Reading Time: 7 minutes

I’m going to write a few things about a paper on the relationship between body size and longevity. Here goes, mates.

First of all, here’s The Paper. I’m going to write about some interesting facts therein. And from the papers it cites that are interesting enough to look up.

Here’s a cite from this paper. In this study in Sardinia, soldiers had a greater survival if they were short. At 70 years of age, the shorter men (<160 cm, or about 5’3″) lived 2 years longer than men taller than 5’3″.

For reference, the difference in life expectancy of 75-year-olds in 1900 and 75-year-olds in 1999 is only 1.5 years. So the difference in height causes a bigger difference in longevity on average than modernity does. How’s that for effect size.

Small dogs have 1/60th the heart failure rate of large dogs.

I have never felt so bad being so tall and handsome as right now.

The author of the same paper directly above makes the point that Staffan Lindeberg’s Kitavan males were on average 5’3″ and the females 4’11”.

A seriously confounding factor when we’re talking about diet and longevity among Kitavans, exemplars of a disease-free lifestyle. What other groups of especially long-lived people might be long-lived simply because they are short? Hint: most or all.

This one is cool. The authors compared the mortality from cardiovascular disease in the five tallest countries with the five shortest countries. Being in the tallest vs. shortest countries increased risk >2X.

Also compare Japan to Finland. 6X the risk being Finnish compared to being Japanese.

What about centenarians? The bummer knob gets turned up a few notches here. Average height of Okinawans, who have the highest rate of centenarians. Male height? 4’10”. Female? 4’6″.

So short you could accidentally step on them.

Average Okinawan centenarian male height is 4’10”, female 4’6″, right?. Well, Okinawans that are 73 years old: 10 cm taller than this. This implies that short people are overwhelmingly overrepresented among centenarians.

Between species, smaller animals live shorter lives. But within species, the smaller animals live longer.

Mice food-restricted as they grow become smaller mice but have an extended lifespan.

Genetically smaller mice live longer, and vice versa. Reference.

The association between size and longevity even holds for trees. Trees that grow on cliffs and are nutrient deprived and much shorter than their tree colleagues have lifespans that are much longer.

Willcox found that among Japanese living in Hawaii, mortality continues decreasing all the way down to 1000 calories, when it starts increasing with further cal restriction.

Anyone want to go on a 1000 cal/d diet with me? Oh wait, I’m too tall.

Willcox did note that the equivalent for a tall European would be about 1400 cal/d. I’m guessing at 6’1″, I’m closer to about 1600 cal/d, which is about half of what the average American male consumes.

What are the mechanisms giving a longevity advantage to smaller body size?

1. Fewer cells = lower cancer risk.

2. Lower food intake = lower IGF and insulin levels.

3. Organs of smaller animals are larger proportional to body size = greater functionality into older age.

4. Reduced toxin intake because decreased food/water intake.

5. Lower left ventricular size and lower blood pressure because less blood pressure necessary to distribute blood.

6. Lower all bad blood biomarkers.

These are the ones I understand anyway.

In this paper, Samaras then takes on the idea that taller people live longer and healthier lives. He says that this relationship is confounded.

Interesting fact: before the 1930s, American blacks had lower rates of chronic disease, until they began to match whites for height and then experienced increased rates of cardiovascular disease, diabetes, stroke, etc.

Let’s return to some of the specific population studies cited in the original paper. Here we will discuss Holzenberger et al’s 1991 paper on Spaniards.

Here is a graph plotting mean survival an additional 70 years at age 18 in each Spanish province against mean height at age 18 in that province.

According to the analysis, each cm of additional height costs 0.7 years of life.

Samaras then goes on to discuss a study conducted by Dennis Miller in Ohio.

Two figures from this paper by Miller are interesting. First, a table showing an analysis done by none other than Samaras, with accompanying text, showing the point clearly.

Miller then discusses the observations that he made in Cleveland, measuring the heights of corpses at the County Coroner’s office. He found that each additional 1.2 inch in height corresponds to a reduction of a year in average age of death.

Interestingly I found a chart with some of this information in a book called Trends in Nutrition Research published in 2005.

In his paper, Miller makes the interesting suggestion that the difference between male and female life expectancy, especially in terms of cardiovascular disease and cancer, is in large part attributable to height.

