High Dose Caffeine Restores Insulin Sensitivity and Limits Total as Well as Visceral Fat Gain Due to High Sugar Diets

High Dose Caffeine Restores Insulin Sensitivity and Limits Total as Well as Visceral Fat Gain Due to High Sugar Diets

caffeine coffee fat gain glucose management health high sugar insulin sensitivity lose fat obesity sugar type II diabetes visceral fat

Yes, the study at hand is on caffeine, but the results are relevant for coffee, too.

A decade ago, the medical community though coffee would dehydrate you, would make you insulin resistant and would increase your risk of heart disease. Recent studies show that coffee does not negatively affect your hydration status (Killer. 2014), that higher coffee consumption is associated with reduced diabetes risk and increasing your coffee consumption can reduce your risk of T2DM (Akash. 2014) and that a "daily intake of ∼2 to 3 cups of coffee appears to be safe and is associated with neutral to beneficial effects" on coronary heart disease, congestive heart failure, arrhythmias, and stroke (O'Keefe. 2013).

Against that background it may not be as surprising as it would have been 10 years ago that Joana C. Coelho, et al. (2016) found caffeine to be able to restores insulin sensitivity and glucose tolerance in high-sucrose diet rats. And yet, I personally believe that it is still worth pointing out the results of this study as the high sucrose diet the mice were fed is the same "high sugar diet" about which you will read all over the news that it is to blame for the obesity and diabetes epidemic.

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Against that background, it is particularly interesting to take a closer look at the data from Coelho's study, because it is the first to actually provide a valid explanation for the observed improvements in glucose sensitivity in response to the ingestion of caffeine.

Figure 1: 16-wk food intake, weight gain, fat gain and visceral fat gain according to caffeine intake (Coelho. 2016).

Now, the bad news is that significant effects were only observed for the highest dose of caffeine, ie..e 1g/L drinking water. That appears to be ridiculously high, but is in fact only "very high". If you do take into consideration that a wistar rat consumes only 100 ml/kg body weight per day, that's a dosage equivalent of 100 mg/kg for a rodent and thus ~16 mg/kg for a human being or ~6-7 cups of coffee (over a 24h period).

University of Memphis: Caffeine can help control the increase in blood lipids and oxidation after inhaling (10 minutes) a high calorie + high fat milk shake, controlled trial involving twelve healthy men shows (Crone. 2016).

Yes, the dosage is high, but actually less may have more benefits, and...  the most relevant benefits (reduced fat gain) were seen at a dosage that would be equivalent to only 4-5 cups of coffee, which happens to be roughly what epidemiological studies show to be in the zone of maximal benefits. Don't mistake this as a recommendation to guzzle liters of coffee, though... and that even if another recent study shows that 400mg of caffeine will lower the fatty acid onslaught and oxidation 12 men experience after consuming a large high fat milk-shake (Crone. 2016)... and speaking of coffee: you may also want to make sure to get a dark roast, because the latter has just been found to improve glucose metabolism and redox balance even if it is low in caffeine (Di Girolamo. 2016). 

While I am not sure how healthy the chronic consumption of these amounts of caffeine actually is. I am aware of several people who get their 6-7 cups of regular coffee per day and are in perfect health. With that being said, the latter may be at least partly due to the the highly beneficial effects of caffeine on the expression of glucose transporter 4 (GLUT4) and insulin receptor expression and phosphorylation (not shown in Figure 2) in the visceral fat depots of coffee connaisseurs.

Figure 2: Effects of different doses of caffeine on GLUT4 and insulin receptor expression in rats (Coelho. 2016).

The above elevations were accompanied by profound increases in protein kinase B (Akt) expression and activity, as well - an observation the scientists regard as being evidence of the fact that "[c]hronic caffeine administration improved whole-body glucose homeostasis and insulin signaling pathways in adipose tissue" (Coelho. 2016).

This conclusion cannot be questioned. What can be questioned, though, is the scientists assumption that this would occur only with high doses of caffeine and in response to increases in GLUT4 and insulin receptor expression in the visceral fat. Why's that? Well take a look at the figure in the bottom line: it shows that significant improvements in glycemia were improved at all dosages. The latter wouldn't have been possible if the lower dosages wouldn't have had an effect on glucose uptake, as well. Whether that's an effect in muscle cells (which would be great), needs further investigation. The previously discussed effects of caffeine on muscle glycogen storage (learn more), on the other hand, would suggest just that: an effect on skeletal muscle, and or a reduction in gluconeogenesis which could, among other things, be triggered by coffee's / caffeine's ability to inhibit the reactivation of glucocorticoids by 11β-hydroxysteroid dehydrogenase type 1" (Atanasov. 2006).

As you can see sign. improvements in glycemia occured even with the lowest amount of caffeine in the drinking water. And that in spite of the fact that the GLUT4 and insulin receptor levels in the visceral fat did not increase significantly... well, maybe those in the rodents' muscle did?

Bottom line: I am not suggesting that the rodent study at hand would provide enough evidence to suggest that everyone should drink at least 4 cups of high caffeine coffee per day. What I do suggest, however, is that the study at hand provides more evidence on potential mechanisms that explain why coffee drinkers are plagued less often by metabolic disease.

With that being said, I would like to remind you that the abuse of caffeine to combat a lack of sleep and/or overtraining may make you dig a deep black hole out of which you will be able to crawl only within weeks of abstinence... and I am talking about abstinence from caffeine and exercise, assuming that it was the combination of both that got your into trouble | Comment on Facebook!

