International SportMed Journal
Resistance training and protein intake: Muscular mass and volume variations in amateur bodybuilders
Dr Francesco Masedu, PhD, Mr Salvatore Ziruolo, MSc, Professor Marco Valenti, PhD, *Professor Antonio Di Giulio, PhD
Faculty of Human Movement and Sport Sciences, University of L'Aquila, Italy
*Corresponding author. Address at the end of text.
Background: Optimal nutrition, especially in terms of protein ingestion, is a tool to enhance the hypertrophic response to resistance training. The ingestion of high amounts of dietary protein in conjunction with resistance training reduces the rate of muscle protein breakdown when muscular hypertrophy of optimal restitution is the goal. Research question: The purpose of this study was to determine if and how protein intake increases muscular mass and volume after a six-month resistance training period in amateurs. Type of study: Longitudinal 'one-within, one-between' study. Methods: The sample group consisted of 13 amateur bodybuilders. The control group consisted of 36 amateur bodybuilders of the same age. Participants followed a controlled specific exercise protocol 3 times/week, using 3 sets of 8-6-4 Maximal Repetitions (MR). Subjects were interviewed about their usual diet to determine their daily protein intake, i.e. 2.03 ± 0.62 and 1.04 ± 0.05g/kg BW, in the experimental and control groups respectively. Anthropometric characteristics (body weight, body girth and skin-folds) were measured. A statistical analysis for longitudinal data was carried out using a random intercept model. Results: No statistical evidence of dietary regimen influence in muscle increase or statistically significant interaction between time and diet were found. The statistically significant changes detected in some muscles (i.e. chest girth p<0.05) come down from time trends, supporting the authors' hypothesis that they had only a training effect on the solicited body segments. Conclusions: This study's data analysis does not justify the excessive protein intake in amateur bodybuilders' diets aimed at increasing muscular mass and volume. Keywords: bodybuilder, exercise, muscle hypertrophy, nutrition, physical fitness
Dr Francesco Masedu, PhD
Dr Masedu works at the University of L'Aquila, Italy, he has got a PhD in Medical Statistics, his research interest is Biostatistics applied to Medicine and Sports.
Mr Salvatore Ziruolo, MSc
Mr Ziruolo is a PhD student at the University of L'Aquila. His research interest is Sport Nutrition.
Professor Marco Valenti, PhD
Professor Valenti is Associate Professor of Epidemiology and Medical Statistics at the Faculty of Sport Science at the University of L'Aquila, Italy. His research interest is Biostatistics applied to Medicine and Sports.
*Professor Antonio Di Giulio, PhD
Professor Di Giulio is Associate Professor of Biochemistry at the Faculty of Sport Science at the University of L'Aquila, Italy. His research interests are in Biochemistry and Nutrition.
Bodybuilding is a sport based on aesthetic appearance of the body and is considered a "technical-combinatory sport". Therefore the aim and training regimen for bodybuildiing is the increase and sculpture of the muscular mass.
Provided that the exercise intensity is of sufficient magnitude, acute changes in the rate of skeletal muscle protein turnover may occur, resulting in increases in both protein synthesis and degradation 1. The muscle protein synthesis rate is increased in humans after bouts of resistance training providing a stimulus are of sufficient magnitude 2. This process may account for about 20% of resting energy expenditure 3. Due to the mass of this tissue, protein turnover in muscles accounts for 30-50% of the whole body protein turnover. However, in the absence of sufficient nutritional intake, muscle protein degradation may exceed synthesis in the early stages of recovery from exercise 4. On the contrary, it has been shown that exercise-induced muscle protein synthesis can be exacerbated by protein and/or amino acid intake immediately before and after resistance exercise 5-7. In addition, the availability of protein and/or amino acids during recovery from resistance exercise significantly enhances muscle protein synthesis while inhibiting muscle protein degradation 4. Protein supplementation and the subsequent availability of circulating amino acids, in conjunction with a resistance-training programme, is associated with elevations in serum insulin and IGF-1, both of which may increase muscle protein synthesis 8. Andersen and colleagues 9 reported that 14 weeks of resistance training and a diet supplemented with a blend of whey and casein resulted in Types 1 and 2 muscle fibre hypertrophying and an improved muscle performance.
