From Volume 4, Issue 6 of MASS
Protein Distribution Matters, To An Extent
by Eric Trexler Ph.D. CSCS*D, CISSN
One of the most common questions in the world of nutrition is, “How much protein should I eat, and when?” A new study adds some nuance to the conversation, and suggests that protein distribution matters in some contexts. Read on to find out if you’re maximizing the impact of the protein in your diet.
Study Reviewed: Evenly Distributed Protein Intake over 3 Meals Augments Resistance Exercise–Induced Muscle Hypertrophy in Healthy Young Men. Yasuda et al. (2020)
- The presently reviewed study (1) evaluated the effects of two different diets (one with a high-protein breakfast and even protein distribution; another with a low-protein breakfast and uneven protein distribution) on strength and lean mass following 12 weeks of resistance training.
- Both groups made gains in strength and lean mass, but the high-protein breakfast group had slightly larger increases for all five strength outcomes and total lean soft tissue, although none of these between-group differences were statistically significant.
- The protein distribution literature doesn’t paint an entirely clear picture yet, and it’s a virtual certainty that total caloric intake, total protein intake, and an adequate training stimulus are far more important than protein distribution or timing. Nonetheless, there are potential benefits and no clear drawbacks from aiming to get about 3-5 sufficiently sized (≥0.24g/kg) doses of protein throughout the day if you’re interested in absolutely maximizing your gains.
How much protein should we eat, and when? For lifters with strength and physique goals, it’s a question that has dominated nutrition discussions for decades. For a time, it was generally thought that more frequent protein feedings were inherently better, as they provided a “steady drip” of amino acids into the bloodstream, fueling muscle protein synthesis around the clock. Then, mechanistic research introduced some more nuance to the conversation, indicating that the protein synthesis response to a single protein bolus has a limit, and there appears to be a “refractory” period between protein feedings (that is, a dose of protein doesn’t re-stimulate muscle protein synthesis if it’s consumed within a couple hours or so of a previous protein feeding) (2). These mechanistic findings would suggest that we’re better off splitting our protein between multiple meals, and spacing them throughout the day in a manner that allows for a maximal spike in protein synthesis, a maximal number of times per day. However, as Dr. Helms discussed in a previous MASS article, these mechanistic rationales have some shortcomings. Many studies that shape our understanding of acute responses to protein are conducted with subjects in a fasted state, net muscle accretion is dictated by both muscle protein synthesis and breakdown, and the protein dose required to maximize protein synthesis is impacted by the magnitude of the prior training stimulus. Further, the mechanistic rationale would seem to suggest that we can maximize our muscle gains by paradoxically low total protein intakes (~4-5 daily servings of ~0.24g/kg of protein, for a total of ~1.0-1.25g/kg of daily protein), whereas the available research generally indicates that protein intakes at or above 1.6g/kg are most likely to support maximal gains in fat-free mass (3). In addition, at the surface level, it seems to be contradicted by studies showing equivalent body composition results with intermittent fasting or time-restricted feeding interventions.
Fortunately, a new study came along this month to add more nuance to the protein distribution discussion. In the presently reviewed study (1), subjects were randomly assigned to one of two groups: one had a low-protein breakfast (~8g) with a higher protein dinner (~55g), while the other had a more equal protein distribution between breakfast (~23g) and dinner (~32g). Both groups had approximately the same total daily protein intake (high-protein breakfast group = 89 ± 6g, equivalent to 1.3g/kg body mass; low-protein breakfast group = 97 ± 3g, equivalent to 1.45g/kg body mass). Throughout the 12-week dietary intervention, subjects completed a supervised resistance training program three times per week. There were no statistically significant interaction effects for the strength and body composition measures taken, but the high-protein breakfast group had slightly more favorable strength increases for all five exercises tested (leg curl, leg extension, arm curl, row, chest press), and had slightly more favorable increases in lean soft tissue (2.5 ± 0.25kg versus 1.8 ± 0.26kg). So, can we finally conclude that uneven protein distribution impairs muscle and strength gains? Read on to find out why the conclusion isn’t quite that simple.
Purpose and Hypotheses
The primary purpose of the presently reviewed study was to determine if having an adequate bolus of protein at breakfast led to greater increases in lean mass in response to a 12-week resistance training program. In addition, the researchers evaluated the intervention’s effects on strength adaptations as well. For the purpose of this study, an “adequate” bolus of protein was defined as ≥0.24g/kg of body mass, based on a study indicating that this dose was sufficient to acutely maximize muscle protein synthesis in young men (4).