References:

• Akash, Muhammad Sajid Hamid, Kanwal Rehman, and Shuqing Chen. "Effects of coffee on type 2 diabetes mellitus." Nutrition 30.7 (2014): 755-763.
• Atanasov, Atanas G., et al. "Coffee inhibits the reactivation of glucocorticoids by 11β-hydroxysteroid dehydrogenase type 1: A glucocorticoid connection in the anti-diabetic action of coffee?." FEBS letters 580.17 (2006): 4081-4085.
• Coelho, Joana C., et al. "Caffeine Restores Insulin Sensitivity and Glucose tolerance in High-sucrose Diet Rats: Effects on Adipose Tissue."
• Crone, et al. "Impact of Meal Ingestion Rate and Caffeine Coingestion on Postprandial Lipemia and Oxidative Stress Following High-Fat Meal Consumption." Journal of Caffeine Research (2016): Ahead of print. DOI: 10.1089/jcr.2016.0004.
• Di Girolamo, Filippo Giorgio, et al. "Roasting intensity of naturally low-caffeine Laurina coffee modulates glucose metabolism and redox balance in humans." Nutrition (2016).
• Killer, Sophie C., Andrew K. Blannin, and Asker E. Jeukendrup. "No evidence of dehydration with moderate daily coffee intake: a counterbalanced cross-over study in a free-living population." PloS one 9.1 (2014): e84154.
• O'Keefe, James H., et al. "Effects of habitual coffee consumption on cardiometabolic disease, cardiovascular health, and all-cause mortality." Journal of the American College of Cardiology 62.12 (2013): 1043-1051.

Cure! Diabetes With 8 + 24 Week Diet Intervention: 40% Stay Normo-Glycemic After Switching from VLCD to Normal Diet

Cure! Diabetes With 8 + 24 Week Diet Intervention: 40% Stay Normo-Glycemic After Switching from VLCD to Normal Diet

diabesity diabetes diabetes cure health lose fat obesity T2DM very-low-calorie-diet VLCD

If gaining body fat triggers T2DM, is is not surprising that losing it, cures it.

From the SuppVersity Facebook News you will remember that studies have shown that type II diabetes can be send into remission with "nothing" but a very low energy diet (Steven. 2015). The question scientists still had to answer, though, was whether the astonishing improvements in glycemia and overall health could be maintained on an energy-sufficient diet. In a newstudy from the Newcastle University scientists did now try to confirm just that by combining an 8-week dieting phase with a stepped return to isocaloric diet based on a structured, individualized (isocaloric) program of weight maintenance.

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Glucose control, insulin sensitivity, insulin secretion, and hepatic and pancreas fat content were quantified at baseline, after return to isocaloric diet, and after 6 months to permit the primary comparison of change between post–weight loss and 6 months in responders.

Table 1: Fasting anthropometric and metabolic data in responders and nonresponders at baseline, after VLCD and return to isocaloric eating, and after the 6-month weight maintenance period (Steven. 2016).

To qualify as "responder" and thus patient who successfully reversed his diabetes, the subjects, thirty individuals with T2DM who had been suffering from T2DM for either either short- (<4 years) or long (<8 years)-duration, had to achieve a fasting blood glucose <7 mmol/L - and that not just after the initial 6 weeks, but after return to isocaloric diet.

Figure 1: The weight loss speaks in favor of the efficacy of the diet intervention in both groups; filled responders, open circles non-responders (Steven. 2016).

What did the diet look like? The VLCD consisted of a liquid diet formula (43% carbohydrate, 34% protein, and 19.5% fat; 2.6 MJ/day [624 kcal/day]; OPTIFAST; Nestle Nutrition, Croydon, U.K.) taken as three shakes per day. In addition, up to 240 g of nonstarchy vegetables was consumed, making total energy intake 624–700 kcal/day. Participants were encouraged to drink at least 2 L of calorie-free beverages per day and to maintain their habitual level of physical activity. To maximize adherence, one-to-one support was provided weekly by telephone, e-mail, text message, or face-to-face contact (S.S.).

During stepped food reintroduction, shakes were gradually replaced by solid food over 7 days; with one meal replacing a shake every 3 days. Isocaloric intake was determined from resting energy expenditure measured by indirect calorimetry using an open circuit calorimeter (Quark RMR; COSMED, Rome, Italy) and a canopy hood and ended up ~1/3 below their previous obesogenic food intake - no wonder that they got diabetic before at an energy intake that was ~30% above what they'd needed to stay in a healthy body fat range. Physical activity was encouraged, but food behaviors were the priority.

As the average weight loss in Figure 1 tells you, all but one subject that was excluded after the initial 8-week VLCD phase, achieved a highly significant weight loss. What not all subjects achieved, however, was the desired diabetes remission. To be more precise, only 40% of the participants (12 of 30) achieved the targeted fasting glucose <7.0 mmol/L levels (responders) after return to isocaloric eating (to put that in perspective | even RYGB weight loss surgery achieves only 9% remission rates; albeit measured over 14 vs. 4 months | Wood. 2015). Since that's in spite of similar weight loss, the question is: What is it that made the difference between responders and non-responders? The answer is complex and consists of many factors:

• The responders (n = 12 [8 males, 4 females]) had a shorter diabetes duration (3.8 +/- 1.0 vs. 9.8 +/- 1.6 years, P = 0.007) 
• The responders were also younger (52.0 +/- 2.9 vs. 59.9 +/- 2.1 years, P = 0.032) than nonresponders (n = 17 [7 males, 10 females]). 
• Responders were more likely to suffer from diabetes for a short(er) duration (9 of 15 of the short-duration and 3 of 14 of the long-duration groups).
• At baseline, responders had lower fasting glucose(8.9 +/- 0.7 vs. 13.2 6 0.6 mmol/L, P < 0.001) and HbA1c (7.1 +/- 0.3 vs. 8.4 6 0.3% [55 +/- 4 vs. 68 +/- 3 mmol/mol], P = 0.01). 