Other papers have focused on optimal nutrition, especially in terms of protein ingestion, as a tool to enhance the hypertrophic response to resistance training revealing that muscle protein metabolism can be modulated not only by resistance exercise, but also by changes in circulating amino acids 1, 4, 10, 11. Consequently, the ingestion of sufficient amounts of dietary protein in conjunction with resistance training, followed by sufficient post-exercise carbohydrate intake, reduces the rate of muscle protein breakdown 12 when muscular hypertrophy of optimal restitution is the goal.
Hence, the purpose of this study was to investigate whether a high-protein diet (subjects, group A) affects the development of muscle hypertrophy with respect to normal-protein diet (subjects, group B) during a six-month resistance training programme. The study was carried out by a direct investigation of 49 amateur bodybuilders and aimed to assess whether high-protein diets increase muscular mass and volume.
Participants, training programme and study design
Forty-nine volunteers were involved in this investigation. All were male amateur bodybuilders attending L'Aquila gyms; 25 of the bodybuilders were students in the authors' sports school. The initial anthropometric characteristics of the group involved were: age 20-29, height 1.60-1.89m and body weight 61.80-94.00kg. The subjects, coming off of a three-month uncontrolled self-training period, were monitored during six months of a specific resistance training programme (from September 2009 to March 2010). Other training than that prescribed was not controlled for in this study during the follow-up. The programme setting was: 3 sets of 8-6-4 maximal repetitions (that is, 8 RM in the first set, 6 RM in the second, and 4 RM in the third), with 60-90s of rest among sets, performed 3 times per week. Resistance was established on the ability of the subjects. The exercises proposed in the controlled training programme included: squats and calf-raises for the lower body and pull-downs, push-downs, rows, bench-presses, pull-ups and push-ups for the upper body, alternating between the lower body and the upper body among times/week (Table 1).
Table 1: Training programme
Exercise training protocols administered to the subjects recruited for the study, divided into two workouts
The measurements of the anthropometric characteristics of the subjects (i.e., muscular mass and volume) were performed at the start (September), middle (December) and end (March) of the study. The analysis of the data was performed by subdividing the groups into Group A (high-protein diet), consisting of 13 subjects, and Group B (normal-protein diet), consisting of 36 subjects.
Alimentary consumptions and dietary habits survey
Subjects were questioned about their diet and eventual supplementation using the "Memory Interview: Dietary History" according to Burke's method 13, which reported the nutrition that the subjects consumed during the study. The success of this approach depends on two factors. The first is the ability of the interviewer to ask questions, and the second is the subject's ability to accurately remember the characteristics of meals. The subjects did not follow any specific diet. The consumption of the macronutrients was estimated through information reported by subjects and through use of the food nutrition tables published by the Italian Society of Human Nutrition (SINU; www.sinu.it). On the basis of this estimation, the whole group was divided into Group A, subjects (n = 13) with a daily protein intake greater than 1.2 g/kg body mass, i.e., 2.03 ± 0.17 (mean value ± SEM) and Group B (n = 36), subjects with a daily protein intake of 1.04 ± 0.05 g/kg body mass. The subjects were instructed to communicate if the habitual diet is changed during the training programme.
Anthropometric measurements survey
Anthropometric procedures used in the study to predict percentage of body fat were based upon body weight, girth and skin-fold values. Each measurement was repeated three times (to avoid skin compression). All the parameters included both sides of the body and averaged the data obtained. Body weight was estimated through a digital balance in the morning and temporally far from a training session (to avoid lowering the value due to dehydration). Subjects were fasting and wore underclothes.
Girth measurements were calculated using a tape measure at specific anatomic landmarks. The tape measure was applied lightly to the skin surface (without any clothes) avoiding skin compression, at the following anatomic sites: leg, thigh, hips, waist, chest, chest-shoulders, shoulders, upper arm and forearm.
Skin-fold measurements were estimated using a plastic pincer-type Accu-Measure calliper. Skin-fold thickness was measured by grasping a fold of skin and subcutaneous fat firmly with the thumb and forefinger, pulling it away from the underlying muscle tissue following the natural contour of the skin-fold and recording the skin-fold within 2 seconds after applying the full force of the calliper (10 g/mm2, approximately). The skin folds which best predict body fatness 14, 15 were measured i.e.: calf, abdomen, supra-iliac, sub-scapular, mid-axillary, triceps, biceps and forearm.