Back to the original paper. Also cited is one by Rantanen et al showing among Japanese men living in Hawaii a statistically significant trend (p=0.015) toward decreased height at later age of death, with ~2cm difference between >100 and <80.

Let’s detour, because I want to explain something I stumbled across. We briefly touched on it early, but there’s something called Laron’s syndrome, where mutations cause a person to be entirely insensitive to growth hormone. People with Laron’s syndrome are dwarves.

Not THAT kind of dwarf. THIS kind.

Not only are people with Laron syndrome short in stature, they are also virtually immune to diabetes and cancer.

Here’s a paper showing the cancer rate in people with Laron syndrome versus first-degree relatives, co-authored by the man Laron himself.

No cancer in 230 individuals = 0% cancer rate.

Here’s another paper looking at diabetes. Much higher insulin sensitivity, lower insulin levels, lower rate of diabetes, and so forth, despite higher obesity caused by the syndrome. (This is because growth hormone causes elevation in blood glucose; absence of the receptor as exists in these patients therefore causes lower blood glucose.)

Patients with Laron syndrome have similar mortality to controls, however, because Laron syndrome patients have seizures due to periodic hypoglycemia and die more frequently from accidents. They also tend to have developmental abnormalities.

Why am I going on about people with Laron syndrome? Here’s why. Mice with a similar defect–not a GH receptor defect but a growth hormone deficiency–show a similar phenotype, but this time, with enhanced life expectancy. They are also dwarves and are called Ames mice.

Now the interesting thing about Ames mice is if you give them growth hormone in early life, you increase the adult size but cut the lifespan extension by ~1/3. EVEN if you stop giving the growth hormone after the 7th week.

This implies that a substantial part of the long-term longevity advantage of Ames mice may not be lifetime low GH but lifetime low body-size. And that for best results, you want to restrict calorie intake during the growth period.

Elephant in the room:

“Should I starve my kids?”

We will address this issue head-on later in part 2. But since we haven’t definitively established it yet, be sure not to starve your kids until we’ve finished part 2.

OK 9am and I haven’t slept and I drank like 5 coffees to do this. Time to go to sleep with disrupted circadian rhythms and significantly increased systemic inflammation. I’m probably going to die earlier for staying up late writing about longevity.

Series will continue later. Spoiler: this is a prolegomenon to the Okinawa thread to be finished in a few years. #CantFinishAnything

And about the starving kids thing. That was a joke, and I am seriously concerned about the effects of calorie restriction during childhood growth on brain development. We will look at the evidence for that and try to see what tradeoffs there might be between increased longevity from body size restriction versus brain development and other possible issues.

If we can’t find tradeoffs, though, we would then want to rethink our valorization of height and body-size and growth during childhood. But if we can find tradeoffs, we will need to more carefully consider the issue.

See you in the next wonky post. And if you enjoyed this, please subscribe to this blog, sign up for my Discord, listen to my podcast, and/or become a Patreon subscriber. Your support matters. All links are available below or on my Twitter profile.

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Reading Time: 9 minutes

This blog post was part of a draft for a comprehensive review paper on the ketogenic diet in the treatment of cancer.

After Otto Warburg, Thomas Seyfried is the most important and influential scientist for having put carbohydrate-restricted diets and in particular the ketogenic diet “on the map” in current cancer research, starting with seminal research in 2003 [1] and continuing to the present [2]. His influence on the reception of the ketogenic diet in the popular press has been profound. Seyfried’s papers are extensively cited and his views discussed in many recent and important reviews [3–6] as well as in the clinical trial literature [7,8]. Thus, while his views on cancer metabolism lie far outside the mainstream of cancer research, they have some influence among those interested in the use of the ketogenic diet for cancer, and it may be useful to readers to address some of the core features of these views here. As authors of a recent, major review write:

Some tumor entities are not able to properly respire due to a dysfunctional OXPHOS system. …Tumors with dysfunctional mitochondria or decreased mitochondrial activity seem to compensate their energy requirements by aerobic fermentation. Replacing glucose by ketone bodies requires that the tumors have functional mitochondria to be able to use ketone bodies efficiently for growth and survival [3].

