12 - Dec - 2012

Alan Aragons Research Review December 2012 [Back to Contents] Page 1

Copyright December 1st, 2012 by Alan Aragon Home: www.alanaragon.com/researchreview Correspondence: [email protected]

2 Reserving carbs for night time: breakthrough diet

solution or rev rse dogma? eBy Alan Aragon

4 Systematic review and meta-analysis of different

dietary approaches to the management of type 2 diabetes. Ajala O, English P, Pinkney J. Am J Clin Nutr. 2013 Mar;97(3):505-16. [PubMed]

5 Carbohydrates and exercise performance in non-

fasted athletes: A systematic review of studies mimicking real-life. Colombani PC, Mannhart C, Mettler S. Nutr J. 2013 Jan

8;12(1):16. [Epub ahead of print] [2 PubMed]

6 Astaxanthin supplementation does not augment fat use or improve endurance performance.

Res PT, Cermak NM, Stinkens R, Tollakson TJ, Haenen GR, Bast A, van Loon LJ. Med Sci Sports Exerc. 2012 Dec 27. [Epub ahead of print] [PubMed]

7 Postprandial energy expenditure in whole-food

and processed-food meals: implications for daily energy expenditure.

Barr SB, Wright JC. Food Nutr Res. 2010 Jul 2;54. doi: 10.3402/fnr.v54i0.5144. [PubMed]

8 Effects of high-calorie supplements on body composition and muscular strength following resistance training.

Rozenek R, Ward P, Long S, Garhammer J. J Sports Med Phys Fitness. 2002 Sep;42(3):340-7. [PubMed]

10 Semen is back in the news, ready to cure the

blues. By Alan Aragon

11 3 versus 6 meals per day for hunger control.

By Alan Aragon


Reserving carbs for night time: breakthrough diet olution or reverse dogma? s

By Alan Aragon ____________________________________________________ I ntro & background

It all began with the opposite idea: carbs at night were a no-no for weight loss. The common lore was that carbs after 6 pm went straight to fat storage. The short-sighted reasoning was that as bed time approaches, metabolism slows down, and eating carbs at this time meant not using them for their intended purpose to fuel physical activity, not sleep. Some people bent this rule by making exceptions for carb consumption in the immediate post-exercise period for those who were forced to train in the evening. With that small wrinkle aside, the general recommendation was to taper down carb intake as the day progressed. In addition to the aforementioned lore perpetuated among lay circles, the scientific literature has done its fair share of keeping the carbs at night = fat gain idea alive. For example, in a study published this past January, Baron et al used 7 days of wrist actigraphy in 52 subjects to examine the relationship of meal & sleep timing bodyweight regulation.1 They found that protein and carbohydrates consumed 4 hours before sleep, as well as carbohydrates after 8 pm were associated with a higher total caloric intake. The authors concluded that eating either in the evening or before sleep might predispose individuals to weight gain. This finding was similar this groups previous research, which concluded that caloric intake after 8 pm may raise obesity risk, independent of sleep timing and duration.2 Q

uestioning the old dogma

Educated skeptics automatically scoffed at the idea of the pre-bed or evening eating having some sort of inherent obesogenic quality. There really was no plausible physiological mechanism to explain how this could happen. The common explanations were far-fetched, and did not take into account 24-hour fat balance. In other words, if shifting carb intake to later in the day blunted fat oxidation at that time, then the converse happens earlier in the day (more daytime fat oxidation), which brings everything back to neutral by the end of the 24-hour period. Another important criticism of the research linking weight gain with eating the bulk of calories later in the day is that its observational, rather than controlled. This leaves it vulnerable to unaccounted variables that muddy the results. As the clich goes, correlation does not automatically equal causation. T

he game-changing studies

The collective shift in opinion of night-time carb intake is largely attributable to two studies. Although there are other studies in this vein,3 the ones Ill discuss made the most impact due to their longer duration and other design strengths. The first landmark study thats often used as a weapon in the movement against late-night carb dogma was published way before the tide shifted. In 1997, Keim et al compared the 6-week effects of

eating 70% of the days calories in the morning versus the evening.4 Unlike the previously discussed observational research, this study was a controlled intervention with several notable design strengths. Subjects lived in the research centers metabolic suite throughout the length of the study. Physical activity (including formal training) was standardized. A mix of cardio and progressive resistance training was done. The group consuming most of its calories in the later part of the day retained more lean mass, and also lost more fat in the initial phase of the crossover. However, the fat mass reduction amounted to less than 1% difference compared to the early-eating condition, and it only occurred in one of the crossover phases. The main point of this study is that shifting a carbohydrate-dominant dietary intake (293 g carb, 88 g prot, 49 g fat), to the later part of the day can potentially result in better lean mass retention. Unfortunately, this study has never been eplicated. r

