Introduction: Calorie restricted weight loss results in approximately 20-30% of mass lost as lean body mass (LBM). The ability of an athlete to retain LBM is important for the athlete to maintain their physical performance. Diets which allow athletes to lose weight while either maintaining or gaining LBM are of significant importance. One such strategy is the consumption of supplemental protein combined with resistance training. Preliminary research has demonstrated 30 grams of protein consumed after resistance training while in an energy deficit increased muscle protein synthesis (MPS) to a greater degree than 15 grams of protein (Areta, Burke, Camera, West, Crawshay, Moore, … Coffey, 2014). Other findings have suggested daily protein intake twice the Recommended Dietary Allowance (RDA) attenuated LBM loss during an energy deficit (Pasiakos, Cao, Margolis, Sauter, Whigham, McClung… Young, 2013). Given these findings, the authors proposed there would be a synergistic effect between resistance training (RT), high intensity interval training (HIT)/sprint interval training (SIT), and higher protein diet during a marked energy deficit (40%)
Purpose: The purpose of this study was to compare the effects of a high-protein (2.4 g x kg -1 x d-1) to a lower protein diet (1.2 g x kg -1 x d-1) in combination with RT and HIT over 28 days. The authors hypothesized the higher protein would allow for better maintenance and possibly augmentation of LBM.
Subject Description: Forty overweight (BMI kg/m2>25) young men (23+/- 2 years, 184 +/- cm, 97.4+/- kg) were recruited by posters and newspaper advertisements from the local community. The individuals were recreationally active (physically active 1-2 days per week) but did not actively engage in RT or a structured exercise program.
This population choice appears to be a population choice of convenience. The authors recruited active males whom are young and healthy, but generally overweight but not obese. Choosing a group of novices to exercise makes interruption of the results challenging. Untrained individuals are more likely to experience gains in LBM due to the novelty of the exercise stimulus. Therefore, the results of the study have to be cautiously interrupted and further studied in trained individuals.
Methods and Procedures: Participants were randomly allocated to either a control group (CON) (n=20) or a protein group (PRO)(n=20). The CON group was assigned a diet with a 40% +/- 3% estimated calorie restricted diet with a macronutrient intake of 15% protein ((1.2 g x kg -1 x d-1), 50% carbohydrate, and 15% fat. The PRO group was also assigned a 40% +/- 3% estimated calorie restricted diet with a macronutrient intake of 35% protein (2.4 g x kg -1 x d-1), 50% carbohydrate, and 15% fat. Estimated calorie restriction was determined by the formula 33 +/- kcal x kg-1 LMB x d-1. Participants were subjected to an initial baseline VO2 max to determine aerobic capacity. The test was performed using a ramp protocol and a Wingate Anaerobic Test on a cycle ergometer. After a 10 hour fast, participants underwent a body composition evaluation along with blood samples. Total body volume was determined with the use of air-displacement plethysmography (BodPod). Total body water was determined via bioelectrical impedance. Bone mineral content was evaluated using dual x-ray absorptiometry (DEXA). Coefficient of variation for repeated measures was 1.2% for BodPod, 1.9% for bioelectrical impedance, and 0.8% for DEXA. Participants were provided with all meals and beverages to consume throughout the intervention. The diet consisted of a 3 day rotating meal schedule of frozen pre-packaged meals. Both groups received whey protein beverages to be consumed throughout the day with one specifically to be consumed after training. Adherence was assessed by daily contact with the participants, checklists, and daily weight monitoring. Adherence was estimated to be 93%. Compliance with exercise was >96%. Blinding of the subjects was accomplished by altering the macronutrient content of the beverages, with the high protein group receiving a higher content of protein. Exercise training occurred 6 days per week and included a full-body resistance training program (2 days), HIT (2 days), a time trial cycle ergometer (1 day), and a plyometric body weight circuit (1 day). Resistance training included 3 sets of 10 repetitions at 80% repetition maximum (RM) with the last set to failure and 1 minute of rest between sets. HIT consisted of 1 day of 4-8s sprints on a cycle ergometer with 4 minutes of rest between bouts and 1 day of 10 all out sprints for 1 minutes at 90% of peak power with 1 minute of rest pedaling at 50 W. Plyometrics consisted of a body weight circuit with 30s of rest between exercises. Strength and muscular performance were measured at baseline and post intervention. Participants completed 1 RM for the bench press and leg press. Push-up and sit-up tests were included and consisted of the maximum number with correct form per 60 s. Blood sampling occurred following a 10-h fast and analyzed for cortisol, testosterone, growth hormone, ghrelin, and total and free IGF-1.
Sample size was determine prior to the study using LBM as the primary outcome measure to determine power. To detect LBM of 1 kg with p=0.05 and power of 90%, it was determine a sample size of 16 in each group would be adequate.
