Journal of Strength & Conditioning Research:
Factors That Contribute to and Account for Strength and Work Capacity in a Large Cohort of Recreationally Trained Adult Healthy Men With High- and Low-Strength Levels
Kerksick, Chad M.1; Mayhew, Jerry L.2,3; Grimstvedt, Megan E.4; Greenwood, Mike5; Rasmussen, Chris J.5; Kreider, Richard B.5
1Department of Health, Exercise and Sport Sciences, University of New Mexico, Albuquerque, New Mexico;
2Human Performance Laboratory, Department of Health and Exercise Science, Truman State University, Kirksville, Missouri;
3Department of Physiology, A. T. Still University of Health Sciences, Kirksville, Missouri;
4Department of Kinesiology, Northeast Lakeview College, Universal City, Texas; and
5Exercise and Sports Nutrition Laboratory, Department of Health and Kinesiology, Texas A&M University, College Station, Texas
Address correspondence to Chad M. Kerksick, email@example.com.
Abstract: Kerksick, CM, Mayhew, JL, Grimstvedt, ME, Greenwood, M, Rasmussen, CJ, and Kreider, RB. Factors that contribute to and account for strength and work capacity in a large cohort of recreationally trained adult healthy men with high- and low-strength levels. J Strength Cond Res 28(5): 1246–1254, 2014—The factors that best account for differences in strength across all types of exercise, body types, and training histories are not well understood. The purpose of this study was to assess the effects of strength level and body composition on upper- and lower-body work capacity in adult men. From a cohort of 295 adult men (25.6 ± 7.5 years, 178 ± 8 cm, 85.2 ± 15 kg), low-strength (LS, n = 72) and high-strength (HS, n = 66) samples were selected based on 1 repetition maximum (1RM) bench press (BP) and leg strength (LP) values. Work capacity for each exercise was determined from the product of repetition weight (80% 1RM) and maximum repetitions-to-fatigue (RTF). Body composition was measured using dual-energy x-ray absorptiometry. The HS group was significantly greater than the LS group in total body mass and fat-free mass but not in age, height, fat mass, or %fat. Low-strength and HS groups were not significantly different (p > 0.05) in RTF for either BP (8.7 ± 3.1 vs. 8.3 ± 1.9 reps, respectively) or LP (15.6 ± 7.6 vs. 17.0 ± 6.3 reps, respectively), making the ratio of RTF for BP vs. LP nonsignificant (LS = 2.0 ± 1.0; HS = 2.2 ± 0.9). The HS group produced significantly greater (p < 0.001) absolute and relative work capacities for both BP and LP compared with the LS group. Repetitions-to-fatigue had a greater influence on BP (r2 = 0.74) and LP (r2 = 0.85) work capacities in the LS group than did RepWt (r2 = 0.07 and 0.28, respectively). In the HS group, RTF (r2 = 0.79) had a greater influence than RepWt (r2 = 0.10) on BP work capacity, whereas the 2 components were more similar for LP work capacity (r2 = 0.64 and 0.47, respectively). When evaluated at the same %1RM, muscular endurance is similar across divergent strength levels meaning that work capacity (load × reps) will be greater for HS individuals. Controlling for the influence of body composition variables (e.g., fat or fat-free mass) does not eliminate the difference in work capacity between strength groups suggesting that other factors are accounting for strength expression. Prescribing repetitions against a fixed relative load is largely dependent on exercise type and must be considered by strength and conditioning professionals.
Improving maximal strength is a universal goal across divergent fitness groups. In addition, the ability to maximize muscular endurance and work capacity also holds great importance. Muscular endurance is typically evaluated by the number of repetitions-to-fatigue (RTF) that can be completed with a fixed load. Commonly in these settings, the number of repetitions performed can be multiplied by the load to derive work capacity, which has been shown to strongly correlate (r ≥ 0.97) with mechanical work (23).
Greater strength, endurance, and work capacity could all be factors to enhance someone's ability to repeatedly produce or withstand greater levels of force over an extended period of time. Moreover, increasing work capacity could result in a greater overall training volume being produced as part of a resistance training program, which may be closely associated with enhanced physiological adaptations to resistance training (2,38). Finally, injured individuals and populations with reduced functional capacity, such as the elderly, may also benefit from increasing associated work capacity (10).