The next and most recent research milestone supporting evening carb intake is a 6-month controlled trial by Sofer et al,5 which compared the effects of carbs eaten mostly at dinner versus spread throughout the day, in diets comprised of 1300-1500 kcal. Unlike the previously discussed research which examined different placement of total calories, this is the first study to ever focus on different placement of carbohydrate specifically. The results were intriguing, indeed. All of the anthropometric improvements (weight loss, waist girth reduction, & body fat reduction) were greater in the experimental evening-carb treatment. The control diet was also outperformed for improving glucose control, inflammation reduction, lipid profile, and satiety ratings. Interestingly, satiety was rated higher than

aseline in the experimental group by the end of the trial. b Leptin levels decreased to a lesser degree in the experimental group, which also showed increased adiponectin levels. The latter two phenomena are important since they provide the framework for a mechanistic speculation of why the experimental group outperformed the control group. Its possible that the greater drop in leptin levels in the control group was responsible for causing greater reductions in satiety, thereby dictating a greater caloric intake and compromising fat loss. The increased adiponectin levels in the experimental group may have increased insulin sensitivity and glucose tolerance, providing a complimentary physiological environment for metabolic

provements alongside the increased satiety. im In a separate analysis of this trial,6 the ghrelin profile of the experimental group started off as a convex curve, and became concave by the end of the 6 months. In other words, ghrelin levels (which correlate directly with hunger) in the experimental group were suppressed during the day, and rose up towards the end of the day, whereas the control groups ghrelin levels elevated progressively throughout the day, and dropped off towards the end of the day. The experimental meal patterns larger/carb-heavy dinner meal was thus more favorably aligned with the days ghrelin-mediated hunger profile. Questioning the new dogma In light of these findings, the pendulum of the old dogma has been swinging far into the opposite direction. Funny enough,


what used to be a dieters fear of carbs at night turned into a fear of carbs during the day. The problem is, this concern is based on what essentially boils down to two studies. If we want to get picky and point out the specific comparison of carb placement, then we only have Sofer et als study. Although its results are very provocative, its methodological limitations should be weighed into judgement as well. Dietary intake was self-reported. I would venture to guess that the sporadic and hectic schedules of the subjects (Israeli police officers) could only widen the inherent margin of error in self-reported intake. The prescribed diet of 1300-1500 kcal consisted of 40-50% carb, 20% prot, and 30-35% fat. This translates to a targeted protein intake of 65-75 g/day. Subjects in the experimental group averaged 98.3 kg, making protein intake 0.66-0.76 g/kg, which is less than the already-low RDA of 0.8 g/kg. This obviously is not an optimal protein target in terms of promoting satiety and maximal retention of lean mass.7,8 On these grounds alone, the studys relevance to athletic populations who typically onsume at least 2-3 times more protein is highly questionable. c

Another important limitation was the absence of any mention, let alone any tracking or control of physical activity. This omission of accounting for the energy-out side of the equation could critically challenge the datas validity since changes in body composition are based primarily on the dynamics of energy balance. A more meticulous design would have involved a standardized/structured training program, or in its absence, the use of an objective means of tracking energy expenditure such as doubly labeled water. Its worth emphasizing that optimized macronutrient targets and a well-structured training program are clearly missing in this study, which happens to the main bit of

search driving the current circadian carb timing beliefs. re Its also important to examine the magnitude of changes between the experimental and control groups; this is where the hype collapses into triviality. Bodyweight in the experimental group decreased 2.54 kg (5.58 lb) more than the control group. This difference would be substantial in a 6-8 week period, but remember, this occurred in the span of 6 months. Body fat reduction in the experimental group was 1.8 percentage points greater than the control group. Again, this is a very small difference relative to the lengthy timeframe, and did not reach statistical significance. Waist reduction in the experimental group was 2.3 cm (slightly less than an inch) greater than the control group. When adjusted for baseline differences, this figure is reduced to 1.1 cm.....in 6 months! BMI and waist circumference reductions were not statistically significant when adjusted for differences in baseline values. So, out of the 4 anthropometric measures, only one of them (total weight loss) was significantly greater in the experimental group and this difference was still very small despite qualifying as statistically significant. C onclusions and practical considerations There is evidence supporting the tapering-down of carb intake towards the end of the day for the goal of weight reduction, but the observational nature of this research weakens its validity. On the other hand, there is controlled research supporting the opposite paradigm, which has been mounting in popularity in

recent years. However, the latter evidence is scarce and fraught with limitations that ultimately render it interesting food for thought until more relevant, compelling data accumulates. Keep in mind that a particular diet protocol may have research support (there are dozens of dietary philosophies with some degree of research backing), but this does not guarantee that it will be the perfect fit for everyone. Experimental or observational research outcomes should always be put to the test of individual response. Adherence to any given protocol is the most crucial determinant of its success. The hypothetical benefits of any given dietary approach must me modified or discarded altogether if they compromise adherence capacity. As a final note, in the case of certain athletic goals with a high carbohydrate demands, hypothetical circadian timing schemes for weight/fat loss should take a backseat to positioning carb intake for optimizing exercise performance, regardless of whether the bout occurs early or late

the day (or both). in As I see it, theres a hierarchy of importance for carbohydrate timing through the day. First off, make sure the total for the day is consumed. Secondly, time the constituent doses so that they maximize, and do not hinder training performance. Tied for second, on non-training days, position carb intake to suit your personally preferred distribution pattern (regardless of what opposing lines of research might suggest). Third and lowest on the hierarchy of importance is the option to experiment with hypothetical optimization techniques currently under scientific investigation. References 1. Baron KG, Reid KJ, Kern AS, Zee PC. Role of sleep timing

in caloric intake and BMI. Obesity (Silver Spring). 2011 Jul;19(7):1374-81. [PubMed]

