…but it isn’t dead, imo, because that would be really hard to do. Like, seriously.
side note: please consider the modern views of Taubes, Lustig, Gardner, Attia, and others on Carbs™. They’re less “Carbs-cause-obesity, keto-for-all, etc.,” and more thinking it might not be Carbs™ per se, but rather processed and refined foods. And #context… And I tend to agree at the moment (nuances and caveats are subject to change, as more evidence accumulates).
disclaimer: I haven’t seen the full text of Hall’s recent study, but that’s not really relevant to what I want to discuss. In other words, I don’t think the full text will provide any additional details on this particular point.
Tl;dr: this study was not designed to prove or disprove metabolic advantage or the insulin-obesity hypothesis.
It’s in the study design: four weeks of low fat followed by four weeks of low carb. We KNOW that weight loss slows over time (especially if calories are controlled, as they were in this study). It has to do with the order of treatments.
Weight loss-slowing over time in the Minnesota Experiment:
Posted in Advanced nutrition, diabetes, diet, Dietary fat, empty calories, Grains, insulin, Ketosis, Leptin, Protein, sleep, Sun, TPMC
Tagged calories, carbs, diet, empty calories, energy balance, fiber, grains, insulin, ketogenic, ketones, ketosis, leptin, nutrition, obesity, Paleo, processed food, protein, sugar, trans fat
Social jet lag is basically a general term that refers to circadian arrhythmia. Sort of like insulin resistance, it’s rampantly abundant — some have estimated a prevalence of up to 75%! Social jet lag can be induced by shift work, East/West travel, late meal timing, artificial light at night, sleeping late, not enough sunlight in the morning, etc., etc. And while any of the above insults, by themselves, may not really screw up your circadian rhythms, you can see how easy it is for one person to fall prey to nearly of them:
Eat a late dinner, stay up late using artificial light (eg, computer, smart phone, etc.), sleep late the following day so you skip breakfast and don’t get any sunlight in the morning.
CIRCADIAN MISMATCH ACCOMPLISHED
This increases your risk for a wide variety of ailments, ranging from cancer to diabetes to bipolar disorder: no bueno.
One key mediator of the effects of LIGHT is melatonin. Artificial light at night suppresses melatonin. Sunlight in the morning can blunt the impact of this! It all ties in together. Gravitas.
Great review article here.
Posted in Advanced nutrition, angiotensin, Bromocriptine, Cabergoline, chronopharmacology, circadian, diabetes, diet, Dopamine, Energy balance, Ketosis, Leptin, melatonin, resveratrol, Sun
Tagged calories proper, carbs, circadian rhythm, energy balance, ketosis, melatonin, sleep
Bear with me here… this could be very important (or just all in my imagination haha)
Fact: melatonin secretion happens at night (or at least that’s when it’s supposed to happen):
And it’s important to adopt healthy circadian behaviors early on to prevent or minimize the age-related decline in melatonin secretion:
Posted in Advanced nutrition, chronopharmacology, circadian, Dopamine, Leptin, melatonin, muscle, sleep, TPMC
Tagged calories proper, circadian rhythm, insulin, ketosis, nutrition
Brief background reading: amylin (according to Wikipedia)
In a study by Hollander on type II diabetics, the synthetic amylin analog pramlintide was tested (Hollander et al., 2003). In this year-long RCT, over 600 patients were treated with placebo or up to 120 ug pramlintide BID (twice per day). On average, these subjects were obese (BMI 34), diabetic for ~12 years, and had an HbA1c of 9.1%. After one year, HbA1c declined 0.62% and they lost about 1.4 kg… not very impressive.
But it’s not all bad news; after viewing those relatively negative results (3 lb weight loss over the course of 1 year), another group of researchers led by Louis Aronne and Christian Weyer believed amylin had yet to be tested proper. So they designed a better study; it was shorter, used higher doses of pramlintide, and they enrolled obese yet non-diabetic patients (Aronne et al., 2007). They opted for higher doses of pramlintide (240 ug TID [three times per day]) because in dose-escalation studies, the incidence and severity of adverse drug reactions was consistently low at all doses tested.
They chose to study obese-er subjects (BMI 38, compared to 34 in the Hollander study) because obese subjects lose fat more readily than lean people, so if the study is designed to measure fat loss, then it is better to select a population of subjects where more fat loss is predicted. They selected non-diabetic subjects for a similar reason; diabetics must regularly inject insulin which promotes the accumulation of fat mass — this could counteract any fat reducing effects of pramlintide.