In addition, the responders had a lower total fat mass than the nonresponders at baseline (P = 0.04) (see Table 1) and didn't try as many (failed) treatment options, such as diet control (five vs. two); metformin only (six vs. four); metformin and sulfo nylurea (one vs. seven); metformin, sulfonylurea, and insulin (zero vs. two); metformin, sulfonylurea, and thiazolidi nedione (zero vs. one); and insulin only (zero vs. one), as the nonresponders did before participating in the study at hand.

Diabetes can be cured by dieting down below your personal fat threshold! A previous study led by Professor Roy Taylor from 2011, who commented on the study at hand in press release stating that "[t]he study also answered the question that people often ask me - if I lose the weight and keep the weight off, will I stay free of diabetes?" and answering his own question as follows: "The simple answer is yes!" In the same press release from the Newcastle University, Taylor highlights that the results of the study at hand "supports our theory of a Personal Fat Threshold. If a person gains more weight than they personally can tolerate, then diabetes is triggered, but if they then lose that amount of weight then they go back to normal" and adds "[t]he bottom line is that if a person really wants to get rid of their Type 2 diabetes, they can lose weight, keep it off and return to normal."

It is important to point out that the study at hand is part of a growing body of evidence showing that people with Type 2 diabetes who successfully lose weight can reverse their condition (Lim. 211; Steven. 2015)- probably because the fat loss correlates with a reduced fat deposition and increased function in / of the pancreas.

Figure 2: While there were no sign. differences in weight loss, there were other antropometric and related differences between the two groups: BMI, body fat %, triglycrides and the insulin resistance of the liver (Stevens. 2016).

And with a larger trial involving 280 free-living patients is already underway, it may only a question of time before people can no longer ignore that type II diabetes, which is triggered by bad lifestyle choices, can be reversed by healthy ones. This can be "tough" as Allan Tutty, 57, from Sunderland, who transformed his health by taking part in the study and is now

"eat[ing] normal foods though [...] less than [he] used to, and enjoy[ing] takeaways and chocolate but not on a regular basis so [he has] maintained my lower weight [and] changed [his life]completely thanks to this research" (Tutty in press release),

says; and still, I am pretty sure that, just like Tutty who says that, "with [his] diabetes in remission, I haven't looked back", those who are able and willing to follow Tutty's example won't look back either.

The elevated liver enzymes observed in the study point, once again, to the liver - Learn how to help your liver manage your glucose metabolism in this SuppVersity Classic.

Dieting is a diabetes cure, but one that does not work for everyone - yet? While it is not clear whether a longer weight-loss phase that would have brought the non-responders to similarly low bodyfat percentages as the responders wouldn't have changed the results, we have to be honest:  losing weight is easy, but eating 30% less than before, because that's all you need w/ your now normal weight is difficult... too difficult for many, probably.

With that being said, it should be obvious that further research is necessary to determine the factors that distinguish responders from non-responders and whether the latter simply failed to pass their "personal fat threshold" as Professor Taylor's remarks suggest | Comment!

References:

• Lim, Ee Lin, et al. "Reversal of type 2 diabetes: normalisation of beta cell function in association with decreased pancreas and liver triacylglycerol." Diabetologia 54.10 (2011): 2506-2514.
• Steven, S., and R. Taylor. "Restoring normoglycaemia by use of a very low calorie diet in long‐and short‐duration Type 2 diabetes." Diabetic Medicine 32.9 (2015): 1149-1155.
• Steven, et al. "Very-Low-Calorie Diet and 6 Months of Weight Stability in Type 2 Diabetes: Pathophysiologic Changes in Responders and Nonresponders." Diabetes Care (2016) Accepted Article.
• Wood, G. Craig, et al. "Preoperative use of incretins is associated with increased diabetes remission after RYGB surgery among patients taking insulin: A retrospective cohort analysis." Annals of surgery 261.1 (2015): 125-128.

High Protein Medium CHO Promotes Lean Mass Gains and Stable Metabolic Rates Compared to Two Different Macros

High Protein Medium CHO Promotes Lean Mass Gains and Stable Metabolic Rates Compared to Two Different Macros

dieting gain muscle high protein lose fat lose weight macronutrient composition macronutrients medium protein obesity weight loss

This could not be a meal from the study too few carbohydrates... even for the medium CHO group.

As a SuppVersity reader you're not going to be surprised to hear about beneficial effects of increased (dairy) protein intakes on weight loss.

What may be surprising, though, is that the statistics based conclusion of a recent study that determined the effects of 16-week high[er]-dairy-protein, variable-carbohydrate diets and exercise training on body composition in men and women with overweight/obesity says: "Compared to a healthy control diet, energy-restricted high-protein diets containing different proportions of fat and CHO confer no advantage to weight loss or change in body composition in the presence of an appropriate exercise stimulus" (Parr. 2016).