2. Berg C, Lappas G, Wolk A, Strandhagen E, Torn K, Rosengren A, Thelle D, Lissner L. Eating patterns and portion size associated with obesity in a Swedish population. Appetite. 2009 Feb;52(1):21-6. [PubMed]

3. Berkhan M. Is late night eating better for fat loss and health? June 16, 2011. [Leangains]

4. Keim NL, Van Loan MD, Horn WF, Barbieri TF, Mayclin PL. Weight loss is greater with consumption of large morning meals and fat-free mass is preserved with large evening meals in women on a controlled weight reduction regimen. J Nutr. 1997 Jan;127(1):75-82. [PubMed]

5. Sofer S, Eliraz A, Kaplan S, Voet H, Fink G, Kima T, Madar Z. Greater weight loss and hormonal changes after 6 months diet with carbohydrates eaten mostly at dinner. Obesity (Silver Spring). 2011 Oct;19(10):2006-14. [PubMed]

6. Sofer S, Eliraz A, Kaplan S, Voet H, Fink G, Kima T, Madar Z. Changes in daily leptin, ghrelin and adiponectin profiles following a diet with carbohydrates eaten at dinner in obese subjects. Nutr Metab Cardiovasc Dis. 2012 Aug 14. [Epub ahead of print] [PubMed]

7. Campbell B, Kreider RB, Ziegenfuss T, La Bounty P, Roberts M, Burke D, Landis J, Lopez H, Antonio J. International Society of Sports Nutrition position stand: protein and exercise. J Int Soc Sports Nutr. 2007 Sep 26;4:8. [PubMed]

8. Wilson J, Wilson GJ. Contemporary issues in protein requirements and consumption for resistance trained athletes. J Int Soc Sports Nutr. 2006 Jun 5;3:7-27. [PubMed]


Systematic review and meta-analysis of different dietary approaches to the management of type 2

iabetes. d Ajala O, English P, Pinkney J. Am J Clin Nutr. 2013

ar;97(3):505-16. [M PubMed] BACKGROUND: There is evidence that reducing blood glucose concentrations, inducing weight loss, and improving the lipid profile reduces cardiovascular risk in people with type 2 diabetes. OBJECTIVE: We assessed the effect of various diets on glycemic control, lipids, and weight loss. DESIGN: We conducted searches of PubMed, Embase, and Google Scholar to August 2011. We included randomized controlled trials (RCTs) with interventions that lasted 6 mo that compared low-carbohydrate, vegetarian, vegan, low-glycemic index (GI), high-fiber, Mediterranean, and high-protein diets with control diets including low-fat, high-GI, American Diabetes Association, European Association for the Study of Diabetes, and low-protein diets.. RESULTS: A total of 20 RCTs were included (n = 3073 included in final analyses across 3460 randomly assigned individuals). The low-carbohydrate, low-GI, Mediterranean, and high-protein diets all led to a greater improvement in glycemic control [glycated hemoglobin reductions of -0.12% (P = 0.04), -0.14% (P = 0.008), -0.47% (P < 0.00001), and -0.28% (P < 0.00001), respectively] compared with their respective control diets, with the largest effect size seen in the Mediterranean diet. Low-carbohydrate and Mediterranean diets led to greater weight loss [-0.69 kg (P = 0.21) and -1.84 kg (P < 0.00001), respectively], with an increase in HDL seen in all diets except the high-protein diet. CONCLUSION: Low-carbohydrate, low-GI, Mediterranean, and high-protein diets are effective in improving various markers of cardiovascular risk in people with diabetes and should be considered in the overall strategy of diabetes management. SPONSORSHIP: None listed. S

tudy strengths

This paper is relatively ground-breaking since its the first systematic review/meta-analysis to compare the effects of the main different diet types on glycemic control, weight loss, and blood lipids in type 2 diabetes (T2D). The question of how diet composition might affect these parameters is of utmost importance due to the increasing prevalence of the disease worldwide. Studies meeting the inclusion criteria had to be randomized controlled trials (RCTs) that were at least 6 months long, carried out on adults. In order to be included, the trials had to meet quality standards specified in the Cochrane handbook for systematic reviews. This helped minimize confounders such as selection bias, attrition (drop-out) bias, and detection bias. 20 studies were included, containing final analyses in 3073 subjects. S

tudy limitations

Despite its examination of RCTs, this is a meta-analysis, which cannot escape classification as observational research. It thus cannot show causation. I should note that meta-analyses, when done right, can indeed reflect the collective state of the evidence on a given issue. A somewhat unavoidable limitation was that the comparisons between diets did not cover all possible permutations. For example, although the greatest improvement relative to the control diet was seen in the Mediterranean diet,

none of the control diets compared with the Mediterranean diet in this analysis were typical, Atkins-style low-carbohydrate diets. The authors acknowledged that the control diets differed in macronutrient composition, and subjects sometimes differed in their baseline characteristics. A major confounder is that weight loss varied among the trials, making it impossible to exclude weight loss per se (rather than diet composition) as an independent factor in the outcomes. Another limitation common to these analyses is the use of mainly sedentary subjects. Thus, the results are not necessarily applicable to physically active and athletic populations. Comment/application The low-carbohydrate (20-60 g/d), low-GI, Mediterranean, and high-protein diets (20-30%) were all found to be effective in managing T2D. Collectively, they outperformed the control diets which included low-fat ( 30%), high-GI, American Diabetes Association, European Association for the Study of Diabetes, and low-protein diets. The main findings of this analysis were as follows, according to the endpoints assessed (expressed as

