Performance Research for August: Fat loss exercise

More cutting edge research on ways to deflate that spare tire and destroy that muffin top! Some great info on the supplement CLA, the fat vs fit debate, and other cool stuff. Running a little behind since technically it is October now, but all of these were published in August 2008.

On to the data

Beneficial effects of conjugated linoleic acid and exercise on bone of middle-aged female mice.

Banu J, Bhattacharya A, Rahman M, Fernandes G. Department of Medicine, Division of Clinical Immunology and Rheumatology, University of Texas Health Science Center at San Antonio, San Antonio, TX, 78229, USA.

Conjugated linoleic acids (CLA) are a group of polyunsaturated fatty acids that has recently been shown to have several beneficial effects on different diseases, including prevention of bone loss. The important feature of CLA is to reduce fat mass, thereby reducing body weight significantly.

Although loss of body weight is known to increase bone loss, there is increasing evidence that CLA maybe beneficial to bone. Another factor that can reduce body weight is exercise (EX). It is well established that moderate EX stimulates bone formation. In this study, we analyzed the changes in bone using pQCT densitometry in middle-aged C57Bl/6 mice fed CLA (0.5%) and/or exercised. Twelve-month-old mice were divided into the following groups: group 1, corn oil, sedentary (CO SED); group 2, corn oil, exercise (CO EX); group 3, CLA, sedentary (CLA SED); and group 4, CLA, exercise (CLA EX). Mice were maintained in the respective experimental regimens for 10 weeks, after which mice were scanned using DEXA and killed. The lumbar vertebrae, femur, and tibia were analyzed using pQCT densitometry. CLA, when given alone or in combination with EX, significantly reduced body weight and increased lean mass. CLA treatment also significantly increased bone mass. Further, additional increase in bone mass was observed in mice treated with a combination of CLA and EX in almost all the bone sites analyzed.

Conclusion: We conclude that CLA, when consumed as a dietary supplement along with moderate treadmill exercise, significantly increases bone mass in middle-aged female mice.

My Notes: I believe this is one of the first studies to look at CLA and bone! The HUGE downside is that the effects of CLA for fat loss appear to be VERY specific to species. It is awesome stuff IF you are a mouse or rat! The human studies for fat loss as not nearly as good. My guess is that the same thing probably applies here too. CLA appears to be "safe" so I wish more researchers would study it in humans, although I know first hand that is much higher on the "pain in the butt" factor for those conducting the research.

Whole-body skeletal muscle mass is not related to glucose tolerance or insulin sensitivity in overweight and obese men and women.

Kuk JL, Kilpatrick K, Davidson LE, Hudson R, Ross R. School of Kinesiology and Health Studies, Queen's University, Kingston, ON K7L3N6, Canada.

The relationship between skeletal muscle mass, visceral adipose tissue, insulin sensitivity, and glucose tolerance was examined in 214 overweight or obese, but otherwise healthy, men (n = 98) and women (n = 116) who participated in various exercise and (or) weight-loss intervention studies. Subjects had a 75 g oral glucose tolerance test and (or) insulin sensitivity measures by a 3 h hyperinsulinemic-euglycemic clamp technique. Whole-body skeletal muscle mass and visceral adipose tissue were measured using a multi-slice magnetic resonance imaging protocol.

Total body skeletal muscle mass was not associated with any measure of glucose metabolism in men or women (p > 0.10). These observations remained independent of age and total adiposity. Conversely, visceral adipose tissue was a significant predictor of various measures of glucose metabolism in both men and women with or without control for age and (or) total body fat (p < style="font-weight: bold;">

Conclusion: Although skeletal muscle is a primary site for glucose uptake and deposition, these findings suggest that unlike visceral adipose tissue, whole-body skeletal muscle mass per se is not associated with either glucose tolerance or insulin sensitivity in overweight and obese men and women.

My Notes: Rather surprising results, as I would have expect muscle mass to correlate well with insulin sensitivity. Visceral adipose (that spare tire area) was a predictor though! So time to drop some abdominal fat if you want better insulin sensitivity (which is a good thing). See this post on Fit or Fat
and Metabolic Flexibility for a literature review

Exercise but not diet-induced weight loss decreases skeletal muscle inflammatory gene expression in frail obese elderly persons.