Although a great deal of literature exists to indicate that the expression of strength is consistent with greater work capacity, previous investigations also have indicated that upper-body work capacity (bench press) after periodized heavy resistance training was enhanced when work capacity was determined at low intensity but may be reduced when work capacity was performed at high intensity in untrained men (27), untrained women (29), and college athletes (5). In addition, the gains seen in muscular work capacity did not seem to be paralleled by the changes in muscular strength of any group (5,29). Thus, other factors may be providing meaningful contributions to the ability to produce strength, work capacity or a combination of the two, which could have implications for nearly all strength and conditioning professionals.
One problem with the current state of the literature is that most of the research has focused on upper-body work capacity (5,27) with less information available for determining the relationship of various factors in lower-body resistance activities (6). Another problem is that the variability associated with performing RTF testing and training is much greater for lower-body activities (17,18,39,40) when compared with upper-body activities. In addition to the challenges presented by examining these factors across both upper- and lower-body activities, few studies have sought to examine the extent to which body composition status is related to strength level and work capacity in both forms of exercise. The impact of fat-free mass (FFM) on strength, power, and performance seems to be unquestioned in the literature. Furthermore, limited investigations have assessed the impact of body composition variables simultaneously on upper- and lower-body expressions of strength, endurance, and work capacity. Therefore, the 3 primary objectives of this investigation were (a) to report strength performances for both upper- and lower-body exercises in the same population, (b) to determine the interaction of strength, muscular endurance, and work capacity relative to body composition variables, (c) to determine if accurate predictions of maximal strength can occur for both upper- and lower-body exercises. According to the literature, it is hypothesized that higher strength individuals will perform greater amounts of work and that FFM will significantly account for differences in work capacity between high-strength (HS) and low-strength (LS) individuals.
Experimental Approach to the Problem
To assess the impact of LS and HS levels and body composition on upper- and lower-body muscular endurance and work capacity, recreationally resistance-trained adult men of diverse ages (18–50 years) were recruited for this study. Before all testing, subjects were required to be fasted and abstain from unaccustomed strenuous exercise for at least 24 hours. All participants were encouraged to consume water leading up to testing and were instructed to not make any changes in their diet. After determination of 1 repetition maximum (1RM) levels for bench press and leg press, LS and HS limits were determined from the lower (below 40th percentile) and upper (above 60th percentile) 40th percentiles of the sample. To control for differences in training status, all participants self-reported to have been consistently resistance training within the past 12 months using exercises that involved both the upper and lower body for a minimum of 8 weeks at a frequency of 2–4 workouts per week.
The maximal strength tests included a free-weight bench press and an incline leg press/hip sled. Maximal RTF were evaluated on the same devices using a weight equivalent to 80% of 1RM for each lift. Work capacity was then determined using the product of repetition weight multiplied by the number of repetitions completed (5,6). Body composition was determined using dual-energy x-ray absorptiometry (DXA).
From a sample of 295 adult men (18–49 years old) who were measured for strength and muscle endurance, LS (n = 72) and HS (n = 66) groups were determined based on the lower (below 40th percentile) and upper (above 60th percentile) 40th percentiles. Strength was assessed from a 1RM bench press and leg press. Before testing, subjects completed a medical history, training history, and signed an informed consent document approved by the institutional review board. All participants were above 18 years of age. All subjects were free of any disease and not currently taking any nonprescription or prescription medications. Additionally, all subjects were required to be free of any ergogenic levels of nutritional supplements purported to enhance training adaptations (e.g., creatine, ribose, glutamine, HMB, testosterone precursors, DHEA, etc.) for a minimum of 6 weeks before participation in the study. Participants who had never resistance trained were not included in the study. All participants self-reported to have been consistently resistance training within the past 12 months using exercises that involved both the upper and lower body for a minimum of 8 weeks at a frequency of 2–4 workouts per week. Before all testing, subjects were required to be fasted and abstain from unaccustomed strenuous exercise for at least 24 hours. All participants were encouraged to consume water leading up to testing and were instructed to not make any changes in their diet. Demographic characteristics, baseline strength, muscular endurance, and training history are all shown in Table 1.