The authors did not explicitly state a hypothesis. However, based on the way the introduction is written, it seems like they suspected that more evenly distributed protein, resulting in a larger protein bolus at breakfast, would have a more favorable impact on increases in lean mass.
Subjects and Methods
This study recruited 33 healthy men between the ages of 18-26. Potential participants were excluded if they smoked, had been resistance training within the past year, had any chronic diseases, or were on any medications. Of the 33 subjects, 17 were randomly assigned to the high-protein breakfast group, and 16 were assigned to the low-protein breakfast group. Five subjects in the high-protein breakfast group dropped out of the study due to difficulty adhering to the diet intervention (n = 3) or “injury and surgery” (n = 2). In the low-protein breakfast group, one subject dropped out due to difficulty adhering to the diet intervention, and one dropped due to surgery. We don’t know exactly what those injuries or surgeries were, but the authors noted that they were not directly related to the intervention. As a result of this attrition, the study ended with 12 subjects in the high-protein breakfast group and 14 subjects in the low-protein breakfast group; their baseline characteristics are presented in Table 1.
As previously noted, subjects were randomly assigned to one of two groups. The high-protein breakfast group received a standardized breakfast meal consisting of yogurt, granola, and whey protein, while the low-protein breakfast group received the same breakfast without whey protein, and instead had their whey protein serving with dinner. As a result, the diets were designed so that the high-protein breakfast group would achieve an “adequate” intake of protein at all three meals of the day, whereas the low-protein breakfast group would have an inadequate protein intake at breakfast, with a much larger intake at dinner. The diets were intended to be approximately equal in terms of total protein intake and total energy intake, but it’s important to note that only the standardized breakfasts and whey protein shakes were provided for subjects, so the actual dietary assessments were based on self-reported three-day food records that were completed at baseline and at week 12 of the intervention. Before the start of the study, participants were educated about how to complete accurate food records, and they also took photographs of their food and completed face-to-face interviews with a dietitian to verify the accuracy of their food records.
Throughout the 12-week study, participants completed a supervised resistance training program. Workouts were 3 days per week (36 total sessions), and subjects were allowed to choose the timing of their training (morning session or afternoon session). The first 8 sessions were for familiarization purposes; after that, participants did 3 sets of 10 for each exercise, with the final set taken to failure, and loads were incrementally increased from session to session based on the repetitions achieved in the final set. It’s not 100% clear exactly what exercises were included in the training program, but the strength outcomes in the study included 1RM for leg curl, leg extension, arm curl, row, and chest press, so I’m assuming that those were the exercises performed during each workout. These performance outcomes were secondary outcomes, as the main focus of the study was to assess changes in body composition variables (total lean soft tissue mass, appendicular lean soft tissue mass, bone mineral content, and fat mass), which were measured via DEXA.
Finally, it’s important to note that the authors used standard error rather than standard deviation throughout their paper, and I have followed suit for this article. In many cases, when you see something like “105 ± 12kg,” you’re inclined to interpret that as a mean of 105kg, and a standard deviation of 12kg. The standard deviation simply gives an indication of how tightly the values are clustered around the mean value (smaller standard deviation, tighter clustering around the mean). Standard error is the same kind of thing, but it has a slightly different formula, which makes it a smaller number. If you want to convert standard error to standard deviation, you can just multiply the standard error by the square root of the sample size. So if a group has 12 subjects, and the standard error is 4.0, you’d multiply 4.0 by the square root of 12, and you’d have the standard deviation for that group.
Nutrient intakes for both groups at baseline and at week 12 are presented in Table 2. The high-protein breakfast group consumed slightly fewer calories based on the week 12 assessment (2456 ± 147 versus 2543 ± 114), but they were pretty close given that the numbers are based on self-reported intakes in a free-living population (that is, subjects who are not confined to a metabolic ward for the duration of the trial). As expected, the high-protein breakfast group had higher protein at breakfast (22.6 ± 0.02g versus 7.68 ± 0.03g), and lower protein intake at dinner (32.4 ± 3.06g versus 55.4 ± 3.17g). Overall, the high-protein breakfast group actually had less total daily protein intake (89.4 ± 5.51g [1.30 g/kg] versus 97.1 ± 3.46g [1.45 g/kg]). This wasn’t statistically significant, but it’s potentially notable given the nature of the study. The high-protein breakfast group also had higher daily intake of carbohydrate (323 ± 16.4 versus 315 ± 15.1) and lower intake of fat (84.4 ± 8.22g versus 94.5 ± 5.55g), but these were not statistically significant either.
