Friday, October 24, 2014

Testing hypotheses for high morning Blood Glucose

I've focused more on measurements of Hemoglobin A1c than blood sugar, as that gives a time average indication. Even so, my A1c numbers, while good for a diabetic at between 5% and 5.4%, are not great by Steve's targets. A value of 5.4% corresponds to an average BG of 108 mg/dL. Going the other way, having an average BG less than 100 mg/dL means an A1c of 5.1. The fact that my averages are much higher than my fasting levels during the day suggests that my post-meal levels, and early morning levels, are very much higher than I'd like. I've got a series of experiments underway looking at BG after eating, but what about overnight highs in Blood Glucose?

So I think this is a perfect setup for adaptive management.

There are two hypotheses for high morning blood glucose in a Type 2 diabetic. The "hormone hypothesis" posits that an increase in growth hormone production in the middle of the night triggers a cascade of events leading to the release of glucose from the liver. Presumably this is to set one up for a vigorous start to the day. In a healthy person this extra glucose triggers an insulin response, and blood glucose remains steady. In a person with insulin resistance (like me), the insulin response is not effective, and blood glucose rises. The second hypothesis is "The Somogyi effect", where low blood glucose values overnight trigger the the release of glucose from the liver to avoid too low blood sugar values. That also involves hormones, but they are activated for different reasons.

Which of these hypotheses is true does matter; under the 2nd hypothesis I should be able to avoid high morning sugar by making sure my overnight sugar levels don't drop too low. I could eat a snack before going to bed, for example. Under the hormone hypothesis there's not much I can do except to try harder to ameliorate the insulin resistance. I could start taking Metformin, which acts in two ways, first by suppressing liver production of glucose and second by reducing insulin resistance. Both of those actions should act directly on the dawn phenomenon.

I can also learn which of these hypotheses is true by monitoring my blood sugar. Ideally, I'd measure my blood sugar every hour or so all night ... hmm. That sounds like a sucky experiment. According to this article, I can get away with just measuring at bedtime, 3 a.m., and the morning.

So I tried it for 2 nights, and I think I've discovered a 3rd hypothesis, the "Drew Tyre Effect"! On the first night, 9pm 101, 3am 116, and 6am 122! OK, that's consistent with the hormone hypothesis, but maybe I missed a drop in BG between 9pm and 3am. So last night I took the middle measurement earlier, and 9:20pm 112, 12:25am 110, and 6:40am 116. My BG is high all night. 

So, a bit of reading on what stimulates Cortisol levels is warranted. As it happens, sleep deprivation stimulates cortisol production, so this could be an instance in which the observation of a process affects the process itself. I need one of those continuous glucose monitors!

Here's another hypothesis: I've been taking a fish oil supplement for the past 3 months after learning that I was low in tissue levels of EPA and DHA. However, it turns out that fish oil supplements can blunt insulin response and increase resting glucose levels. So looks like I have to wait 18 weeks and then try this experiment again.

And another hypothesis! I'm swimming in the damn things ... It turns out that taking a statin can interfere with blood glucose control. I starting taking 10 mg of Crestor every evening about the same time I started taking fish oil. Well, the results of my latest bloodwork will be very interesting. 

It's harder to be healthy when you're poor

I'm not poor. But I came across a very illustrative example of how eating real food is more expensive this week.

Wednesday, October 22, 2014

Walkabout Wednesday: peak meat, what math you should know, and Tiny Data.

The USA hit peak meat in 2004, Bryan McGill laid out a perfect math ecology curriculum, and Tiny Data should be all the rage in the near future.

Monday, October 20, 2014

Famine & the evolution of diet

One cornerstone assumption of a lot of diet theories based on emulating hunter-gatherer diets is that famine was a constant companion. Predictable seasonal famines occur in all environments, the dry season in the tropics and winter in the high latitudes. The just-so story goes like this: in a predictable feast-famine environment "thrifty genes" that take advantage of feast times to store fat in preparation for the lean times would be selected for. And when you take a population that has these thrifty genes and put them in a constant "feast" environment, they get fat and develop diabetes. Like the Pima Indians in North America*, and the Tokelau people in the south pacific. To avoid triggering these "thrifty genes", paleo diet proponents suggest avoiding the products of agriculture, both modern and historical.

Colette Berbesque and co-authors [1] decided to test the frequent famine assumption by looking at anthropological evidence of famine in a fairly sophisticated way. In particular, they controlled for the effects of habitat richness by only comparing hunter gatherers from warm climates (Effective Temperature > 13C) with agriculturalists, and by using a metric of habitat productivity (a linear combination of Net Primary Productivity and Effective Temperature) as a covariate. From their abstract, they found:
... if we control for habitat quality, hunter–gatherers actually had significantly less—
not more—famine than other subsistence modes.
Digging into the details though, we find that this is true for some measures of famine but not others. For instance, on the variables Occurrence, Severity, Persistence, Recurrence, and Contingency of famine warm climate hunter gatherers do better (that is, less famine). In terms of short term or seasonal famine however, there is no difference between warm climate hunter gatherers and agricultural peoples. And that's important, because it is seasonal famine that would lead to the evolution of thrifty genes. And there was plenty of time for such genes to arise in paleolithic people before the advent of agriculture, so the fact that agricultural peoples are no better at avoiding seasonal famine simply means the selection for these genes wouldn't go away after agriculture.

Although Berbesque et al. paint their research as a critique of the "paleo diet" approach, it seems to me that it reinforces a key tenet: paleolithic peoples had it better than their agricultural neighbors. Hunter gatherers do significantly better on  "ordinary nutritional conditions and endemic starvation", have no difference in seasonal famine, and less long term and unpredictable famine. Huh.