Subjects completed 1 familiarization session before baseline testing. During familiarization, subjects performed practice trials of both upper- and lower-body strength testing to standardize grip width, foot placement, and specific aspects of exercise technique. Approximately 1 week separated the familiarization session from baseline testing to ensure adequate recovery.
Maximal Strength Assessment
Upper-body maximal strength was represented by a 1RM bench press and completed using the same procedures and equipment for all participants. The 1RM testing used a traditional bench press platform (Nebula Fitness, Columbus, OH, USA), standard Olympic bars and plates according to procedures previously described (2). The bar and plates had been certified within ±1% accuracy before testing. After a warm-up (2 × 10 reps at 50% of self-reported 1RM), the participant was assisted by a spotter in removing the bar from the support rack to a straight-arm position above the chest. The bar was lowered slowly from arms' length to touch the chest and was returned immediately to full-arm extension. No bouncing of the bar off the chest was permitted, and the head, back, and buttocks were required to remain in contact with the bench and both feet remained on the floor throughout the lift. Subjects used ∼75% of their estimated 1RM to begin their 1RM attempts. Additional weight was added dependent on ease of lift completion, and 2-minute rest was given between each attempt (2,22). This approach was continued until the participant could not complete a single repetition through the full range of motion. The 1RM was established within a maximum of 5 attempts to minimize neuromuscular fatigue and subsequent decrements in lifting performance (11,24). All lifts were supervised by individuals with several years of resistance training experience and many were certified as Strength and Conditioning Specialists (NSCA).
Lower-body maximal strength was represented by the 1RM leg press and completed using the same procedures and equipment. The 1RM leg press was assessed on a Nebula 35° hip sled/leg press (model 6000-A; Versailles, OH, USA) following similar procedures as described for the bench press. Specifically, all leg press repetitions began in the bottom or flexed position with the hip and knee angles at approximately 90° depending on exact sled position settings. This position was preferred because of the elimination of contribution from stored elastic energy, in addition to ensuring the subject completed all repetitions through the entire range of motion (7). Sled position and foot position were recorded and standardized between lifts, and all subjects were instructed on proper breathing techniques (2). Participants completed all lifts by positioning their hands away from the thighs, placing feet flat on the lifting platform in a position that was close to the width of their shoulders, and pressing the sled upwards by extending the hips, knees, and ankles to a fully extended position. On full extension, subjects then lowered the lifting platform in a controlled fashion to the starting position. Test-retest reliabilities of these techniques to determine maximal strength have been previously noted to be r = 0.86–0.90 (13).
Muscular Endurance Assessment
After determination of the 1RM for each exercise, subjects rested for 10 minutes and then completed a maximal RTF test using 80% of their predetermined 1RM for each lift. The lifting technique employed for the RTF was the same as for the 1RM test. No more than a 3-second pause was allowed between repetitions, and subjects were not allowed to lock out their elbows or knees, respectively. Subjects used a self-selected cadence but were encouraged to maintain a smooth motion to minimize the stretch-shortening cycle. Verbal encouragement was provided for all subjects to complete as many repetitions as possible. The highest number of successfully completed repetitions was counted as the subject's muscular endurance. Absolute work capacity (kg·reps) was determined as the product of repetition weight and the maximum number of repetitions completed. Relative work capacity (kg·reps·kg−1) was calculated as a ratio standard of absolute work capacity to body mass. Reliabilities of these techniques have been previously noted to be r = 0.84 (9).
Body Composition Assessment
Body mass was determined using a calibrated electronic scale with a precision of ±0.02 kg (Health-O-Meter, Bridgeview, IL, USA). Whole-body (excluding cranium) composition was estimated according to previous procedures (20) using DXA (Hologic QDR-4500W DXA with software version 9.80c, Waltham, MA, USA). No overt directions were made to control or measure hydration status, but all subjects were instructed at the beginning of the study to drink water leading up to each test and to not change any particular aspect of their diet. Quality control calibration procedures were performed on a spine phantom (Hologic X-CALIBER Model DPA/QDR-1 anthropometric spine phantom) the morning of every testing session according to standard procedures. Mean coefficients of variation for bone mineral content and bone mineral density measurements on the spine phantom ranged from 0.41 to 0.55%. Test-retest reliability studies performed on male athletes with this DXA machine yielded a mean deviation for total bone mineral content and total fat free/soft tissue mass of 0.31% with a mean intraclass correlation coefficient of 0.985 (1). Subjects were positioned on the DXA table using standardized methods for each test. Percent body fat (%fat) was determined by dividing the amount of fat mass (FM) by the total scanned mass. Lean mass plus bone mineral content was used to assess FFM.
