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Senin, 30 Mei 2016

Ad-Libitum Paleo Diet W/ a Handful of Simple Rules Cuts 5-7 kg of Body Fat in 12 Weeks - Plus: Paleo Research Overview

Yes, these foods were "allowed" - Even nuts, albeit in limited amounts.
Ok, I have to admit that I have repeatedly made fun of "paleo" in the past. Its "cultish", sometimes even "sectarian" appeal is and will remain as hilarious in my eyes as the (for some people life-or-death-)question whether certain foods "are paleo" or not (who cares, as long as they are healthy?). If you happen to have seen my presentation at the Paleo Convention in Berlin, last year, you will know that, despite my apathy against the quasi-religious sides of "paleo", I do appreciate a certain set of "rules" or "principles" (or whatever you may call them) all iterations of "paleo" have in common.

These principles work! And they have just been shown to help middle-aged type II diabetics (age 59±8 years) shed a quite impressive 6.7 kg of body fat (w/out exercise "only 5.7kg) in 12 weeks - without dieting as in not eating, although you're hungry (Otten. 2016).
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As the headline already tells you, the subjects, individuals diagnosed with type 2 diabetes within the past 10 years, who had a BMI of 25–40 kg/m2 and were weight stable (i.e. <5% weight loss) for 6 months (that's important, because otherwise the data on the energy deficit in Figure 1, which was calculated as baseline vs. study intake would be inaccurate) were allowed to eat "as-libitum", which practically means "as much as they wanted", as long, as they adhered to (a) "paleo foods", i.e. lean meat, fish, seafood, eggs, vegetables, fruits, berries, and nuts, but no cereals, dairy products, legumes, refined fats, refined sugars, and (extra) salt (canned fish and cold cuts like ham were allowed) and (b) followed the following simple food-specific rules:
  • Paleo Goes "Real Science" - First Meta-Analysis of Available RCTs Shows Improvements in Health + Body Composition | learn more
    eggs - maximally 1–2/day, and no more than 5/week,
  • potatoes - only 1 medium sized potato per day
  • dried fruit - 130 g/day, not more,
  • nuts - 60 g/day, so no snacking on almonds 24/7
  • rapeseed or olive oil - maximum 15 g/day
  • honey and vinegar - only small amounts as flavoring in cooking
  • coffee & tea - max 300 ml/day (each, I assume)
  • red wine - only one glass per week
Since the participants were also instructed to drink mainly still water, you will probably not be surprised that all subjects, irrespective of whether they had been randomly assigned to the no exercise or exercise group ended up in a significant energy deficit - in spite of being allowed to eat "ad-libitum" (see Figure 1 for the most relevant information about their diet(s)).
Figure 1: Energy and macronutrient intake; differences, rel. + abs. above bars (Otten. 2016).
It is also not surprising that the extra-exercise (1h of exercise, 3x per week | details see blue box below) that was done on top of the (at least) 30 min of moderate intensity exercise like brisk walking all patients had been prescribed as part of their regular T2DM treatment, almost doubled the energy deficit of the subjects in the paleo + exercise, i.e. the PD-EX group (remember: the subjects were allowed to eat more, as long as they stuck to the previously presented rules - since the intake of foods like steak or chicken breast was not limited, they would have been able - within certain limits - to significantly increase their energy intake and still did not fully compensate the energy expended during the workouts; this should remind you of previous articles of mine outlining that "exercise does not just make you hungry" | learn more)
What about compli-ance? Both groups increased their relative intake of protein and their intake of monounsatu-rated and polyunsatu-rated fatty acids. Both groups lowered their intake of carbohydrates and saturated fatty acids. The reduction of sodium intake was only significant in the PD-EX group. Nine of the 14 participants in the PD-EX group completed the 36 exercise sessions according to the study protocol. The remaining five participants completed between 27 and 35 workouts during the study period. The participants in the PD-EX group increased the cumulative weight load (weight × repetitions × sets) with the leg press during one exercise session from 1350 kg (900−1800) to 3000 kg (2700−4000) after 12 weeks.
What did the 1h workouts look like? The PD-EX group underwent a program comprising a combination of aerobic exercise and resistance training in 1-h sessions three times weekly at the Sports Medicine unit at Umeå University. The exercise sessions were performed on weekdays, with at least 1 day of rest between sessions. They were supervised by experienced personal trainers with bachelor’s degrees in Sports Medicine.
All exercise sessions started with aerobic exercise. The first session of each week consisted of low-intensity aerobic training at 70% of the maximum heart rate on a crosstrainer (Monark Prime, XT 50, Vansbro, Sweden). The second session of the week consisted of ten high-intensity sprint intervals at 100% of the maximal workload on a cycle-ergometer (Monark, Ergomedic 839E, Vansbro, Sweden), with low-intensity cycling between the sprints. The third session of each week comprised six moderate-intensity 5-min intervals between 45 and 60% of maximal workload on a cycle-ergometer. The duration/workload of the intervals increased every other week. When necessary, the intensity of the aerobic exercise sessions was adjusted in accordance with the participant’s performance.
