Sleep and the Metabolic Syndrome

ACSM
Off to ACSM this Wed, so drop me a line if you are going to be there! Hope to see some of you there and I will have updates as soon as possible

Another sleep study!
Since we are on the topic of sleep, here is more evidence that sleep may mess up your body. The interesting part is that short and LONG sleep duration seem to have an effect. It will be interesting to see more data on this in the future as it is conflicting on some areas currently (e.g abdominal obesity). There are some other growing data (hahaha, bad attempt at humor) to suggest that lack of sleep interferes with insulin sensitivity which could promote a growing waistline! (REF). In the meantime, your mom was right once again that you need your sleep!

Take Away
Short sleep duration compared with 7 to 8 hours of sleep is associated with greater risk for metabolic syndrome and metabolic syndrome criteria of abdominal obesity, elevated glucose, and elevated triglycerides, but not BP and HDL cholesterol.

Long sleep duration compared with reference criteria is associated with increased risk for metabolic syndrome and abdominal obesity but not with increased glucose, triglyceride level, BP, or low HDL cholesterol level.

Self-Reported Sleep Duration is Associated with the Metabolic Syndrome in Midlife Adults

Conclusion: "These data suggest that sleep duration is a significant correlate of the metabolic syndrome. Additional studies are needed to evaluate temporal relationships among these measures, the behavioral and physiologic mechanisms that link the two, and their impact on subsequent cardiometabolic disease."

From Medscape

May 21, 2008 — Risk for metabolic syndrome was associated with sleep duration, according to the results of a cross-sectional community-based cohort study reported in the May issue of Sleep.

"Short and long sleep duration have been linked to various risk factors for cardiovascular disease," write Martica H. Hall, PhD, from the University of Pittsburgh School of Medicine in Pennsylvania, and colleagues. "In the present study, we evaluated the relationship between sleep duration and presence of the metabolic syndrome, which is a cluster of physiologically interrelated risk factors for cardiometabolic disease."

In the Adult Health and Behavior Project registry, 1214 participants aged 30 to 54 years were divided into 4 groups on the basis of their reported sleep duration. American Heart Association/National Heart Lung and Blood Institute criteria were used to define the metabolic syndrome. The hypothesis that sleep duration significantly correlates with the metabolic syndrome and its components was tested with logistic regression.

The rate of observed metabolic syndrome was 22%, similar to that of published health statistics for US adults. Adjusted odds for metabolic syndrome were increased 45% in both short and long sleepers vs those sleeping 7 to 8 hours per night. Sleep duration was also associated with individual components of the metabolic syndrome (abdominal obesity, elevated fasting glucose, and hypertriglyceridemia). However, after further adjustment for use of antihypertensive medication, prevalence of the metabolic syndrome and its components remained increased only in short-duration sleepers.

"These data suggest that sleep duration is a significant correlate of the metabolic syndrome," the study authors write. "Additional studies are needed to evaluate temporal relationships among these measures, the behavioral and physiologic mechanisms that link the two, and their impact on subsequent cardiometabolic disease."

Limitations of this study include possibly insufficient power to evaluate relationships between sleep duration and the blood pressure component of the metabolic syndrome, as well as the use of cross-sectional data, which cannot address questions of causality.

"Additional experimental and prospective observational studies are needed to evaluate the extent to which sleep duration affects, or is affected by, the metabolic syndrome, abdominal obesity, glucose and lipid metabolism, and blood pressure," the study authors conclude. "Although the present study evaluated a community sample of healthy adults, relationships between sleep and the metabolic syndrome might differ in important ways in other populations. Finally, identification of the proximal behavioral and biologic pathways by which sleep affects components of the metabolic syndrome is essential to developing treatment strategies to augment behavioral and pharmacologic interventions for cardiometabolic disease.

The National Institutes of Health supported this study. Two of the authors have disclosed various financial relationships with Pro Consulting, Actelion, Arena, Cephalon, Eli Lilly, GlaxoSmithKline, Merck, Neurocrine, Neurogen, Pfizer, Respironics, Sanofi-Aventis, Sepracor, Servier, Stress Eraser, and Takeda.

Source: Sleep. 2008;31:635-643 and Medscape

New Study--Insulin, Exercise and Metabolism

New study time!

Here is another study talking about nutrient timing.

Effect of timing of energy and carbohydrate replacement on post-exercise insulin action
Stephens BR, Sautter JM, Holtz KA, Sharoff CG, Chipkin SR, Braun B.
Appl Physiol Nutr Metab. 2007 Dec;32(6):1139-47


The concept has been around for a few years now and it underscores the importance of WHEN in addition to WHAT you eat.