Independent t-tests were computed to determine the difference between the LS and HS groups on selected variables. Pearson correlations were computed to identify the relationships among key variables. Multiple linear regression analysis was used to determine the degree of contribution of body composition components to explain muscular strength, muscular endurance, and work capacity. Analysis of covariance (ANCOVA) was used to hold the effect of specific variables constant when analyzing differences between LS and HS groups. Statistical significance was determined at an alpha level of 0.05. Post hoc power analysis revealed statistical power with our sample size and reported effect sizes to exceed 0.90.
The LS and HS groups were not significantly different (p > 0.05) in age, height, body mass index, FM, %fat, bench press RTF, or leg press RTF (Table 1). The HS group had significantly greater values for body mass, FFM, lean mass, 1RM bench press, absolute bench press work capacity, relative bench press work capacity, 1RM leg press, absolute leg press work capacity, and relative leg press work capacity (Table 1).
The 1RM values for bench press and leg press were moderately correlated in the LS group but poorly correlated in the HS group (Figure 1). The ratio of 1RM leg press to 1RM bench press was not significantly different between the LS group (2.0 ± 1.0) and the HS group (2.2 ± 0.9) suggesting that most of the subjects in both groups had approximately twice the lower-body strength as upper-body strength. Repetitions-to-fatigue values for bench press and leg press were significantly correlated in the LS group but not in the HS group (Figure 2). The ratio of RTF values between bench press and leg press was not significantly different (p > 0.05) between the LS and HS groups (Table 1), indicating that most individuals can perform twice as many repetitions with the legs as with the arms at equivalent %1RMs independent of their baseline strength. Because of the significantly greater RepWt, the HS individuals produced significantly greater absolute and relative work capacities for both bench press and leg press when compared with the LS group (Table 1). The absolute work capacities for bench press and leg press were significantly correlated in the LS group, whereas they were not in the HS group (Figure 3). These correlations did not change substantially for LS (r = 0.40) and HS (r = 0.07) groups when work capacity was considered relative to body mass. The ratio of leg press work capacity to bench press work capacity was significantly greater (p < 0.001) for the HS group (5.7 ± 3.0) that for the LS group (3.8 ± 2.3) attributable most to the difference in RepWt rather than RTF.
The correlation of RTF with work capacity was significantly greater than the correlation of RepWt with work capacity for bench press in both strength groups and for leg press in the LS group; the 2 correlations were not significantly different for leg press work capacity in the HS group (Table 2). Further analysis using multiple regression analysis indicated that RTF made a larger percent contribution to explaining bench press and leg press work capacities in the LS group (79 and 85%, respectively) than did RepWt (21 and 15%, respectively). In the HS group, RTF (81%) contributed more than RepWt (19%) to explaining bench press work capacity, whereas the 2 components were more similar in explaining leg press work capacity (60 and 40%, respectively).
The pattern of correlations of body composition variables with 1RM and work capacity was similar between the LS and HS groups (Table 2). In the LS group, FFM was significantly correlated with 1RM for bench press, leg press, and absolute bench press work capacity but not with absolute leg press work capacity. In the HS group, only FFM and FM were significantly correlated with 1RM bench press. However, none of the correlations accounted for more than 28% of the common variance in either 1RM or work capacity for either LS or HS groups.
Step-wise linear regression selected FFM, height, and FM (in that order) to predict 1RM bench press (Table 3). Fat-free mass made a substantially greater contribution to the explained variance in bench press (85%) than did height (8%) or FM (7%). For 1RM leg press, regression analysis selected FFM, body mass, and height (in that order) to estimate 1RM leg press, with FFM explaining the largest part of the variance (86%) and body mass and height (7%) offering lesser contributions. For bench press work capacity, FFM (83%) again produced the largest contribution to the explained variance with body mass (13%) and height (3%) making smaller contributions. For leg press work capacity, FFM was the largest contributor to the explained variance (87%) along with height making a smaller contribution (13%). However, removing the effects of FFM, body mass, height, and %fat using ANCOVA did not remove the significant difference between LS and HS for 1RM or work capacity for either exercise.