For the strength training sessions, neither total workload performed nor total reps completed over the course of the 12-week training program were significantly different between groups. Interestingly, the high-protein breakfast group opted to complete a smaller percentage of their workouts in the morning (37.3 ± 5.2%) than the low-protein breakfast group (57.1 ± 5.3%), opting instead to complete more of their sessions in the afternoon. When it comes to actual strength outcomes, there were no statistically significant interaction effects observed. However, as you can see in Figure 1, the high-protein breakfast group tended to improve slightly more than the low-protein breakfast group for each individual lift.
Both groups had very similar changes in body weight and BMI, with both groups gaining about 2kg of total weight. The high-protein breakfast group lost about 0.5kg of fat mass while the low-protein breakfast group gained about 0.03kg of fat mass, but these changes were non-significant and are too small to consider noteworthy given the margin of error associated with DEXA measurements. The authors noted that the high-protein breakfast group gained more total lean soft tissue than the low-protein breakfast group (2.50 ± 0.25 kg vs 1.77 ± 0.26 kg); this was not statistically significant (p = 0.056), but a p-value of 0.056 warrants some degree of closer inspection, particularly with groups this small. The groups had virtually identical changes in appendicular lean soft tissue (1.14 ± 0.18 kg vs. 1.14 ± 0.17 kg); as a point of clarification, this appendicular measure only includes the arms and legs, and ignores the head and trunk region. As a result, we can infer that the differences in total lean soft tissue were almost exclusively attributable to differences in the trunk rather than the arms or legs. Changes in lean soft tissue, both at the group level and individual level, are presented in Figure 2.
It seems as if a lot of people frame the protein distribution discussion in terms of whether or not it matters, but I struggle to imagine anyone would truly argue that it doesn’t. For example, I can’t imagine there are many people who would suggest that eating an enormous bolus of protein once every 14 days is sufficient for optimizing muscle protein accretion. Same things goes for every 7 days, or even every 2 days. As a result, I think over 99% of people would agree that, at the most basic level, it matters. In reality, a more nuanced discussion pertains to how much it matters, the circumstances and settings in which it matters, and exactly how precise our approach to protein distribution needs to be.
Before we contextualize the current findings within the broader literature, let’s acknowledge some limitations of this study. Total protein intake wasn’t shockingly low in this study, but it was still comfortably below the 1.6-2.2g/kg range that is commonly recommended for promoting hypertrophy (3). As a result, some might argue that protein distribution could become less relevant as total protein is increased to 1.6g/kg and beyond. In addition, the magnitude of between-group body composition differences was quite small (a difference of 0.73kg for total lean soft tissue), particularly when you consider the measurement error that is associated with DEXA scans. The authors also offered very little detail regarding the pre-visit standardization procedures for DEXA scans, which could be really important when we’re talking about changes this small. Along those lines, there was virtually no difference for appendicular lean soft tissue, with all of the lean soft tissue differences occurring in the trunk region, which tends to be more sensitive to acute fluctuations induced by things like acute water consumption and contents of the gastrointestinal tract. Along those lines, it’s important to note that lean soft tissue of the trunk cannot be viewed synonymously with muscle mass of the trunk, as this region includes a ton of lean soft tissue that is not muscle (5). The study also featured a pretty small sample size; while this generally makes it less likely to observe super low p-values, it also increases the likelihood that we might see fluctuations in the mean values that are really “noise” rather than an actual generalizable effect. Finally, subjects were allowed to choose their training session timing (morning versus afternoon), and more subjects in the low-protein breakfast group tended to opt for morning training sessions. The reasoning for this isn’t known, but it’s possible that individuals in the high-protein breakfast group felt more full than they otherwise would, and weren’t enthusiastic about a morning workout on a full stomach. While the evidence-based fitness community has largely moved away from stressing over ultra-precise protein timing before and after workouts, this was a cohort of individuals eating three meals per day, and the low-protein breakfast group was getting about 7-8g of protein at breakfast, after an overnight fast. I’m not saying you need an enormous post-workout protein shake to be in your hand before you rack your last set of the day, and we don’t know the exact timing of these morning sessions in proximity to breakfast and lunch, but it’s not hard to imagine that some subjects were implementing suboptimal peri-workout protein timing strategies.
