Is Hypoglycemia Obesogenic? Is the GI Totally Worthless? Is Mild, But Chronic Stress Behind the Diabesity Pandemic? Is Leptin Obesogenic? And How Do You Calculate the Energy Requirements of Diabetics?

One of the mistakes researchers and dieters make time and again, using the scale as their only guide

Since I had a couple of interesting, but not earth-shatteringly exciting studies on obesity, body weight gain, the GI, leptin and a couple of other things lying around, I thought I'd compile a brief potpourri for you to get you on par with the helplessness with which researchers are still facing the diabesity pandemic. So don't expect any of the one-size-fits-it-all solutions the scientists still appear to be looking for from any of the following items. What you may find, however, is some inspiration when you read between the lines or follow up on the suggested reads, I mention. And if that's not the case, you can still browse previous articles on fat loss or simply go to the gym and try the fat loss example routine from the SuppVersity "Step By Step Guide for Your Own Workout Routine" or simply go to be early to preserve your circadian rhythm.

• Going "Hypo" time and again will make you fat (McNay. 2013) -- Usually you think of hyogylcemia as a sign of a lack of energy, yet despite the fact that this may well be the case this very lack in energy has recently been shown to exert obesogenic effects in a rodent model.
  
  

  

  Often a picture says more than 1000 words: Normal (left) and repeatedly hypoglycemic rodents after 8 months of weekly insulin injections (McNay. 2013)

  The weekly injections Ewan C McNay and his colleagues administered to their rodents and the subsequent episodes of hypoglycemia lead to profound weight gain in the absence of diabetes, hyperphagia, changes in hypothalamic NPY or POMC mRNA expression and  the other usual suspects that could explain this phenomenon. The one thing that's left is therefore what the researchers call a "multi-faceted deficit in metabolic regulation" (McNay. 2013) - interestingly enough the 69.5% higher body weight at 12 months went hand in hand with the usual laziness (-25% activity) of people whose brains are starving in abundance (e.g. type II diabetics).
  
  What remains to be seen, though, is whether similar effects would occur in response to "regular" non-insulin induced hypoglycemia. In view of the easy with which crash dieters and people with roller-coaster blood glucose levels gain weight, it is yet not unlikely that it is actually the avoidance of (reactive) hypoglycemia and not so so much the prevention of hyperglycemia that makes low GI diets successful for weight maintenance (for weight loss the picture is more complicated, since this will require a energy deficit and that's a game changer).

• Dietary glycemic index and load are not associated with type II diabetes risk in 12,403 Europeans (Sluijs. 2013) -- Apropos GI, scientists from the University Medical Center in Utrecht did not find statistical significant correlations dietary glycemic index and/or glycemic load and the risk to develop type II diabetes in in a subcohort of the European Prospective Investigation into Cancer and Nutrition Study (n = 12,403 participants).
  
  Even when they compared participants in the highest and lowest quantiles, the increase in risk was only 5% and 7% for GI and GL respectively. Since this is by no means the first study that suggests that the still propagated concept of the beneficial health effects "low GI diets" is faulty, I would suggest you rather watch the actual food items, than their respective glycemic indexes if you intend to ward off obesity and diabetes. Potatoes for example may have a high GI (including sweet potatoes, by the way), but their high potassium and overall mineral content, as well as the mere fact that you can hardly eat the same amount of total carbohydrates you can easily annihilate, when you are eating pasta still makes them one of the best sources of starchy carbs you have (learn more in the Potato Manifesto, Part I & II).

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  Figure 1: There were no statistically significant difference in terms of weight gain or loss, but the 2-week re-feed had a greater impact on blood glucose and insulin levels in the high GI group (Lagerpusch. 2013)

  There is use for the GI on a bulk or after a diet, but only if you are concerned about insulin sensitivity (Lagerpusch. 2013) -- While the general value of the GI as a means to distinguish good from bad carbohydrate sources is certainly questionable, the recently published results from a study that was conducted at the Institute of Human Nutrition and Food Science, of the -Albrechts University in Kiel, Germany, does suggest that monitoring the GI of your diet and adding additional fiber to reduce the insulin response to your meals can come quite handy, in phases, where you are particularly prone to store body fat. On a bulk, for example, or even more so when you have been dieting and are trying to return to a normal caloric intake.
  