The primary finding of this study indicated that despite significant differences in FFM and lean mass between LS and HS groups, these factors did not explain the difference in either upper- or lower-body strength or work capacity between the groups. Previous studies on the topic are equivocal, with some noting significant relationships of strength with FFM (26,27) and others finding a lack of relationship of structural dimension with strength (4,21). In this study, body composition did not seem to explain more than 55% of the variance in either 1RM or 28% in either work capacity. Keogh et al. (16) noted no significant difference between stronger and weaker powerlifters in height, body mass, FFM, FM, or %fat. However, stronger powerlifters tended (p = 0.07) to have a greater percent of muscle mass than weaker powerlifters. Another study by Keogh et al. (15) found that lightweight and middleweight powerlifters, with body masses similar to subjects in this study, were similar in muscle mass but substantially above the level of phantom models based on normal individuals. In this study, the HS group was significantly heavier and had greater absolute FFM than the LS group, although the proportions of FFM to body mass were approximately equal between the 2 groups (76.5 ± 6.2% vs. 75.1 ± 7.0%, respectively).
Part of the discrepancy contributing to the difference in the correlation of body composition components with strength measures may be the body composition method used. Dual-energy x-ray absorptiometry seems to yield higher values for %fat which could mean a lower estimate of FFM (35). This might not be a major issue if the relationships between DXA values and other body composition techniques were consistently high, but research seems to indicate this may not be the case (8,35,37).
Furthermore, an issue that has not been explored is the effect of variability among testers in anthropometrics on the relationship between body composition estimates and strength measures. When the validity of various body composition prediction equations has been assessed, little mention has been made of the variability among testers, leaving the impression that it is the prediction equation that is being evaluated and not the tester. It is obvious that part of the measurement error in testing must be assigned to the tester and the technique. To date, no study has attempted to partition out the error associated with the tester from that of the prediction equation. Such information might shed more light on the wide variation in the correlations of body composition components with muscle strength tests.
Our work supports a number of previous studies that indicate a rather wide range exists for the correlations of body composition components to strength performance. This seems to hold true no matter whether the subjects are adolescent athletes (r = 0.55–0.73) (3,19,28,30), moderately trained adults (r = −0.15 to 0.68) (12,14,25), or college athletes (r = 0.53–0.72) (3,32,33) and bringing into question the impact of another variable, training experience, to explain the relationship between body composition and strength. In this study using the entire sample (n = 138), the correlation of 1RM bench press with body mass (r = 0.49) rose significantly when 1RM was correlated with FFM (r = 0.74). However, the correlations did not change significantly when 1RM leg press was compared with body mass (r = 0.42) and FFM (r = 0.59). Thus, global body composition components (FM, FFM, and fat percentage) were more successful in estimating 1RM bench press than any other variable (Table 3).
However, in what is likely the most intriguing and worthwhile point of discussion in this study is the fact that removing the contributions of these body composition parameters that were highly correlated with upper- and lower-body strength performance failed to account for the significant differences that existed between the LS and HS groups. These findings are important for the strength and conditioning professional to more fully understand that expressions of strength and work capacity in a large cohort of recreationally resistance trained men are impacted by a wide variety of factors and that approaches which rely heavily on body composition parameters may not always yield desirable outcomes. In fact, previous studies have had more success in estimating strength performances from regional anthropometric dimensions (26,31–33) than what was found with a more sophisticated technique for determining body composition (i.e., DXA).