Having said all of that, let’s look at some of the positive features of the study. While the findings were not statistically significant, they were internally consistent, which counts for something. For example, if you see that one group had (non-significantly) larger gains in leg extension strength, but (non-significantly) smaller gains in leg press strength, you’re inclined to believe that you’re just seeing some noise in the data, rather than a discernible pattern. In the current study, the high-protein breakfast group experienced small advantages in comparison to the low-protein breakfast group, but they were internally consistent across all strength outcomes and lean soft tissue of the trunk. While I previously acknowledged that trunk lean soft tissue includes a ton of lean mass that isn’t skeletal muscle, we also can’t adopt the overly simplistic idea that trunk soft tissue is just “organs and stuff”– it includes core musculature, pecs, lats, and upper back, in addition to some of the musculature surrounding the shoulders and hips. The findings also fit quite nicely with our mechanistic understanding of how dietary protein contributes to muscle protein accretion. We know that an insufficient bolus of protein fails to maximize the acute muscle protein response, but beyond a certain point, adding more and more protein to a single bolus does not further increase muscle protein synthesis. We also know that muscle protein synthesis is acutely increased following a bolus of dietary protein, but this is a transient effect, and adding an additional bolus shortly after the first one does not have an additive effect on muscle protein synthesis. We essentially aim to maximize muscle protein synthesis with a sufficiently large dose of protein, wait out the refractory period for a couple hours or so, then we have another opportunity to induce another maximal increase in muscle protein synthesis. The results also appear to indicate that there is more to the story than total protein intake alone, as the low-protein breakfast group actually tended to eat more protein per day (89.4 ± 5.51g [1.30 g/kg] versus 97.1 ± 3.46g [1.45 g/kg]; not statistically significant). So, even though the low-protein breakfast group more than made up for it at the dinner meal, their strength and body composition outcomes were still a little less favorable.
In the interest of full transparency, this explanation of our current understanding of protein timing and distribution is oversimplified. For example, the concept of the refractory period was established using tightly controlled experimental designs that generally provided the initial protein or amino acid bolus in a fasted state, did not incorporate resistance exercise, and focused on muscle protein synthesis alone while neglecting protein breakdown, which is also a major contributor to net protein balance (6). In addition, it would be incorrect to suggest that a protein dose greater than the amount required to acutely maximize muscle protein synthesis is necessarily “wasteful.” In fact, research shows that even though a larger dose may not further increase muscle protein synthesis, it does reduce protein breakdown to a greater extent (6), which would tilt protein balance more positively. That doesn’t necessarily discount the possibility that there are some diminishing returns with super large protein boluses, such that the relative gram-for-gram effect on net muscle accretion is reduced with exceptionally large boluses, but it definitely refutes the idea that the excess protein is totally wasted in terms of net protein balance. This also intuitively makes sense; a very literal application of protein dosing based on maximizing acute muscle protein synthesis and refractory periods would suggest that someone could essentially maximize their gains by consuming about 1-1.25g/kg of protein per day (that is, a dose of 0.24g/kg, spaced 4 or 5 times throughout the day). This contradicts a pretty large body of evidence indicating that 1.6-2.2g/kg per day is a much safer bet for total daily protein intake if maximizing hypertrophy is the goal (3).
While this literature supporting our theoretical understanding of protein distribution is certainly incomplete in nature, there is some experimental evidence that lends support. In 2017, Norton et al (7) reported that an even distribution of protein across all three meals led to greater muscle mass in adult rats compared to uneven distribution, which involved suboptimal protein intakes at breakfast and lunch, with a large bolus of protein at dinner. In a human study with a much shorter study timeline, Areta and colleagues (8) tested three different protein timing strategies following a bout of resistance exercise: one group had eight 10g doses every 1.5 hours, a second group had four 20g doses every 3 hours, and a third group had two 40g doses every 6 hours. Results indicated that the 20g doses every 3 hours were most effective for stimulating muscle protein synthesis. Another human study found that equal protein distribution (~30g per meal, for 3 meals each day) led to greater rates of 24-hour muscle protein synthesis than a skewed distribution (~11g, ~16g, and ~63g at breakfast, lunch, and dinner), although this study did not involve a resistance training component (9). In addition, there is some evidence indicating that pre-sleep protein ingestion may enhance resistance training adaptations; while it’s certainly possible that an increase in total protein intake is driving some of these positive benefits, it’s also quite plausible that pre-sleep protein intake confers an additional benefit by exploiting another daily opportunity to stimulate muscle protein synthesis (10).