  According to the results Lagerpusch et al. present in the November issue of the British Journal of Nutrition even healthy young men who were subjected to a 3-week diet phase (-50% in caloric intake) and subsequent overfeeding (+50% in caloric intake) the subjects in the high GI study arm had a 135% higher increase in fasting insulin levels during the refeed than those in the low GI group. In view of the fact that the glucose clearance (measured in an oral glucose tolerance test) was identical, it is not only no wonder that the weight gain did not differ either (see figure 1), but also unlikely that we would see significant differences as far as the fat gains are concerned (the latter were unfortunately not measured in the study at hand). At the same time, longer hyper-caloric high GI diets are certainly a risk factor for both insulin resistance and obesity, so that you are probably still at lower risk with 65g instead of 27g of fibre per day and a mean GI of 40 vs. 74.
  
  If you are interested in the influence of different diets on weight gain and health during overfeeding, I suggest you check out the following two SuppVersity posts: "194 Bananas in Three Weeks" and "A Tale of Macro- and Micronutrient Modifications".

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  Figure 2: Chronic mild stress leads to an overactivation of the HTPA and subsequen metabolic dysregulations (Takahashi. 2013)

  Further evidence that chronic mild stress is to blame for the obesity pandemic (Takahashi. 2013) -- As researchers from the Tohoku University Graduate School of Medicine in Japan report in the latest issue of the  American Journal of Physiology - Endocrinology & Metabolism, the localized re-setting of the clock genes in the liver, yet not the hypothalamic suprachiasmatic nuculeus (SCN), of BALB/c mice in response to chronic mild stress exposure elevated and phase-shifted serum corticosterone levels (see figure 2).
  
  Takahashi et al. argue that the observed changes are indicative of an overactivation of the HPA axis, which induced disturbances in the rhythmic expressions of core clock genes, e.g. Clock, Npas2, Bmal1, Per1 and Cry1 in the liver and subsequently circadian patterns of glucose and lipid metabolism-related genes such as the proliferator activated receptor (PPAR) family which favor the storage and hamper the oxidation of fatty acids.
  
  If you want to learn more about clock genes and how you can modify them, (re-)read the SuppVersity Circadian Rhythm Series!

• Scientists develop improved formula to calculate the resting energy expenditure of diabetics (Ikeda. 2013) -- While I would hope that you don't belong to the group who would have to use the new and improved formula scientists from the Department of Diabetes and Clinical Nutrition at the Kyoto University in Japan have now proposed, you may have clients or relatives who could benefit from its high predictive validity (78% +/- 103kcal vs. 50% for Harris-Benedict; 38% for Oxford, 42% for Liuand 63% for Ganpule):
  
  
  What you should keep in mind though, is that this equation was tested on Japanese individuals. Since we know from other studies that there are certain metabolic differences between people with different ethnic backgrounds I would remain a "healthy skeptic" as far as the outcomes of this equation are concerned - the same obviously goes for any other equation, e.g. the ones for athletes I provided in part III of the Female Athlete Triad series.

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  If you are interested in ways to modulate your leptin levels that may facilitate weight gain, I suggest you take a look at my second "Carbs Past 6PM Won't Make You Fat" post.

  Leptin induced weight gain? 13% more body fat in 2 weeks, when it hits the wrong part of the brain (Harris. 2013) -- With the mixed results from intervention trials, the enthusiasm around leptin has abated over the past months, the general consensus is yet still that leptin and leptin resistance loom large in the metabolic dysregulation that's at the heart of the diabesity pandemic. Against that background, the results Ruth B.S: Harris presents in her latest paper in the American Journal of Physiology - Endocrinology & Metabolism are unquestionably surprising.
  
  When Harris injected twice the amount of leptin (0.6 µg leptin/day) that had previously been shown to decreased 24 food intake, body fat and lean tissue, when it was injected into the third ventricle of the hindbrain, into the fourth ventricle of her lab rats, the rodents gained an almost incredible amount of 13% body fat within only 2 weeks! And that in the absence of statistically significant change in daily food intake, suggests an "increase in efficiency of energy utilization" (Harris. 2013). Fortunately, further experiments showed that the pro-obesogenic effects of leptin in the 4th ventricle was antagonized when both the 3rd and the 4th ventricle were exposed to leptin. In this scenario the leptin exposure of the 4th ventricle did even protect the lean mass of the rodents from the negative effects the exclusive exposure of the 3rd ventricle had. Overall, the study is yet somewhat chaotic and a clearcut message aside from "look people things are even more complex than we already thought", is probably not going to contribute to a solution of the obesity dilemma in the near future. 

There are, as usual more news on Facebook, some of them, such as the relation between hypothyroidism during pregnancy and the diabetes risk of the offspring later in life, are even related to the topic at hand. And if that's nothing you are interested, you may want to read about ...