Another aspiration of this study was to determine if enough interrelatedness was present between upper- and lower-body strength that one prediction equation could be developed that would accurately predict maximal strength performance of both bench press and leg press. This objective was based on the work of Hortobagyi et al. (14) who previously suggested that when the correlation among strength measurements exceeded 0.70, there is a commonality among the different measurement techniques. Whether or not this held true across exercises of different parts of the body was unknown, and as a result it may be difficult to apply this assertion to different lifts because the relationship among various exercises may vary considerably from study to study. Previous studies have illustrated correlations between bench press and squat that range from 0.67 (32) to 0.80 (34). Furthermore, the correlation between bench press and deadlift for high school football players (r = 0.80) seems to be higher than for college football players (r = 0.61) (3), bringing about the question of whether a greater history of resistance training can dissociate the relationship between various lifts. This last point is critical relative to this study because the intercorrelations between upper- and lower-body strength and work capacities were moderate at best and in some instances relatively low with similar regression slopes; as a result, estimates of one lift from another may not be possible in all cases. Moreover, rank-order correlations in both the LS group (ρ = 0.11) and HS group (ρ = 0.02) supported the idea of relative independence between 1RM values and only reached a significant level (ρ = 0.77) when the 2 groups were collapsed together. It is tempting to arbitrarily compare the training status of our study participants with that of a high school or college athlete, and as such it would be reasonable to state that from the training status data provided in Table 1 that our participants fell somewhere between these 2 groups of athletes. In this light, our findings of a relative lack of interdependence are consistent with previous findings and bring forth an intriguing and important consideration particularly for strength and conditioning professional working with young or completely untrained populations. With yet to be explained factors notwithstanding, the potential accuracy of predicting upper- or lower-body strength from one another may be highest in lesser trained or novice populations.
At a specific %1RM, previous research has indicated that LS and HS individuals can be expected to perform approximately the same number of repetitions in a specific lift (5,6). When comparing upper body to lower-body lifting performance, individuals of different strength levels tended to perform approximately twice as many repetitions in a bilateral lower-body exercise as in a bilateral upper-body exercise when performing at the same %1RM (5,6). This would suggest that when muscular endurance is evaluated by maximal RTF performed at the same intensity, LS and HS groups would complete approximately the same number of repetitions (5,6). It is thus intuitive and expected that when work capacity is evaluated as the product of repetitions and load lifted, HS individuals will produce significantly greater amounts of work when compared with LS individuals mainly because of them being able to handle heavier loads at the same intensity. The number of repetitions performed seems to explain more of the variance in work capacity in both upper- and lower-body exercises than did the load used to perform those repetitions, although this phenomenon seems to be more evident in LS individuals than in HS individuals. It is important to highlight that findings from this study confirm the initial findings of Hoeger et al. (13) and later those of Shimano et al. (36) that the maximal number of repetitions that are capable of being performed at a fixed load (in this case 80% 1RM) is not the same as indicated by repetition continuum charts and other methods of resistance training prescription (2).
In conclusion, a large group of healthy, resistance-trained, adult men were separated into either individuals with high strength or low strength. An examination to determine the factors that explained the differences in strength did not reveal any global body composition component (FM, FFM, percent body fat) to exert any meaningful influence. Independent of strength level, study participants were able to complete approximately the same number of repetitions for both the bench press and leg press exercises; approximately 2 times more repetitions were completed for the leg press when compared with the bench press. Additionally, 1RM levels across our chosen upper- and lower-body exercises were poorly related and eliminated any possibility of accurately predicting the maximal strength of one of these lifts. These findings conferred with previous studies and provided additional evidence that predicting maximal strength of one lift from the other may be best suited in a novice or untrained population. Finally, current results also add additional evidence to indicate that the maximal number of repetitions that can be performed at a fixed load vary from one exercise to the other and using a fixed repetition number to reflect maximal repetitions completed may not be appropriate.
Strength and conditioning professionals who develop programs with the intention to increase work capacity will find a number of important conclusions from this study. For starters, strength and conditioning professionals should realize that strength and work expression are the result of a combination of factors and in particular basing programming or prescription outcomes on body composition variables may not be an effective approach. The authors of this study hoped to successfully develop a prediction equation that allowed for the accurate prediction of bench press or leg press maximal strength from the other, but results from this study indicated this was not appropriate. Importantly, our findings did support previous work to indicate this approach may be best suited in situations where novice or lesser training individuals are being considered. If future research does determine this to be possible this could be particularly useful for strength and conditioning professionals working with limited equipment or with large number of people to determine strength. Finally, strength and conditioning professionals should also take notice that findings from this study provide additional evidence to indicate that the maximal number of repetitions that can be performed at a fixed load is oftentimes substantially different depending on the movement pattern, level of stability involved, and muscle mass activated. As a result, assigning a fixed number of repetitions in a blanket fashion across a varying group of exercises is not appropriate and will likely result in ineffective overload and loading for some exercises.
