February 2017 AARR



Copyright ? September 1st, 2019 by Alan AragonHome: Correspondence: support@ 2Oral contraceptives and performance. By Astrid Naranjo9The effect of intermittent compared with continuous energy restriction on glycaemic control in patients with type 2 diabetes: 24-month follow-up of a randomised noninferiority trial.Carter S, Clifton PM, Keogh JB. Diabetes Res Clin Pract. 2019 May;151:11-19. [PubMed]11Postprandial levels of GLP-1, GIP and glucagon after 2 years of weight loss with a Paleolithic diet: a randomised controlled trial in healthy obese women.Otten J1, Ryberg M1, Mellberg C1, Andersson T1, Chorell E1, Lindahl B1, Larsson C2, Holst JJ3, Olsson T1. Eur J Endocrinol. 2019 Jun 1;180(6):417-427 [PubMed]13Branched-chain amino acids do not improve muscle recovery from resistance exercise in untrained young adults. Estoche JM, Jacinto JL, Roveratti MC, Gabardo JM, Buzzachera CF, de Oliveira EP, Ribeiro AS, da Silva RA, Aguiar AF. Amino Acids. 2019 Aug 29. doi: 10.1007/s00726-019-02776-5. [PubMed] 15Research update on training to failure.By Alan Aragon 19Green powders & pills: are they necessary or beneficial? By Alan AragonMenstrual cycle, oral contraceptives, & health: a review of the art & science of synchronizing diet and training throughout the cycle.By Astrid Naranjo_________________________________________________I have been looking forward to writing about this topic for months now, as I know there are countless women out there wanting to learn more about the basics of the menstrual cycle and understanding how this can be synchronized with diet and training for increasing better adherence to the programs and achieve results in a smoother way. There is also growing interest regarding whether the menses synchronization theory would be applicable to women of child-bearing age regardless of the cycle length or the use of hormonal contraceptives. The main purpose of this review is to make it as simple as possible so you can digest the information and educate others around you. Therefore, as a woman’s dietitian and health advocate, I have put my heart in this article for you!Understanding the basics & physiology of the menstrual cycle The term ‘menstrual cycle’ simply refers to the changes that occur naturally in a woman’s body to prepare and get it ready for pregnancy. It can be seen as a sequence of bodily changes controlled by female hormones that cause a regular cycle of bleeding. This bleeding, which usually occurs monthly, comes from the uterus (womb) and flows out naturally from the vagina. 'Period', 'menstruation' or 'menses' are all words used to describe the blood loss women experience at this time.1,2The menstrual cycle begins at menarche (the first period) and ends with menopause (a period of events leading to the final period). The average age of menarche occurs usually around 12-13 years, but it can start as early as 9 or as late as 16 years old. However, it seems to initiate most frequently when a young woman reaches around 17% body fat,3 though, it may not be the amount of body fat per se that affects the beginning of menarche.4 It has been shown that also height, weight, and skinfold thickness all appear to play a role here. The menstrual cycle, then, continues to occur until the onset of menopause around the age of 45-50 years when the ovaries stop producing estrogen and the reproductive system gradually starts shutting down.5,6Every woman's cycle is unique. The length may vary from woman to woman, but generally, the typical length of the cycle is 28 days (some shorter, some longer). It is common for women to experience cycles that last anywhere from 20 to 40 days.1 Cycles longer than six weeks are considered unusual. Bear in mind that the length of a woman’s cycle can change throughout her life. Irregular periods tend to be common amongst adolescent women and in those approaching menopause.Meanwhile, the follicle containing the eggs starts to produce and I am a passionate Accredited Practicing Dietitian (APD) with a Master degree from Bond University with experience across a wide range of areas (bariatric surgery, Fitness, Weight loss, clinical and sports nutrition, eating disorders) and with a deep interest in research and evidence-based practice. My mission as a professional is to become a recognized Dietitian offering an evidence-based, holistic, customized and professional nutritional approach to all my audience in social media and patients, helping them to become and achieve healthier and better versions of themselves. Instagram: @antidiet_dietitianTwitter: @astridnar Email: astridfit6@ ____________________________________________________ReferencesMihm M, Gangooly S, Muttukrishna S. The normal menstrual cycle in women. Animal reproduction science. 2011;124(3-4):229-36. [PubMed]Branched-chain amino acids do not improve muscle recovery from resistance exercise in untrained young adults. Estoche JM, Jacinto JL, Roveratti MC, Gabardo JM, Buzzachera CF, de Oliveira EP, Ribeiro AS, da Silva RA, Aguiar AF. Amino Acids. 