Lambert CP, Wright NR, Finck BN, Villareal DT. Department of Internal Medicine, Washington University School of Medicine, Campus Box 8303, St. Louis, MO 63110, USA.

Many obese elderly persons have impaired physical function associated with an increased chronic inflammatory response. We evaluated 12 wk of exercise (aerobic and resistance) or 12 wk of weight loss (approximately 7% reduction) on skeletal muscle mRNAs for toll-like receptor-4 (TLR-4), mechanogrowth factor (MGF), TNF-alpha, and IL-6 in 16 obese (body mass index 38+/-2 kg/m2) older (69+/-1 yr) physically frail individuals. Vastus lateralis muscle biopsies were obtained at 0 and 12 wk and analyzed by real-time RT-PCR. Body composition was assessed by dual-energy x-ray absorptiometry. Body weight decreased (-7.5+/-1.2 kg, P=0.001) in the weight loss group but not in the exercise group (-0.3+/-0.8 kg, P=0.74). Fat-free mass (FFM) decreased (-2.9+/-0.6 kg, P=0.010) in the weight loss group and increased (1.6+/-0.6 kg, P=0.03) in the exercise group.

Exercise resulted in a 37% decrease in TLR-4 mRNA (P<0.05) style="font-weight: bold;">

Conclusion: In conclusion, exercise but not weight loss had a beneficial effect on markers of muscle inflammation and anabolism in frail obese elderly individuals.

Obesity and obstructive sleep apnea: Or is it OSA and obesity?

Carter R 3rd, Watenpaugh DE. Centre de Recherche du Service de Santé des Armées, La Tronche, France; United States Army Research Institute of Environmental Medicine, Natick, MA, USA.

Obstructive sleep apnea (OSA) consists of repetitive choking spells due to sleep-induced reduction of upper airway muscle tone. Millions of adults and children live unaware of this condition, which can have a profound affect on their health and quality of life. Obesity, gender, genetic, and hormonal factors mediate risk for OSA and interact in a multifaceted manner in the pathogenesis of this disease. Obesity is the most established and primary risk factor given that body mass index, visceral fat, and neck circumference are major predictors in the clinical expression of OSA. Many studies have shown weight loss or gain significantly impacts OSA severity. More recently, accumulating evidence indicates OSA promotes weight gain, obesity, and type II diabetes in a variety of ways, such that obesity and OSA form multiple interleaved vicious cycles. Thus, creative strategies to increase physical activity, improve diet, and otherwise facilitate weight management become particularly vital given the epidemics of obesity and OSA in the United States. In this regard, the American College of Sports Medicine recently launched the "Exercise is Medicine" (initiative exerciseismedicine.org). In the future, medications may emerge to treat obesity, OSA, and their sequelae with minimal side effects.

Conclusion: However, there are effective ways to approach these problems now without waiting for "the magic pill".

My Notes: Knowledge is key, but agreed that there is no "magic pill"

New Study---Fit and Fat?

Very interesting study! This adds more fuel to the "Fit vs Fat" debate. Is it OK to be a big over weight (or carry more body fat) IF you exercise? Or is it better to have a lower body fat, but maybe you don't exercise as much?

My thought is that maybe Metabolic Flexibility will be a way to differentiate between the groups? For some more info on that, see this post on Metabolic Inflexibility.

"Identification and Characterization of Metabolically Benign Obesity in Humans"

Norbert Stefan, MD; Konstantinos Kantartzis, MD; Jürgen Machann, PhD; Fritz Schick, PhD; Claus Thamer, MD; Kilian Rittig, MD; Bernd Balletshofer, MD; Fausto Machicao, PhD; Andreas Fritsche, MD; Hans-Ulrich Häring, MD

Arch Intern Med. 2008;168(15):1609-1616.

Background Obesity represents a risk factor for insulin resistance, type 2 diabetes mellitus, and atherosclerosis. In addition, for any given amount of total body fat, an excess of visceral fat or fat accumulation in the liver and skeletal muscle augments the risk. Conversely, even in obesity, a metabolically benign fat distribution phenotype may exist.