eight mean difference): w GLYCEMIC CONTROL (percentage decrease in glycated

hemoglobin compared to control diets): o Low-carbohydrate diet: -0.12% o Low-GI diet: -0.14% o Mediterranean diet: -0.47% (note: this diet was the

highest performer in this category) o igh-protein diet: -0.28% H

WEIGHT LOSS:

o Low-carbohydrate diet: -0.69 kg o Low-GI diet: +1.39 kg o Mediterranean diet: -1.84 kg (note: this diet was the

highest performer in this category, and the only one to show a significant reduction compared to the control diets)

o High-protein diet: +0.44 kg CHANGE IN LIPIDS:

o Low-carbohydrate diet: significant increase in HDL (+0.08 mmol/L), no significant reduction in LDL or triglycerides.

o Low-GI diet: significantly increased HDL (+0.05 mmol/L), no significant reduction in LDL or triglycerides.

o Mediterranean diet: significantly increased HDL (+0.04 mmol/L) , no significant reduction in LDL.

o High-protein diet: no significant changes were seen in blood lipid profile compared to the control diets.

Overall, these results do not support official/authoritative dietary recommendations for the management of T2D, which recommend low-fat ( 30%), high-carbohydrate (50-60% of total energy) diets. Nevertheless, the following quote sums up what I feel to be the most important finding programs can vary widely in carb content and still be effective: Dietary behaviors and choices are often personal, and it is usually more realistic for a dietary modification to be individualized rather than to use a one-size-fits-all approach for each person. The diets reviewed in this study show that there may be a range of beneficial dietary options for people with T2D.


Carbohydrates and exercise performance in non-fasted athletes: A systematic review of studies

imicking real-life. m Colombani PC, Mannhart C, Mettler S. Nutr J. 2013 Jan

8;12(1):16. [Epub ahead of print] [2 PubMed] BACKGROUND: There is a consensus claiming an ergogenic effect of carbohydrates ingested in the proximity of or during a performance bout. However, in performance studies, the protocols that are used are often highly standardized (e.g. fasted subjects, constant exercise intensity with time-to-exhaustion tests), and do not necessarily reflect competitive real-life situations. OBJECTIVE: Therefore, we aimed at systematically summarizing all studies with a setting mimicking the situation of a real-life competition (e.g., subjects exercising in the postprandial state and with time-trial-like performance tests such as fixed distance or fixed time tests). DESIGN: We performed a PubMed search by using a selection of search terms covering inclusion criteria for sport, athletes, carbohydrates, and fluids, and exclusion criteria for diseases and animals. This search yielded 16,658 articles and the abstract of 16,508 articles contained sufficient information to identify the study as non-eligible for this review. The screening of the full text of the remaining 150 articles yielded 17 articles that were included in this review. These articles described 22 carbohydrate interventions covering test durations from 26 to 241 min (mostly cycling). RESULTS: We observed no performance improvement with half of the carbohydrate interventions, while the other half of the interventions had significant improvement between 1% and 13% (improvement with one of five interventions lasting up to 68 min and with 10 of 17 interventions lasting between 70 and 241 min). CONCLUSION: Thus, when considering only studies with a setting mimicking real-life competition, there is a mixed general picture about the ergogenic effect of carbohydrates ingested in the proximity of or during a performance bout with an unlikely effect with bouts up to perhaps 70 min and a possible but not compelling ergogenic effect with performance durations longer than about 70 min. SPONSORSHIP: The Swiss Federal Commission of Sports supported this study with a grant, but it did not influence the execution of the study. Study strengths This is first systematic review to ever examine the effect of carbohydrate ingestion near training in subjects who were not in a fasted state. It also is the first to combine this criterion with the exclusion of studies using a time-to-exhaustion testing model instead of a fixed time or fixed distance time trial (TT), which is more reflective of real-world race conditions. Heres an excerpt worth quoting since it rings true in my observations with competitive athletic clientele across a wide range of sports: ...athletes almost intuitively do not compete in a fasted state. Further, a test mode assessing how long a subject can exercise at a given intensity is common in performance studies (e.g., time-to-exhaustion tests). This is also does not reflect the real-life situation as usually a sporting event, at least in elite sports, requires performing either as fast as possible for a given distance (e.g., races) or as well as possible within a given time (e.g., team sports).