The strengths of this study included a unique way to blind the subjects by hiding the protein content in supplements. This made it nearly impossible for the participants to guess which group they were in. Another strength to this study was the control of the diet by providing the meals. Many studies fail to provide the meals due to increased costs. Diets are notoriously difficult to maintain compliance. By providing preset meals, the authors made it convenient for the subjects to diet and achieved very high adherence to the diet. This is superior to simply providing a meal plan, which the participants may not adhere too. Additionally, the daily contact with the participants also played a key role in maintaining adherence. The exercise protocol was unique and provided a combination of different exercise stimulus. The combination of aerobic, resistance training, and plyometric training helped ensure fat loss while providing a stimulus to generate LBM. The authors choosing to include 20 subjects in each arm while only requiring 16 subjects, which was determined via the pre-trial power analysis, ensured the study had adequate power in the event a few subjects dropped out. A limitation to the methods include differing fat content in each diet. The high protein diet consumed more protein and less fat, while the CON consumed more fat and less protein. Overall, I thought the methods section was well-written and the authors utilized a unique protocol to accomplish their goals.
Results: There was significant weight loss in both groups from pre to postintervention, but no differences between groups (p>0.8). LBM remained unchanged in the CON group (0.1 +/- 1.0 kg). LBM increased in the PRO group (1.2 +/- 1.0 kg). The gain in LBM was statistically significant (p<0.05). Fat loss was significantly greater in the PRO group (-4.8 kg +/- 1.6 kg) compared to the CON (-3.5 +/-1.4 kg) (p<0.05). There were no statistically significant differences in any strength or muscle performance measures between groups. Strength and performance increases were found in all tests of anaerobic and aerobic capacity. Blood urea nitrogen increased significantly in the PRO group (p<0.05) and was unchanged in the CON group. Body mass was significantly decreased from 100.1 +/- 12.8 kg to 94.2 +/- 13.7 kg in the PRO. Body mass significantly decreased from 96 +/- 14.6 kg to 92.5 +/- 14.0 kg. No differences or correlations were found for any hormone measures between groups. VO2 max increased from 41.1 +/- 5.6 mL x kg -1 x min-1 to 46.4 +/- 8.4 mL x kg -1 x min-1 in the PRO group. VO2 max increased from 4o.5 +/- 4.9 mL x kg -1 x min-1 to 47.4 +/- 6.9 mL x kg -1 x min-1 in the CON group.
The results were reported in a concise and clear manner. The authors used a table to report the results of the performance variables as well as body composition variables. This made the results easy for the reader to interpret and gain a quick understanding of the significant values. The standard deviations appears a little high, which was most likely due to small sample size. For instance, the standard deviation for post body mass measurement in the PRO group was 13.7 kg, which equates to 30.2 pounds. The authors did not post the specific results of the blood panel. This was most likely because none of the variables found were significantly different between groups. Another consideration would be space restrictions by the research journal. It would obviously be more beneficial if the reader and other researchers had these values for closer scrutiny.
Discussion: This study found a protein intake 3 times the RDA resulted in significant lean body mass gains in untrained individuals during a marked (40%) energy deficit. Additionally, greater fat loss was noted in the PRO group compared to the CON. Interestingly, there were no differences in performance measures between groups. This may be due to the short duration of the study, which a longer study and possible greater differences in LBM accounting for performance differences. A larger and longer duration study will be needed to further investigate this hypothesis. The loss of fat mass was the sole reason individuals lost mass. The inclusion of HIT most likely increased subjects’ fat oxidation. The data of the study also suggests consuming higher amounts of protein during an energy deficit results in increased stimulation of muscle protein synthesis, which is evident by the gains in LBM in the PRO group.
Conclusion/Limitations: In conclusion, this study demonstrated in young men a higher protein diet during an energy deficit combined with intense exercise can augment gains in LBM. Limitations to this study include the untrained population, inability to fully control the diet, and small sample. It may be possible these results only apply to untrained individuals. It is plausible trained individuals may respond differently during an energy deficit. Although meals were provided, it is nearly impossible to know with absolute certainty the individuals were consuming the meals without supervision. Lastly, the small sample size resulted in wider standard deviations. A larger study would reduce the variability in the samples.
Primary Reference
Longland, T. M., Oikawa, S. Y., Mitchell, C. J., Devries, M. C., & Phillips, S. M. (2016). Higher compared with lower dietary protein during an energy deficit combined with intense exercise promotes greater lean mass gain and fat mass loss: a randomized trial. American Journal of Clinical Nutrition, 103(3), 738-746. doi:10.3945/ajcn.115.119339
Secondary References
Areta, J. L., Burke, L. M., Camera, D. M., West, D. W., Crawshay, S., Moore, D. R., … Coffey, V. G. (2014). Reduced resting skeletal muscle protein synthesis is rescued by resistance exercise and protein ingestion following short-term energy deficit. AJP: Endocrinology and Metabolism, 306(8), E989-E997. doi:10.1152/ajpendo.00590.2013
Pasiakos, S. M., Cao, J. J., Margolis, L. M., Sauter, E. R., Whigham, L. D., McClung, J. P., … Young, A. J. (2013). Effects of high-protein diets on fat-free mass and muscle protein synthesis following weight loss: a randomized controlled trial. The FASEB Journal, 27(9), 3837-3847. doi:10.1096/fj.13-230227
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