After the aerobic exercise, the sessions progressed to resistance training with both upper and lower body exercises, including leg presses, seated leg extensions, leg curls, hip raises, flat and incline bench presses, seated rows, dumbbell rows, lat pull-downs, shoulder raises, back extensions, burpees, sit-ups, step-ups, and wall ball shots. At each training session, the participant performed 3–5 of the aforementioned resistance exercises, with 10–15 repetitions and 2–4 sets. Once participants could complete all repetitions, the workload was increased for the following session.
Still, the main advantage of exercise was not, as you may now falsely expect due to the ~100% increase in energy deficit, a significantly increased loss of body fat (the latter did not double and that must not surprise you!). Neither was it a powerful increase in insulin sensitivity (HOMA-IR), which increased in both groups similarly (45% | p<0.001). Yeah, and even the extra 0.2% decrease in HbA1c, the sugar coating on the subjects' red blood cells  (-0.9% in diet only, -1.1% in diet + exercise), is not the main reason you must not miss your workouts while dieting (paleo-style or not ;-).
Figure 2: Fat mass (a), insulin sensitivity (b), and cardiovascular fitness (c and d) during 12 weeks following either a Paleolithic diet with a supervised exercise program (PD-EX) or a Paleolithic diet combined with general exercise recommendations (PD). Boxes represent medians and IQRs, whiskers represent the most extreme values besides outliers, and filled circles represent outliers (>1.5 IQR); **p<0 .01="" 2016="" p="" td="" tten.="">
So why are workouts important, then? It's the increased fitness, as evidenced by the PD-EX exclusive increase in maximum oxygen uptake (0.2 L/min) and the conservation of lean mass, which reached statistical significance (1.2kg in PD-EX vs. 2.6 kg in PD) only in the male subjects (p<0.05 for the difference between intervention groups), however (it is well possible that this is due to a lack of protein in the women's diet, cf. bottom line), that made / makes exercise (esp. resistance training) so valuable while dieting... this and another thing, the abstract of the study does not appreciate, because it did not reach statistical significance: The increase in relative resting energy expenditure (REE), the scientists observed in the PD-EX group (this adds to the extra energy expenditure during workouts, by the way!). While the relative REE didn't change in the PD group, it increased by a(n over the long-term) potentially relevant (but statistically non-significant) 3% in the PD-EX group - an effect that more than countered the nasty reduction in REE scientists still hold responsible for the yoyo-effect most "biggest losers" experience after successfully losing weight.
Is this the first paleo study? Even though, the number is still low, this is not the first one. In 2009, already, Jönssen et al. reported that "a 3-month study period, a paleolithic diet improved glycemic control and several cardiovascular risk factors compared to a diabetes diet in patients with type 2 diabetes" (Jönssen. 2009). In 2013, the same authors found that a "Paleolithic diet is more satiating per calorie than a diabetes diet in patients with type 2 dia-betes [and that t]he Paleolithic diet was seen as instrumental in weight loss, albeit it was difficult to adhere to" (Jönssen. 2013) - a result they had previously observed in patients with heart disease, too, when they compared a paleo to a Mediterranean diet (Jönssen. 2010), which also improve glucose tolerance less effectively than the paleo diet in said subject group (Lindeberg. 2007). Furthermore, studies in healthy individiuals Frassetto et al. (2015) like Österdahl et al. report that even "a short-term intervention showed some favourable effects by the diet" (Österdahl. 2008) such as weight loss, waist reductions and an improved quality of the diet and improved "BP [blood pressure] and glucose tolerance, decreases insulin secretion, increases insulin sensitivity and improves lipid profiles without weight loss" (Frassetto. 2015). In view of the fact that the less than a handful of long-term (>1 year), studies similar benefits when comparing paleo to other recommended diets, such as the Nordic Nutrition Recommendations in Mellbert et al. (2014) also show "greater beneficial effects" (e.g. fat mass, abdominal obesity and triglyceride levels just as they were observed by Ryberg, et al. in 2013) for the paleo diet(s), one could argue that the evidence in favor of paleo dieting in health and disease is slowly accumulating.
Eventually, diet is king, ... and that, just like the fact that doubling the energy deficit you have on paper won't double the loss of fat mass, shouldn't be news to you. That doesn't mean that dieting with exercise would not increase the loss of fat mass, but what is more important is that it helped the subjects - at least the male ones - maintain significantly more lean mass (=muscle and organ mass, which also affects you REE!).