In other words, it was a more powerful and better designed study.
After 16 weeks, pramlintide-treated subjects lost an average of 3.6 kg (~8 lbs), or about half a pound per week. 30% of patients lost over 15 pounds (1 lb/wk)! Importantly, the weight loss didn’t appear to have reached a plateau by week 16, so it would have most likely continued along a similar trajectory had the study been longer. There were no side effects, and a battery of psychological evaluations showed that the patients receiving pramlintide felt it was easier to control their appetite and BW, they didn’t mind the daily injections, and overall well-being increased. At the very least, these evaluations meant the subjects weren’t losing weight because of nausea or malaise. In fact, it was quite the opposite.
Posted in Advanced nutrition, diet, Dietary fat, Energy balance, fat, insulin, Ketosis, Leptin, liver, microbiome, muscle, pair-feeding, Protein, TPMC
Tagged body composition, calories proper, carbohydrates, carbs, diet, energy balance, energy expenditure, insulin, ketogenic, ketosis, nutrition, obesity, protein
1st Generation: ketone salts. Only problem is the huge dose of salt limits how much you can take without adverse effects… but these are the ones on the market.
2nd Generation: ketone esters.
Advantage: no salt, and probably “slow-release.”
Disadvantage: gonna be WAY more expensive than the salts (which are still pretty expensive).
~40 grams of (R)-3-hydroxybutyl (R)-3-hydroxybutyrate (a ketone ester) (from Clarke et al., 2013):
They did this thrice daily, so some people were getting up to 170 grams.
ONE HUNDRED SEVENTY GRAMS
[keep that number in mind]
Posted in Advanced nutrition, circadian, coconut, diet, Dietary fat, Energy balance, fiber, insulin, Ketosis, Leptin, microbiota, muscle, TPMC
Tagged Atkins, carbs, insulin, ketogenic, ketones, ketosis, leptin, microbiota, muscle, nutrition, protein
Does it matter where fatty acids are oxidized, liver or skeletal muscle? Of course, they’re oxidized in both tissues (quantitatively much more in the latter), but relative increases in one or the other show interesting effects on appetite and the regulation of fat mass [in rodents].
Warning: a lot of speculation in this post.
It’s known that LC diets induce a spontaneous decline in appetite in obese insulin resistant patients. Precisely HOW this happens isn’t exactly known: the Taubes model? improved leptin signaling? probably a little bit of both, other mechanisms, and possibly this one:
Exhibit A. Oxfenicine
Posted in coconut, diet, Dietary fat, Energy balance, insulin, Ketosis, Leptin, liver, muscle, TPMC
Tagged Atkins, body composition, calories proper, carbs, diet, energy expenditure, insulin, ketosis, obesity
More on Zeevi et al. (2015) (this is a follow-up to part 1)
I like this study a lot, or at least the fundamentals… or new tools that it might bring to the table. Like, we know sleep and physical activity are important, and we know all calories aren’t created equal. This study is the next level, showing there are even big differences in specific carb-rich foods depending on who’s eating them.
And more interestingly, if I’m interpreting the results of the intervention study correctly (which may not be the case), gut microbial responses to specific foods were very individualized… and predictable!
But first, the main part of the study — standardized meals (after overnight fast): 50g carbs from glucose, white bread, bread and butter, bread and dark chocolate, and fructose. All repeated at least once (except fructose). Everyone responded pretty similarly to fructose (little to no blood glucose spike), but a wide range of responses to glucose.
PPGR = PostPrandial Glucose Response
The range of PPGR to bread was ~15 to 79!
Again, here are some of the findings I found most interesting (besides the huge range in glycemic response to bread):
Participant #468 has a consistently higher response to glucose than to white bread. Participant #663 is the opposite. And participant #445 is still winning.
I truly wonder if there’s a gut microbe (or something) that’s involved here…
Posted in Advanced nutrition, chocolate, diet, Dietary fat, insulin, Leptin, microbe, microbiome, microbiota, Protein
Tagged calories, carbs, fat, fiber, insulin, nutrition, prebiotics, protein
“please stop asking gurus how many carbs you need to optimize health”
An interesting paper came out recently by Zeevi et al. (2015), showing, in part, that we’re all unique snowflakes (in some contexts).