• the non-existent effects of coffee consumption before bed on the sleep quality of habitual coffee drinkers (read more),
• the problem with inaccurate vitamin D tests and the absence of a reliable and scientifically sound definition of "vitamin D deficiency" (read more), or
• the strength promoting in-vitro effects of sodium bicarbonate, or in other words, a rather alkaline milieu on muscular force production (read more)

... and if neither of those can satisfy your thirst for more information from the realms of exercise and nutrition sciences, you can still wait for the next serving of facebook news or tomorrow's SuppVersity article :-)


References:

• Harris RB. Leptin-induced increase in body fat content of rats. Am J Physiol Endocrinol Metab. 2013 Dec 4.
• Ikeda K, et al. A new equation to estimate basal energy expenditure of patients with diabetes. Clinical Nutrition. 2013 [article in press] 
• Lagerpusch M, Enderle J, Later W, Eggeling B, Pape D, Müller MJ, Bosy-Westphal A. Impact of glycaemic index and dietary fibre on insulin sensitivity during the refeeding phase of a weight cycle in young healthy men. Br J Nutr. 2013 Nov 28:1-11.
• McNay EC, Teske JA, Kotz CM, Dunn-Meynell A, Levin BE, McCrimmon RJ, Sherwin RS. Long-term, intermittent, insulin-induced hypoglycemia produces obesity without hyperphagia or insulin resistance: a model for weight gain with insulin therapy. Am J Physiol Endocrinol Metab. 2013 Nov 20.
• Sluijs I, Beulens JW, van der Schouw YT, van der A DL, Buckland G, Kuijsten A, Schulze MB, Amiano P, Ardanaz E, Balkau B, Boeing H, Gavrila D, Grote VA, Key TJ, Li K, Nilsson P, Overvad K, Palli D, Panico S, Quirós JR, Rolandsson O, Roswall N, Sacerdote C, Sánchez MJ, Sieri S, Slimani N, Spijkerman AM, Tjønneland A, Tumino R, Sharp SJ, Langenberg C, Feskens EJ, Forouhi NG, Riboli E, Wareham NJ; on behalf of the InterAct consortium. Dietary Glycemic Index, Glycemic Load, and Digestible Carbohydrate Intake Are Not Associated with Risk of Type 2 Diabetes in Eight European Countries. J Nutr. 2013 Nov 28.
• Takahashi K, Yamada T, Tsukita S, Kaneko K, Shirai Y, Munakata Y, Ishigaki Y, Imai J, Uno K, Hasegawa Y, Sawada S, Oka Y, Katagiri H. Chronic mild stress alters circadian expressions of molecular clock genes in the liver. Am J Physiol Endocrinol Metab. 2013 Dec 4.

Predictive Value of Equations to Calculate Your Resting Metabolic Rate (RMR) Flawed: Results Can Be 14-29% Off

Would she still look so happy, if she knew that thee treadmill just lied to her?

I have written, said and, in person, even shouted it out often enough: Once you start to rely on the figures certain formulas generate (and this includes what your treadmill, your heart rate monitor etc. will produce, 'cause they use the same flawed formulas), you are lost.

The message of today's SuppVersity article is therefore by no means a new one. What's pretty new, though, is the study by V. Bonghana and colleagues from University of Campinas who have compared five predictive equations that are supposed to predict your and everyone else's basal (=excluding physical activity) energy demands (Bonghana. 2013).

"Start with a 15% energy deficit" - based on what?

The above, i.e. to start dieting by consuming ~15% less energy than you usually do, is my usual suggestion for anyone who's not in the "so fat that your health is in danger" zone, someone like you, maybe - someone who wants get rid of his/ her belly to finally see a at least the uppermost portion of his / her abs.

Table 1: The five equations the researchers used to calculate the predicted resting metabolic rate (RMR) that was then compared to the measured RMR (indirect calorimetry by respiratory gas analysis) of the 43 participants (Bonganha. 2013)

Now, what do you think would happen if this person was a postmenopausal women (of whom many, as we all know, love to "diet" exactly as they are told to, counting calories and what not) who is too lazy to follow my even more important advice to track her caloric intake for 2 weeks in order to get a "baseline reading"? What would happen if this woman, instead of doing just that simply used one of the calculators on the Internet and build her diet right according to the number the machine vomits out?