In general, exercise enhances the body's ability to use insulin. Insulin is a storage hormone and is most often mentioned in the storage of excess fatty acids into fat cells (yes, adding to your "muffin top"). Controlling insulin may help your fat loss progress then. While this is a drastic over simplification of many many processes, better insulin sensitivity is viewed as a good thing. A way to increase this is to exercise! Score another one for exercise.

The interesting part about this study was that they took subjects and reduced their insulin sensitivity and then determined the effect of exercise. They concluded that a bout (singular) of exercise enhanced insulin even when carbs and protein were replaced. So, even if you burn 200 calories and then replace them with 200 calories, your insulin sensitivity should still be better than if you never burned them at all. Further evidence that movement/exercise is good for you!
They mention that lean, health subjects that they put into a temporary state of insulin insensitivity may still keep a high level of "metabolic flexibility"; so they can "recover" with less exercise than some who possess less metabolic flexibility. If you are interested in metabolic flexibility, see my review on it.

We don't need more evidence to show that exercise is good for us, but it does shine light on the mechanisms that may be happening.

If you have enjoyed this, I need to thank Alan Aragon for reviewing this study in his first Research Review that he puts out. In it he reviews several studies and provides awesome insights into each. I highly highly recommend you check it out by clicking here. It is WELL worth the 10 clams a month. I get ZERO money to say this and make no money off of anyone that signs up at his site. He does a great job of doing all of the "leg work" for you!

Reasarch Round Up, Coconut Oil, Optimal Foods?

Research Round Up time for January. Here are just a few studies I found interesting.
Enjoy!

Gastric Banding Surgery May Help Promote Remission of Type 2 Diabetes in Obese Patients
According to the study, "of the 60 patients enrolled, 55 (92%) completed the 2-year follow-up. Remission of type 2 diabetes was achieved by 22 (73%) in the surgical group and 4 (13%) in the conventional-therapy group."
Pretty amazing difference and appears to be related to weight loss. Most likely there are more feedback loops going on than we realize! It used to be thought that fat cells sat on their collective fat asses all day and did nothing, but now we know they are involved in all sorts of regulation.
Link here

Caffeine Increases Ambulatory Glucose and Postprandial Responses in Coffee Drinkers With Type 2 Diabetes

This debate has been going on for some time now. There is evidence on both sides and diabetics are different from healthy people and there are probably differences depending if they used coffee or just caffeine. See this link for a roundtable with Dr. John Beradi, Dr. Kalman and Dr. Lonnie Lowery from 2002. Link here

Concentration of Vitamin E Linked to Physical Decline in Older Persons
The study stated, "In a logistic regression analysis that was adjusted for potential confounders, only a low concentration of vitamin E (<1.1> significantly associated with subsequent decline in physical function"
What? It means that it a study of a group of free living people, Vit E concentration was associated (does not mean that it is causative) with less issues as people aged. Score another one for Vit E (although not all studies have been positive). It appears they only looked at one type of Vit E (alpha tocpherol).
Link here

Brief, Intensive Therapy for OCD Altered Brain Activity, Improved Symptoms
Yet another study showing how incredible neuroplasticity is in the brain, especailly in this case to a cognitive form of therapy. Neuroplasticity is a fancy term that means the brain can adapt to many changes and quite quickly. It was not long ago that researchers believe the brain would not change much, especially as you age. Newer researcher is showing that this is not true.
Link here

Muscle Vibration May Retrain Abnormal Sensorimotor Organization in Focal Hand Dystonia
Score another one for the amazing ability of the body to adapt!
Link here


Question and Answer Time
Q: Should there be more attention paid to an individual's unique fuel needs to better help them stay in a healthy weight range/ avoid Syndrome X, etc..?

Maybe we should should look at appropriate food mixes (fats/proteins/carbs) pertaining to the individual (assuming you get the right amount of exercise). Thoughts?

Your question about fuel needs is a good one. I think in a healthy body, you can use some protein (generally not a lot for energy needs since it is caloric intensive) and either carbs or fats. This can be measured in the lab by looking at the RER (respiratory exchange ratio). For info on RER click here

A RER ratio of 0.7 is 100% fat, 0.85 is 50/50 carbs/fat and 1 is 100% carbs (glycogen, etc).