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If this is not your first visit to www.suppversity.com, you will probably be here, because you know that I never settle for a 1-2 sentence conclusion from an abstract - and guess what: If you take a look at the actual study outcomes, it turns out that there is a noteworthy difference between the three diet groups, in which the participants, one hundred and eleven participants (age 47 6 6 years, body mass 90.9 +/- 11.7 kg, BMI 33 +/- 4 kg/m², values mean +/- SD) were randomly stratified to one of the following (isocaloric) three diets:

• High dairy protein, high CHO (HDPHC; 30% protein, 55% CHO, 15% fat; 41 dairy servings/day of sweetened, low-fat products)  
• High dairy protein, moderate CHO (HDPMC; 30% protein, 40% CHO, 30% fat; 41 dairy servings/day of unsweetened/artificially sweetened, full-fat products)  
• Low dairy protein, high CHO (CON; 15% protein, 55% CHO, 30% fat: 1-2 dairy servings/day) 

All three dietary interventions were implemented as a free-living energy restricted eating plan where energy intake was based on a mild restriction (2250 kcal/day) from estimated maintenance energy
requirements (Frankenfield. 2005).

Table 1: Sample of a 1-day meal plan for each of the diets (1,600 kcal version) - aBold items correspond to a “Basket” of foods that could be consumed as a post-exercise recovery snack or added to the meal structure. For the first 8 weeks, participants consumed a prescribed meal plan consisting of a meal structure 1one “Basket” per day. From weeks 8 to 16, participants were encouraged to develop their own meal structure (using a points system to achieve a desired energy and macronutrient intake) and add one of 5-7 “Basket” combinations to the day’s intake (Parr. 2016).

Over the course of the study, the subjects got more leeway (no wonder they didn't lost that much fat during the 2nd phase of the study). While week 1-8 required the subjects to consume a prescribed menu that met the desired energy restriction and macronutrient composition, week 9-16 involved a more flexible self-chosen plan (week 9-16) that was based on a points system. The points system was yet only one of the things that was supposed to increase the subjects' adherence. In addition ...

"[...p]articipants met fortnightly with a dietitian and were provided with edu cation resources. Menus for each diet provided for three meals/day and a “Dairy/Snack Basket” (food choices that achieved most of the nutrient manipulation for each diet; Table 1). For the higher protein diets, the Baskets contained foods equivalent to four to five dairy servings (NHMRC. 2011) where two servings were to be consumed as soon as practical post-EXT. In the moderate-protein CON diet, “Baskets” provided CHO-rich choices (e.g., non-dairy) for post-EXT recovery snacks and meal additions" (Parr. 2016).

To optimize fat and minimize muscle loss, all participants had to follow the same combined resistance (REX) plus aerobic exercise (EXT) training:

• REX - 3 sessions per week (total 48 sessions in 16 weeks) of an individualized training program; a range of exercises were employed to train the same muscle groups (chest, back, legs and core) for 3-4 sets of 8-15 reps at 40-70% of 1RM. Exercise diaries kept by the study trainers were used to ensure the appropriate weight and number of sets was completed.
• EXT - 4 sessions on days without REX equating to 250 kcal/day energy expenditure; more specifically, the subjects performed exercises such as a 4 km walk, 16 km cycle or 1 km swimming, or equivalent combinations

The effects on body composition were monitored by pre-/inter-/post-DXA scans. The results, which are also the reason why I previously said that the statistics-based conclusion may be misleading are plotted in Figure 1, which shows no sign. difference in fat, but a meaningful difference in lean mass loss (in the CON group), respectively gains (in the protein groups, HDPHPC, HDMPC).

Figure 1: Effects of a 16-week diet and exercise intervention on the percentage change relative to baseline in (left) fat mass, and (right) lean mass (LM) for three different diets (Parr. 2016).

In that, the lean mass advantage of the high protein medium carbohydrate group (HDPMPC) is most meaningful in the first 8 weeks - meaningful enough to be practically relevant, albeit not statistically significant over the complete 16 week study period. Even if ...

• the body mass loss in the three groups was virtually identical (HDPMC: 27.2 +/- 3.3 kg; HDPHC: 27.0 +/- 3.3 kg; CON: 27.7 +/- 3.6 kg; P = 0.42), and 
• the loss of body fat in all groups was significant in both absolute and relative-to-baseline changes across, but not significantly different

The lean mass retention or rather increase in the high protein groups may later literally turn the scale, when the high protein, medium carbohydrate group (HDPMPC) don't experience the same weight rebound as the subjects in the CON and maybe even the HDPHPC group, where the resting energy expenditure started to plummet more steeply after 8 weeks of dieting (see Figure 2).

This is no "high protein diet" study as the ones by Jose Antonio the total protein intake in the so-called "high protein" groups averaged ~110-120g and was thus hardly more than 1.3g/kg body weight. In view of the fact that the only really tightly controlled study on the effects of protein intake on weight and fat loss shows optimal results with a similar protein intake (1.6g/kg) at albeit overall much lower total energy intakes, it is also questionable, whether the lack of significant differences in the study at hand has anything to do with the "low" protein intakes in the high protein groups.

Additional non-significant benefits of the HDPMPC diet compared to the CON diet that were reported only as supplementary data, yet not in the full-text, were:

• 

  Figure 2: Effects of the diet intervention on total energy expenditure er day (Parr. 2016).

  greater reductions in waist circumference and waist:hip ratio over the full study duration (-1.1 cm and -0.02 vs. CON),
• greater reductions in trunk fat and greater increases in trunk lean mass,
• greater reductions in leg fat and greater increases in leg lean mass, as well as
• greater reductions in glucose, insulin, HOMA-IR, and total cholesterol.