Methods In 314 subjects, we measured total body, visceral, and subcutaneous fat with magnetic resonance (MR) tomography and fat in the liver and skeletal muscle with proton MR spectroscopy. Insulin sensitivity was estimated from oral glucose tolerance test results. Subjects were divided into 4 groups: normal weight (body mass index [BMI] [calculated as weight in kilograms divided by height in meters squared], <25.0), style="font-weight: bold;">Conclusions: A metabolically benign obesity that is not accompanied by insulin resistance and early atherosclerosis exists in humans. Furthermore, ectopic fat in the liver may be more important than visceral fat in the determination of such a beneficial phenotype in obesity.

Performance Research for July: Fat Loss

More great studies showing the benefits of lifting weights and proper nutrition!

Separate and combined effects of exercise training and weight loss on exercise efficiency and substrate oxidation.

Amati F, Dube JJ, Shay C, Goodpaster BH. University of Pittsburgh.

Purpose: Perturbations in body weight have been shown to affect energy expenditure and efficiency during physical activity. The separate effects of weight loss and exercise training on exercise efficiency or the proportion of energy derived from fat oxidation during physical activity, however, are not known. The purpose of this study was to determine the separate and combined effects of exercise training and weight loss on metabolic efficiency, economy and fat oxidation during steady state moderate submaximal exercise.

Methods: 64 sedentary older (67+/-.5) overweight to obese (30.7+/-.4kg/m(2)) volunteers completed four months of either diet induced weight loss (WL,n=11), exercise training (EX,n=36) or the combination of both interventions (WLEX,n=17). Energy expenditure, gross efficiency (GE), economy (EC) and proportion of energy expended from fat (EF) were determined during a one-hour submaximal (50% of VO2peak) cycle ergometry exercise before the intervention and at the same absolute work rate after the intervention.

Results: EX increased GE by 4.7+/-2.2%. EC was similarly increased by 4.2+/-2.1% by EX. The addition of concomitant WL to EX (WLEX) resulted in greater increases in GE (9.0+/-3.3%) compared to WL alone but not compared to EX alone. These effects remained after adjusting for changes in LBM. The proportion of energy derived from fat during the bout of moderate exercise increased with EX and WLEX but not with WL.

Conclusion: Exercise training, either alone or in combination with weight loss, increases both exercise efficiency and the utilization of fat during moderate physical activity in previously sedentary, obese older adults. Weight loss alone, however, neither significantly improves efficiency nor utilization of fat during exercise.

My Notes: Very cool study---more evidence that you need to change your LIFESTYLE and get in some exercise for benefits, not just dropping some weight

Resistance training and timed essential amino acids protect against the loss of muscle mass and strength during 28 days of bed rest and energy deficit.

Brooks N, Cloutier GJ, Cadena SM, Layne JE, Nelsen CA, Freed AM, Roubenoff R, Castaneda-Sceppa C. Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, Massachusetts, USA. Spaceflight and bed rest (BR) result in losses of muscle mass and strength.

Resistance training (RT) and amino acid (AA) supplementation are potential countermeasures to minimize these losses. However, it is unknown if timing of supplementation with exercise can optimize benefits, particularly with energy deficit. We examined the effect of these countermeasures on body composition, strength, and insulin levels in 31 men (ages 31-55 yr) during BR (28 days) followed by active recovery (14 days). Subjects were randomly assigned to essential AA supplementation (AA group, n = 7); RT with AA given 3 h after training (RT group, n = 12); or RT with AA given 5 min before training (AART group, n = 12). Energy intake was reduced by 8 +/- 6%. Midthigh muscle area declined with BR for the AA > RT > AART groups: -11%, -3%, -4% (P = 0.05). Similarly, greatest losses in lower body muscle strength were seen in the AA group (-22%). These were attenuated in the exercising groups [RT (-8%) and AART (-6%; P < p =" 0.05)." style="font-weight: bold;">

Conclusion: Combined resistance training with AA (amino accid) supplementation pre- or postexercise attenuated the losses in muscle mass and strength by approximately two-thirds compared with AA supplement alone during BR and energy deficit. These data support the efficacy of combined AA and RT as a countermeasure against muscle wasting due to low gravity.

