Category Archives: diabetes

Circadian arrhythmia in different types of obesity

This study was pretty interesting.

Three groups of women:

1) normal weight

2) gynoid obesity (stores more fat in hips & butt), defined by WC/HC < 0.85

3) android obesity (stores more fat in belly, which is rare in women), defined by WC/HC > 0.85

 

First, we get confirmation that insulin sensitivity (IS) is better in morning than evening.  But then we get these interesting glucose tolerance curves:

 

circadian-glucose-tolerance

 

Fat stored in your hips & butt is thought to be healthier than that stored in your belly region.  This is confirmed here.  Gynoid obesity, while exhibiting an attenuated AM/PM difference, was able to restore euglycemia by the end of the experiment at both time points.  Ie, gynoid obesity selectively improved IS in the evening.

 




 

Android obesity, which is more nefarious than gynoid (also confirmed here), had a similar though not as robust effect in the evening but deteriorated IS in the morning.

One potential interpretation: it’s better to have a little extra fat stored in your hips and butt than to be lean or have belly fat.  However, I have a qualm with that interpretation.  Healthy people show a robust circadian difference in glucose tolerance.  Just as insulin resistance (IR) is an accepted physiological phenomenon observed in some ketogenic dieters, I view this circadian difference, also, as physiological.

 

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Circadian timing with REV-ERB and PERIOD

The circadian proteins Bmal and casein kinase (CK) enhance and degrade Period (PER), respectively, by completely different mechanisms.  Both are necessary, but at different times of day… #context

Gross oversimplification: the Bmal party is kicked off in the morning by LIGHT, and acts to increase PER by night (among many, many other things).  As the day progresses, REV-ERB the Repressor slowly shuts down Bmal, so that peak PER occurs in the evening and doesn’t carry over until the next morning.  GSK3b activates REV-ERB the Repressor.  Lithium puts the system in fast forward, leading to phase advance* and ZZZ’s when timed right, at night… I think

 

Lithium GSK3b image

 

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Insulin resistance and obesity

Some people believe insulin resistance (IR) causes obesity, and they are not pleased when I say this is actually a controversial topic in the field…

“Bill isn’t toeing the company line.  Again.”

So I asked a simple question: if IR causes obesity, how?

 

 

The Common Response: 1) IR -> 2) hyperinsulinemia -> 3) more insulin = more fat mass.

However, this is flawed.

Easiest rebuttal (somewhat of a strawman, but whatevs): Barbara Corkey and her group has done a lot of work showing that insulin hypersecretion (caused by dietary additives, preservatives, weird chemicals, etc.) may actually precede & causes IR… not enough insulin hypersecretion to induce hypoglycemia, just enough to induce IR.

So that basically breaks the 1st step in the Common Response, but doesn’t really disprove the possibility that IR still causes obesity (or can cause obesity).

In any case, check out Corkey’s 2011 Banting Lecture.  Highly recommended, a lot of food for thought.

 

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the insulin-obesity hypothesis is under attack

…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:

 

 

Minn-Starvation-weight

 

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Social jet lag

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.

 

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Insulin resistance is a spectrum

The history of low fat diets is riddled with crappy low fat food-like products.

Food quality matters.

Free full article on Patreon! <- link

Take a group of obese people and assess insulin sensitivity however you like: some researchers demand nothing less than a hyperinsulinemic-euglycemic clamp (Gold Standard), others are OK with insulin levels during an oral glucose tolerance test.

Next, divide the people up based on this — there are a few ways you can do it.  You can: take the top half vs. the bottom half (a method which includes everyone); take the top third vs. bottom third (excluding the middle third); take the top quarter vs. bottom quarter (excluding the middle 50%), etc.

THIS MATTERS because in referencing this topic, many people claim most obese are insulin resistant.  They may be more insulin resistant than lean people, but even within obese people, there’s a spectrum, and the spectrum matters in this #context.

 

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Personalized Nutrition by Prediction of Glycemic Responses

“please stop asking gurus how many carbs you need to optimize health”

 

bananas cookies

An interesting paper came out recently by Zeevi et al. (2015), showing, in part, that we’re all unique snowflakes (in some contexts).

 

#context

#context

 

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).

End rant.

Background reading:

  1. The Atlantic ran a decent piece on this study (certainly more colorful than my take)
  2. 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.

 

bananas cookies[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…

#context

 

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The “Insulin Index”

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…

STORY TIME

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.

 

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“Insulin Dynamics”

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.

 

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Some nuances of Intermittent Fasting

Intermittent fasting (IF) is not a universal panacea, regardless of whether you’re not eating anything at all for a few days each week/month or just restricting your feeding window to a few hours per day.

Some protocols, eg, 20h fasting every second day, significantly improve insulin sensitivity in adipose tissue (Halberg et al., 2005). This is expected to make fat gain easier, and while this wasn’t meant to be a study on body composition per se…

 

body composition

 

After just a few weeks, things weren’t changing in a good way (NS).

 

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