[1] J. Colette Berbesque, Frank W. Marlowe, Peter Shaw and Peter Thompson. 2014. Hunter−gatherers have less famine than agriculturalists. Biology Letters 10, 20130853.

*The Pima aren't necessarily a good example, as they were agricultural before becoming "modern western". It is interesting to me that the National Institute of Diabetes and Digestive and Kidney disease article I linked to focuses on the increase in fat in the Pima diet, rather than the exchange of whole grains for refined carbohydrate.

Thursday, October 16, 2014

Today is National Feral Cat Day

And I feel I should say something. After all, feral cats are an issue in our fair city, Lincoln NE, and I have some relevant expertise ...

Wednesday, October 15, 2014

Walkabout Wednesday: people vary, what should ecologists learn less of, and a Republican cries "Climate Change"!

This week I got a little pre-occupied and didn't spend alot of time following up things on the interwebs. I did meditate a lot.

My Health

It turns out that people's physiological responses to fructose vary. Unsurprising, but good that the mechanisms are getting worked out.

AND, researchers at Harvard have figured out how to get embryonic stem cells to act like pancreatic beta cells, sensing glucose levels in the environment and releasing insulin. Cures Type I diabetes in mice. Don't hold your breath waiting for the cure though. 

Your Education

Jeremy Fox ran a little poll last week asking what ecologists (graduate and undergraduate) should learn less of. The results didn't surprise me too much. Most popular "learn more" subjects are math, statistics and programming. It might surprise some to learn that I didn't say ecologists should learn more of those things. The trouble with any curriculum decision is that putting something in means you have to take something else out. At the undergraduate level I think chemistry could be reduced in programs focused on pre-medicine students. At least here at UNL they pratically get a minor in chemistry, which is fine if you're going to be a doctor, but if not they could use the space for more important things like evolution and natural history. I answered 'it depends' for what could be left out, because some graduate students will need more chemistry, some more physics, and maybe some more math, depending on the direction they want to go in. I answered 'Philosophy of Science' for what should be added. After all, its the foundation for all inference in science. No kidding. And typically ecologists take 0. Zip. Null. I recall the first day of my philosophy of science class at University of Alberta. The prof asked 'how many of you are Physics majors', and the front half of the class put up their hands. Then, 'how many of you are Philosophy majors', and the back half of the class put up their hands. Then, 'what about the rest of you'. I put up my hand. I looked around, and I was alone. 'And you're in?' Zoology ...?

Universities are increasingly run like corporations, says Noam Chomsky in some remarks transcribed from a speech to the Adjunct Faculty Association of the United Steelworkers. I learned some new words, (like neoliberal and precariat), and an interesting hypothesis that corporatization is a way to ensure students are appropriately indoctrinated. Load them up with student debt and limit their contact with faculty, and you've got a recipe for dependent and therefore controllable workers. I certainly see the focus on the bottom line at UNL as well as increased reliance on adjunct and non-tenured faculty. Or as I mentioned last week the dependence of the public R&D machine on graduate students and postdocs. Not sure about indoctrinating future workers part.

The news isn't all bleak, however. Apparently Michigan has increased funding for public higher ed, and Iowa State has hired 41% more full time faculty over the last 8 years while simultaneously reducing administration. Wow. How does UNL compare on that statistic?  Well, 2009 to 2013 we went from 1556 "general regular faculty" to 1644, an increase of 5.7%. However, "general regular faculty" includes Professors of Practice, lecturers and senior lecturers. Tenured faculty have actually decreased 3% while non-tenure faculty have increased 27%. Administrators and staff increased 3% over the same period. So, the question is, can we describe UNL as a cannibal rat infested ghost ship, as Rebecca Shuman characterizes public instutitions other than Michigan and Iowa State? Given that Fall semester student credit hour production only increased 2% between 2009 and 2013, I'd have to say yes.

Our Environment

Henry Paulson was secretary of the treasury in the years leading up to the 2008 crash. In this op-ed he highlights a few lessons for dealing with global climate change that he sees in the lead up to that recession.
The solution can be a fundamentally conservative one that will empower the marketplace to find the most efficient response. We can do this by putting a price on emissions of carbon dioxide — a carbon tax.
That sounds like it would be a good idea. I wonder why I haven't heard more about this idea in the 6 months since this was published.

Tuesday, October 14, 2014

Diabetes Management Experiment I

One of the key tenets of Adaptive Management is to "learn while doing", or using management actions to reduce uncertainties. In the management of Type 2 diabetes the real key is figuring out how your body responds to different meals. Meals are management actions, and the uncertainties are how one's body responds to each meal.

I just did one of these experiments. I've been trying to figure out why my A1c levels are representing an average blood glucose level higher than I measure before eating (pre-prandial). There are two possibilities. First, I know I have high blood glucose in the morning, which could be the "Dawn Phenomenon". The other possibility is that I experience high blood glucose levels after eating, a "post-prandial spike". The typical recommendation is to measure post-prandial blood glucose 2 hours after starting a meal. My post-prandial values then are typically pretty good, < 120 mg/dl.

So today I measured at 30, 60, and 90 minutes as well. The results are not good:

Minutes   BG
0              83
30            106
60            120
90            150
120          110

Check that out! A rise of more than 60 mg/dl! Now, if I'd eaten something loaded with carbohydrate... but no: stir fried vegies (cabbage, onions, carrots and green pepper. Not many carrots and green pepper either) along with 4 Lightlife Tofu dogs, and a couple tablespoons of Mayonnaise.

Now comes the difficulty with Adaptive Management. N=1. Even attempting to repeat the experiment I'll never replicate the conditions I had today exactly. However, the hypothesis that stirfried veg + tofu dogs isn't spiking my blood sugar just dropped in probability.