Given its prominence in the field, if largely disregarded in most cancer metabolism research, it will be useful to now briefly critically evaluate this theory in light of available evidence.

Following Warburg [9], Seyfried claimed that cancer (and human glioblastoma multiforme in particular) have a mitochondrial respiratory defect and are therefore dependent on glucose to generate ATP. This concept formed the basis of his advocacy for the ketogenic diet for cancer, which, by restricting glucose and providing ketones in its place, would selectively cause cancer cells (which would then have no available energy substrate due to defective mitochondria) to die, while normal cells, which could use ketones, would be spared [10].

Recently, in a paper entitled “Provocative Question: Should Ketogenic Metabolic Therapy Become the Standard of Care for Glioblastoma?”, Seyfried defended his view that cancer and in particular glioblastoma have impaired capacity mitochondrial respiration, writing:

A multitude of findings support the notion that oxidative phosphorylation is defective in GBM. Based on the biological principle that mitochondrial structure determines mitochondrial function, these multiple mitochondrial abnormalities, which can be of genetic and/or environmental origin, will compromise effective energy production through oxidative phosphorylation [italics ours][2].

Thus, Seyfried argues that their respiratory capacity should be impaired by virtue of the structural changes observed via electron microscopy. This then, according to Seyfried, underlies the basic science rationale behind using the ketogenic diet for glioblastoma multiforme [2].

However, a weakness of this suggestion should be immediately obvious: Seyfried does not provide evidence that this structural change actually leads to a functional change in respiration, i.e. that morphological changes in cancer mitochondria lead to a respiratory defect in the mitochondria. Seyfried’s evidence is strictly circumstantial, and he cites no direct evidence for his proposed mechanism. Indeed, contra Warburg and Seyfried, several investigators have shown that respiration is not defective in many cancer cells, with Sidney Weinhouse providing what many have considered to the definitive statements on the topic first in direct response to Warburg in 1956 [9,11], then six years after Warburg’s death in 1976 [10,12]. More recently, investigators have shown that lactate dehydrogenase A knockdown stimulates mitochondrial respiration, while complementation with the human ortholog LDH-A rescued the Warburg phenotype [13], suggesting that mitochondrial respiration is not defective but merely inactivated. Likewise, a paper published in 1983 showed that glioblastoma cells widely vary in their enzyme activity, with many having relatively low glycolytic activity compared to the brain and some having relatively high mitochondrial enzyme activity compared to the brain; in most cases, both glycolytic and mitochondrial enzyme activity was significantly depressed, but no pattern of metabolic enzyme expression could be gleaned, by tumor or in general, to the disappointment of investigators [14]. Another paper concluded that metabolic diversity with a sliding scale of dependence on oxidative phosphorylation and glycolysis, rather than a single metabolic phenotype, was the rule in glioma cell lines [15]. Still others suggest heterogeneity of metabolic phenotypes within a single cancer [16] and a higher degree of metabolic plasticity in cancer cells than in healthy cells [17].

Although Seyfried provides an intriguing and apparently sound series of arguments in his textbook explaining why the experiments supporting some the above findings are flawed, as well as interpretations of other experiments that would seem to contradict them [10], direct evidence for his view remains equivocal and relies on a particular and unresolved interpretation of a small body of scientific literature.

Glycolytic modulation

Perhaps more importantly, Seyfried’s theory of defective mitochondrial respiration as the cause of cancer is not necessary for glucose restriction to be efficacious in cancer. While Warburg and Seyfried’s explanation of the Warburg effect—that it is the cause of cancer—is not based on strong evidence and is at odds with the views of most cancer biologists, the existence and potential therapeutic importance of the effect itself is not in question. That therapeutic relevance will be the focus of the remainder of this discussion on the ketogenic diet for cancer.