Yes, none of these changes was statistically significant, and still... they occurred over only 16 weeks and the way the energy expenditure (Figure 2) develops, the advantage of the HDPMPC  (open squares) over the MDPHDC (black triangles) and the HDPMDC (black circles) diet is going to increase, not decrease over time.

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Bottom line: Yes, from a statistic perspective, there's no difference between the three diet interventions. From a common-sense perspective, however, everything points towards the high-protein, medium carbohydrate diet as the most effective way to eat during combined weight loss and exercise interventions... well, unless you want to lose weight, not fat while building muscle, that is.

Speaking of building muscle, I hope you realize that the subjects did the latter with little protein (high pro only ~1.3g/kg body weight), but high effort (7 w/outs/week). Goes to show you: You can eat yourself lean, but not lean and muscular | Comment on Facebook!

References:

• Frankenfield, David, et al. "Comparison of predictive equations for resting metabolic rate in healthy nonobese and obese adults: a systematic review." Journal of the American Dietetic Association 105.5 (2005): 775-789.
• National Health and Medical Research Council (NHMRC). A modelling system to inform the revision of the Australian Guide to Healthy Eating. In: Australian Dietary Guidelines, Dietitans Association of Australia, K. Baghurst, L Cobiac, P Baghurts and A. Magarey, eds. Chapter 3, Table 4. Canberra: Commonwealth of Australia; 2011, pp 1-621.
• Parr, Evelyn B., et al. "A randomized trial of high‐dairy‐protein, variable‐carbohydrate diets and exercise on body composition in adults with obesity." Obesity (2016).

Path to Fat-Induced Obesity is Sprinkled With Salt - Sodium Boosts Food & Energy Intake & Reduces Fat's Satiety Effect

Path to Fat-Induced Obesity is Sprinkled With Salt - Sodium Boosts Food & Energy Intake & Reduces Fat's Satiety Effect

fat fat gain health lose fat obesity salt sodium weight gain

Think you cannot eat the whole pizza? Add salt - this should "help" with the hardest all-you-can-eat challenges.

I am not telling you something new if I tell you that excess fat consumption has been linked to the development of obesity. I hope that it's also not news to you that the consistent association between high(er) fat intakes and weight gain in epidemiological studies cannot be reproduced in human studies where the diet is just high in fat and doesn't have the perfect "potato chips"-combination of fat and carbohydrate that has not just been proven to increase food intake, but also to have pro-addictive effects on the brain (Hoch. 2015).

The fat to carbohydrate ratio Hoch et al. identified as a crucial determinant of snack food intake and brain reward responses in their 2015 study is yet not the only characteristic feature of potato chips.

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Another similarly striking feature chips share with a couple of other highly addictive foods is their salt content. The same salt content of which Bolhuis et al. write in their soon-to-be-published paper in The Journal of Nutrition that we don't know yet how it interacts with the appetitive effects of fat. Apropos fat, whether fat will increase or decrease your appetite is actually highly individual question. Some studies even suggest that a high fat content has appetite reducing effects - at least in those individuals with a high fat taste sensitivity.

Unfortunately, the results of pertinent studies are inconclusive; and that even in people with intact fat taste sensitivity. In view of previous research showing similar associations between the salt content of snack foods and their appetizing effects as they were observed for high carbohydrate + high fat foosds, Bolhuis et al. speculated that our fat taste sensitivity may be influenced by the co-ingestion of salt. To test this hypothesis, the researchers recruited forty-eight healthy adults [16 men and 32 women, aged 18–54 y, body mass index (kg/m2): 17.8–34.4]. After an initial assessment of their individual fat taste sensitivity, the subjects participated in a randomized 2 x 2 crossover design trial, in which each participant attended 4 lunchtime sessions after a standardized breakfast.

Figure 1: The high salt meals were generally rated as more pleasant, while fat had no effect on the perceived pleasantness of the meal (Bolhuis. 2016).

The meals seemed to be identical elbow macaroni (56%) with sauce (44%); the sauces, however, were manipulated to be

• low-fat (0.02% fat, wt:wt)/low-salt (0.06% NaCl, wt:wt),
• low-fat/high-salt (0.5% NaCl, wt:wt), 
• high-fat (34% fat, wt:/wt)/low-salt, or 
• high-fat/high-salt.  

Ad libitum intake (primary outcome) and eating rate, pleasantness, and subjective ratings of hunger and fullness (secondary outcomes) were measured.

The results indicate that salt increased food (= food weight) intakes by 11%, independent of fat concentration (P = 0.022), while increasing the fat intake had no independent effect of fat on food intake (P = 0.6 for the amount of food, not its energy content).

Figure 2: This is what really counts, the effects of modfiying fat and salt content of the meals on total energy intake during the meals; data in kcal per meal (Bolhuis. 2016).

A slightly different picture emerges for the total energy intake, though. Here, the salt intake still mattered (significant with high vs. low salt meals), the main determinant of the total energy intake, however, was the fat content of the meal, with the high-fat meals triggering a whopping +60% (P < 0.001) increase in energy intake in the average subject.

Figure 3: When the diet was high in salt, the mediating effect of fat taste sensitivity on food intake (in g) is lost (Bolhuis. 2016)

Unlike the amount of fat in the meals, the sex of the participants had an effect on the food intake (P = 0.006), with women consuming 15% less by weight of the high-fat meals than the low-fat meals.