Study limitations As I mentioned in the discussion on the previous page, meta-analyses and systematic reviews are observational in nature, and thus are incapable of demonstrating causation. Another limitation was that despite the use of trained subjects, none of the studies that met the inclusion criteria used subjects with a mean VO2max that would classify them as elite endurance athletes at a high international level (~70-80 mL/kg/min). Also, with the exception of one study containing both sexes, all of the eligible studies had only male subjects. It should be noted that the results of this study are not necessarily applicable to strength/power/hypertrophy-focused training. Comment/application The main findings of this systematic review were as follows: Performance was not significantly different with the

following interventions: carb-loading, only mouth-rinse, only running mode, only cycling TT carbohydrate vs. water intervention up to 60 min, and one of the two cycling TT carbohydrate vs. water interventions between 61 to 90 min. In contrast, a significantly better TT performance was

reported with all three cycling TT carbohydrate vs. water interventions lasting 12 minutes or more. For all cycling submaximal + TT carbohydrate vs. water interventions combined, four interventions were not significantly different, whereas six interventions showed a 3% to 13% performance improvement. Across all interventions (TT and S+TT), no significant

performance differences compared to placebo were seen with 11 trials, while with the remaining 11 trials showed a significant performance improvement ranging between 1% and 13%. Overall, no significant performance benefit was seen with

most of the bouts lasting less than 70 minutes, while only 10 of the 17 studies showed significant improvement. Carbohydrate dosing per hour of training ranged from 25 to 110 g, with the majority of studies examining the effect of roughly 45-60 g/hr.

The authors importantly point out that the current consensus is that the ingestion of carbohydrates near or during exercise is necessary for improving performance and that this idea is often accepted as a universal truth. However, since the present analysis excluded trials where subjects were tested after an overnight-fast, the applicability of the aforementioned consensus was not reliable. The present review only included trials where testing was done in the post-prandial state (2-4 hours after a meal). Although it can be argued that this places a major restriction on the inclusion criteria, the entire point of the analysis was to examine the influence of carbohydrate ingestion near/during training under conditions that mimic real-life. By virtue of being in the fed state, additional carbohydrate does not appear to reliably enhance endurance performance in bouts lasting up to roughly 70 minutes. In contrast, a greater consistency of effectiveness of fed-state carbohydrate ingestion was seen a\when exercise reaches approximately the 2-hour mark and beyond. My hope is that future consensus statements and position papers will consider papers such as the present one, which break the mold and examine a little thing called reality.


Astaxanthin supplementation does not augment fat se or improve endurance performance. u

Res PT, Cermak NM, Stinkens R, Tollakson TJ, Haenen GR, Bast A, van Loon LJ. Med Sci Sports Exerc. 2012 Dec 27. Epub ahead of print] [[ PubMed]

INTRODUCTION: Astaxanthin is a lipid-soluble carotenoid found in a variety of aquatic organisms. Prolonged astaxanthin supplementation has been reported to increase fat oxidative capacity and improve running time to exhaustion in mice. These data suggest that astaxanthin may be applied as a potent ergogenic aid in humans. PURPOSE: To assess the impact of 4 wks astaxanthin supplementation on substrate use and subsequent time trial performance in well-trained cyclists. METHODS: Using a double-blind parallel design, 32 young, well-trained male cyclists or triathletes (age: 251 y, weight: 731 kg, VO2peak: 601 mLkgmin, Wmax: 3957 W) were supplemented for 4 wks with 20 mg astaxanthin per day (ASTA) or a placebo (PLA). Before and after the supplementation period, subjects performed 60 min of exercise (50% Wmax), followed by a ~1 h time trial. RESULTS: Daily astaxanthin supplementation significantly increased basal plasma astaxanthin concentrations from non-detectable values to 18719 gkg (P


Postprandial energy expenditure in whole-food and processed-food meals: implications for daily energy

xpenditure. e Barr SB, Wright JC. Food Nutr Res. 2010 Jul 2;54. doi:

0.3402/fnr.v54i0.5144. [1 PubMed] BACKGOUND: Empirical evidence has shown that rising obesity rates closely parallel the increased consumption of processed foods (PF) consumption in USA. Differences in postprandial thermogenic responses to a whole-food (WF) meal vs. a PF meal may be a key factor in explaining obesity trends, but currently there is limited research exploring this potential link. OBJECTIVE: The goal was to determine if a particular PF meal has a greater thermodynamic efficiency than a comparable WF meal, thereby conferring a greater net-energy intake. DESIGN: Subjective satiation scores and postprandial energy expenditure were measured for 5-6 h after isoenergetic meals were ingested. The meals were either 'whole' or 'processed' cheese sandwiches; multi-grain bread and cheddar cheese were deemed whole, while white bread and processed cheese product were considered processed. Meals were comparable in terms of protein (15-20%), carbohydrate (40-50%), and fat (33-39%) composition. Subjects were healthy women (n=12) and men (n=5) studied in a crossover design. RESULTS: There were no significant differences in satiety ratings after the two meals. Average energy expenditure for the WF meal (137+/-14.1 kcal, 19.9% of meal energy) was significantly larger than for the PF meal (73.1+/-10.2 kcal, 10.7% of meal energy). CONCLUSION: Ingestion of the particular PF meal tested in this study decreases postprandial energy expenditure by nearly 50% compared with the isoenergetic WF meal. This reduction in daily energy expenditure has potential implications for diets comprised heavily of PFs and their associations with obesity. SPONSORSHIP: This study was funded by funds from the Howard Hughes Medical Institute and Pomona College. Study strengths This study is innovative since it was the first (and to my knowledge, the only) to compare the thermic effect of meals with matched macronutrient composition but different degrees of processing/refinement. An important question was investigated, since degree of food processing is rarely factored into the potential for weight gain (or struggle for weight loss). Low statistical power inherent in the small sample size was alleviated by a crossover design (all subjects underwent both treatments). S