My Notes: See my last post about a protein carb drink around your training time! Very beneficial

The danger of weight loss in the elderly.

Miller SL, Wolfe RR. R.R. Wolfe, 4301 W. Markham St., #806, Little Rock, AR 72205, Ph:501-526-5708,Fax: 501-526-5710, e-mail:rwolfe2@uams.edu. Aging is generally accompanied by weight loss made up of both fat mass and fat-free mass. As more people, including elderly, are overweight or obese, weight loss is recommended to improve health. Health risks are decreased in overweight children and adults by dieting and exercise, but the health benefits of weight loss in elderly, particularly by calorie restriction, are uncertain. Rapid unintentional weight loss in elderly is usually indicative of underlying disease and accelerates the muscle loss which normally occurs with aging. Intentional weight loss, even when excess fat mass is targeted also includes accelerated muscle loss which has been shown in older persons to correlate negatively with functional capacity for independent living. Sarcopenic obesity, the coexistence of diminished lean mass and increased fat mass, characterizes a population particularly at risk for functional impairment since both sarcopenia (relative deficiency of skeletal muscle mass and strength) and obesity have been shown to predict disability. However, indices of overweight and obesity such as body mass index (BMI) do not correlate as strongly with adverse health outcomes such as cardiovascular disease in elderly as compared to younger individuals. Further, weight loss and low BMI in older persons are associated with mortality in some studies. On the other hand, studies have shown improvement in risk factors after weight loss in overweight/obese elderly. The recent focus on pro-inflammatory factors related to adiposity suggest that fat loss could ameliorate some catabolic conditions of aging since some cytokines may directly impact muscle protein synthesis and breakdown. Simply decreasing weight may also ease mechanical burden on weak joints and muscle, thus improving mobility.

Conclusion: Until a strategy is proven whereby further loss of muscle mass can be prevented, weight loss by caloric restriction in individuals with sarcopenic obesity should likely be avoided.

My Notes: Ideally, you want to drop FAT and KEEP MUSCLE! Weight training and proper nutrition can help you do it

Exercise attenuates the weight-loss-induced reduction in muscle mass in frail obese older adults.

Frimel TN, Sinacore DR, Villareal DT. Program in Physical Therapy, Washington University School of Medicine, St. Louis, MO, USA.

PURPOSE: To evaluate the effect of adding exercise to a hypocaloric diet on changes in ppendicular lean mass and strength in frail obese older adults undergoing voluntary weight loss.

METHODS: Thirty frail older (age, 70 +/- 5 yr) obese (body mass index, 37 +/- 5 kg.m) adults were randomly assigned to 6 months of diet/behavioral therapy (diet group, n = 15) or diet or behavioral therapy plus exercise that incorporated progressive resistance training (PRT; diet + exercise group; n = 15). Body composition was assessed using dual-energy x-ray absorptiometry, and muscle strength was assessed using one-repetition maximum. The volume of upper extremity (UE) and lower extremity (LE) exercise training was determined by multiplying the average number of repetitions performed by the average weight lifted during the first three exercise sessions and during the last three exercise sessions of the study. RESULTS: The diet and the diet + exercise groups had similar (P > 0.05) decreases in weight (10.7 +/- 4.5 vs 9.7 +/- 4.0 kg) and fat mass (6.8 +/- 3.7 vs 7.7 +/- 2.9 kg). However, the diet + exercise group lost less fat-free mass (FFM; 1.8 +/- 1.5 vs 3.5 +/- 2.1 kg), LE lean mass (0.9 +/- 0.8 vs 2.0 +/- 0.9 kg), and UE lean mass (0.1 +/- 0.2 vs 0.2 +/- 0.2 kg) than the diet group (P < r =" 0.64-0.84;" style="font-weight: bold;">

CONCLUSION: Exercise added to diet reduces muscle mass loss during voluntary weight loss and increases muscle strength in frail obese older adults. Regular exercise that incorporates PRT (progressive resistance training) should be used to attenuate muscle mass loss in frail obese older adults on weight-loss therapy.

My Notes: See my above comments!


Inflammatory Response to a High-fat, Low-carbohydrate Weight Loss Diet: Effect of Antioxidants.