More importantly, however, the fat taste sensitivity appeared to decrease signifi-cantly with increasing amounts of salt in the high-fat meals (fat taste x salt interaction on delta intake of high-fat - low-fat meals; P = 0.012), which tended to trigger a satiety effect in the fat sensitive subjects only if they were also low in salt (see Figure 3).

The Overfeeding Overview: High Fat, Carb, Protein, MCTs, Leptin, Testosterone, T3 & Reverse T3 - Get an Overview of the Consequences of Short- & Long-Term Overfeeding - Yes, the existing research shows that high fat intakes (in the presence of carbo-hydrates) are the most fattening.

Bottom line: As the authors of this intriguing study rightly point out, their results "suggest that salt promotes passive overconsumption of energy in adults" (Bolhuis. 2016) and as if that was not bad enough, even those who are sensitive to a higher fat content of food will be fooled into overeating when the high salt content of said foods overrides the fat-mediated satiation.

Ah,... before you rejoice and start eating tons of unsaltet potato chips - there's one thing I should remind you of: even though an excessive increase in dietary fat (from 0.6 to 15.5 g/100g) did not have a main effect on food intake by weight, it led to a 60% higher energy intake, irrespective of the salt content of the meal - an observation that should remind you of the "volume hypothesis" of satiety | Comment!

References:

• Bolhuis, Dieuwerke P. et al. "Salt Promotes Passive Overconsumption of Dietary Fat in Humans." The Journal of Nutrition (2016): Ahead of print.
• Hoch, Tobias, et al. "Fat/carbohydrate ratio but not energy density determines snack food intake and activates brain reward areas." Scientific reports 5 (2015).

Sleep Science Update: New Insights into the Effect of a Lack of Quality Sleep on Glucose Control and Diabesity Risk

Sleep Science Update: New Insights into the Effect of a Lack of Quality Sleep on Glucose Control and Diabesity Risk

diabesity diabetes glucose management health insulin insulin resistance obesity on short notice sleep

Blue light is not the only enemy of sleep, but it's the most prevalent one, today.

Personally, I believe that sleep, "a condition of body and mind which typically recurs for several hours every night, in which the nervous system is inactive, the eyes closed, the postural muscles relaxed, and consciousness practically suspended" (that's what Google's "define"-feature will tell you about sleep), is still an under-appreciated determinant of optimal health and performance.

Evidence to support this assertion comes from a series of studies that were presented at the Winter Meeting of the British Nutrition Society on December 8-9, 2015 - a meeting with the telling title: "Roles of sleep and circadian rhythms in the origin and nutritional management of obesity and metabolic disease" (O'Sullivan. 2015).

Learn more about the health effects of correct / messed up circadian rhythms

Sunlight, Bluelight, Backlight and Your Clock

Sunlight a La Carte: "Hack" Your Rhythm

Breaking the Fast to Synchronize the Clock

Fasting (Re-)Sets the Peripheral Clock

Vitamin A & Caffeine Set the Clock

Pre-Workout Supps Could Ruin Your Sleep

• Circadian disruption in shift workers – the effects of insufficient sleep on dietary and lifestyle behaviours (Nea. 2016) - It will not surprise you that shift workers report more sleep problems compared to the general public. Studies estimate that 10–30 % of shift workers suffer from a circadian rhythm disorder known as “shift work disorder”(Gumenyuk. 2012). With their new quantitative study, a team of young researchers from the Dublin Institute of Technology and the University of Ulster provides some insights into the consequences of this problem.
  
  As the scientists point out, overall, just 34·3 % of the sample was achieving adequate sleep. A number of factors were associated with insufficient sleep – being male (p < 0·001), being 35–54 years of age (p < 0·001), having adult/child dependents (p < 0·001), working in larger organisations (p = 0·045), working in distribution/logistics, manufacturing or construction (p = 0·005), working night shifts (p = 0·042), and working longer shifts (p = 0·002).
  

  

  Factors that increased the subject's risk of not getting adequate sleep (Nea. 2016).

  Furthermore, the scientists observed that insufficient sleep had an effect on the diet of workers. Those who did not achieve adequate sleep were more likely to skip meals on working days and skipped meals significantly more frequently (p = 0·023).

  "Workers with insufficient sleep were also significantly less likely to consume the recommended 5 portions of fruit and vegetables per day (37·5 % vs 43·3 %, p = 0·045) and were less likely to consume the recommended 3 portions of milk/cheese/yoghurt per day (11·6 % vs 8·1 %, p = 0·050). In addition, those with insufficient sleep had higher prevalence of hypertension (10·2 % vs 5·7 %, p = 0·008) and depression/anxiety (7·3 % vs 3·4 %, p = 0·008)" (Nea. 2016)

  Participants were also questioned how they perceived shift work impacts on various aspects of their lives. Compared to those who achieve adequate sleep, those who had insufficient sleep were significantly more likely to report that shift work had a negative effect on their physical health (p < 0·001), mental health (p = 0·003), family life (p = 0·001), social life (p = 0·046), physical activity levels (p = 0·029) and overall quality of life (p = 0·002). Those with insufficient sleep were also significantly more likely to report that shift work increases how much alcohol they drink (p = 0·041).
• Oral glucose tolerance test results are affected by prior sleep duration: a randomised control crossover trial of normoglycaemic adults (Ellison. 2016) - As Ellison et al. rightly point out, "[o]ral glucose tolerance tests (OGTTs) remain the key clinical tool for assessing glucose control and diagnosing diabetes" (Ellison. 2016). In that, they criticize that "[c]urrent guidelines for administering such tests emphasise the importance of a preceding 8 hour fast (often undertaken overnight) but overlook the potential role that preceding sleeping patterns night might play in glucose control the following day" (ibid.). In view of the number of recent observational and experimental studies, which suggest that poor sleep is associated with an increased risk of diabetes, these tests may very well be messed up by a lack of sleep during the previous 8h fast. The aim of the latest study by scientists from the Sound Asleep Laboratory in Leeds was therefore "to explore the effect of early vs. late bedtimes on OGTT results using a cross-over randomised controlled trial" (ibid.).
  