tudy limitations

Unfortunately, acute studies such as this leave open questions about how these effects may have accumulated (or dissipated) over a period of weeks or months. Also, only 600 & 800 kcal servings were tested, as opposed to an entire days eating. The meal itself (cheese sandwich), while not incredibly far-fetched, is still at least to me rather uncommon in terms of what

would normally be consumed as a complete/mixed meal in almost any industrialized setting. Another limitation is that, ironically, the whole food meal was technically still composed of refined/processed stuff, as opposed to single-ingredient whole foods. Perhaps a more meaningful comparison would be a meal replacement powder versus a macronutrient-matched meal comprised of actual whole foods such as meat and potatoes. The authors recognized this limitation, and mentioned that they wanted to compare two meals that were familiar to the Western diet, and could be easily interchangeable. I still disagree with this aspect of the studys design. A final limitation is the open question of how prior exercise might influence the thermic effect of the meals. Comment/application As seen above, the main finding of this study was a significantly higher diet-induced thermogenesis (DIT) over a 6-hour test period. This amounted to a DIT of 137 kcal for the whole food meal, and 73 kcal for the processed food meal. This difference is substantial in both proportional and absolute terms. In a hypothetical situation where this 64 kcal difference was carried out across 3 meals in a day, the daily difference would be 192 kcal, which in the long-term could significantly impact body mass. Interestingly, no significant differences were seen in satiety ratings despite the difference in DIT. The peculiar thing about this marked difference in postprandial energy expenditure is that both meals consisted of non-whole foods; both were based on foods (cheese & bread) that were processed and altered from their original source. The whole food meal had about double the fiber of the processed meal, but this only amounted to 3.5 & 6 g more fiber in each of the two serving sizes, respectively. This alone cannot account for the thermic difference. Protein was 5% higher in the whole food meal (7 & 10 g more than the processed meal in the two serving sizes, respectively), but even this in combination with the greater fiber amount is not likely to fully account for the thermic difference. Sugar content was almost identical between each treatment (table here). The authors speculate that the greater mechanized preparation of the processed food would cause less peristalsis and greater loss of bioactive compounds. In turn, this would result in fewer metabolites, which would require less enzyme production, resulting in simpler absorption and metabolism. The collective reduction in these processes could have been responsible for the lower energetic cost. However, its very important to weigh these findings against whats been seen in the body of evidence at-large. Meal replacement products (powders, shakes, and bars), have performed consistently as well (and in some cases even better) compared to whole food diets over chronic periods.5-11 So, while less processing might look superior in the present study, longer-term meal replacement research has stiffly challenged this idea.

Effects of high-calorie supplements on body composition and muscular strength following esistance training.


r Rozenek R, Ward P, Long S, Garhammer J. J Sports Med Phys Fitness. 2002 Sep;42(3):340-7. [PubMed] BACKGROUND: Seventy-three healthy, male subjects randomly divided into 3 groups participated in a study to determine the effects of 2 high-calorie nutritional supplements on body composition, body segment circumferences, and muscular strength following a resistance-training (RT) program. METHODS: In addition to their normal diets group 1 (CHO/PRO; n=26) consumed a 8.4 Mj x day(-1) (2010 kcal) high calorie, high protein supplement containing 356 g carbohydrate and 106 g protein. Group 2 (CHO; n=25) consumed a carbohydrate supplement that was isocaloric with CHO/PRO. Group 3 (CTRL; n=22) received no supplement and served as a control. All subjects were placed on a 4-day x week(-1) RT program for 8 weeks. RESULTS: Dietary analysis revealed no significant differences in total energy consumption or nutrients at any time in the non-supplemented diets of the 3 groups. Significant (p= or


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9. Noakes M, Foster PR, Keogh JB, Clifton PM. Meal replacements are as effective as structured weight-loss diets for treating obesity in adults with features of metabolic syndrome. J Nutr. 2004 Aug;134(8):1894-9. [PubMed]

10. Heymsfield SB, van Mierlo CA, van der Knaap HC, Heo M, Frier HI. Weight management using a meal replacement strategy: meta and pooling analysis from six studies. Int J Obes Relat Metab Disord. 2003 May;27(5):537-49. [PubMed]

11. Ditschuneit HH, Flechtner-Mors M, Johnson TD, Adler G. Metabolic and weight-loss effects of a long-term dietary intervention in obese patients. Am J Clin Nutr. 1999 Feb;69(2):198-204. [PubMed]

12. Campbell B, Kreider RB, Ziegenfuss T, La Bounty P, Roberts M, Burke D, Landis J, Lopez H, Antonio J. International Society of Sports Nutrition position stand: protein and exercise. J Int Soc Sports Nutr. 2007 Sep 26;4:8. [PubMed]