You are probably familiar with the crossover over theory that as the intensity of the exercise increases, the body shifts more to carb usage. What many forget is that after high intensity work, the REPAYMENT of the disturbance from homeostasis (EPOC, afterburn, etc) is almost all fat metabolism. This is the main reasons that many recommend interval work for fat loss.

Of course everyone is different and your body can change quite well from one fuel to the next over time, shown by athletes on low carb diets even doing quite well still .

I personally like the idea of Metabolic Flexibility since it may be a way to customize fuel source or show that it doesn't make any difference. We know as someone gets closer to a diabetic condition, they have a much harder time using different fuel sources and get closer to "locking into" one--they lose their flexibility. Click here for more info than you ever cared about on it!

Q: What are your thoughts on coconut oil? Should I be using it? Some say it is great and others cry that there is too much saturated fat?

Coconut Oil is mostly saturated, of that it is about 44.6% lauric acid, 16.8% myristic acid a 8.2% palmitic acid and 8% Caprilic Acid. Different types of saturated fat may have different effects on blood cholesterol levels, as is there individual differences. Click here for a reference

Jeff Volek and friends has shown that in a low carbohydrate environment, the type of fat may have less or even no effect on blood cholesterol.

Coconut oil is a major source of medium chain trigylcerides (MCTs), but I am not sold that they are amazing. If you remember back in the mid 90s, they were touted as an ergogenic aid (increases performance) but tasted like crap and were not all that effective.

Coconut oil is also lacking in high amounts of (essential fatty acids) EFAs. They are essential since your body can NOT make them. Coconut oil is fine to use for cooking since it has a relatively high smoke point, but make sure you get your EFAs first and there is nothing all that magical about it in my opinion (which is open to change at any time-hehhe).

Take away on coconut oil
Get in your EFAs first in fish oil and omega 3s like flax oil.

For all you wanted to know on fats check out this article by Dr. John Berardi The F Word.

That is all for now! Any questions, post them in the comments
Rock on
Mike N

Metabolic Inflexibility Literature Review

Below is a shorter literature review I did as part of my PhD research. It can be on the dry side, but the take away is that as your body gets closer to a Metabolically INflexible state (e.g. diabetes) you have a much harder time process any food and turning it into a good fuel sources.

If you are very Metabolically Flexible, you can adapt to virtually any fuel source (e.g. various foods). Now this is not an argument for going crazy and eating Ho Hos and Krispy Kremes, there are limits!

The point is that every is different and perhaps there is a way to quantify how metabolically efficient each person's body is without subjecting them to IVs and sticks in the arm for hours at a time.

Any questions, let me know and I will be happy to discuss. Big thank you to my advisor Dr. Don Dengel and Dr. George Biltz for the ideas, background, and all the support.

Enjoy

Mike N

METABOLIC INFLEXIBILITY

It is no secret that in the United States, the rate of obesity in children is on the rise. In fact, childhood obesity in the US has tripled over the last 40 years and doubled in the past 15 years

(32). About 40% of adolescents seen in the University of West Virginia pediatric clinic have body mass index (BMI) greater than 85% for gender and age (44). Body fat and its distribution is related to cardiovascular disease, hypertension and type 2 diabetes, all diseases that are considered to have an “incubation period” during childhood and adolescence (51). In 2003-2004 17.1% of US children and adolescents (age 2 to 19) were overweight (defined as at or above the 95^th percentile of the sex specific BMI for age growth charts) (29). If the current epidemic of child and adolescent obesity continues at the same rate, life expectancy could be shortened by two to five years in the coming decades(30) and it will be the first time in recent history that life

expectancy has decreased.

LITERATURE REVIEW

Metabolic Flexibility

Due to possible discontinuities in both the supply and demand for energy, humans need a “clear capacity to utilize lipid and carbohydrate fuels and have the ability to transition between them.” (18). This capacity is a healthy state and termed “Metabolic Flexibility”. It is hypothesized that metabolic inflexibility may play a role in various disease processes such as the metabolic syndrome that may even start in childhood (3, 27, 28, 46). Location of body fat may affect

disease risk also and data from prospective studies using waist to hip ratio or waist circumference confirmed that abdominal obesity is more closely associated with disease risk than total body fatness(6, 7, 22).