Peairs AT, Rankin JW. 1Department of Human Nutrition, Foods, and Exercise, Virginia Tech, Blacksburg, Virginia, USA. The objective of this study was to test the hypothesis that the inflammatory response to a high-fat, low-carbohydrate weight loss diet (HF) we previously observed was due to oxidative stress. Nineteen overweight subjects (BMI > 27 kg/m(2)) were randomly assigned to either an antioxidant supplement (AS) (1 g vitamin C/800 IU vitamin E) or a placebo (P) group and provided with a HF for 7 days. Fasted pre- and post serum samples were measured for markers of inflammation (C-reactive protein (CRP), interleukin-6 (IL-6), and monocyte chemoattractant protein-1 (MCP-1)), oxygen radical absorbance capacity (ORAC), and glucose, whereas urine was measured for oxidative stress (8-epi-prostaglandin-F(2alpha) (8-epi)). HF resulted in significant reductions in weight (-3.2%), glucose (-18.7%), and MCP-1 (-15%) (all P < p =" 0.076)." r =" -0.501)," r =" -0.863)," r =" -0.546)" style="font-weight: bold;">

Conclusion: Longer term diet-controlled studies are necessary to further explore the trend for a differential response in CRP (C-reactive protein) with antioxidant supplementation.

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!

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.

References

1. The Cell Physiology of Biphasic Insulin Secretion -- Rorsman et al. 15 (2): 72 -- Physiology. 2007(12/12/2007).

2. Amiel S. A., S. Caprio, R. S. Sherwin, G. Plewe, M. W. Haymond, W. V. Tamborlane. Insulin resistance of puberty: a defect restricted to peripheral glucose metabolism. J Clin Endocrinol Metab. 72(2):277-282, 1991.

3. Arslanian S., C. Suprasongsin. Insulin sensitivity, lipids, and body composition in childhood: is "syndrome X" present? J Clin Endocrinol Metab. 81(3):1058-1062, 1996.

4. Bornas X., J. Llabres, M. Noguera, A. Pez. Sample entropy of ECG time series of fearful flyers: preliminary results. Nonlinear Dynamics Psychol Life Sci. 10(3):301-318, 2006.

5. Bruce D. G., D. J. Chisholm, L. H. Storlien, E. W. Kraegen. Physiological importance of deficiency in early prandial insulin secretion in non-insulin-dependent diabetes. Diabetes. 37(6):736-744, 1988.

6. Donahue R. P., R. D. Abbott. Central obesity and coronary heart disease in men. Lancet. 2(8569):1215, 1987.

7. Ducimetiere P., J. Richard, F. Cambien. The pattern of subcutaneous fat distribution in middle-aged men and the risk of coronary heart disease: the Paris Prospective Study. Int J Obes. 10(3):229-240, 1986.

8. Goedecke J. H., A. St Clair Gibson, L. Grobler, M. Collins, T. D. Noakes, E. V. Lambert. Determinants of the variability in respiratory exchange ratio at rest and during exercise in trained athletes. Am J Physiol Endocrinol Metab. 279(6):E1325-34, 2000.

9. Goodpaster B. H., J. He, S. Watkins, D. E. Kelley. Skeletal muscle lipid content and insulin resistance: evidence for a paradox in endurance-trained athletes. J Clin Endocrinol Metab. 86(12):5755-5761, 2001.

10. Goodpaster B. H., D. E. Kelley. Skeletal muscle triglyceride: marker or mediator of obesity-induced insulin resistance in type 2 diabetes mellitus? Curr Diab Rep. 2(3):216-222, 2002.

11. Goodpaster B. H., S. Krishnaswami, H. Resnick, et al. Association between regional adipose tissue distribution and both type 2 diabetes and impaired glucose tolerance in elderly men and women. Diabetes Care. 26(2):372-379, 2003.

12. Heffernan K. S., C. A. Fahs, K. K. Shinsako, S. Y. Jae, B. Fernhall. Heart rate recovery and heart rate complexity following resistance exercise training and detraining in young men. Am J Physiol Heart Circ Physiol. 293(5):H3180-6, 2007.