Figure 1: Comparison of the predicted resting metabolic rates and the mean difference to the "real" (=measured) RMR of the 43 healthy postmenopausal women who participated in the study (Bonghana. 2013)

Actually a cursory look at the data in figure 1 should suffice to tell you what the result would be. If she was lucky and the calculator used the rather uncommon Mifflin-St Jeor equation she would not lose a single pound, because she would end up right at the 1,063 kcal/day she, a 52-year young women, who's 159cm small has a totally age-appropriate BMI of 25kg/m², but a slightly high body fat level of 33%, just like the "average subject" in our experiment, needs to fuel her most basic metabolic demands (measured those are 1063.8 kcal/day). The former obviously implies that she did also take into account that she spends a few extra calories, even when she does not exercise.

Use the WHO calculation and you are lost

Guess how she got in in shape? Right! The EDC Program (learn more)

If she was not just as lucky and used the WHO equation as a baseline, she would not only overestimate her basal energy requirements by more than 30%. No, even with the 15% reduction she would be continuously gaining gaining wait... now, imagine she had also started to work out and had for once heard received some good advice, which is not to freak out about the weight gain, because it's all muscle. What? Right, she would be working away instead of towards her goal to lose weight and fat, 'cause one thing is sure.

Unless you expend more energy than you eat it is almost impossible to get rid of the belly. Unfortunately, simplistic calories in vs. calories out calculations won't help you find out whether this is the case..

The notion that exercise "alone" can, especially for those who are pretty chubby to begin with, have a "repartitioning effect" may still hold here, but it is more  likely that our imaginary post-menopausal training rookie is - if anything - gaining more muscle than fat and that's certainly not going to give her the look she is aspiring. In fact the situation would probably not be much different from the one in the study I had in the Facebook News a couple of days ago (Tibana. 2013).

Adding exercise on top of a proven (your N=1 experience) obesogenic diet rarely helps

In the course of this 8-week intervention study, the subjects, a group of 14 middle-aged (33.9 ± 8.6 years) overweight/obese women (body mass index - BMI 29.6 ± 4.1 kg/m²) underwent 24 sessions (3 times per week) of a whole body RT program with 3 sets of 8–12 repetitions maximum (RM). Unfortunately, for them without any dietary advice / incentive to modify the baseline diets that were obviously to blame for the extra-weight they were carrying.

Figure 2: Body mass, waist, hip, neck circumference, body adiposity index and visceral fat volume in middle-aged women before and after an 8-week 3x/week full body weight training intervention (Tibana. 2013)

The net result of this "intervention" was thus by no means representative of what you can achieve, when you really commit. If you discard the diet component, or even worse, fall for the common idea that you've worked out for an hour and could thus "afford" that piece of pizza, pie or panacotta, you are effectively bulking. Therefore, you should thus not be surprised, if you got strong and bulky, but don't see improvements in your body fat level, your waist line and any of the biochemical variables, i.e. fasting glucose, HbAIc, insulin,  triglycerides, HDL, and the TG/HDL ratio (not shown in figure 2), your doctor will be eyeballing.

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Without taking a "baseline reading" and accessing where you want to go, you ain't going to succeed (read more)

Bottom line: In conjunction, the results of the Bonghana and Tibana papers only underline the necessity to (a) make a baseline assessment of your current, individual food quantity and quality(!), before you embark on any kind of diet and (b) that the notion of "exercising the fat away" is only useful when you are not making the mistake to chart your dietary intake up against whatever you believe your exercise induced energy expenditure would look like. Even if it's not pizza, pasta and panacotta you are thinking of, when you look at the figure your treadmill or heart rate monitor calculated based on similarly whacky formulas as those used for the RMR, you are still lost whenever you put more faith into a impersonal arithmetics than the signals of your own body... and this, gentleman, is true irrespective of your age and sex.

If you still insist on calculating something, you may also want to take a look at Part III / III of the Female(?) Athlete Triad Series, but please be aware that I am not liable for the damage this type of calorie counting is going to do to your physique and your psyche.

References:

• Bonganha V, Libardi CA, Santos CF, de Souza GV, Conceição MS, Chacon-Mikahil MP, Madruga VA. Predictive equations overestimate the resting metabolic rate in postmenopausal women. J Nutr Health Aging. 2013;17(3):211-4.
• Tibana RA, Navalta J, Bottaro M, Vieira D, Tajra V, Silva AD, de Farias DL, Pereira GB, de Souza JC, Balsamo S, Cavaglieri CR, Prestes J. Effects of eight weeks of resistance training on the risk factors of metabolic syndrome in overweight /obese women - "A Pilot Study". Diabetol Metab Syndr. 2013 Feb 28;5(1):11.