13. Tipton KD, Wolfe RR. Protein and amino acids for athletes. J Sports Sci. 2004 Jan;22(1):65-79. [PubMed]


Semen is back in the news, ready to cure the blues. By Alan Aragon Hello again, Gallup et al A Valentines Day seasonal tradition in the sciency (and not-so-sciency) lay press is to make news headlines about a study by Gallup et al, which investigated the relationship between semen exposure and mood in women.1 Does it matter that this research was published in 2002 and never followed up? Of course not. From a journalistic perspective, theres no sense in neglecting a story thats a sure-bet for attracting a large readership. Lets take a closer look at this research. T

he inspiration for the study Back in 1986, the journal Medical Hypotheses published a case study by Ney,2 who documented a 23 year-old, depressed, child-abusing mothers improvement in mood. This apparently was a result of taking evening primrose oil (EPO, which is rich in gamma-linolenic acid), which may have initiated the return of her sex drive after a 6-week period of post-partum abstinence, which initially was intended for allowing the episiotomy to heal. It was during this period that depression and aggression toward her child manifested. Ney speculated that the EPO helped revive decreased prostaglandin levels that were contributory to her depression. Upon the return of sexual activity, he proposed that the physical exposure to the biologically active constituents of her husbands semen was instrumental in the return of her sense of well-being. The concluding paragraph of Neys study is worth quoting:

Although the role of exogenously given prostaglandins in improving libido and mood has not been established, there appears to be some link. The change in this woman's well being may be due to the absorbed estrogen or testosterone hormones, but in the amounts available from the sperm, it would seem that the prostaglandins would have a greater impact. If the deductions of this paper are correct, the oil of the evening primrose may be an important adjunctive treatment for postpartum depression and infant abuse or neglect.

Gallup et als findings

So, 16 years after the publication of Neys study, Gallup et al set out to test his hypothesis by recruiting 293 female college students who anonymously completed a questionnaire designed to assess sexual activity in terms of intercourse frequency and type of contraception. Condom use was the indirect indicator of the presence of semen in the reproductive tract. This factor and

others were then compared to the subjects score on the Beck Depression Inventory (BDI). 87% of the subjects were sexually active. Among these subjects, BDI scores varied according to frequency of condom use. Those who never used condoms had significantly lower BDI scores than those who usually or always used condoms. In addition, significantly lower levels of depression symptoms were seen in those who did not use condoms compared to those who abstained from intercourse. Number of days since last engaging in sexual intercourse was correlated with BDI scores as well, and this too was influenced by condom use. Those who used condoms most or all of the time showed no significant correlation with BDI score. However, for those who did not use condoms, greater length of time since their last bout if intercourse was positively correlated with depressive symptoms. Of all the variables (which included days since sex, frequency of sex, and duration of relationship), condom use was most closely correlated with variance in depression. A highly tabloid-worthy finding was that only 4.5% of those who never used condoms reported having attempted suicide. This statistic was 7.4% with the sometimes group. In contrast, the usually and always groups checked in at 28% and 13.2%, respectively. The latter two groups thus were significantly more likely to commit suicide. Limitations & future directions Gallup et al diligently acknowledged that their findings are merely correlational, and therefore subject to more rigorous investigation that can demonstrate causation. They conceded that more definitive measures of anti-depressive effects of semen would involve ...more direct manipulation of the presence of semen in the reproductive tract and, ideally, the measurement of seminal components in the recipients blood. Another potential confounder they acknowledged was that 7 out of the 10 sexually active women in the sample used oral contraceptives. Therefore, the possibility that oral contraceptives could at least be partially responsible for anti-depressive effects cannot be ruled out. Yet another potential confounder is that the higher frequency of sex in subjects who never used condoms could have independently nhibitory effects on depression. i

The authors ultimately conclude that their data support Neys seminal research, suggesting that the vaginas absorption of biologically active components in semen (e.g., sex hormones and prostaglandins) has the potential to alleviate depressive symptoms. Are they correct? Gallup et al themselves admitted that their findings ...raise more questions than they answer. However, its fairly certain that as next Valentines Day approaches, Gallup et als work will once again make headlines, and men all over the world will launch campaigns to convince their partners that they found the antidote for depression. R eferences 1. Gallup GG Jr, Burch RL, Platek SM. Does semen have

antidepressant properties? Arch Sex Behav. 2002 Jun;31(3):289-93. [PubMed]

2. Ney PG. The intravaginal absorption of male generated hormones and their possible effect on female behaviour. Med Hypotheses. 1986 Jun;20(2):221-31. [PubMed]


3 versus 6 meals per day for hunger control. By Alan Aragon

___________________________________________________ _ Assumption built into the question This line of thinking has been gaining popularity in the recent wake of research related to intermittent fasting and meal frequency. However, the idea that 3 meals per day controls hunger better than 6 meals is questionable. Is there a study showing this? Yes. But the outcomes of a study cannot definitively prove anything. The most it can do is contribute to, and thus, help shape the evolving body of evidence. The weight of the evidence (the direction it leans, if it leans in any particular direction in the first place) is what determines our current opinion of a given claim or idea. In the case of meal frequency and hunger control, the answer is far from simple. Lets take a chronological look at the recent surfacing of research focusing specifically on 3 versus 6 meals. These meal distributions have perhaps the greatest relevance to the majority concerned with this question. The research An 8-week trial by Cameron et al compared the effects of low meal frequency (3 meals per day) with a high meal frequency (3 meals plus 3 snacks per day).1 Energy restriction was approximately 700 kcal below maintenance. No significant differences were seen in bodyweight and body fat reduction between the groups. No significant differences in subjective appetite ratings or objective measurements of appetite-regulating gut peptides (PYY the fullness hormone & ghrelin the hunger hormone) were detected. Leidy et al compared the 11-hour effects of eucaloric diets composed of either normal protein (79 g per day) or higher protein (138 g per day) distributed over 3 versus 6 meals, and found contrasting results.2 Unsurprisingly, the higher-protein conditions resulted in greater fullness ratings independent of meal frequency. The 6-meal pattern resulted in lower daily fullness ratings, as well as lower PYY concentrations. A subsequent 12-week study by Leidy et al (the final 5 weeks compared meal frequency) examined the chronic effect of 3 versus 6 meals per day in a diet whose energy restriction was 750 kcal below maintenance.3 The higher-protein diet (25% of total energy) resulted in lower late-night hunger compared to the normal protein diet (14% of total energy). The 3-meal pattern resulted in greater evening & late-night fullness compared to the 6-meal condition, but only within the higher-protein diet. A 6-month trial by Bachman & Raynor compared the effects of a low frequency (3 meals per day) with a grazing pattern (at least