2019 Aug 29. doi: 10.1007/s00726-019-02776-5. [PubMed]PURPOSE: The purpose of this study was to investigate the effects of BCAA supplementation on muscle recovery from resistance exercise (RE) in untrained young adults. DESIGN: Twenty-four young adults (24.0 ± 4.3 years old) were assigned to 1 of 2 groups (n = 12 per group): a placebo-supplement group or a BCAA-supplement group. The groups were supplemented for a period of 5 days. On day 1 and 3, both groups underwent a RE session involving two lower body exercises (hack squat and leg press) and then were evaluated for muscle recovery on the 3 subsequent moments after the RE session [30 min (day 3), 24 h (day 4), and 48 h (day 5)]. The following indicators of muscle recovery were assessed: number of repetitions, rating of perceived exertion in the last RE session, muscle soreness and countermovement jump (CMJ) during recovery period (30 min, 24 h, and 48 h after RE session). RESULTS: Number of repetitions remained unchanged over time (time, P > 0.05), while the rating of perceived exertion increased (time, P < 0.05) over 3 sets, with no difference between groups (group × time, P > 0.05). Muscle soreness increased (time, P < 0.05) and jumping weight decreased (time, P < 0.05) at 30 min post-exercise and then progressively returned to baseline at 24 and 48 h post-exercise, with no difference between groups (group × time, P > 0.05). CONCLUSIONS: The results indicate that BCAA supplementation does not improve muscle recovery from RE in untrained young adults. FUNDING: This study was funding by North University of Paraná (UNOPAR) (Grant number: 02.2016).StrengthsThis study is conceptually strong since it investigates the effects of a highly popular sports supplement. Branch chain amino acids (BCAA), particularly leucine, which plays a crucial role in the process of muscle growth by activating the mammalian target of rapamycin (mTOR) signaling pathway.1 Hackett et al4 reported that BCAA are the third-most common dietary supplement used by male bodybuilders (in first and second place were protein powder and creatine). Right behind BCAA was glutamine, which has consistently failed to enhance muscular size and strength.5 This trial was double-blind, and placebo-controlled. 3-day, software-analyzed dietary records were used to guide subjects in duplicating their 24-hour intake leading up to each testing session. LimitationsThe authors acknowledged three limitations: 1) Blood amino acid levels were not assessed to confirm the absorption of BCAA – but this is a reach, given previous research consistently showing high bioavailability. 2) Direct markers of muscle repair and remodeling such as IGF-I, mTOR, and p70S6k were not assessed; this would have required biopsies which are invasive, and 48-72 hours of recovery before strenuous physical activity can resume, and this would have conflicted temporally with the design of this study. 3) Markers of muscle recovery were only analyzed after the second exercise session. This opens the possibility for missing the tracking of physiological effects of the first session that could have influenced the subsequent session. I would add that the use of untrained subjects renders limited generalizability to trained and athletically advanced individuals seeking the competitive edge. Also, this acute-effect investigation, through tightly controlled, cannot chronic or long-term effects of BCAA supplementation. Comment/applicationAs seen above, BCAA supplementation was ineffective for increasing the number of reps, lowering the rate of perceived exertion, or decreasing soreness. Unshown is a lack of effect on jumping height and peak power output. In summary, BCAA didn’t do jack. An important acknowledgement by the authors is that “…daily protein intake (~1.5 g/kg/day) might have been sufficient to maximize muscle recovery in our participants, masking the BCAA effects.” This is one of the rare times that this possibility is mentioned by the authors of BCAA supplementation trials. Another rare instance of self-awareness in reporting was when Aguiar et al7 reported a lack of effect of 3 g leucine taken post-resistance exercise on muscle strength and cross-sectional area, and noted that the protein intake of the subjects ranged 1.6-1.7 g/kg/day. Spillane et al8 found that a total of 9 g BCAA taken before and after resistance training failed to enhance body composition and performance. Baseline protein in the BCAA group was 1.34 g/kg, which is suboptimal, In this case, the authors speculated that their BCAA dose possibly could have been too low to impart ergogenic effects. I’d say, just toss the BCAA and consume a scoop of whey, where you’d get far more bang for the buck. The so-called “leucine trigger” is a leucine-dependent intracellular sensing mechanism that relies on elevations in leucinemia to stimulate muscle protein synthesis (MPS) and the related activation of mTOR.2 A “leucine threshold” is a dosing break-over point required to raise MPS above resting levels.3 This dose is estimated to be approximately 1 g in younger subjects and >2 g in older subjects due to less sensitivity/greater age-related anabolic resistance. These qualities of leucine have created an alluring mystique, which has been great for marketing the purported effectiveness of BCAA supplementation for a wide range of athletic pursuits. The persistence of BCAA’s popularity among bodybuilders and performance athletes will likely continue despite its weak theoretical and evidential basis for efficacy – especially within the context of sufficient total daily protein from a mix of high-quality sources (which already consist of 18-26% BCAA).9,10ReferencesDuan Y, Li F, Liu H, Li Y, Liu Y, Kong X, Zhang Y1, Deng D, Tang Y, Feng Z, Wu G, Yin Y. Nutritional and regulatory roles of leucine in muscle growth and fat reduction. Front Biosci (Landmark Ed). 2015 Jan 1;20:796-813. [PubMed]Phillips SM. Current Concepts and Unresolved Questions in Dietary Protein Requirements and Supplements in Adults. Front Nutr. 2017 May 8;4:13. [PubMed]Witard OC, Wardle SL, Macnaughton LS, Hodgson AB, Tipton KD. Protein Considerations for Optimising Skeletal Muscle Mass in Healthy Young and Older Adults. Nutrients. 