The upregulation of glycolysis in the presence of oxygen is now understood to be an important feature of cancer cell proliferation, because such upregulation increases the activity of biosynthetic pathways that branch off of glycolysis, especially the pentose phosphate pathway, thereby enabling cancer cells to rapidly build biomolecules and proliferate [18]. According to this understanding, while glucose restriction would not selectively kill cancer cells unable to use alternative sources of energy substrate (as posited by the Warburg-Seyfried hypothesis), it might inhibit cancer metabolism sufficiently to provide an additional and adjunctive benefit when combined with conventional cancer treatments. The therapeutic implication well-known: drugs that directly inhibit glycolysis have also been shown to provide therapeutic benefit in preclinical studies [19]. A ketogenic diet, which might mimic the effect of such drugs on glycolytic flux, might therefore reverse components of the Warburg phenotype and inhibit tumor proliferation.

Correspondingly, observational studies suggest that fasting and average hyperglycemia and diets with high glycemic load might increase cancer mortality (see section Epidemiology). Animal models also seem to suggest a similar effect [1,20]. Moreover, a recent study has demonstrated that hyperglycemia drives intestinal barrier dysfunction in mice, that this intestinal barrier dysfunction is associated with changes in relevant immune cell localization, and that blood glucose levels are associated with microbial product influx in humans [21]. Because impaired intestinal barrier activity might predispose to cancer [22], together these findings suggest that glycolytic inhibition and a ketogenic diet in particular may have cancer-preventive properties, consistent with anticancer findings from animal longevity studies [23,24].

The effect of glucose in enhancing tumorogenesis was apparently confirmed by a retrospective cohort analysis showing high vs. random blood glucose levels associating with reduced survival in esophageal and lung squamous cell carcinoma patients but no difference in lung adenocarcinoma patients. Knockdown of the target gene that predicted protection from oxidative stress also slowed growth. Correspondingly, a diet that lowered blood glucose, the ketogenic diet, also caused slowed growth. However, the key experiment that would have linked the mechanism of GLUT1 expression to the efficacy of the ketogenic diet, i.e. showing that the ketogenic diet did not affect tumor growth in GLUT1 knockdowns xenografts, was not reported [25].

However, several lines of evidence substantially complicate the simple view that high blood glucose levels are directly causal in tumor growth. First, in a single-arm crossover study that provided parenteral glucose or lipid to twelve colorectal cancer patients with liver metastases and observed the impact on uptake of [18]2-fluoro-2-deoxy-D-glucose (FDG) using PET, while metastases predictably had a much greater uptake of FDG than healthy tissue, there was no difference between lipid and glucose boluses in FDG uptake in tumor metastases. Intriguingly, and in contrast to the null findings in metastases, normal liver tissue showed an increase of 60% in FDG uptake [26]. This suggests that additional available glucose is on average not readily taken up by colon cancer metastases but that normal tissue might be more flexible than tumor tissue. On the basis of current evidence, it is unclear whether other cancer types would show similar or different findings.

In another study examining the impact of parenteral nutrition on tumor cell proliferation as measured by thymidine labeling index, with seven subjects with gastrointestinal cancers in each group, the glucose-based formula caused a 32.2% increase in growth, while the lipid-based formula caused a 24.3% decrease, but these results were not statistically significant [27].

But perhaps more problematically for the claim that high blood glucose fuels cancer (based as it is almost entirely on correlations in animal models and observational studies): it has been widely known at least since Gerald Reaven’s work on the metabolic syndrome that glucose dysregulation is highly correlated with many gross metabolic disturbances [28], mediated by insulin resistance [29], and with an inflammatory phenotype [30]. Because few studies reporting to demonstrate a relationship between hyperglycemia and cancer control for these other metabolic and inflammatory markers, it is difficult to know whether the association between elevated blood glucose and cancer is causal or is instead indicative of a confounding biological variable (or variables) or both. In other words, is cancer caused or exacerbated by elevated blood glucose per se, or is the cause some other pathway that is altered in the profoundly metabolically dysregulated state that itself causes hyperglycemia? In future installments, we will discuss some of these possibilities in turn.

1.        Seyfried, T.N.; Sanderson, T.M.; El-Abbadi, M.M.; McGowan, R.; Mukherjee, P. Role of glucose and ketone bodies in the metabolic control of experimental brain cancer. Br. J. Cancer 2003, 89, 1375–82.

2.        Seyfried, T.N.; Shelton, L.; Arismendi-Morillo, G.; Kalamian, M.; Elsakka, A.; Maroon, J.; Mukherjee, P. Provocative Question: Should Ketogenic Metabolic Therapy Become the Standard of Care for Glioblastoma? Neurochem. Res. 2019.