Whether the failure of the workout to produce significant lean mass maintenance in the women was due to their sex, their hormonal status (the females included in the study were postmenopausal) or the fact that they gravitated to eat less protein (this is speculative, since the study does not provides sex-specific intakes) cannot be said. Even in the men, the lean mass loss is yet large enough to speculate that we'd have seen sign. less muscle loss with higher protein intakes. After all, the 79g the subjects in the PED-EX group consumed on a daily basis amount to only 0,84g protein per kg of body weight. This has repeatedly been shown to be too little for older individuals - even if they were not dieting. A follow up to the study which includes (a) simply more protein or (b) an extra protein shake after the workouts that would bump the subjects' total protein intake into the ~1.6-2.0g/kg region would thus be something I'd like to see in the (not so distant) future.
As long as said study will not have been done, though (something tells me that it won't ;-), you can still reference Otten's study as evidence that you can effectively lose weight without cereals, dairy products, and legumes... I have to admit, though, that I suspect that especially the latter two of these "forbidden" foods would rather have augmented, not messed with the improvements in body composition Otten et al. observed in the study at hand | Comment!
References:
  • Frassetto, Lynda A., et al. "Metabolic and physiologic improvements from consuming a paleolithic, hunter-gatherer type diet." European journal of clinical nutrition 63.8 (2009): 947-955.
  • Jönsson, Tommy, et al. "Beneficial effects of a Paleolithic diet on cardiovascular risk factors in type 2 diabetes: a randomized cross-over pilot study." Cardiovasc Diabetol 8.35 (2009): 1-14.
  • Jönsson, Tommy, et al. "A paleolithic diet is more satiating per calorie than a mediterranean-like diet in individuals with ischemic heart disease." Nutrition & metabolism 7.1 (2010): 1.
  • Jönsson, Tommy, et al. "Subjective satiety and other experiences of a Paleolithic diet compared to a diabetes diet in patients with type 2 diabetes." Nutrition journal 12.1 (2013): 1.
  • Mellberg, Caroline, et al. "Long-term effects of a palaeolithic-type diet in obese postmenopausal women: a two-year randomized trial." European journal of clinical nutrition 68.3 (2014): 350.
  • Lindeberg, Staffan, et al. "A Palaeolithic diet improves glucose tolerance more than a Mediterranean-like diet in individuals with ischaemic heart disease." Diabetologia 50.9 (2007): 1795-1807.
  • Österdahl, M., et al. "Effects of a short-term intervention with a paleolithic diet in healthy volunteers." European journal of clinical nutrition 62.5 (2008): 682-685.
  • Otten, J, et al. "Effects of a Paleolithic diet with and without supervised exercise on fat mass, insulin sensitivity, and glycemic control: a randomized controlled trial in individuals with type 2 diabetes." Diabetes/Metabolism Research and Reviews (2016 |Accepted Article). doi: 10.1002/dmrr.2828
  • Ryberg, Mats, et al. "A Palaeolithic‐type diet causes strong tissue‐specific effects on ectopic fat deposition in obese postmenopausal women." Journal of Internal medicine 274.1 (2013): 67-76.