2016 Mar 23;8(4):181. [PubMed]Hackett DA, Johnson NA, Chow CM. Training practices and ergogenic aids used by male bodybuilders. J Strength Cond Res. 2013 Jun;27(6):1609-17. [PubMed]Ramezani Ahmadi A, Rayyani E, Bahreini M, Mansoori A. The effect of glutamine supplementation on athletic performance, body composition, and immune function: A systematic review and a meta-analysis of clinical trials. Clin Nutr. 2019 Jun;38(3):1076-1091. [PubMed]Shanely RA, Zwetsloot KA, Triplett NT, Meaney MP, Farris GE, Nieman DC. Human skeletal muscle biopsy procedures using the modified Bergstr?m technique. J Vis Exp. 2014 Sep 10;(91):51812. [PubMed]Aguiar AF, Grala AP, da Silva RA, Soares-Caldeira LF, Pacagnelli FL, Ribeiro AS, da Silva DK, de Andrade WB, Balvedi MCW. Free leucine supplementation during an 8-week resistance training program does not increase muscle mass and strength in untrained young adult subjects. Amino Acids. 2017 Jul;49(7):1255-1262. [PubMed]Spillane M, Emerson C, Willoughby DS. The effects of 8 weeks of heavy resistance training and branched-chain amino acid supplementation on body composition and muscle performance. Nutr Health. 2012 Oct;21(4):263-73. [PubMed]Wolfe RR. Branched-chain amino acids and muscle protein synthesis in humans: myth or reality? J Int Soc Sports Nutr. 2017 Aug 22;14:30. [PubMed]Dieter BP, Schoenfeld BJ, Aragon AA. The data do not seem to support a benefit to BCAA supplementation during periods of caloric restriction. J Int Soc Sports Nutr. 2016 May 11;13:21. [PubMed]Intermittent compared with continuous energy restriction on glycaemic control in patients with type 2 diabetes: 24-month follow-up of a randomised noninferiority trial.Carter S, Clifton PM, Keogh JB. Diabetes Res Clin Pract. 2019 May;151:11-19. [PubMed]AIMS: We investigated the effects of intermittent compared to continuous energy restriction on glycaemic control in patients with type 2 diabetes mellitus. METHODS: Adults (N = 137) with type 2 diabetes (mean [SD] HbA1c level, 7.3% (56 mmol/mol) [1.3%] [14.2 mmol/mol]) were randomised to one of two diets for 12 months. The intermittent group (n = 70) followed a 2100-2500 kJ (500-600 kcal) diet 2 non-consecutive days/week and their usual diet for 5 days/week. The continuous group (n = 67) followed a 5000-6300 kJ (1200-1500 kcal) diet for 7 days/week. Follow-up occurred at 24 months, 12 months after the completed intervention. The primary outcome was change in HbA1c and the secondary outcome was weight loss. RESULTS: Intention-to-treat analysis showed an increase in mean [SEM] HbA1c level at 24 months in both the continuous and intermittent groups (0.4% [0.3%] vs 0.1% [0.2%] respectively; P = 0.32) (4.4 [3.3 mmol/mol] vs 1.1 [2.2 mmol/mol]; P = 0.32), with a between-group difference of 0.3% (90% CI, -0.31 to 0.83%) (3.3 mmol/mol [90% CI, -3.2 to 9.1 mmol/mol]) outside the prespecified boundary of ± 0.5% (5.5 mmol/mol), so statistical equivalence was not shown. Weight loss was maintained (P < 0.001) at -3.9 kg [1.1 kg] in both groups at 24 months, with a between-group difference of 0.07 kg (90% CI, -2.5 to 2.6 kg) outside the prespecified boundary of ±2.5 kg. There were no significant differences between groups in body composition, fasting glucose levels, lipid levels, or total medication effect score at 24 months, which remained less than baseline. CONCLUSIONS: In this prospective analysis weight loss was maintained but despite this HbA1c increased to above baseline levels in both groups. FUNDING: SC was supported by a University of South Australia Postgraduate award. PMC was supported by a National Health and Medical Research Council principal research fellowship. StrengthsThe topic of dietary/non-drug means to alleviate type 2 diabetes (T2D) is a highly relevant, and the disease has been described as one of the fastest growing public health concerns in the United States.1 The 5:2 variant of intermittent energy restriction has consistently performed as well as continuous energy restriction for weight loss and other markers of cardiometabolic health.2 This variant of intermittent energy restriction (IER) had subjects consuming their habitual diet on 5 days per week, with 2 days consisting of a very-low calorie diet; 500-600 kcals with at least 50 g protein. Energy-restricted days were mostly non-consecutive. In order to bolster compliance, Dietary counseling was provided by a dietitian every 2 weeks for the first 3 months, and every 2-3 months for the final 9 months of the trial. A standout strength of this trial is its long-term duration (24 months), and relatively large sample size (104 subjects). This is the longest trial examining the 5:2 variant of IER to date. Body composition was assessed via dual X-ray absorptiometry (DXA), and daily step count was tracked via pedometer. Medication changes were also tracked. LimitationsSince no food or meal replacements were provided, we’re left with self-reported dietary intakes, which are notoriously inaccurate.3-5 However, in their previous 12-month study6 the authors mentioned that their aim was to make the study as pragmatic and reflective of real-world conditions as possible. The intervention’s physical activity element was generally weak (they merely asked subjects to maintain habitual physical activity). As previously mentioned, a design strength was the tracking of daily step counts. However, without a physical activity goal, the program is simply not ideal for mitigating or managing T2D. At baseline, daily step count averaged 6344. By the 24-months, it was nearly back to baseline at 6505. At 3 and 12 months, step counts were 7812 and 7192, respectively. This physical activity regressed toward baseline levels, which were below the recommendations of several governmental & professional health agencies.7 A profound limitation was the lack of compliance by the end of the two-year period in both groups. Quoting the authors:“It is important to note that none of the participants were following the diets at 24 months. Most participants reported following parts or principles from the diets e.g. occasionally using intermittent energy restriction or watching portion sizes in the continuous energy restriction group to help maintain weight.”Comment/applicationAs shown above, (larger image here), HbA1c increased by 0.3% (7.3% at baseline to 7.6% at 24 months) from baseline by the end of the 24-month trial. 