3.        Weber, D.D.; Aminzadeh-Gohari, S.; Tulipan, J.; Catalano, L.; Feichtinger, R.G.; Kofler, B. Ketogenic diet in the treatment of cancer – Where do we stand? Mol. Metab. 2019.

4.        Poff, A.; Koutnik, A.P.; Egan, K.M.; Sahebjam, S.; D’Agostino, D.; Kumar, N.B. Targeting the Warburg effect for cancer treatment: Ketogenic diets for management of glioma. Semin. Cancer Biol. 2019, 56, 135–148.

5.        Sremanakova, J.; Sowerbutts, A.M.; Burden, S. A systematic review of the use of ketogenic diets in adult patients with cancer. J. Hum. Nutr. Diet. 2018, 31, 793–802.

6.        Oliveira, C.L.P.; Mattingly, S.; Schirrmacher, R.; Sawyer, M.B.; Fine, E.J.; Prado, C.M. A Nutritional Perspective of Ketogenic Diet in Cancer: A Narrative Review. J. Acad. Nutr. Diet. 2018, 118, 668–688.

7.        van der Louw, E.J.T.M.; Olieman, J.F.; van den Bemt, P.M.L.A.; Bromberg, J.E.C.; Oomen-de Hoop, E.; Neuteboom, R.F.; Catsman-Berrevoets, C.E.; Vincent, A.J.P.E. Ketogenic diet treatment as adjuvant to standard treatment of glioblastoma multiforme: a feasibility and safety study. Ther. Adv. Med. Oncol. 2019, 11.

8.        Santos, J.G.; Da Cruz, W.M.S.; Schönthal, A.H.; Salazar, M.D. alincour.; Fontes, C.A.P.; Quirico-Santos, T.; Da Fonseca, C.O. Efficacy of a ketogenic diet with concomitant intranasal perillyl alcohol as a novel strategy for the therapy of recurrent glioblastoma. Oncol. Lett. 2018, 15, 1263–1270.

9.        Warburg, O. On the origin of cancer cells. Science (80-. ). 1956, 123, 309–314.

10.      Seyfried, T.N. Cancer as a metabolic disease : on the origin, management, and prevention of cancer; John Wiley & Sons, 2012; ISBN 9780470584927.

11.      Weinhouse, S.; Warburg, O.; Burk, D.; Schade, A.L. On respiratory impairment in cancer cells. Science (80-. ). 1956, 124, 267–272.

12.      Weinhouse, S. The Warburg hypothesis fifty years later. Z. Krebsforsch. Klin. Onkol. Cancer Res. Clin. Oncol. 1976, 87, 115–126.

13.      Fantin, V.R.; St-Pierre, J.; Leder, P. Attenuation of LDH-A expression uncovers a link between glycolysis, mitochondrial physiology, and tumor maintenance. Cancer Cell 2006, 9, 425–34.

14.      Lowry, O.H.; Berger, S.J.; Carter, J.G.; Chi, M.M.; Manchester, J.K.; Knor, J.; Pusateri, M.E. Diversity of metabolic patterns in human brain tumors: enzymes of energy metabolism and related metabolites and cofactors. J. Neurochem. 1983, 41, 994–1010.

15.      Griguer, C.E.; Oliva, C.R.; Gillespie, G.Y. Glucose metabolism heterogeneity in human and mouse malignant glioma cell lines. J. Neurooncol. 2005, 74, 123–33.

16.      Miccheli, A.; Tomassini, A.; Puccetti, C.; Valerio, M.; Peluso, G.; Tuccillo, F.; Calvani, M.; Manetti, C.; Conti, F. Metabolic profiling by 13C-NMR spectroscopy: [1,2-13C2]glucose reveals a heterogeneous metabolism in human leukemia T cells. Biochimie 2006, 88, 437–48.

17.      Berridge, M. V; Herst, P.M.; Tan, A.S. Metabolic flexibility and cell hierarchy in metastatic cancer. Mitochondrion 2010, 10, 584–8.

18.      Heiden, M.G. Vander; Cantley, L.C.; Thompson, C.B. Understanding the warburg effect: The metabolic requirements of cell proliferation. Science (80-. ). 2009, 324, 1029–1033.