Rabu, 30 Maret 2016

How Accurate Are Activity Trackers? EE Data From Omron, Fitbit, Jawbone & Other Devices Reveals 10% Error & More

Even though the study doesn't provide a straight-forward answer to the question "Which is the best activity tracker?", it is still revealing.
I hope you don't rely on the data from your activity tracker as a basis to decide how much you can, should or may eat on a daily basis. Why? Well, the first and most important result of a recent study from the Human Performance Laboratory at the Ball State University is that "consumer-based PA [physical activity] monitors should be used cautiously for estimating EE [energy expenditure]" (Nelson. 2016) - and this goes for the data from all the devices that were tested by Nelson et al.: The BodyMedia FIT and the NikeFuel armband, the DirectLife monitor, the Omron HJ-720IT, the Fitbit One, the Fitbit Zip, the Fitbit Flex, the Jawbone UP24, the Basis B1 Band Monitor and the ActiGraph.
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In view of the fact that tracking your energy expenditure is only one of the functions activity trackers are supposed to fulfill and considering the fact that you probably use them only to see if you have gotten more or less active (I do at least hope that you don't use them to guide your appetite ;-), it is still worth to take a look at the detailed results of this recent study.

As you will have guessed, the study was designed to "examine the validity of EE estimates from a variety of consumer-based, physical activity monitors under free-living conditions" (Nelson. 2016). To this ends, sixty (26.4 ± 5.7 yr) healthy men (n = 30) and women (n = 30) wore eight different types of activity monitors simultaneously while completing a 69-min protocol.
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"The monitors included the BodyMedia FIT armband worn on the left arm, the DirectLife monitor around the neck, the Fitbit One, the Fitbit Zip, and the ActiGraph worn on the belt, as well as the Jawbone Up and Basis B1 Band monitor on the wrist.

The validity of the EE estimates from each monitor was evaluated relative to criterion values concurrently obtained from a portable metabolic system (i.e., Oxycon Mobile) [which is obviously in itself not 100% exact]. Differences from criterion measures were expressed as a mean absolute percent error and were evaluated using 95% equivalence testing" (Nelson. 2016).
A brief glance at Figure 2 reveals that the accuracy was surprisingly similar among the devices. To be more precise, the mean absolute percent error values (computed as the average absolute value of the group-level errors) were 9.3%, 10.1%, 10.4%, 12.2%, 12.6%, 12.8%, 13.0%, and 23.5% for the BodyMedia FIT, Fitbit Zip, Fitbit One, Jawbone Up, ActiGraph, DirectLife, NikeFuel Band, and Basis B1 Band, respectively (unfortunately, not all data appears to be fully reported in the manuscript version of the study I had access to, so don't ask me about missing data, please ;-).
What did the test protocol look like? Subjects took part in a structured activity protocol consisting of 11 activities (three sedentary, four household, and four ambulatory/exercise) chosen by researchers from a list of 21 activities ranging from lying around on the couch to treadmill jogging. Activities were counterbalanced so that sex and age categories had approximately equal participation in the activities. All subjects began by lying quietly on a bed for 10 min. All other activities were performed for 5 min each, in order of generally increasing intensity. All activities were performed at a self-selected intensity by the subject. Subjects chosen to perform the jogging activity had the option of participating in a brisk walk if unable to jog for 5 min.
As the scientists point out, of all tested devices, only "[t]he results from the equivalence testing showed that the estimates from the BodyMedia FIT, Fitbit Zip, and NikeFuel Band (90% confidence interval = 341.1-359.4) were within the 10% equivalence zone around the indirect calorimetry estimate. If you still insist on trying to match your energy intake "exactly" to your energy expenditure, you should plan for a 10% + X% difference from your actual energetic demands - after all, even the indirect calorimetry that was used as a yardstick to judge the accuracy of the devices is not 100% accurate.
Figure 1: Mean absolute percent error when estimating energy expenditure for selected devices (Nelson. 2016).
In that, it is also worth mentioning that the accuracy of the devices was activity and device dependent. The Fitbit One, for example, produces the least error for stair climbing. For the Jawbone UP24, however, the "activity" for which it predicts your energy expenditure best is sitting around.