The authors thank the entire group of dedicated undergraduate, masters, doctoral research assistants, and laboratory personnel for their help in collecting the data for this project. The authors have no conflicts of interest to declare for this project.
1. Almada A, Kreider R. Comparison of the reliability of repeated whole body DEXA scans to repeated spine and hip scans. J Bone Miner Res 14: S369, 1999.
2. Baechle T, Earle R. Essentials of Strength Training and Conditioning. Champaign, IL: Human Kinetics, 2002.
3. Bale P, Colley E, Mayhew JL, Piper FC, Ware JS. Anthropometric and somatotype variables related to strength in American football players. J Sports Med Phys Fitness 34: 383–389, 1994.
4. Ballmann K, Scanlan J, Mayhew J, Lantz C. Prediction of bench press strength in untrained females from anthropometric dimensions and psychological indicators of activity involvement. J Hum Mov Stud 37: 217–233, 1999.
5. Brechue WF, Mayhew JL. Upper-body work capacity and 1RM prediction are unaltered by increasing muscular strength in college football players. J Strength Cond Res 23: 2477–2486, 2009.
6. Brechue WF, Mayhew JL. Lower-body work capacity and one-repetition maximum squat prediction in college football players. J Strength Cond Res 26: 364–372, 2012.
7. Chui LZ, Fry AC, Weiss LW, Schilling BK, Brown LE, Smith SL. Postactivation potentiation response in athletic and recreational trained individuals. J Strength Cond Res 17: 671–677, 2003.
8. Clark RR, Kuta JM, Sullivan JC. Prediction of percent body fat in adult males using dual energy x-ray absorptiometry, skinfolds, and hydrostatic weighing. Med Sci Sports Exerc 25: 528–535, 1993.
9. Desgorces FD, Berthelot G, Dietrich G, Testa MS. Local muscular endurance and prediction of 1 repetition maximum for bench in 4 athletic populations. J Strength Cond Res 24: 394–400, 2010.
10. Ferreira ML, Sherrington C, Smith K, Carswell P, Bell R, Bell M, Nascimento DP, Maximo Pereira LS, Vardon P. Physical activity improves strength, balance and endurance in adults aged 40-65 years: A systematic review. J Physiother 58: 145–156, 2012.
11. Hakkinen K. Neuromuscular fatigue and recovery in male and female athletes during heavy resistance exercise. Int J Sports Med 14: 53–59, 1993.
12. Hart CL, Ward TE, Mayhew JL. Anthropometric correlates of bench press performance following resistance training. Sports Train Med Rehabil 2: 89–95, 1991.
13. Hoeger WWK, Hopkins DR, Barette SL, Hale DF. Relationship between repetitions and selected percentages of one repetition maximum: A comparison between untrained and trained males and females. J Appl Sport Sci Res 4: 47–54, 1990.
14. Hortobagyi T, Katch FI, Lachance PF. Interrelationships among various measures of upper body strength assessed by different contraction modes. Evidence for a general strength component. Eur J Appl Physiol Occup Physiol 58: 749–755, 1989.
15. Keogh JW, Hume PA, Pearson SN, Mellow P. Anthropometric dimensions of male powerlifters of varying body mass. J Sports Sci 25: 1365–1376, 2007.
16. Keogh JW, Hume PA, Pearson SN, Mellow PJ. Can absolute and proportional anthropometric characteristics distinguish stronger and weaker powerlifters? J Strength Cond Res 23: 2256–2265, 2009.
17. Kerksick CM, Rasmussen CJ, Lancaster SL, Magu B, Smith P, Melton C, Greenwood M, Almada AL, Earnest CP, Kreider RB. The effects of protein and amino acid supplementation on performance and training adaptations during ten weeks of resistance training. J Strength Cond Res 20: 643–653, 2006.