  To this ends, the authors recruited 40 normoglycemic adults who were, after they had been stratification by self-reported pre-existing sleep patterns (as assessed using the Pittsburgh Sleep Quality Index; PSQI), allocated to either a ‘short’ (2·00am-7·00am) then ‘long’ (10·00pm−7·00am), or a ‘long’ then ‘short’ sleep duration, on two consecutive nights.

  "On each occasion, objective measures of sleep were obtained using the ‘SleepMeister’ application on an iPhone 4, with additional subjective assessments of sleep provided by subsequent completion of a version of the PSQI adapted to generate self-reports of sleep during the preceding night (as opposed to the preceding month). On each of the mornings following ‘short’ or ‘long’ sleep, participants again completed the PSQI and underwent a two-hour 75 g oral glucose tolerance test (OGTT), with blood glucose readings taken at 0, +30, +60, +90 and +120 minutes thereafter using finger-prick tests. Data were analysed using STATA v12. Ethical approval was granted by the University of Leeds REC (Ref:HSLTLM12075)" (Ellison. 2016).

  As it was to be expected, both the ‘SleepMeister’ application and the PSQI recorded significantly later bedtimes (SleepMeister: −19·9; 95 %CI: −20·1,−19·7; PSQI: −19·9; 95 %CI: −20·1,−19·7) and significantly shorter sleep durations (decimal hours: ‘SleepMeister’: −3·8;95 %CI: −4·3,−3·4; PSQI: −3·4; 95 %CI: −3·9,−2·9) following a 2am (vs.10pm) bedtime (i.e. ‘short’ and ‘long’ sleep duration, respectively) - a fact, the scientists consider evidence "that levels of compliance were high" (ibid.).
  
  In spite of that, there was no significant effect of sleep duration on fasting blood glucose levels prior to the OGTT after adjustment for sleep duration sequence (i.e. ‘short’ then ‘long’ vs. ‘long’ then ‘short’) and a modest imbalance in gender between the two intervention sequence group.
  

  

  Figure 2: Normal response (=expected response in OGGT, not the actual response of the subjects, because the absolute values are not disclosed in the abstract and an FT is not yet available) vs. calculated response as a consquence of insufficient sleep (normal + difference, rel. difference above bars | Ellison. 2016).

  What did differ, though, were the glucose levels recorded after the ingestion of 75 g glucose, which were consistently higher following a ‘short’ as opposed to a ‘long’ sleep duration, as well as the levels recorded at +60 and +90 minutes, which were likewise significantly higher by 1·18 mmol/l (95 %CI: 0·43,1·92; p = 0·003) and 0·55 mmol/l (95 %CI: 0·05,1·06; p = 0·032), respectively. These results, the scientists say, "indicate that short sleep duration the night before results in an immediate elevation in blood glucose levels the following morning in normoglycaemic adults" (ibid.). That this is a problem, should be obvious, after all it may falsely classify healthy individuals as pre-diabetics. Therefore, "further standardisation of pre-OGTT sleep duration, similar to that for an overnight fast," (ibid.) appears warranted.
• Less Sleep Duration and Poor Sleep Quality Lead to Obesity (Parvaneh. 2016) - In a recent cross-sectional study that was carried out to investigate the association of sleep deprivation and sleep quality with obesity, Malaysian scientists analyzed data from 225 Iranian adults (109 males and 116 females) aged 20–55 years.

  "Heart Questionnaire (SHHQ), International Physical Activity Questionnaire (IPAQ) and a 24-hour dietary recall were interview-administered to evaluate sleep pattern, physical activity and dietary intake of the subjects. Besides, anthropometric also were measured, then subjects were categorized into normal weight and over-weight/obese based on WHO (2000). Sleep duration and sleep quality were assessed based on 2 groups of normal weight and overweight/obese" (Parvaneh. 2016).

  The scientists' analysis of the data revealed that overweight/obese individuals have significantly shorter sleep duration (5·37 ± 1·1 hours) as compared to normal weight subjects (6·54 ± 1·06 hours).
  

  

  Figure 3: Overweight / obesity is linked to sign. sleep problems (Parvaneh. 2016).