33% of bodyweight was regained between months 12-24. Nevertheless, bodyweight was 3.9 kg lower at 24 months compared to baseline. The worsening of glucose control despite the weight loss is an unfortunate finding which led the authors to conclude that ongoing intervention and dietetic support is necessary for the progressive nature of T2D. Overall, there were no significant between-group differences in in body composition, fasting glucose, lipid profile, or total medication effect score. When analyzing completers of the study, IER lost significantly more fat free mass at 24 months compared to CER. Overall, the diets were modestly and similarly successful for weight loss, but unsuccessful for improving glycemic control. It’s likely that the weight loss was just not enough to positively impact glucose homeostasis. And judging by the trajectory of the weight change, it’s also possible that the subjects are still en route to further weight gain. More aggressive dietary interventions need to be made, both in imposing a caloric deficit, and likely food choice and macronutrient modification as well. The lack of differing effects led the authors to ultimately conclude that ongoing dietetic support is more important than the type of dietary intervention. I would add to this that a 5:2 model for T2Ds is not ideal if their “usual” diet is the standard western crap-ola diet. In contrast to the disappointing findings of the present study, Shaminie et al8 examined the 2-year effects of the Virta Health program that combines ketogenic dieting with regular monitoring/accountability and online community support. The Virta intervention decreased HbA1c by 0.9%, and more than doubled the weight loss of the present study (10% vs. 4%). Furthermore, medication use decreased significantly, whereas no medication decrease was seen in the present study. Clearly there are lessons to be learned for the Virta system, and the strong points appear to be community support and accountability in addition to higher protein (1.5 g/kg) within the keto diet. I cover the Virta study in-depth in the next section. ReferencesOh W, Kim E, Castro MR, Caraballo PJ, Kumar V, Steinbach MS, Simon GJ. Type 2 Diabetes Mellitus Trajectories and Associated Risks. Big Data. 2016 Mar 1;4(1):25-30. [PubMed]Cioffi I, Evangelista A, Ponzo V, Ciccone G, Soldati L, Santarpia L, Contaldo F, Pasanisi F, Ghigo E, Bo S . Intermittent versus continuous energy restriction on weight loss and cardiometabolic outcomes: a systematic review and meta-analysis of randomized controlled trials. J Transl Med. 2018 Dec 24;16(1):371. [PubMed]Archer E, Lavie CJ2, Hill JO. The failure to measure dietary intake engendered a fictional discourse on diet-disease relations. Front Nutr. 2018 Nov 13;5:105Archer E, Lavie CJ2, Hill JO. The Failure to Measure Dietary Intake Engendered a Fictional Discourse on Diet-Disease Relations. Front Nutr. 2018 Nov 13;5:105. [PubMed]Stubbs RJ, O'Reilly LM, Whybrow S, Fuller Z, Johnstone AM, Livingstone MB, Ritz P, Horgan GW. Measuring the difference between actual and reported food intakes in the context of energy balance under laboratory conditions. Br J Nutr. 2014 Jun 14;111(11):2032-43. [PubMed]Rosell MS, Hellénius ML, de Faire UH, Johansson GK. Associations between diet and the metabolic syndrome vary with the validity of dietary intake data. Am J Clin Nutr. 2003 Jul;78(1):84-90. [PubMed]Carter S, Clifton PM, Keogh JB. Effect of Intermittent Compared With Continuous Energy Restricted Diet on Glycemic Control in Patients With Type 2 Diabetes: A Randomized Noninferiority Trial. JAMA Netw Open. 2018 Jul 6;1(3):e180756. [PubMed]Tudor-Locke C, Craig CL, Brown WJ, Clemes SA, De Cocker K, Giles-Corti B, Hatano Y, Inoue S, Matsudo SM, Mutrie N, Oppert JM, Rowe DA, Schmidt MD, Schofield GM, Spence JC,Int J Behav Nutr Phys Act. 2011 Jul 28;8:79. Teixeira PJ, Tully MA, Blair SN. How many steps/day are enough? For adults. [PubMed]Athinarayanan SJ, Adams RN, Hallberg SJ, McKenzie AL, Bhanpuri NH, Campbell WW, Volek JS, Phinney SD, McCarter JP. Long-Term Effects of a Novel Continuous Remote Care Intervention Including Nutritional Ketosis for the Management of Type 2 Diabetes: A 2-Year Non-randomized Clinical Trial. Front Endocrinol (Lausanne). 2019 Jun 5;10:348. [PubMed]Research update on carbohydrate quality and human health. By Alan Aragon_______________________________________________Reynolds et al1 recently published an ambitious series of systematic reviews and meta-analyses within a single paper. It’s fair to guess that this is thus far the most comprehensive peer reviewed research publication on the topic of carbohydrate quality and health. Before we dive into the findings, here’s the abstract of the paper to provide an overview as well as the dry details for your reference. _______________________________________________BACKGROUND: Previous systematic reviews and meta-analyses explaining the relationship between carbohydrate quality and health have usually examined a single marker and a limited number of clinical outcomes. We aimed to more precisely quantify the predictive potential of several markers, to determine which markers are most useful, and to establish an evidence base for quantitative recommendations for intakes of dietary fibre. METHODS: We did a series of systematic reviews and meta-analyses of prospective studies published from database inception to April 30, 2017, and randomised controlled trials published from database inception to Feb 28, 2018, which reported on indicators of carbohydrate quality and non-communicable disease incidence, mortality, and risk factors. Studies were identified by searches in PubMed, Ovid MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials, and by hand searching of previous publications. We excluded prospective studies and trials reporting on participants with a chronic disease, and weight loss trials or trials involving supplements. Searches, data extraction, and bias assessment were duplicated independently. Robustness of pooled estimates from random-effects models was considered with sensitivity analyses, meta-regression, dose-response testing, and subgroup analyses. The GRADE approach was used to assess quality of evidence. FINDINGS: Just under 135 million person-years of data from 185 prospective studies and 58 clinical trials with 4635 adult participants were included in the analyses. Observational data suggest a 15-30% decrease in all-cause and cardiovascular related mortality, and incidence of coronary heart disease, stroke incidence and mortality, type 2 diabetes, and colorectal cancer when comparing the highest dietary fibre consumers with the lowest consumers. Clinical trials show significantly lower bodyweight, systolic blood pressure, and total cholesterol when comparing higher with lower intakes of dietary fibre. Risk reduction associated with a range of critical outcomes was greatest when daily intake of dietary fibre was between 25 g and 29 g. Dose-response curves suggested that higher intakes of dietary fibre could confer even greater benefit to protect against cardiovascular diseases, type 2 diabetes, and colorectal and breast cancer. Similar findings for whole grain intake were observed. Smaller or no risk reductions were found with the observational data when comparing the effects of diets characterised by low rather than higher glycaemic index or load. The certainty of evidence for relationships between carbohydrate quality and critical outcomes was graded as moderate for dietary fibre, low to moderate for whole grains, and low to very low for dietary glycaemic index and glycaemic load. Data relating to other dietary exposures are scarce. INTERPRETATION: Findings from prospective studies and clinical trials associated with relatively high intakes of dietary fibre and whole grains were complementary, and striking dose-response evidence indicates that the relationships to several non-communicable diseases could be causal. Implementation of recommendations to increase dietary fibre intake and to replace refined grains with whole grains is expected to benefit human health. A major strength of the study was the ability to examine key indicators of carbohydrate quality in relation to a range of non-communicable disease outcomes from cohort studies and randomised trials in a single study. Our findings are limited to risk reduction in the population at large rather than those with chronic disease. FUNDING: Health Research Council of New Zealand, WHO, Riddet Centre of Research Excellence, Healthier Lives National Science Challenge, University of Otago, and the Otago Southland Diabetes Research Trust._______________________________________________StrengthsThe authors acknowledged the following design strengths:A systematic approach was used to quantify the association of key characteristics of carbohydrate quality to mortality and mortality and incidence of the major nutrition-related non-communicable diseases (NCDs). Only prospective studies (both observational and interventional) were considered for this review, which minimized the higher degree of bias and error inherent in retrospective research.Multiple indicators of carbohydrate quality (rather than a single indicator as seen in previous reviews and meta-analyses) were used to provide stronger justifications for recommendations. The health benefits from different doses of fiber were calculated based on the generation of dose-response curves, rather than by arbitrary means.Quality of evidence was assessed by methods developed by the GRADE Working Group was used to assess the quality of evidence.I would add that the expanse of research covered in this analysis is vast (135 million person-years of data from 185 prospective studies and 58 clinical trials with 4635 subjects). LimitationsThe authors were relatively elusive in acknowledging the methodological limitations of their paper; certainly much less explicit than they were with pointing out its strengths. With that said, the one limitation that they implied was that the evidence for the associations between carbohydrate quality markers and outcomes was most frequently rated as moderate or low. This was attributed to inherent limitations with the GRADE method of quality assessment, which biases high quality ratings toward randomized controlled trials (RCTs) with disease endpoints. This can unfairly prejudge other types of studies with other types of endpoints.Another limitation was that the relationship between fruit and vegetable consumption and NCDs was not investigated in this analysis. The authors justified this circumvention by narratively summarizing the findings of Aune et al,2 which I’ll discuss in the next section. Comment/applicationThis series of systematic reviews and meta-analyses (it’s fun to call it a mega-analysis) boils down to 3 main findings: The greatest risk reduction for non-communicable diseases (NCDs) was seen with higher intakes of fiber, and this occurred in a dose-response manner. Based on the collective evidence, a fiber intake of no less than 25-29 g/day should be consumed, “with additional benefits likely to accrue with greater intakes.” The general population tends to consume less than 20 g/day. Insufficient data are available for drawing definitive recommendations of fiber sources and fiber subtypes. The robustly positive health effects of fiber are unsurprising given its consistently favorable track record in the research literature.3-7 NCD risk reduction via whole grain consumption is