here are the two main tables of results comparing the various types of vegetarians to the omnivores (click to enlarge): They also tried doing a longitudinal analysis of the data, but the results weren't too informative, and for most of the subjects (63%) they only had one (baseline) measurement. Most of the baseline differences remained significant and mostly improved for those people who remained vegetarians at follow-up visits. Comparing the various types of vegetarians vs. omnivores, it appears that lacto- and lacto-ovo-vegetarians had a slight advantage over vegans across most of the health markers when compared with omnivores, both before and after adjusting for BMI (see Tables 2 and 3 above). Besides the obvious difference between consumption of eggs and dairy, the biggest difference in the vegan food intakes relative to the other two vegetarian groups were they consumed less beans, less "sweet breads" and less fried vegetables. Perhaps a poorer B12 status or lower bean intake could explain the less advantageous health markers of the vegans vs. the other two types of vegetarians (but all three vegetarian types were better than omnivores). So overall, vegetarians of all types appeared to do better compared with omnivores in all of the commonly acknowledged biomarkers markers of health, except for lower HDL and higher triglycerides among the lacto-ovo-vegetarians. This is pretty much consistent with previous studies, such as the Epic Oxford and Seventh Day Adventists. --Dean --------- [1] Br J Nutr. 2015 Oct;114(8):1313-20. doi: 10.1017/S0007114515002937. Epub 2015 Sep 10. Cross-sectional and longitudinal comparisons of metabolic profiles between vegetarian and non-vegetarian subjects: a matched cohort study. Chiu YF(1), Hsu CC(1), Chiu TH(2), Lee CY(1), Liu TT(3), Tsao CK(3), Chuang SC(1), Hsiung CA(1). Several previous cross-sectional studies have shown that vegetarians have a better metabolic profile than non-vegetarians, suggesting that a vegetarian dietary pattern may help prevent chronic degenerative diseases. However, longitudinal studies on the impact of vegetarian diets on metabolic traits are scarce. We studied how several sub-types of vegetarian diets affect metabolic traits, including waist circumference, BMI, systolic blood pressure (SBP), diastolic blood pressure, fasting blood glucose, total cholesterol (TC), HDL, LDL, TAG and TC:HDL ratio, through both cross-sectional and longitudinal study designs. The study used the MJ Health Screening database, with data collected from 1994 to 2008 in Taiwan, which included 4415 lacto-ovo-vegetarians, 1855 lacto-vegetarians and 1913 vegans; each vegetarian was matched with five non-vegetarians based on age, sex and study site. In the longitudinal follow-up, each additional year of vegan diet lowered the risk of obesity by 7 % (95 % CI 0·88, 0·99), whereas each additional year of lacto-vegetarian diet lowered the risk of elevated SBP by 8 % (95 % CI 0·85, 0·99) and elevated glucose by 7 % (95 % CI 0·87, 0·99), and each additional year of ovo-lacto-vegetarian diet increased abnormal HDL by 7 % (95 % CI 1·03, 1·12), compared with non-vegetarians. In the cross-sectional comparisons, all sub-types of vegetarians had lower likelihoods of abnormalities compared with non-vegetarians on all metabolic traits (P<0·001 for all comparisons), except for HDL and TAG. The better metabolic profile in vegetarians is partially attributable to lower BMI. With proper management of TAG and HDL, along with caution about the intake of refined carbohydrates and fructose, a plant-based diet may benefit all aspects of the metabolic profile. PMID: 26355190
  6. Quoting a decent chunk from Wikipedia as background: 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 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.
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