During the training period (Sept 2009 – March 2010) body weight, girth and skin-folds measurements were determined in September, December and March. The measurements were performed in triplicates and the values were interpreted. The mean value and the relative SEM of each measurement are reported in Table 2.
Table 2: Anthropometric measurements
Mean values and standard errors of the anthropometric measurements with respect to time and their dietary regimen.
A longitudinal 'one-within, one-between' study design was carried out comparing Groups A (13 subjects) and B (36 subjects) according to their dietary habits survey. During the study, six subjects in group B dropped out of the training programme (i.e. interruption of the training programme and/or habitual diet for one week) and were excluded from the statistical analysis.
Addressing the issue of stating differences between the anthropometric measurements in the two groups was initially dealt with by means of a main response feature analysis using mean values during the test period as a measure of response.
Given the longitudinal nature of the data, the responses at different time points for the same individual may not be independent, even after conditioning the covariates 16. Using a linear regression model, this means that the residuals for the same individual are correlated 17. To model these residual correlations, the total residual for subject i at time point j into a subject-specific random intercept ui, constant over time, plus a residual Îij, which varies randomly over time can be partitioned, so that a random intercept model of the form: yij = βT xij + ui + Îij can be obtained18. The random intercept accounts for individual differences in the overall mean level of the response. Descriptive statistics and graphical displays of selected variables are provided.
The analysis was carried out using STATA 8, 2003 software.
The analysis of macronutrients consumption by our subjects, according to the SINU nutrients content tables, revealed no statistically significant differences between Group A and Group B in terms of daily caloric assumption (p<0.05). In both groups, the caloric contribution was prevalently of carbohydrate nature (61.77 ± 2.92% and 63.57 ± 1.45% for Groups A and B, respectively). Large differences between the two groups in the daily lipid and protein intakes were evident. In particular, the protein consumption of Group A (24.45 ± 1.81%) was twice that of group B (13.03 ± 0.64%). From the data of protein intake and the body weight of the subjects a daily protein intake to body weight ratios of 2.03 ± 0.17g/kg BW and 1.04 ± 0.05g/kg BW for A and B groups respectively was calculated
The analysis of the anthropometric parameters of this study's sample groups reveals that the body weight of the subjects did not change significantly during the study (Table 2). The statistical model used which accounts for group, time and interaction between group and time revealed that both the grouping factor and its interaction with time do not display statistically significant modifications with respect to all the anthropometric parameters considered when the two groups are paralleled (p³0.05). Such a result is valid for both girth and skin-fold measurements.
Table 3: Statistically significant time coefficients occurring in the regression model and their symmetrical homologues
Statistically significant time coefficients, standard errors, with the associated z statistics and p values
The analytical model used revealed statistically significant time trend differences in several parameters considered in the study accounting for training effects present at a different magnitude (Table 3). This last effect, reported in Table 3 as time coefficient, ranging from a minimum z-score for the left-abdomen skin-fold (-0.88, p< 0.01) to a maximum z-score for the right thigh girth (3.89, p<0.001), is evidenced by plotting the anthropometric data versus time. For example, the plot of chest-girth modifications, as an index of muscle increase, versus time (Figure 1) demonstrates a parallel increase trend in the two groups even if it is also a statistically significant upwards shift in the graph concerning the high-protein diet group. This trend is similar to those shown by other specific body segments such as the forearm, not reported, and in right and left and girths (Figure 2).
Figure 1: Chest girth means and standard error trends according to their dietary regimen, with Group A as those with a high protein intake. Continuous line (Group A), dotted line (Group B)
Figure 2: On the abscissa are reported the data collection time, on the y-axis the thigh girths are shown, means and standard errors of the subjects according to their dietary regimen, with Group A those with a high protein intake. Continuous line (Group A), dotted line (Group B)
The data concerning the fraction of daily caloric supply derived from carbohydrates are in agreement with the suggestions reported in the LARN (Recommended Nutrients Assumption Limits) of the Italian Society of Human Nutrition (55-65%). The high daily protein intake of Group A, although in line with the suggestions of the American Food and Nutrition Board 19, largely exceeds the SINU recommendations (10-15%) and lipid consumption was far below the suggestions of the SINU (20-25%), the American Food and Nutrition Board (20-35%) and the American College of Sport Medicine (ACSM) (25-30%). The daily protein intake to body weight ratios for both groups were higher than the 0.60 g/kg BW suggested by the FAO (Food and Agriculture Organisation), WHO (World Health Organisation) and UN (United Nations) and the 0.75-0.80 g/kg BW of the RDA (Recommended Dietary Allowance) estimated for maintaining a normal nitrogen balance in healthy adult men.