Before we get too carried away with protein distribution and timing, let’s contextualize the conversation a little bit by focusing on practical application. If you’re looking to add some muscle mass, you need a robust training stimulus, an adequate amount of total calories, and an optimal amount of total daily protein intake. Those three factors are going to explain the overwhelming majority of your results in terms of hypertrophy, and all other factors (including protein distribution and timing) are of secondary or tertiary importance. However, if you’re interested in maximizing your likelihood of maximizing hypertrophy, protein distribution is a factor worth considering. Notably, I would suspect that the relative benefit of “improving” your protein distribution is diminished as we approach optimal distribution. For example, the magnitude of improvement is probably pretty sizable if you switch from an utterly suboptimal distribution, such as consuming a huge protein dose every third day, to consuming a dose of protein each day. The jump from once a day to twice a day is probably smaller, twice a day to thrice a day is probably even smaller, and I would suspect that it gets pretty hard to reliably identify tangible, meaningful improvements when you start going beyond three sizable protein doses per day. Plus, once you get up above the 5-6 doses per day range, you can theoretically run into scenarios where it’s hard to ensure that each individual protein dose is large enough to maximize muscle protein synthesis, or the protein feedings become so frequent that they more or less blend together.
At the surface level, intermittent fasting (also known as time-restricted feeding) advocates may be eager to reject this approach to protein timing and distribution, but I don’t think it’s necessarily that incompatible with intermittent fasting. For example, we’ve seen instances within the intermittent fasting literature where lean mass gains are seemingly impaired by intermittent fasting (11), and other instances in which intermittent fasting has no negative impact on adaptations to resistance training (12). However, the methodological differences between these two studies are pretty informative; in the study showing an apparent impairment of lean mass gains, the feeding window was four hours long, and the time-restricted feeding group consumed about 1g/kg of protein per day while the comparison group consumed about 1.4 g/kg per day (11). In contrast, the study showing no impairment of hypertrophy featured an eight-hour feeding window, and all groups consumed about 1.6g/kg of protein (12). If you’re working with an eight-hour window and adequate total protein for the day, it seems quite feasible to work three large daily protein boluses into your diet. Would you benefit from adding a fourth, either upon waking or prior to bed? Possibly, but it probably wouldn’t make a huge impact if you were applying a solid training stimulus, eating enough protein overall, and already getting three separate boluses of protein each day. It should be really clear by now, based on both published research and practical experience, that people can make excellent gains while implementing intermittent fasting. Even in the current study, the low-protein breakfast group made solid gains on only two protein meals per day, and you could make a strong argument that their gains were hardly distinguishable from those of the high-protein breakfast group. So, the results of this study should not be used to suggest that intermittent fasting is an unequivocal gains-killer. Rather, the decision to use an intermittent fasting approach ultimately comes down to an assessment of the costs and benefits; while it may be beneficial in terms of things like convenience or hunger control, it might be slightly less optimal in terms of stimulating muscle protein synthesis. However, the jump from less optimal to more optimal may only confer a marginal improvement in terms of muscle or strength gains, while making your diet drastically less compatible with your personal preferences. So, if you’re looking to make solid gains, you should feel pretty comfortable using a wide range of protein distribution and timing strategies, provided that you’re training effectively and generally eating enough protein and calories each day. However, if you’re really intent on absolutely maximizing your gains, you might consider taking a closer look at your protein distribution to make sure you’re getting 3-5 sufficiently large (≥0.24g/kg) doses of protein throughout the day. I can’t imagine a scenario in which there’s an adverse effect of achieving a balanced spread of protein intake throughout the day (aside from inconvenience), and it has some potential for a modest benefit.
One of the tricky things about interpreting this body of literature is that it often requires us to make indirect inferences from studies that aren’t specifically designed to evaluate optimal protein distribution. For example, we might make inferences based on studies about pre- or post-workout protein supplementation, time-restricted feeding, or acute protein synthesis responses to a single meal, with studies that may or may not include a resistance training component. However, we’re actually interested in looking at the effect of protein distribution on hypertrophy or strength gains over time. I’d love to see a big, 12 (or more) week study that includes a structured resistance training program. All three groups eat the same amount of protein, split among 2, 3, or 4 meals (if you wanted a more extreme approach, you could go with 1/3/5 meals per day, but you might have trouble finding a group of people that are willing to eat over 1.6g/kg of protein at a single meal every day). Each meal would be designed to deliver a large enough protein dose to maximize the acute muscle protein synthesis response, and meals would be spaced as evenly as possible throughout the day to account for the possibility of refractory periods between meals. I suspect that three meals might be a little bit better than two, and four might be just slightly better than three, but I’d love to see exactly how meaningful (or meaningless) the differences among groups would be. This would tell us a lot about how big or small of a sacrifice you might be making when you let convenience dictate your meal frequency instead of our current mechanistic understanding of protein distribution.