Accordingly, you could argue that you'd have to wear a certain device for a certain activity, e.g. (a) the Fitbit One, when sitting around (13%), working in the household (27%), taking the stairs (11%), jogging (22%) or cycling (43%) [note: on absolute terms, the error of the Fitbit for being sedentary is still lower than with the device from Jawbone], and (b) the Jawbone UP24, when you're simply walking around... but let's be honest: Since even that wouldn't be 100% accurate, it would be dumb to buy multiple fitness / activity trackers, wouldn't it?
Figure 2: With the exception of data from cycling and housework, the step count data (this graph) is sign. more accurate than the EE data in Figure 1 | If you want to learn more about what activity trackers are good / not good for and what you can / should make of the results of the study at hand, listen to me discuss this study on Monday's installment Super HumanRadio | click here to download the complete podcast that also includes discussions of the links NSAIDs and satellite cells and BPC-157 for muscle and tendon repair!
With an error of 10% you will always lose or gain weight involuntarily: The idea that a tiny technical device on your arm or belt could exactly tell you how much energy you need is in itself hilarious. And that's not just because the study at hand shows that even the best devices are on average +/-10% off (remember: that's +/-10% off another rough estimate that's never 100% exact). If you were dumb enough to match your diet blindly to the data your activity tracker provides, you would thus never achieve reliable results.

With that being said, our body is no biological machine that works according to a set of several (complex) equations. Therefore, the whole idea of a "quantified self" - as awesome as it may seem for the average control freak - must be seen as a tool to hold yourself accountable; a qualitative or semi-quantitative tool in the sense of "oh, I have been roughly 20% less active this week than last week, maybe I should..."

If the previously described rationale is behind the way you use the data from your activity tracker, congratulations! If not, I have to warn you: The margin between "quantifying yourself" and suffering from obsessive-compulsive disorder (OCD) and/or using the devices to fuel your exercise addiction is narrower than you may think | Do you agree, disagree? Let's discuss. Leave a comment on Facebook!
References
  • Nelson, Benjamin N; et al. "Validity of Consumer-Based Physical Activity Monitors for Specific Activity Types ED." Med Sci Sports Exerc (2016): Ahead of print.

Rabu, 09 Maret 2016

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

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).

Jumat, 29 Januari 2016

If You Want to Lose Weight and Stave it Off, You'd Better Not Drink Water Instead of Artificially Sweetened Beverages