similar in magnitude to that of fiber consumption (risk reduction is roughly 20%). Notably, cereal fiber is typically the largest contributor to total dietary fiber. Quoting the authors: “Regarding the associations reported here between dietary fibre and whole grains and a wide range of clinical outcomes, the consistency of the findings, the striking dose-response relationships, and the substantial body of mechanistic evidence all contribute to the total body of evidence and increases our confidence in the findings.”Glycemic index and glycemic load comprise the lowest tier of impact, with little to no reductions in risk for NCDs. I’ve spoken at-length about the shortcomings and lack of utility of GI/GL in the Good Questions section of the June 2018 issue of AARR. I’d like to reiterate that that the relationship between fruit & vegetable consumption and NCDs was not analyzed, but its importance was acknowledged by discussing a recent meta-analysis by Aune et al.2 Every 200 g (about 2.5 servings) of combined fruit & vegetable consumption resulted in a 10% risk reduction for coronary heart disease, stroke, and total mortality. Total cancer risk was lowest at an intake of 550–600 g/day (7-7.5 servings/day). Significant dose-response effects were seen for most outcomes up to 800 g (about 10 servings) per day, beyond which point a lack of further benefit is seen. It turns out that fiber is an indispensably important factor in determining the effect of carbohydrate quality on health. This conclusion is contrary to the anti-fiber warnings of folks in the ‘carnivore’ camp, who reach for any reason they can to disparage the consumption of plant foods, and carbohydrate sources in general. Zealotry at its finest. Back to science - a nicely done by Chen et al3 proposed the following mechanisms underlying fiber’s beneficial effects on components of the metabolic syndrome (MetS): MetS componentProposed mechanism of mitigation by dietary fiberObesityEnergy dilution, reduced nutrient absorption rate (via physicochemical properties such as viscosity & solubility); appetite suppression and promotion of satiation & satiety; alteration of gut microbiotaInsulin resistanceLowered postprandial insulin & glucose response; modulation of inflammatory cytokines; alteration of gut microbiota, colonic fermentation & production of short-chain fatty acids (SCFA) which reduce hepatic glucose output DyslipidemiaGel-forming properties increase viscosity & lowers cholesterol; increased fecal bile salts excretion; reduced glycemic response of food; colonic fermentation of soluble fiberHypertensionMechanisms of effects on blood pressure reduction are still unclear; increasing dietary fiber may have a ‘trickle down’ benefit on hemodynamics by lowering related risk factors such insulin resistance and dyslipidemiaClosing caveats & nuancesA caveat I’ll cast into consideration is that observational (uncontrolled) research and experimental (controlled) research on whole grains is not always in agreement. The significance of this discrepancy is that RCTs can establish causal relationships between variables, while observational studies can only draw potential associations; not cause-and-effect. Hence, we have the cautionary note that correlation doesn’t automatically equal causation; it could be guilt (or innocence) by association. For example, Maki et al8 recently reported that the inverse association between BMI and whole grain intake in observational studies was not seen in RCTs. Along these lines, a meta-analysis of cohort studies by Aune et al9 found that higher whole grain intake is associated with reduced type 2 diabetes risk. In contrast, a meta-analysis by Maventano et al10 did not find a significant improvement in insulin sensitivity in healthy subjects in medium- and long-term RCTs. The following excerpt from a recent review by Della Pepa11 captures the incongruity and uncertainty of the current evidence whole grain consumption and type 2 diabetes mellitus (T2DM): “Many intervention trials have been undertaken in order to investigate whether wholegrain consumption is able to improve major risk factors for T2DM; however, findings from these studies have not been as impressive as those from the observational ones. So far, the evidence from these trials do not allow us to draw definite conclusions about the preventive efficacy of wholegrain foods on the development of T2DM or its major risk factors.”On a final note, not all grains are equal in their health effects. Oats have consistently outperformed other grains for improving blood lipid profile.12,13 Oats have also outperformed wheat for reducing postprandial glucose and insulin responses.14 Oats, unless contaminated, can be safely consumed by individuals with celiac disease, which has a prevalence of 0.7-1.4% of the global population.15 ReferencesReynolds A, Mann J, Cummings J, Winter N, Mete E, Te Morenga L. Carbohydrate quality and human health: a series of systematic reviews and meta-analyses. Lancet. 2019 Feb 2;393(10170):434-445. [PubMed]Aune D, Giovannucci E, Boffetta P, et al. Fruit and vegetable intake and the risk of cardiovascular disease, total cancer and all-cause mortality—a systematic review and dose-response meta-analysis of prospective studies. Int J Epidemiol 2017; 46: 1029-56. [PubMed]Veronese N, Solmi M, Caruso MG, Giannelli G, Osella AR, Evangelou E, Maggi S, Fontana L, Stubbs B, Tzoulaki I. Dietary fiber and health outcomes: an umbrella review of systematic reviews and meta-analyses. Am J Clin Nutr. 2018 Mar 1;107(3):436-444. [PubMed]McRae MP. The Benefits of Dietary Fiber Intake on Reducing the Risk of Cancer: An Umbrella Review of Meta-analyses. J Chiropr Med. 2018 Jun;17(2):90-96. [PubMed]Zheng B, Shen H, Han H, Han T, Qin Y. Dietary fiber intake and reduced risk of ovarian cancer: a meta-analysis. Nutr J. 2018 Oct 30;17(1):99. [PubMed]Chen JP, Chen GC, Wang XP, Qin L, Bai Y. Dietary fiber and metabolic syndrome: a meta-analysis and review of related mechanisms. Nutrients. 