19.      Martinez-Outschoorn, U.E.; Peiris-Pagés, M.; Pestell, R.G.; Sotgia, F.; Lisanti, M.P. Cancer metabolism: A therapeutic perspective. Nat. Rev. Clin. Oncol. 2017, 14, 11–31.

20.      Iguchi, T.; Takasugi, N.; Nishimura, N.; Kusunoki, S. Correlation between mammary tumor and blood glucose, serum insulin, and free fatty acids in mice. Cancer Res. 1989, 49, 821–5.

21.      Thaiss, C.A.; Levy, M.; Grosheva, I.; Zheng, D.; Soffer, E.; Blacher, E.; Braverman, S.; Tengeler, A.C.; Barak, O.; Elazar, M.; et al. Hyperglycemia drives intestinal barrier dysfunction and risk for enteric infection. Science (80-. ). 2018, 359, 1376–1383.

22.      Fasano, A. Zonulin and its regulation of intestinal barrier function: The biological door to inflammation, autoimmunity, and cancer. Physiol. Rev. 2011, 91, 151–175.

23.      Newman, J.C.; Covarrubias, A.J.; Zhao, M.; Yu, X.; Gut, P.; Ng, C.P.; Huang, Y.; Haldar, S.; Verdin, E. Ketogenic Diet Reduces Midlife Mortality and Improves Memory in Aging Mice. Cell Metab. 2017, 26, 547-557.e8.

24.      Roberts, M.N.; Wallace, M.A.; Tomilov, A.A.; Zhou, Z.; Marcotte, G.R.; Tran, D.; Perez, G.; Gutierrez-Casado, E.; Koike, S.; Knotts, T.A.; et al. A Ketogenic Diet Extends Longevity and Healthspan in Adult Mice. Cell Metab. 2017, 26, 539-546.e5.

25.      Hsieh, M.-H.; Choe, J.H.; Gadhvi, J.; Kim, Y.J.; Arguez, M.A.; Palmer, M.; Gerold, H.; Nowak, C.; Do, H.; Mazambani, S.; et al. p63 and SOX2 Dictate Glucose Reliance and Metabolic Vulnerabilities in Squamous Cell Carcinomas. Cell Rep. 2019, 28, 1860-1878.e9.

26.      Bozzetti, F.; Gavazzi, C.; Mariani, L.; Crippa, F. Glucose-based total parenteral nutrition does not stimulate glucose uptake by humans tumours. Clin. Nutr. 2004, 23, 417–421.

27.      Rossi-Fanelli, F.; Franchi, F.; Mulieri, M.; Cangiano, C.; Cascino, A.; Ceci, F.; Muscaritoli, M.; Seminara, P.; Bonomo, L. Effect of energy substrate manipulation on tumour cell proliferation in parenterally fed cancer patients. Clin. Nutr. 1991, 10, 228–232.

28.      Meigs, J.B.; Wilson, P.W.F.; Nathan, D.M.; D’Agostino, R.B.; Williams, K.; Haffner, S.M. Prevalence and characteristics of the metabolic syndrome in the San Antonio Heart and Framingham Offspring Studies. Diabetes 2003, 52, 2160–2167.

29.      Reaven, G.M. Role of insulin resistance in human disease. (Banting Lecture 1988). Diabetes 1988, 37, 1595–607.

30.      Dandona, P.; Aljada, A.; Chaudhuri, A.; Mohanty, P.; Garg, R. Metabolic syndrome: A comprehensive perspective based on interactions between obesity, diabetes, and inflammation. Circulation 2005, 111, 1448–1454.

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Reading Time: 2 minutes

A very non-smart tweet recently caught my eye:

To get right to the point.

Studies linking COVID death and hyperglycemia use HbA1c to do so. Current evidence suggests carbohydrate restriction independent of weight loss does not cause lower HbA1c. Studies show low-carb and low-fat diets are comparably efficacious in causing weight loss, especially in the long run and especially when matched for quality. Therefore, carbohydrate restriction cannot be said to be more effective than other diets for reducing COVID risk related to hyperglycemia.