13. Henquin J. C., M. Nenquin, P. Stiernet, B. Ahren. In vivo and in vitro glucose-induced biphasic insulin secretion in the mouse: pattern and role of cytoplasmic Ca2+ and amplification signals in beta-cells. Diabetes. 55(2):441-451, 2006.

14. Javorka M., J. Javorkova, I. Tonhajzerova, A. Calkovska, K. Javorka. Heart rate variability in young patients with diabetes mellitus and healthy subjects explored by Poincare and sequence plots. Clin Physiol Funct Imaging. 25(2):119-127, 2005.

15. Juhl C. B., O. Schmitz, S. Pincus, J. J. Holst, J. Veldhuis, N. Porksen. Short-term treatment with GLP-1 increases pulsatile insulin secretion in Type II diabetes with no effect on orderliness. Diabetologia. 43(5):583-588, 2000.

16. Kaplan D. T., M. I. Furman, S. M. Pincus, S. M. Ryan, L. A. Lipsitz, A. L. Goldberger. Aging and the complexity of cardiovascular dynamics. Biophys J. 59(4):945-949, 1991.

17. Kelley D. E., B. H. Goodpaster. Skeletal muscle triglyceride. An aspect of regional adiposity and insulin resistance. Diabetes Care. 24(5):933-941, 2001.

18. Kelley D. E., J. He, E. V. Menshikova, V. B. Ritov. Dysfunction of mitochondria in human skeletal muscle in type 2 diabetes. Diabetes. 51(10):2944-2950, 2002.

19. Kelley D. E., L. J. Mandarino. Fuel selection in human skeletal muscle in insulin resistance: a reexamination. Diabetes. 49(5):677-683, 2000.

20. Kelley D. E., F. L. Thaete, F. Troost, T. Huwe, B. H. Goodpaster. Subdivisions of subcutaneous abdominal adipose tissue and insulin resistance. Am J Physiol Endocrinol Metab. 278(5):E941-8, 2000.

21. Lake D. E., J. S. Richman, M. P. Griffin, J. R. Moorman. Sample entropy analysis of neonatal heart rate variability. Am J Physiol Regul Integr Comp Physiol. 283(3):R789-97, 2002.

22. Lapidus L., C. Bengtsson, B. Larsson, K. Pennert, E. Rybo, L. Sjostrom. Distribution of adipose tissue and risk of cardiovascular disease and death: a 12 year follow up of participants in the population study of women in Gothenburg, Sweden. Br Med J (Clin Res Ed). 289(6454):1257-1261, 1984.

23. Laplaud D., R. Menier. Reproducibility of the instant of equality of pulmonary gas exchange and its physiological significance. J Sports Med Phys Fitness. 43(4):437-443, 2003.

24. Lewis M. J., A. L. Short. Sample entropy of electrocardiographic RR and QT time-series data during rest and exercise. Physiol Meas. 28(6):731-744, 2007.

25. Nagai N., T. Matsumoto, H. Kita, T. Moritani. Autonomic nervous system activity and the state and development of obesity in Japanese school children. Obes Res. 11(1):25-32, 2003.

26. Nagai N., T. Moritani. Effect of physical activity on autonomic nervous system function in lean and obese children. Int J Obes Relat Metab Disord. 28(1):27-33, 2004.

27. Nistala R., C. S. Stump. Skeletal muscle insulin resistance is fundamental to the cardiometabolic syndrome. J Cardiometab Syndr. 1(1):47-52, 2006.

28. Oakes N. D., P. Thalen, E. Aasum, et al. Cardiac metabolism in mice: tracer method developments and in vivo application revealing profound metabolic inflexibility in diabetes. Am J Physiol Endocrinol Metab. 290(5):E870-81, 2006.

29. Ogden C. L., M. D. Carroll, L. R. Curtin, M. A. McDowell, C. J. Tabak, K. M. Flegal. Prevalence of overweight and obesity in the United States, 1999-2004. JAMA. 295(13):1549-1555, 2006.

30. Olshansky S. J., D. J. Passaro, R. C. Hershow, et al. A potential decline in life expectancy in the United States in the 21st century. N Engl J Med. 352(11):1138-1145, 2005.