2017 Dec 26;10(1). [PubMed]McRae MP. Dietary Fiber Is Beneficial for the Prevention of Cardiovascular Disease: An Umbrella Review of Meta-analyses. J Chiropr Med. 2017 Dec;16(4):289-299. [PubMed]Maki KC, Palacios OM2, Koecher K, Sawicki CM, Livingston KA, Bell M, Nelson Cortes H, McKeown NM. The Relationship between Whole Grain Intake and Body Weight: Results of Meta-Analyses of Observational Studies and Randomized Controlled Trials. Nutrients. 2019 May 31;11(6). pii: E1245. [PubMed]Aune D, Norat T, Romundstad P, Vatten LJ. Whole grain and refined grain consumption and the risk of type 2 diabetes: a systematic review and dose-response meta-analysis of cohort studies. Eur J Epidemiol. 2013 Nov;28(11):845-58. [PubMed]Marventano S, Vetrani C, Vitale M, Godos J, Riccardi G, Grosso G. Whole Grain Intake and Glycaemic Control in Healthy Subjects: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. Nutrients. 2017 Jul 19;9(7). [PubMed]Della Pepa G1, Vetrani C2, Vitale M3, Riccardi G. Wholegrain Intake and Risk of Type 2 Diabetes: Evidence from Epidemiological and Intervention Studies. Nutrients. 2018 Sep 12;10(9). pii: E1288. [PubMed]Hui S, Liu K, Lang H, Liu Y, Wang X, Zhu X, Doucette S, Yi L, Mi M. Comparative effects of different whole grains and brans on blood lipid: a network meta-analysis. Eur J Nutr. 2018 Sep 22. [PubMed]Holl?nder PL, Ross AB, Kristensen M. Whole-grain and blood lipid changes in apparently healthy adults: a systematic review and meta-analysis of randomized controlled studies. Am J Clin Nutr. 2015 Sep;102(3):556-72. [PubMed]Hou Q, Li Y, Li L, Cheng G, Sun X, Li S, Tian H. The metabolic effects of oats intake in patients with type 2 diabetes: a systematic review and meta-analysis. Nutrients. 2015 Dec 10;7(12):10369-87. [PubMed]Singh P, Arora A, Strand TA, Leffler DA, Catassi C5, Green PH, Kelly CP, Ahuja V, Makharia GK. Global Prevalence of Celiac Disease: Systematic Review and Meta-analysis. Clin Gastroenterol Hepatol. 2018 Jun;16(6):823-836.e2. [PubMed]What separates novice, intermediate, and advanced trainees? By Alan Aragon_________________________________________________This is a surprisingly difficult question without a nice, neat, and simple answer. Different sports have different demands that vary in terms of performance along the strength-endurance continuum. Further complicating the answer to this question, physique sports do not have any specific performance demands (except for the psychological endurance of suffering through a prolonged diet, and posing in while feeling like death). Physique competitions are judged primarily on the combination of muscular size, leanness, and aesthetics. Different sports carry their own terminology for classifying training/competitive status. So, the original question must first be met with the question of what type of sport or activity we’re talking about.Endurance-dominant sportsThere are two systematic reviews that comprehensively cover the classification of subjects into escalating categories of aptitude. The first is by De Pauw et al,1 who categorized subjects into 5 performance levels based on biometric parameters (body mass & composition data), physiological parameters (VO2max, peak power output), and training status (competition experience, current daily or weekly training volume). The following table summarizes the characteristics of the 5 performance levels (larger image here):A subsequent systematic review by Decroix et al2 developed guidelines to classify female subject groups. In the following table, you’ll see that the stratification is based on the same parameters (biometric, physiological, & training status data) as previously done in De Pauw et al’s work with male subjects (larger image here): Although this classification system is based on cyclists, it presents a well-organized model with viable application to other endurance-oriented sports (with minimal necessary alterations in the parameters).Lorenz et al3 examined this topic in a more narrative fashion by delineating elite versus nonelite endurance athletes in various endurance sports, based on various parameters (maximal oxygen uptake, running economy, anaerobic threshold, anthropometry, and training characteristics). Several examples were provided. Elite marathon runners typically have a VO2max of 70 to 85 mL/kg/min. Average running economy (steady-state submaximal oxygen uptake at a given running velocity) of 10 top-class marathoners was 210 mL/kg/km. In triathletes, the anaerobic threshold during cycling ranged 61-88%. The average body fat percent for elite female and male runners combined is 8.0%, whereas “good” and “average” runners were 10.7% and 12.1%, respectively.Strength/power-dominant sports, and sports with more evenly mixed strength & endurance demandsIn resistance training research, designations of novice, intermediate, and advanced are not as commonly used. Instead, the binary distinction of trained versus untrained subjects is often preferred, especially in primary research, which often seeks to simplify the variables. Less common designations are recreationally trained and well trained, and highly trained. The definitions of these terms vary from study to study, and they inevitably are subjective and arbitrary. A minimum of 6 months of regular lifting experience typically qualifies subjects as trained. A relative absence of regular lifting for at least 6 months typically qualifies subjects as untrained. These low-barrier definitions have been a longstanding challenge to the external validity (real-world relevance) of research find-ings to athletes who can be considered advanced, or close to their potential. Similar