  Sleep duration was yet not the parameter the scientists from the National University of Malaysia identified as a major risk factor for obesity - that was a poor sleep quality, which was associated with a 100% increased risk for being overweight or obese (OR: 2·0, 95 % CI: 1·18–3·37, p < 0·05). As a conclusion, the scientists state that "lower sleep quality and sleep duration increase the risk of being overweight and obese" and demand: "[S]trategies for the management of obesity should incorporate consideration on sleeping pattern" (Parvaneh. 2016). These strategies, by the way, may also help people keep their triglyceride levels in check. After all, another study that was presented at the same meeting of the Nutrition Society suggests that a high sleep efficiency shows a strong and negative correlation with triglycrides and another important marker of heart disease risk, the total cholesterol to HDL ratio (Al Khatib. 2016).
• Is insulin resistance associated with light at night in healthy sleep deprived individuals? (AlBreiki. 2016) - The simple answer to this question is "Yes!". The more complex one is that a recent study that was designed to investigate the impact of light and/or endogenous melatonin on plasma hormones and metabolites prior to and after a set meal in healthy sleep deprived subjects found that bright blunts the release of melatonin and the effects of insulin on glucose disposal.
  
  In the study, seventeen healthy participants, 8 females (22·2 years (SD 2·59) BMI 23·62 kg/m2 (SD 2·3)) 9 males (22·8 years (SD 3·5) BMI 23·8 kg/m2 (SD 2·06)) were randomised to a two way cross over design protocol; dim light condition (<5lux) and bright light condition (>500lux), separated by at least seven days.

  

  Melatonin promotes female weight loss - Suggested Read: "Trying to Lose Fat & Get "Toned"? Taking 1-3 mg Melatonin Helps Women Lose 7% Body Fat, Gain 3.5% Lean Mass".

  "Each session started at 18:00 h and finished at 06:00 h the next day. All participants were sleep deprived and semi-recumbent throughout the session. An isocalorific breakfast was consumed at 08:00 h and lunch was timed to be 10 hours before the evening meal. Each participant consumed an evening meal (1066 Kcal, 38 g protein, 104 g CHO, 54 g fat, 7 g fibre) at an individualised time based on estimated melatonin onset. Plasma and saliva samples were collected at specific time intervals to assess glucose, insulin and melatonin levels" (AlBreiki. 2016).

  As previously stated, the bright light reduced the salivary levels of melatonin significantly (p = 0·005). What is more relevant to the research question, however is that it also increased the postprandial glucose and insulin levels significantly compared to dim lights (p = 0·02, p = 0·001) respectively.
  
  

  

  Figure 3: Effect of light intensity on melatonin levels and glucose response of 8 female and 9 male normal-weight normoglycemic subjects to standardized meal consumed at night (AlBreiki. 2016).

  For the scientists this result is not exactly surprising. They had expected that the melatonin release would be suppressed due to the light intensity; that the increase in insulin was not able to compensate for the light-induced increased glucose resistance, however, shows that the ill effects of a  'night-shift-esque' bright light exposure at night on glucose metabolism are more severe than previously thought.

Redeem your sleep dept, now!

Bottom line: Along with studies highlighting the importance of sufficient hours of quality sleep on glucose control in pregnancy (Alghamdi. 2016; Alnaja. 2016) and the "largest study to-date to demonstrate a strong inverse association between late-onset diabetes and poor sleep, even after adjustment for potential confounding factors" (Alfazaw. 2016), the previously discussed studies highlight that sleep hygiene' is as important for your health as "clean eating" (whatever that maybe) and a sufficient amount of light and intense physical activity | Comment on Facebook!

References:

• AlBreiki, et al. "Is insulin resistance associated with light at night in healthy sleep deprived individuals?" Proceedings of the Nutrition Society, 75 (2016). 
• Alfazaw, et al. "Variation in sleep is associated with diagnosis of late-onset diabetes: a cross-sectional analysis of self-reported data from the first wave of ‘Understanding Society’ (the UK Household Longitudinal Study)." Proceedings of the Nutrition Society, 75 (2016). 
• Alghamdi, et al. "Short sleep duration is associated with an increased risk of gestational diabetes: Systematic review and meta-analysis." Proceedings of the Nutrition Society, 75 (2016). 
• Alnaja, et al. "Relationship between sleep quality, sleep duration and glucose control in pregnant women with gestational diabetes." Proceedings of the Nutrition Society, 75 (2016). 
• Al Khatib, et al. "The Sleep-E Study: An on-going cross-sectional study investigating associations of sleep quality and cardio-metabolic risk factors." Proceedings of the Nutrition Society, 75 (2016). 
• DeFronzo, Ralph A. "The triumvirate: β-cell, muscle, liver. A collusion responsible for NIDDM." Diabetes 37.6 (1988): 667-687.
• Ellison, et al. "Oral glucose tolerance test results are affected by prior sleep duration: a randomised control crossover trial of normoglycaemic adults." Proceedings of the Nutrition Society, 75 (2016). 
• Gumenyuk, Valentina, Thomas Roth, and Christopher L. Drake. "Circadian phase, sleepiness, and light exposure assessment in night workers with and without shift work disorder." Chronobiology international 29.7 (2012): 928-936.
• Nea et al. "Circadian disruption in shift workers – the effects of insufficient sleep on dietary and lifestyle behaviours." Proceedings of the Nutrition Society, 75 (2016). 
• O’Sullivan (ed.). "Roles of sleep and circadian rhythms in the origin and nutritional management of obesity and metabolic disease." Proceedings of the Nutrition Society. Volume 75 / Issue OCE1 - Winter Meeting, 8–9 December 2015. Published January 2016: E1-E42.
• Parvaneh, et al. "Less Sleep Duration and Poor Sleep Quality Lead to Obesity." Proceedings of the Nutrition Society, 75 (2016). 
• Peschke, Elmar. "Melatonin, endocrine pancreas and diabetes." Journal of pineal research 44.1 (2008): 26-40.