31. Perseghin G., P. Scifo, F. De Cobelli, et al. Intramyocellular triglyceride content is a determinant of in vivo insulin resistance in humans: a 1H-13C nuclear magnetic resonance spectroscopy assessment in offspring of type 2 diabetic parents. Diabetes. 48(8):1600-1606, 1999.

32. Pietrobelli A., M. S. Faith, D. B. Allison, D. Gallagher, G. Chiumello, S. B. Heymsfield. Body mass index as a measure of adiposity among children and adolescents: a validation study. J Pediatr. 132(2):204-210, 1998.

33. Pincus S. Approximate entropy (ApEn) as a complexity measure. Chaos. 5(1):110-117, 1995.

34. Pincus S., R. E. Kalman. Not all (possibly) "random" sequences are created equal. Proc Natl Acad Sci U S A. 94(8):3513-3518, 1997.

35. Pincus S. M. Orderliness of hormone release. Novartis Found Symp. 227:82-96; discussion 96-104, 2000.

36. Pincus S. M. Approximate entropy as a measure of system complexity. Proc Natl Acad Sci U S A. 88(6):2297-2301, 1991.

37. Pincus S. M., I. M. Gladstone, R. A. Ehrenkranz. A regularity statistic for medical data analysis. J Clin Monit. 7(4):335-345, 1991.

38. Pincus S. M., J. D. Veldhuis, A. D. Rogol. Longitudinal changes in growth hormone secretory process irregularity assessed transpubertally in healthy boys. Am J Physiol Endocrinol Metab. 279(2):E417-24, 2000.

39. Platisa M. M., V. Gal. Dependence of heart rate variability on heart period in disease and aging. Physiol Meas. 27(10):989-998, 2006.

40. Platisa M. M., V. Gal. Reflection of heart rate regulation on linear and nonlinear heart rate variability measures. Physiol Meas. 27(2):145-154, 2006.

41. Porta A., T. Gnecchi-Ruscone, E. Tobaldini, S. Guzzetti, R. Furlan, N. Montano. Progressive decrease of heart period variability entropy-based complexity during graded head-up tilt. J Appl Physiol. 103(4):1143-1149, 2007.

42. Richman J. S., J. R. Moorman. Physiological time-series analysis using approximate entropy and sample entropy. Am J Physiol Heart Circ Physiol. 278(6):H2039-49, 2000.

43. Ryan S. M., A. L. Goldberger, S. M. Pincus, J. Mietus, L. A. Lipsitz. Gender- and age-related differences in heart rate dynamics: are women more complex than men? J Am Coll Cardiol. 24(7):1700-1707, 1994.

44. Someshwar J., S. Someshwar, K. C. Perkins. The obese adolescent. Pediatr Ann. 35(3):180-186, 2006.

45. Storlien L., N. D. Oakes, D. E. Kelley. Metabolic flexibility. Proc Nutr Soc. 63(2):363-368, 2004.

46. Stump C. S., E. J. Henriksen, Y. Wei, J. R. Sowers. The metabolic syndrome: role of skeletal muscle metabolism. Ann Med. 38(6):389-402, 2006.

47. Takarada Y., H. Takazawa, N. Ishii. Applications of vascular occlusion diminish disuse atrophy of knee extensor muscles. Med Sci Sports Exerc. 32(12):2035-2039, 2000.

48. Toubro S., T. I. Sorensen, C. Hindsberger, N. J. Christensen, A. Astrup. Twenty-four-hour respiratory quotient: the role of diet and familial resemblance. J Clin Endocrinol Metab. 83(8):2758-2764, 1998.

49. Veldhuis J. D., M. L. Johnson, O. L. Veldhuis, M. Straume, S. M. Pincus. Impact of pulsatility on the ensemble orderliness (approximate entropy) of neurohormone secretion. Am J Physiol Regul Integr Comp Physiol. 281(6):R1975-85, 2001.

50. Veldman R. G., M. Frolich, S. M. Pincus, J. D. Veldhuis, F. Roelfsema. Growth hormone and prolactin are secreted more irregularly in patients with Cushing's disease. Clin Endocrinol (Oxf). 52(5):625-632, 2000.

51. Wells J. C., M. S. Fewtrell. Is body composition important for paediatricians? Arch Dis Child. , 2007.