Well-meaning health misinformation contributes to our inability to discuss and address the epidemics of obesity and metabolic disease. This tweet from Ms. Teicholz is well-meaning health misinformation.

I want to support these claims with references, because they are at odds with received wisdom on the Internet.

First, here are many studies that call into question a weight loss advantage of low-carbohydrate over healthy low-fat diets: DIETFITS, Kevin Hall and Juen Guo’s meta-analysis analyzing trials that looked at differences in metabolic rate between low-fat vs. low-carbohydrate diets, Kevin Hall’s metabolic ward study comparing the impact of low-fat and a ketogenic diets on metabolic rate, and finally, Kevin Hall’s most recent metabolic ward study comparing ad libitum calorie intake on low-carb vs. low-fat diets.

Next, here are some passages in from a document prepared by the National Lipid Association that call into any weight-independent advantage in average glycemia (as measured indirectly by HbA1c):

And, while low-carb diets reduce weight and HbA1c more than a standard American diet, there are two problems:
1. This is not the case compared to healthy high-carbohydrate diets;
2. Average adherence to low-carb diets declines to the point of seeing no difference beyond a year.

Advocacy of low-carb diets in the context of HbA1c and glycemic control is a distraction (at least on a population level), preventing us from having a fact-based conversation about effective interventions for obesity and metabolic disease in America. We need to make our decisions based on facts, not misinformation.

We really do need to move past the diet wars in the first place. Might I direct readers…

===

Find the original thread here:

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Reading Time: 2 minutes

Part 1

Original thread here. (This thread earned me a spontaneous block by @lchfRD. Bless her soul.)

For people with diabetes, low-carbohydrate diets that produce similar weight loss as high-carbohydrate diets also produce similar reductions in HbA1c, a measure of blood glucose.

Reference:
https://www.lipid.org/nla/review-current-evidence-and-clinical-recommendations-effects-low-carbohydrate-and-very-low

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Caveat: Blood glucose variability might be improved on a low-carbohydrate diet, with higher fasting blood glucose but fewer glucose “spikes”. Likewise for triglycerides: LCHF tends to lower fasting triglycerides. What benefit these have is unclear.

Weight loss drives most of the improvements in T2DM. On average, there is no advantage to carbohydrate-restricted diets for weight loss when diets compared are both low in refined carbohydrate and processed foods.

References:
https://jamanetwork.com/journals/jama/fullarticle/2673150
https://www.ncbi.nlm.nih.gov/pubmed/28193517

Therefore: there is no clear advantage on average in terms of biomarkers to treating type 2 diabetes with a low-carbohydrate diet, except perhaps for triglycerides and glucose variability, each of which have unclear importance. The downside to LCHF of course is LDL-C.

Thus, the evidence in favor of LCHF for T2DM comes in the form of unestablished biomarkers, while the evidence against comes in the form of established biomarkers.

In other words, evidence in favor of a clear benefit does not exist while clear evidence of potential harm does.

Therefore, if this is right: while it makes sense for LCHF to be an option for type 2 diabetes in some people, it also makes sense to recommend against it, and it is understandable why scientific organizations are reluctant to endorse LCHF for type 2 diabetes.

Caveat: those with type 2 diabetes may need fewer medications when on a lower carbohydrate diet. This makes sense. Because there is lower insulin secretion on a low-carbohydrate diet to maintain the same blood glucose levels, it would make sense that less medication would be required to do the same thing.

This advantage should not be overlooked. But neither should the speculative nature of most other claimed advantages. Nor the concrete, established disadvantage of LDL.

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Originally posted here.

A preprint published last month shows that among 175 recovered COVID-19 patients from Shanghai, 30% showed a low neutralizing antibody response, with 10 patients showing undetectable antibodies.

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Fortunately, apart from those 10 cases, serology can generally clearly distinguish between healthy and previously infected individuals.

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Antibody levels seem to spike at around 14 days of disease.

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There was a robust relationship between age and neutralizing antibody levels, with older patients having higher levels and with the large majority of cases of undetectable antibody levels in the younger patients.

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There was no decline in antibody levels when tested two weeks later.

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Duration of disease, length of stay, older age, and male gender were each correlated with higher antibody levels.

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Those with undetectable antibodies seemed to have a very mild course of disease.