However, the RDA for protein is appropriate for physical activities related to daily life, whereas the bodybuilders' intense training, along with the goal of these athletes of increasing their muscular mass and volume, is a different matter. Therefore, it is conceivable that these subjects have an increased demand for both energy and dietary proteins. The daily protein intake of Group A is comparable with that reported in a Lemon's study 20 with a daily mean protein intake values ranging from 1.70 to 2.20 g/kg BW in individuals with physical activities similar to those of this group. These values were further confirmed by another study 21. However, more recently, Lemon and colleagues 22 limited this range with differences between endurance and strength-power activities in which the suggested values were 1.20-1.40 and 1.60-1.80 g/kg BW, respectively.
The parallel analysis of this study's sample groups does not display statistically significant modifications of all the anthropometric parameters with respect to the grouping factor and its interaction with time. The absence of interaction between group and time indicates a similar trend of muscle increase in the two groups.
The skin folds used as indicators of fat did not show any statistically significant changes, suggesting that this anthropometric parameter remains unaltered. Nevertheless, the increase of the chest-shoulder and upper arm girths, due to the increase of muscular volume cannot be directly ascribed to the high-protein diet of the subjects.
Consolazio and colleagues 23 reported a growth in Fat Free Mass (FFM) in athletes when they increased the mean protein intake from 1.40 to 2.80g/kg b.w. (i.e., from 175 to 350% of the RDA). Similarly, Dragan and colleagues 24, found an increase of 6% of the FFM in Romanian weightlifters passing from 2.20 to 3.50g/kg b.w., even if, according to McArdle and colleagues 25 after the correct training programme, the FFM cannot increase more than 0.30kg per week.
However, Group A, despite having a dietary regimen with a mean protein intake of 254% of the RDA, did not show an increase in muscle volume comparable to those reported above and did not show significant differences in muscle growth compared to Group B. This present study's data partially agree with the report of Lemon and colleagues 26 in which an increase of daily protein intake from 1.35 to 2.62g/kg b.w. did not affect either strength or muscle mass in terms of muscle density and area and biceps nitrogen content. It is important to underline that the protocol adopted in the gyms is slightly different. In fact, it is known that bodybuilders train with moderate loads and short intervals between sets, unlike power lifters who train with high loads and rest for long periods of time 27. Thus this study's protocol appears to be a mix of both methods. Considering that the said protocol is 3 days/week, and that the metabolic stress is responsible for these gains, Lemon and colleagues 26 found gains in muscle mass with 6 days/week with increased protein intake. Thus this study's data seems to indicate that for amateur athletes, a high-protein diet does not improve either physical performance or muscle mass.
The discrepancy may be ascribed to the different training status of the subjects. This study's data may suggest that a hyper-protein diet is superfluous for amateur bodybuilders because the metabolic stress related to the elimination of the excessive nitrogen is not counterbalanced with a real FFM increase. Currently, there is no evidence that high-protein intake results in a long-term increase in functional lean tissue 28.
However, as evidenced by statistical analysis, only the time-trend in both groups is significant, indicating that the correct training exerts a positive role in muscular increase with no influence from the different dietary regimen or interaction between this variable and time. This hypothesis needs to be confirmed by a comparative experimental study that includes well-trained athletes. Considering that only relatively short-term experimental studies on the effect of high-protein intakes have been performed, the long-term consequences of chronic nutrient intake are difficult to judge 29.
Address for correspondence:
Professor Antonio Di Guilio, Deartment of S.T.B., University of L'Aquila, I-67010 Coppito-L'Aquila, Italy.
Tel.: +39 0862 432926
Fax: +39 0862 432903,