Meanwhile, even many of those who are against the use of sweeteners admit that drinking diet coke is less of an obstacle to weight loss than regular coke. That it could, as the study at hand clearly indicates, even promote weight loss compared to water is controversial, though.
It is one of the die-hard rumors in the fitness industry: Artificial sweeteners will stall your weight / fat loss and have your weight jojo back up, when you stop dieting. As a SuppVersity reader you know that this claim is not supported by science. For the first part, controlled trials like the 2014 study by Sørensen et al. actually show that the exact opposite is the case, i.e. that the consumption of artificially sweetened beverages promotes, not hinders weight loss.
Skeptics, however, will say that "in a caloric deficit, and in comparison to regular beverages", which was the scenario in the Sørensen study,  "everything will work" - a valid argument, I have to admit. After all, the alleged insulinogenic effects said people ascribe to non-nutritive sweeteners would be more harmful during phases of attempted weight maintenance; phases as they've been investigated in a recent follow up to a previous study by Peters et al. (2015).
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To be more precise, Peters' study was a year-long trial designed to compare the effects of beverages sweetened with non-nutritive sweeteners (NNS) to water as part of a behavioral weight management program consisting of 12 weeks of active weight loss (results previously published in Peters et al. 2014) and 40 weeks of weight maintenance (results now published in Peters, et al. 2016).
Figure 1: Weight and waist loss during the initial 12-week weight loss phase of the study (Peters. 2014).
As previously discussed in the SuppVersity News on Facebook, the results from the 12-week weight
loss phase of this trial were in line with those of the previously cited study by Sørensen et al. (2014) - with the important difference, however, that Sørensen et al. compared non-nutritive sweeteners (NNS) to sugar-sweetened beverages, while Peters et al. found that the NNS group experienced greater weight loss during the 12 weeks of active weight loss, as well as more pronounced reductions in waist circumference, blood pressure, cholesterol, LDL, and triglycerides, even if the control group consumed plain water group (Peters. 2014 | see Figure 1 for weight and waist data).
Figure 2: Consuming NNSs decreased the hunger of the subjects during the 12-week weight loss phase (Peters. 2014).
Mechanistically, the observed benefits may be explained by the opposing effects the consumption of NNS sweetened beverages and water had on the subjects' appetite: Unlike the group that kept consuming artificially sweetened beverages and experienced a significant reduction in hunger scores even while dieting, the ones who were allowed to consume only water reported significantly increased levels of hunger on the 0-100 pts hunger scale Peters et al. used (see Figure 2).
Saccharin may be the unhealthy exception to the "inert sweetener" rule.
What about the effects on the microbiome? You may have heard it on BBC's "Trust me I am a doctor": saccharin appears to mess with the gut microbiome in some of us to a degree that affects our blood glucose levels. That's at least what the TV-crews mini-study shows; and in fact, as a SuppVersity reader you know that the grand daddy of artificial sweeteners (that is by the way no longer used in many products) appears to actually exert the negative effects some people ascribe to every form of sweetener. Speaking of other forms. The TV team was also able to show that stevia, which has been shown to affect the microbiome, as well (learn more), does not affect fasting glucose levels.
In the follow up paper, Peters et al. (2015) now report that the 158 male and female subjects in the NNS group did also have an easier time maintaining their weight loss than their 150 peers in the water only group (see Figure 3); a result of which the scientists say that it was neither due to differences in physical activity / sedentary time or caffeine intake, which were (within the usual statistical margins) identical in both groups.
Figure 3: Body weight (in kg) after 52-week (weight maintenance phase | left) and percent body weight regained during the weight maintenance phase (grey = water; black = NNS | right; Peters. 2015).
While Peters et al. (2015) rightly point out that "it is not possible from the present data to explain why the NNS group lost more weight than the water group despite receiving identical weight loss instruction and beverage interventions that both contained zero calories", they are right to conclude that their findings ...
"[...] are important as there continues to be uncertainty about the benefit of NNS for weight management based largely on observational studies showing associations between NNS consumption, obesity and weight gain." (Peters. 2015).
This is particularly true in view of the fact that the data clearly opposes the often voiced claim that NNS promote obesity by interfering with normal mechanisms of energy balance.
Sponsorship? Yes, the study was funded by the American Beverage Association, but (a) the American Beverage Association was not involved in the design, conduct, interpretation, or manuscript preparation of this study and a third-party organization was hired at the PIs’ request to audit data at both clinical sites to check for the accuracy and integrity of the data. Since the latter are furthermore not really open to intepretation, the "sponsorship argument" is a weak one when it comes to defending the initially defined weight loss myth. In addition, it must be said that it is unrealistic to assume that you could do a 1-year study with more than 300 subjects without external funding - especially, if the research question is not on the TOP-list of the government.
This claim, however, is - as far as experimental evidence is concerned - based exclusively on animal studies; studies that conflict with both, the study at hand and the few other published long-term human trials that evaluated NNS for weight loss (Blackburn. 1997; Tate. 2012):
Figure 4: Tate et al. observed that drinking diet beverages (DB) promotes weight loss over water (WA) or paying more attention (attention control | AC) to what you eat (Tate. 2012).
  • In a prospective randomized trial, Blackburn et al. found that people with obesity in a weight loss program using NNS food and beverage products lost more weight and maintained a greater weight loss over 2 years compared to subjects not using NNS (Blackburn. 1997). 
  • Tate et al. (2012) conducted a 6-month randomized trial in people with obesity and found greater weight loss over 6 months and a greater likelihood of achieving a 5% weight loss in participants drinking beverages with NNS compared with participants in an attention control group. There was no difference in the likelihood of achieving a 5% weight loss between participants in the water group versus the control or between the water group versus the NNS group.
And if we take a look at the totality of research, it becomes obvious that even observational data, some of which is often used to support the claim that artificial / non-nutritive sweeteners were among the driving motors of the obesity pandemic, indicate that artificially sweetened beverages and foods are valuable weight loss tools (Phelan. 2009). Among those of the subjects listed in the National Weight Control Registry who maintained a weight loss of at least 30 pounds for at least 1 year, for example, the vast majority of 78% says that artificially sweetened products has helped them tremendously to achieve and maintain their weight loss (Catenacci. 2014).
Artificial Sweetened Foods Promote, Not Hinder Fat(!) Loss. 1.2kg Body Fat in 70 Days By Eating Artificially Sweetened Products. Lower Hunger, Higher Fat Oxidation | more
So what's the verdict? Reliable experimental evidence for the alleged obesogenic effects of artificially or, more generally, non-nutritively sweetened beverages in humans does not exist. The number of studies showing that it supports short- and long-term weight loss and weight maintenance, on the other hand, is ever increasing.