A key to understanding metabolic flexibility is the vital role of insulin. In humans, insulin is a regulatory hormone synthesized in the pancreas within the beta cells (β-cells) of the islets of Langerhans. Insulin can be characterized by two phases an initial (cephalic phase) driven by the nervous system and a sustained secondary phase (1). Some data indicated that variations in prestimulatory glucose can secondarily affect the magnitude and pattern of subsequent glucose-induced insulin secretions (13). Humans in a healthy state with normal insulin

metabolism have the ability to effectively switch from primarily a fat metabolism to a carbohydrate metabolism. Also, in human subjects that reach a stage in the metabolic syndrome characterized by insulin resistance and glucose intolerance bordering on frank diabetes, there is still considerable beta-cell capacity demonstrating a clear absence of the normal initial peak of insulin secretion (5, 45). Skeletal muscle is a major player in energy balance due to its metabolic activity, storage capacity for both glycogen and lipids, and its effects on insulin sensitivity (9-11). Obesity/visceral fat, transient state of puberty, ethnicity, genetic factors, and physical inactivity all may lead to insulin resistance (2).

Elevated lipid content and intramuscular triglyceride (IMTG) are both linked to insulin

resistance (20)and thus compromise efficient lipid utilization. Perseghin et al. (31) used magnetic resonance spectroscopy (MRS) to report that lipids contained within muscle fibers were strongly correlated with the severity of insulin resistance. In metabolically inflexible subject, lipid oxidation may fail to increase with fasting and fail to suppress with hormonal insulin elevation. Lowered post-absorptive fatty acid oxidation leads to excess accumulation of IMTGs and begins a downward spiral. Interestingly, endurance trained athletes also have an increased IMTG level, but remain insulin sensitivity (perhaps from increased turnover rate) (9).

Kelley et al. (17) (as shown in Figure 1 below) showed that under basal fasting conditions glucose uptake and oxidation are normal or even increased in obese subjects compared with lean subjects. Fatty acid uptake is also normal, but fatty acid oxidation is lower and its storage is elevated in the obese group which may explain why they have a higher body fat as they are more apt to store fat.

During a hyperinsulinaemic euglycaemic clamp condition the differences between lean and obese are quite different. In lean subjects, glucose uptake increased 10 fold with both oxidation and storage primarily contributing while fatty acid uptake decreased equally dramatically. In

obese subjects however, glucose uptake, oxidation and storage are reduced; which is quite a different response from the lean group.

Figure 1 (47) shows the contributions of lipid and glucose oxidation to resting energy expenditure of the leg. Obese subjects derived relatively less energy from lipid oxidation during basal conditions; showing a blunted fat burning response. During insulin-stimulated conditions, lean subjects show a greater suppression of lipid oxidation compared to the obese group under

the same conditions.

Figure 1 from Kelley et al. 1999

In summary, Kelley et al. (17) presented data from subjects with type 2 diabetes showing metabolic inflexibility as obese subjects derived relatively less energy from lipid oxidation during basal conditions (P<0.01). Lean subjects showed a greater suppression of lipid oxidation during insulin-stimulated conditions (p<0.01). As shown in Figure 2 below, lean subjects have a different response compared to obese and diabetic's subjects as carbohydrate oxidation is increased (19).

Figure 2 from Kelley et al. (19)

Assessment of Metabolic Inflexibility

One way to assess metabolic flexibility is by the infusion of drugs (insulin, glucose, etc) to alter the metabolic environment. The downside is that this is more difficult to use in a clinic, requires more specialized training, and is not generally an option for children due to its invasive nature. Metabolic inflexibility is also dynamic in nature and the data collected are normally for acute settings and brief time periods only. An ideal method of assessment would be non invasive and able to collect dynamic data.

HRV

A noninvasive measure of a dynamic system is done currently by the collection of cardiac data via heart rate variability (HRV) (40). HRV analysis has been used extensively to assess autonomic control of the heart under various physiologic conditions. Most often linear analysis is done in both the time and frequency domain.

There are some data to suggest a difference in HRV for obese and non-obese individuals (25). It is well know that the autonomic nervous system ANS) plays an important role in regulating energy expenditure and body fat content, but to what extent is not exactly clear. Nagai, et al. (25) studied 42 non-obese and obese healthy school children where both groups were matched for age, gender, and height. ANS activity was assessed by HRV power spectral analysis. The results showed that the obese children had reduced sympathetic as well as parasympathetic nerve activity which could be a factor in preventing and treating obesity.