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What this study seems to suggest is that serology clearly distinguishes between previously infected individuals and never-infected ones about 95% of the time but not always.

The implications of low antibody producers may yet to be fully understood.

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Reposted from Twitter, December 16th, 2017.

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Reposted from Twitter, December 3, 2017.

For those wondering what the source of the fat calories were, I’ve created two more graphs telling that story. Answer: vast majority of added fat calories in the American diet 1970-2010 come from soybean oil.

Reposted from Twitter December 6, 2017.

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I would like to push back on one point here, and that is that martia arst are not necessarily a scam.

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I don’t want to write this. It is inappropriate that I should be writing about COVID-19 at all. I am a nutrition scientist. A Ph.D. student, in fact. I am not an infectious disease expert.

But here I am. Trump does not value expertise. Not valuing expertise, he has not communicated clearly and frankly about the COVID19 pandemic and has prevented his best scientists from doing so. This was avoidable: Singapore was transparent, science-based, and honest with its public. The Trump administration has decided to take a different approach.

The magazines and newspapers have filled the information void, to disastrous consequence. These outlets are not equipped to relay information accurately. In the social media age, the mainstream media outlets have been forced to shift from a subscription-based model (which allows companies to focus on quality) to an engagement-based model (which forces companies to focus on generating engagement). Years of adapting to such a system has come at the expense of media companies’ ability to serve as impartial communicators of the facts.

The outcome for COVID19 is not good. Not being able to vet quality as they should be able to, mainstream media companies cannot serve as gatekeepers to protect the public from misinformation, even if they wanted to. The result is widespread confusion. Mainstream media could promote content from infectious disease experts and virologists. Instead they promote flashy pieces by celebrities and “opinion leaders”.

I write this post therefore to clear up some avoidable confusion. The confusion in this case is about the mortality rate from infection with COVID19.

My main points.

1. CFR is probably overestimated when it exceeds 1%; real CFR is probably well below 1%;
2. The discussion about CFR is academic and not of much practical importance.

Now, CFR is defined as the number of deaths divided by the number of infections

CFR = deaths / infections x 100

This gives us a percentage of people who die who are infected.

CFR relies on accurate counts of deaths and infections. Our count of deaths is probably somewhat accurate. Our count of infections is not. Studies show rate of undetected infections between 70-90%. This means that the CFR of many countries is in some cases an overestimate by as much as 10-fold.

For example, this would suggest that in Italy’s case, their CFR of 7-8% is actually closer to 0.7-0.8%. I think this is probably true. This is the story the data are telling us, without any exceptions of which I am aware.

Real CFR (as opposed to measured CFR) is therefore probably around 0.5-1% in most countries.

When CFR exceeds this figure, we can suggest the following relationship:

CFR ∝ infection rate / testing reach

More infections means more undetected cases. Lower testing reach means more undetected cases. These compound each other. Correspondingly, CFR shoots up. Hence the above equation.

High CFRs are the result of only testing the sickest patients, because there are not enough tests for everyone or because catastrophe has struck because of # of infections. This is supported by reports on the ground in Italy.

It is important to realize that the discussion about whether 500,000 or 1,000,000 or 2,000,000 die without action is academic. It would be a lot, and the medical, economic, and political systems would enter a crisis state greater than the one we are now confronting.

No matter what action we take, the pandemic will be catastrophic in America. This will begin to unfold vividly in the coming week in NYC.

COVID19 is catastrophic because of the rate at which it strikes and kills and hospitalizes and our inability to control spread once it has taken hold if we do not implement drastic measures.

The power of COVID19 is NOT dependent on percent of people who die of those who are infected but on its rapidity, penetration, ubiquity, and thereby, even with modest CFR: mass deaths and hospitalizations.

Neither reported CFRs nor the real CFRs are a measure of the damage that the pandemic will do. Even if CFR is 0.5%, we have no choice: we must respond with drastic measures. COVID19 is not causing pandemonium because it will kill 500,000 or 1,000,000 people. It is doing so because it is incredibly and visibly disruptive to human life.

Asia understands this. We in the West are just starting to understand it. Yet we are still arguing about it. Soon, we won’t be.

Good luck everyone.

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