definitions are nevertheless are echoed in the position stand of the American College of Sports Medicine (ACSM),4 which defines novices as “untrained individuals with no RT [resistance training] experience or who have not trained for several years.” Intermediates are defined as “individuals with approximately 6 months of consistent RT experience.” Advanced trainees are defined as “individuals with years of RT experience.” The following classification system by the National Strength & Conditioning Association (NSCA) also shares similar definitions (larger image here):5In the realm of powerlifting, an attempt to stratify novice, subelite, and elite strength athletes according to strength performance was recently done by Latella et al.6 The performance of 2,137 competitors from local (LOC), national (NAT), and international (INT) competitions was evaluated by using the total (TOT) competition score within weight classes and age categories. A moderate to large difference in performance between LOC and NAT competitions for all weight classes. But interestingly, performance of athletes at NAT and INT competitions were similar with no clear overall effects across weight classes or age categories. This lack of difference preserves the existing uncertainty of how to objectively distinguish subelite and elite-level powerlifters. Physique sportsThe problem of classifying trainees involved with physique sports is compounded by a lack of objective performance requirements. Ironically, it’s within physique sports that people tend to obsess over which category they’re in. In conceptual terms, the closer you are to your potential for muscular size, the more advanced you are. Conversely, the further you are from your potential, the more of a novice you are. The inevitable imprecision of these constructs makes categorization extremely difficult. It's fair to say that professional bodybuilders (the ones who actually earn prize money within major organizations such as the IFBB) are advanced trainees. As we proceed down the ranks, things get progressively muddier. National and state-level bodybuilding champs are safe to call advanced trainees. As we go further down, the subjectivity increases, and the lines between intermediate and advanced begin to blur – even in formal competition. As we proceed away from the competitive realm, what if you are one of the top-5 most jacked people at your gym? What if you have the best physique at the apartment complex pool (credit to Paul Carter for that one)?A bodybuilder and mathematician named Casey Butt developed a good resource for estimating the muscular potential of natural bodybuilders (calculator here, methodology described here).7 In the following table, Lyle McDonald used the calculator to estimate the bodyweight and lean body mass of individuals of different heights, at 10% bodyweight, given a 7-inch wrist and 8.75-inch ankle circumference:8Being close to the figures above is a potential indicator of advanced training status. While it’s fun to mess around with the calculator to generate estimations, remember that these are inevitably hypothetical. It’s useful for arriving at realistic ballpark figures – not for pinpointing the exact thresholds of natty destiny. St. Brad Schoenfeld weighs in on defining novice, intermediate, & advanced liftersI’ll close this article with personal communication I had with St. Schoenfeld. Quoting him: “My view is that the stratification has little basis. Most importantly, it doesn't give any attention to *how* the subjects are training. Are they pushing themselves? Are they using proper form? What modalities are they using? Etc... I know people that after several months of training are more "advanced" than those with years of training. Now in fairness, there is no way I know that you can quantify "how" a person trains. One possible alternative method is to use markers based on performance. For instance, the ability to bench bodyweight, or squat bodyweight. You can conceivably use multiples (i.e. 1.5x BW for the squat) as an indicator of advanced training experience. But this has limitations as it is exercise-specific: some people don't squat and yet still can be well-trained in other exercises.”References De Pauw K, Roelands B, Cheung SS, de Geus B, Rietjens G, Meeusen R. Guidelines to classify subject groups in sport-science research. Int J Sports Physiol Perform. 2013 Mar;8(2):111-22. [PubMed]Decroix L, De Pauw K, Foster C, Meeusen R. Guidelines to classify female subject groups in sport-science research. Int J Sports Physiol Perform. 2016 Mar;11(2):204-13. [PubMed]Lorenz DS, Reiman MP, Lehecka BJ, Naylor A. What perfomance characteristics determine elite versus nonelite athletes in the same sport? Sports Health. 2013 Nov;5(6):542-7. [PubMed]American College of Sports Medicine. American College of Sports Medicine position stand. Progression models in resistance training for healthy adults. Med Sci Sports Exerc. 2009 Mar;41(3):687-708. [PubMed]Clayton N, et al. Foundations of fitness programming. National Strength & Conditioning Association. 2015. [NSCA]Latella C, van den Hoek D, Teo WP. Differences in Strength Performance Between Novice and Elite Athletes: Evidence From Powerlifters. J Strength Cond Res. 2019 Jul;33 Suppl 1:S103-S112. [PubMed]Butt C. Maximum Muscular Bodyweight and Measurements Calculator. [The WeighTrainer]McDonald L. What’s my genetic muscular potential? June 9, 2009. [ HYPERLINK "" BodyRecomposition]“It’s not about shining so others can see you. It’s about shining so others can see their own beauty through you.” – Shawne DuperonIf you have any questions, comments, suggestions, bones of contention, cheers, jeers, guest articles you’d like to submit for consideration, send it over to support@. ................
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