Activity is also known to affect HRV (26). Nagai et al. (26) presented data that lean active children demonstrated a lower resting heart rate (HR) as well as higher total power (TP), low frequency (LF), and high frequency (HF). LF reflects mixed sympathetic (SNS) and parasympathetic (PNS) activity, HF reflects PNS activity and TP evaluating the overall ANS activity. In contrast, obese-inactive group showed significantly lower TP, LF and HF. These data suggest obese children have reduced sympathetic and parasympathetic nervous activities as compared to lean children with similar physical activity levels. This autonomic reduction that is associated with the amount of body fat in inactive state may be an important factor for the onset or development of childhood obesity. The good news is that regular physical activity could contribute to enhance the ANS activity in both lean and obese children (26).

There are some data to suggest alterations in HRV in young patients with diabetes (14). Autonomic neuropathy is a common complication of diabetes mellitus (DM) and the aim of the study was to assess HRV changes during prolonged (40 minute) supine rest in 17 young patients with DM compared to an aged matched healthy control group. HRV analysis consisted of time/frequency domains, Poincare and sequence plots and sample entropy. The study found that HRV was able to distinguish cardiac dysregulation in young patients with DM from a control group. However, it did not find any significant difference in sample entropy between the groups, perhaps due to the subtle nature of the cardiovascular impairment in young DM patients (14). Data from Porta et al. (41) used SampEn and ApEn to analyze HRV during a head-up tilt test and concluded that with short duration data SampEn was significantly more reliable at producing accurate entropy scores.

HRV provides a non invasive method that is able to capture data in a dynamic fashion, but to date it has very limited data regarding its relation to metabolic inflexibility.

Sample Entropy

Entropy, in the original context of thermodynamics is a measure of system disorder and randomness. Approximate entropy was first coined by Pincus et al. (36) in 1991 as a way to quantify the dynamic control of a system (such as HR control) and possibly analyze many other “random” sequences (34). The promise of approximate entropy (ApEn) is that it can classify complex systems with only 100 data values in diverse setting that include both deterministic chaotic and stochastic processes (34). To date, ApEn has been used in the analysis of medical data (37), cardiology (16, 43) and neurohormonal responses (15, 35, 38, 49, 50).

The ApEn algorithm counts each sequence as matching itself to avoid the occurrence of ln (0) in the calculations. ApEn is heavily dependent on the record length and is uniformly lower than expected on short records (42). It is also lacking in relative consistency meaning that if ApEn for one data set is higher than another, it should but does not remain higher for all conditions tested (33).

Sample entropy (SampEn) was developed to reduce the bias of ApEn as it does not count self-matches. Richman et al. (42) defines SampleEn as “precisely the negative natural logarithm of the conditional probability that two sequences similar for m points remain similar at the next point, where self-matches are not included in calculating probability.” So a lower value of SampEn indicates more self-similarity (and thus less variability). SampEn is defined in terms (m,r, N) where m is the length of sequences to be compared, r is the tolerance for accepting matches and N is the length of the time series. Another benefit of SampEn is that it does not use a template-wise approach when estimating conditional probabilities as it is in essence an event-counting statistic (42). In a study by Richman et al. (42) SampEn agreed much better than ApEn statistics with theory for random numbers with known probabilistic character over a broad range of operating conditions and it has successful been used to calculate HRV on very short ECG mV recordings (10 to 60 seconds); so it does not appear to require long periods of data collection (4). HRV calculated by SampEn has been used in studies on recovery post exercise training (12, 24) and alterations due to disease and aging (39). Lake et al. (21)performed a sample entropy analysis of neonatal HRV in an attempt to predict sepsis and found that entropy falls before clinical signs of neonatal sepsis and also that missing data points were well tolerated.

RER

The RER is the ratio of the volume of CO2 to O2 and can be measured with a metabolic cart to collect expired gases. The RER at steady state is displayed as a ratio between 0 .7 to 1.0 where 0.7 corresponds to 100% fat metabolism, 0.85 corresponds to 50% fat and 50% carbohydrate metabolism and 1 corresponds to 100% carbohydrate metabolism.

RER has been found to be reproducible during exercise under standardized conditions (23), but factors such as age, gender, dietary substrate intake, insulin, and plasma free fatty can influence the selection of substrates during exercise and hence alter RER(8, 48).

IMPLICATIONS

With the rise in obesity, it will be imperative to have a method to determine which children are on the fast track to further metabolic damage. Current methods such as insulin clamps may be effective, but they require more training on the clinician side, more difficult to obtain IRB approval and many times will not be used children due to their invasive nature. Future studies may be conducted on newer non-invassive methods to determine metabolic inflexibility and potentially investigate the effects of various forms of exercise and nutrition methods to combat obesity in children and target those in high risk groups.

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