This does not mean, though, that individual differences may make you more susceptible to overeat when you consume artificially sweetened beverages while dieting. For the average dieter, however, the 2014 study by Peters et al.  and its follow-up show that the opposite is the case. It is thus only logical that the majority of 78% of the successful weight maintainers in Catenacci's observational study from 2014 say "that they helped them control or reduce their total food or calorie intake" | Comment on Facebook!
References:
  • Blackburn, George L., et al. "The effect of aspartame as part of a multidisciplinary weight-control program on short-and long-term control of body weight." The American journal of clinical nutrition 65.2 (1997): 409-418.
  • Catenacci, Victoria A., et al. "Low/No calorie sweetened beverage consumption in the National Weight Control Registry." Obesity 22.10 (2014): 2244-2251.
  • Peters, John C., et al. "The effects of water and non‐nutritive sweetened beverages on weight loss during a 12‐week weight loss treatment program." Obesity 22.6 (2014): 1415-1421.
  • Phelan, Suzanne, et al. "Use of artificial sweeteners and fat-modified foods in weight loss maintainers and always-normal weight individuals." International Journal of Obesity 33.10 (2009): 1183-1190.
  • Sørensen, Lone B., et al. "Sucrose compared with artificial sweeteners: a clinical intervention study of effects on energy intake, appetite, and energy expenditure after 10 wk of supplementation in overweight subjects." The American journal of clinical nutrition (2014): ajcn-081554.
  • Tate, Deborah F., et al. "Replacing caloric beverages with water or diet beverages for weight loss in adults: main results of the Choose Healthy Options Consciously Everyday (CHOICE) randomized clinical trial." The American journal of clinical nutrition 95.3 (2012): 555-563.

Rabu, 13 Januari 2016

Phosphorus, an Anti-Obesity Agent? 3x375 mg With Each Meal Strip Almost 4 cm Off Obese Waists in Only 12 Weeks

You knew that all these fat burning high protein foods are high in phosphorus?!
1 cm per week? What sounds like an advertisement for the next best useless fat burner, is in fact the rate at which the 47 obese, but otherwise "healthy" subjects in a recent study from the American University of Beirut had to tighten their belts (Ayoub. 2015)... Ok, I know that this is not DNP-like earth-shatteringly fast, but in view of the fact that the placebo group had to loosen their belts to accommodate for an additional 0.36 cm increase in waist circumference, it is still quite amazing. I mean, would you have expected that the amount of phosphorus of ca. 300 g salmon would have such an effect if there's no other difference in diet or physical activity between the two groups of overweight participants?
If you're looking for a true fat burner, try coffee ;-)