Application and Takeaways
People can make really great gains using low meal frequencies that restrict their protein intake to a narrow time window. In addition, it’s safe to say that meal frequency and timing aren’t nearly as important as having a robust training stimulus, eating the correct number of calories, and taking in sufficient total daily protein. However, the results of this study agree with some other literature suggesting that there might be modest strength and hypertrophy benefits associated with a more even distribution of protein throughout the day. It’s clearly not a huge effect, and there are some instances when the benefits of lower protein frequency with a skewed protein distribution, such as convenience or hunger management, outweigh the potential benefits of higher protein frequency with more even protein distribution throughout the day. However, for individuals who are solely focused on maximizing their gains, there might be a slight advantage to obtaining 3-5 sufficiently large (≥0.24 g/kg) doses of protein throughout the day.
- Yasuda J, Tomita T, Arimitsu T, Fujita S. Evenly Distributed Protein Intake over 3 Meals Augments Resistance Exercise-Induced Muscle Hypertrophy in Healthy Young Men. J Nutr. 2020 Apr 22; ePub ahead of print. doi: 10.1093/jn/nxaa101.
- Mitchell WK, Phillips BE, Hill I, Greenhaff P, Lund JN, Williams JP, et al. Human skeletal muscle is refractory to the anabolic effects of leucine during the postprandial muscle-full period in older men. Clin Sci Lond Engl 1979. 2017 Oct 27;131(21):2643–53.
- Morton RW, Murphy KT, McKellar SR, Schoenfeld BJ, Henselmans M, Helms E, et al. A systematic review, meta-analysis and meta-regression of the effect of protein supplementation on resistance training-induced gains in muscle mass and strength in healthy adults. Br J Sports Med. 2018 Mar;52(6):376–84.
- Moore DR, Churchward-Venne TA, Witard O, Breen L, Burd NA, Tipton KD, et al. Protein ingestion to stimulate myofibrillar protein synthesis requires greater relative protein intakes in healthy older versus younger men. J Gerontol A Biol Sci Med Sci. 2015 Jan;70(1):57–62.
- Reidy PT. Muscle or Nothing! Where Is the Excess Protein Going in Men with High Protein Intakes Engaged in Strength Training? J Nutr. 2020 Mar 1;150(3):421–2.
- Kim I-Y, Schutzler S, Schrader A, Spencer HJ, Azhar G, Ferrando AA, et al. The anabolic response to a meal containing different amounts of protein is not limited by the maximal stimulation of protein synthesis in healthy young adults. Am J Physiol – Endocrinol Metab. 2016 Jan 1;310(1):E73–80.
- Norton LE, Wilson GJ, Moulton CJ, Layman DK. Meal Distribution of Dietary Protein and Leucine Influences Long-Term Muscle Mass and Body Composition in Adult Rats. J Nutr. 2017;147(2):195–201.
- Areta JL, Burke LM, Ross ML, Camera DM, West DWD, Broad EM, et al. Timing and distribution of protein ingestion during prolonged recovery from resistance exercise alters myofibrillar protein synthesis. J Physiol. 2013 May 1;591(9):2319–31.
- Mamerow MM, Mettler JA, English KL, Casperson SL, Arentson-Lantz E, Sheffield-Moore M, et al. Dietary protein distribution positively influences 24-h muscle protein synthesis in healthy adults. J Nutr. 2014 Jun;144(6):876–80.
- Snijders T, Trommelen J, Kouw IWK, Holwerda AM, Verdijk LB, van Loon LJC. The Impact of Pre-sleep Protein Ingestion on the Skeletal Muscle Adaptive Response to Exercise in Humans: An Update. Front Nutr. 2019 Mar 6;6:17.
- Tinsley GM, Forsse JS, Butler NK, Paoli A, Bane AA, La Bounty PM, et al. Time-restricted feeding in young men performing resistance training: A randomized controlled trial. Eur J Sport Sci. 2017 Mar;17(2):200–7.
- Tinsley GM, Moore ML, Graybeal AJ, Paoli A, Kim Y, Gonzales JU, et al. Time-restricted feeding plus resistance training in active females: a randomized trial. Am J Clin Nutr. 2019 Sept;110(3):628–40.