100 kcal every 2-3 hours).4 Total energy intake ranged 1200-1500 kcal per day. Despite significant reductions in BMI, no between-group differences were seen. Unsurprisingly, no differences in total energy intake were seen. The grazing group averaged 5.8 meals per day, and reported a significant reduction in hunger from 0 to 6 months. In contrast, no such hunger reduction was reported in the lower-frequency group averaging 3.2 meals per day.

I read an articlesaying that eating3mealsperdaycontrolshungerbetter than6mealsperday.He saidthat thishasbeenprovenwithascientificstudy. Is this true?Thanks.

In the most recent study to-date, Ohkawara et al compared the 24-hour effect of 3 versus 6 meals on 24-hour fat oxidation (using whole-room calorimetry) and subjective appetite ratings.5 No significant differences were seen in fat oxidation. There were no differences in ratings of fullness, but greater hunger was reported in the 6-meal condition. Summary & application To re-cap, one 8-week study reported no difference in appetite control,1 one 11-hour study reported lower fullness in the 6-meal condition,2 one 12-week study (whose final 5 weeks compared frequency effects) found greater hunger control in the 3-meal pattern when higher protein was consumed,3 one 6-month study reported hunger reduction with 6 meals but not with 3 meals,4 and finally, one 24-hour study reported greater hunger in the 6-meal condition.5 As the evidence stands, it cannot correctly be claimed that 3 meals per day is consistently superior to 6 meals a day for hunger control. The data is highly equivocal, with no clear winner. To me this is good news, since meal frequency for controlling appetite can be optimized according to personal preference and individual response. This sort of flexibility is contrary to the philosophy of a single-best way which is a common theme in a wide range of nutritional topics. However, there is a downside to these findings. The elusiveness of a singularly supreme approach to meal frequency is not good for building marketing hype.

References 1. Cameron JD, Cyr MJ, Doucet E. Increased meal frequency

does not promote greater weight loss in subjects who were prescribed an 8-week equi-energetic energy-restricted diet. Br J Nutr. 2010 Apr;103(8):1098-101. [PubMed]

2. Leidy HJ, Armstrong CL, Tang M, Mattes RD, Campbell WW. The influence of higher protein intake and greater eating frequency on appetite control in overweight and obese men. Obesity (Silver Spring). 2010 Sep;18(9):1725-32. [PubMed]

3. Leidy HJ, Tang M, Armstrong CL, Martin CB, Campbell WW. The effects of consuming frequent, higher protein meals on appetite and satiety during weight loss in overweight/obese men. Obesity (Silver Spring). 2011 Apr;19(4):818-24. [PubMed]

4. Bachman JL, Raynor HA. Effects of manipulating eating frequency during a behavioral weight loss intervention: a pilot randomized controlled trial. Obesity (Silver Spring). 2012 May;20(5):985-92. [PubMed]

5. Ohkawara K, Cornier MA, Kohrt WM, Melanson EL. Effects of increased meal frequency on fat oxidation and perceived hunger. Obesity (Silver Spring). 2012 Sep 13. doi: 10.1002/oby.20032. [Epub ahead of print] [PubMed]

Here is a clip featuring Phil Heath, the current Mr. Olympia for the second consecutive year. Hes being interviewed by some unknown/funny/skinny dude, and the result will bring a smile to y our face. How can anyone not be a Heath fan?

If you have any questions, comments, suggestions, bones of contention, cheers, jeers, guest articles youd like to submit, or any feedback at all, send it over to [email protected].


Table of ContentsEditor's Cut: Reserving carbs for night time: breakthrough diet solution or reverse dogma?Nutrition & ExerciseSystematic review and meta-analysis of different dietary approaches to the management of type 2 diabetes.Carbohydrates and exercise performance in non-fasted athletes: A systematic review of studies mimicking real-life.

Supplementation: Astaxanthin supplementation does not augment fat use or improve endurance performance.Less Recent Gems: Postprandial energy expenditure in whole-food and processed-food meals: implications for daily energy expenditure. Effects of high-calorie supplements on body composition and muscular strength following resistance training.

Study Comment ReferencesIn the Lay Press: Semen is back in the news, ready to cure the blues.Good Question: 3 versus 6 meals per day for hunger control.

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12 - Dec - 2012