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Speaking of which,... there were 47 participants (placebo group n = 21; phosphorus group n = 26), 16 men and 31 women, who completed the intervention over the course of all subjects were requested to take three tablets that contained either 375 mg phosphorus or a placebo (Nutricap Labs, Farmingdale, NY, USA) with each main meal (breakfast, lunch and dinner) for 12 weeks (there were no detectable differences in size or weight between intervention and control envelopes | see Table 1).
Table 1: Overview of the baseline characteristics of the subjects in the placebo and phosphorus group (Ayoub. 2015).
Otherwise, the subjects had to maintain their regular dietary and (sedentary) physical activity habits. Whether this was actually the case, however, was unfortunately not monitored by the scientists -- I know that's a bummer, but it is (a) very unlikely that the subjects suddenly started to work out, when they were asked not to, and (b) unrealistic to assume that any effects on the diet that would not be a consequence of the phosphorus supplementation would occur only in the treatment, but not in the active treatment group. Changes in dietary intake that may have occurred in response to the phosphorus treatment, on the other hand, must be expected to occur in the real world as well and would thus only add to the practical relevance of the study at hand compared to a study, where the diet was standardized and potential effects on appetite intake could not have been measured, anyway (as we are going to see further down, this is actually an important fact, even though it would still be nice if we had at least data from food logs).
Figure 1: Weight, waist circumference and serum phosphorus levels expressed rel. to baseline (Ayoub. 2015).
If you look at the selected study outcomes in Figure 1 (please note the non-existing effects on serum phosphorus!), it is still sad that Ayoub et al didn't at least tell their subjects to run food logs, because now everything we have as a basis to speculate about the mechanism that triggered the 'weight and waist loss' are the highly unreliable appetite scores in Table 2; and the latter clearly suggest, but certainly don't prove that the effect was the result of a mere reduction in energy intake.
Table 2: Changes in subjective appetite scores from baseline to 12 weeks (Ayoub. 2015).
Since we don't have those food logs, though, we will have to rely on older studies and a few assumptions to make sense of the results. Well, then...
  • there's firstly the evidence from observational studies linking high protein, high dairy and high whole grains intakes to reduced risk of overweight and metabolic syndrome - since a high intake of all three of these food groups is also associated with an increased intake of phosphorus, that's the first line of evidence which supports a mechanistic role of increased phosphorus intakes in weight management,
  • there's secondly epidemiological evidence showing an inverse association between an individuals phosphorus status and his or her body weight and waist circumference, and 
  • there's thirdly the well-known effect of phosphorus on ATP production, especially in the liver, of which previous studies suggest that it regulates afferent neural signals to the central nervous system which will result in a reduction in food intake (Friedman. 2007).
If we take all three lines of evidence into consideration, we are yet back to square one: the most likely, but unproven mechanism by which the addition of phosphorus to the diet helped the obese subjects in the study at hand lose weight is a reduction in energy intake.
Figure 2: In a previous study the addition of 500mg of phosphorus to a non-caloric or caloric pre-load has already been shown to significantly reduce the food intake during ad-libitum (pizza) lunch (Obeid. 2012).
The latter, by the way, is not just in line with the subjective appetite ratings of Ayoub's study participants, but also with the results of a previous study by Obeid et al (2012), in which the addition of phosphorus to a water, sucrose, fructose + glucose, or pure glucose preload that was administered before an ad-libitum meal lead to an additional attenuation of food intake (see Figure 3). Against that background it is actually very reasonable to assume that the same effect, i.e. a mere reduction in energy intake, is responsible for the 'weight and waist loss' in the study at hand, too.
If you're a loyal SuppVersity, you will probably remember that phosphorus supplements have also been shown to ameliorate the decrease of the active thyroid hormone T3 dieters experience as they progressively reduce their food intake | learn more
Disappointed that it all comes back to eating less, once again? I know the mechanism, a reduction in food intake, is not exactly exciting. It means, after all, that you can still not eat as much junkfood as you want and stay lean if you only supplement with enough phosphorus (in view of the potential diarrhea you may get from very high doses, I suspect you could eat as much as you want... but you certainly don't want to ;-).

With the previously reported beneficial effects of phosphate supplements against the metabolic slow down in response to significantly reduced energy intake, the study at hand does yet contribute another line of evidence that suggests that our diet may eventually not really be so much too high in phosphorus / -phates as we believe it was | Comment!
References:
  • Ayoub et al. "Effect of phosphorus supplementation on weight gain and waist circumference of overweight/obese adults: a randomized clinical trial." Nutrition & Diabetes (2015) 5, e189; doi:10.1038/nutd.2015.38.
  • Friedman, Mark I. "Obesity and the hepatic control of feeding behavior." Drug News Perspect 20.9 (2007): 573-8.
  • Obeid, O. A., S. Dimachkie, and S. Hlais. "Increased phosphorus content of preload suppresses ad libitum energy intake at subsequent meal." International Journal of Obesity 34.9 (2010): 1446-1448.