Mini-rant: this study is in line with a lot of my beliefs about individuality in human biology. We don’t know all the mechanisms, but we do know that some people respond better to some interventions than others. We learn a lot from studies on diet, light, sleep, physical activity, etc., but the findings rarely/never apply equally to everyone (and some people experience completely opposite effects; eg, see studies where individual data are reported). LIGHT exposure can improve sleep quality in some but cause agitation in others. Low carb diets can help weight loss in some people but low fat is better for others. Dairy, wheat, protein, the ‘biome, and fibre/resistant starch all fall into this category. Sleep ‘requirements’ vary by person, season, geography, etc., etc… there’s no QED answers in many of these contexts.
anecdote: some people say they’ve never had better blood glucose than when they were having a few servings of beans/legumes per week; others just report bloating & farts (no bueno).
- The Atlantic ran a decent piece on this study (certainly more colorful than my take)
- Reddit AMA with some of the people involved in the study
In this particular study (video summary below): they continuously monitored the blood glucose responses in 800 people to all of their meals for a week, including a variety of test meals. Main result: many different responses, even to the same foods! An oversimplified example: some people had smaller relative postprandial glucose excursions after 50g carbohydrate from rice compared to 50g carb from potatoes, and other people responded oppositely. And friggin’ tomatoes?!
Translation: need to move beyond recommending #IIFYM.
Some foods were universally well-tolerated [in this population] in the context of mixed meals, like quinoa and salmon; other foods did the opposite, like chocolate chip cookies and sushi. And lastly, some foods like cottage cheese and hummus were good for some people but others.
[participant 445 is winning]
*In general, I don’t believe in labeling foods as categorically good or bad, which is pretty much confirmed by this study, but some patterns emerged wrt postprandial glucose excursions in this population…
Posted in Advanced nutrition, diabetes, diet, Dietary fat, fat, insulin, Leptin, microbiome, microbiota, Protein
Tagged calories proper, carbs, diet, fat, insulin, nutrition, prebiotics, protein
Similar to the glycemic index, which is an estimate of the rise in blood glucose after eating a particular food, the insulin index is an estimate of the rise in insulin after eating a particular food. In general, these indices are obvious: processed carbs have high glycemic and insulin indices, whereas whole foods are lower. Some exceptions are things like dairy and lean meat, which induce more insulin than you’d expect given to their low carbohydrate content…
When some protein-rich foods were discovered to induce insulin secretion, people thought this information might help type 1 diabetics more accurately calculate their insulin dose. Interesting rationale, worth testing.
Tl;dr: it didn’t work very well.
More of the protein-derived amino acids may have been incorporated into lean tissue, but the extra insulin load ended up causing hypoglycemia more often than not. Hypoglycemia is acutely more harmful than hyperglycemia, and is still quite harmful in the long-term. Some studies on incorporating the insulin index for type 1 diabetics are mixed, ie, increased or no change in risk of hypoglycemia, but no studies show it reduces the risk.
Posted in Advanced nutrition, diabetes, diet, Dietary fat, Energy balance, fat, insulin, Ketosis, Leptin, muscle, Protein
Tagged carbs, diet, insulin, ketosis, muscle, nutrition, obesity, Paleo, processed food, protein, sugar
This one has a bit for everyone.
Relationship of Insulin Dynamics to Body Composition and Resting Energy Expenditure Following Weight Loss (Hron et al., 2015)
I think study was actually done a few years ago, originally published here (blogged about here), and re-analyzed through the eyes of Chris Gardner. I think. (But it doesn’t really matter as the study design appears to be identical.)
Experiment: give someone an oral glucose tolerance test (75 grams glucose) and measure insulin 30 minutes later. Some people secrete more insulin than others (a marker of insulin resistance); these people also have a lower metabolic rate after weight loss = increased propensity for weight regain. However, if these people follow a low carbohydrate diet, then the reduction in metabolic rate is attenuated. Some people who don’t secrete a lot of insulin after a glucose load may do better in the long-run with a lower fat diet.
Posted in Advanced nutrition, circadian, diabetes, diet, fat, insulin, Ketosis, Leptin, Protein, sleep, TPMC
Tagged Atkins, body composition, calories proper, carbs, circadian rhythm, diet, energy balance, energy expenditure, ketosis, nutrition, protein