18. Kerksick CM, Rasmussen C, Lancaster S, Starks M, Smith P, Melton C, Greenwood M, Almada A, Kreider R. Impact of differing protein sources and a creatine containing nutritional formula after 12 weeks of resistance training. Nutrition 23: 647–656, 2007.
19. Kinney K, Kinney J, Roberts S, Mayhew JL. Prediction of 1-RM squat performance in high school male athletes. MO J Hlth Phys Ed Rec Dance 18: 79–87, 2008.
20. Klesges RC, Ward KD, Shelton ML, Applegate WB, Cantler ED, Palmieri GM, Harmon K, Davis J. Changes in bone mineral content in male athletes. Mechanisms of action and intervention effects. JAMA 276: 226–230, 1996.
21. Kravitz L, Akalan C, Nowicki K, Kinzey SJ. Prediction of 1 repetition maximum in high-school power lifters. J Strength Cond Res 17: 167–172, 2003.
22. Lesuer DA, Mccormick JH, Mayhew JL, Wasserstein RL, Arnold MD. The accuracy of prediction equations for estimating 1-RM performance in the bench press, squat, and deadlift. J Strength Cond Res 11: 211–213, 1997.
23. Mann JB, Stoner JD, Mayhew JL. NFL-225 test to predict 1RM bench press in NCAA Division I football players. J Strength Cond Res 26: 2623–2631, 2012.
24. Matuszak ME, Fry AC, Weiss LW, Ireland TR, Mcknight MM. Effect of rest interval length on repeated 1 repetition maximum back squats. J Strength Cond Res 17: 634–637, 2003.
25. Mayhew JL, Ball TE, Arnold MD, Bowen JC. Relative muscular endurance performance as a Predictor of bench press strength in college men and women. J Appl Sport Sci Res 6: 200–206, 1992.
26. Mayhew JL, Ball TE, Ward TE, Hart CL, Arnold MD. Relationships of structural dimensions to bench press strength in college males. J Sports Med Phys Fitness 31: 135–141, 1991.
27. Mayhew JL, Brechue WF, Smith AE, Kemmler W, Lauber D, Koch AJ. Impact of testing strategy on expression of upper-body work capacity and 1-RM prediction following resistance training in college men and women. J Strength Cond Res 25: 2796–2807, 2011.
28. Mayhew JL, Hill SP, Thompson MD, Johnson EC, Wheeler L. Using absolute and relative muscle endurance to estimate maximal strength in young athletes. Int J Sports Phys Perf 2: 305–314, 2007.
29. Mayhew JL, Johnson BD, Lamonte MJ, Lauber D, Kemmler W. Accuracy of prediction equations for determining one repetition maximum bench press in women before and after resistance training. J Strength Cond Res 22: 1570–1577, 2008.
30. Mayhew JL, Kerksick CD, Lentz D, Ware JS, Mayhew DL. Using repetitions to fatigue to predict one-repetition maximum bench press in male high school athletes. Ped Exerc Sci 16: 265–276, 2004.
31. Mayhew JL, Mccormick TP, Piper FC, Kurth AL, Arnold MD. Relationships of body dimensions to strength performance in novice adolescent male powerlifters. Ped Exerc Sci 5: 347–356, 1993.
32. Mayhew JL, Piper FC, Ware JS. Anthropometric correlates with strength performance among resistance trained athletes. J Sports Med Phys Fitness 33: 159–165, 1993.
33. Mayhew JL, Piper FC, Ware JS. Relationships of anthropometric dimensions to strength performance in resistance trained athletes. J Phys Ed Sport Sci 5: 7–16, 1993.
34. Mayhew JL, Ware JS, Prinster JL. Using lift repetitions to predict muscular strength in adolescent males. Nat Strength Cond Assoc J 15: 35–38, 1993.
35. Plank LD. Dual-energy X-ray absorptiometry and body composition. Curr Opin Clin Nutr Metab Care 8: 305–309, 2005.
36. Shimano T, Kraemer WJ, Spiering BA, Volek JS, Hatfield DL, Silvestre R, Vingren JL, Fragala MS, Maresh CM, Fleck SJ, Newton RU, Spreuwenberg LP, Hakkinen K. Relationship between the number of repetitions and selected percentages of one repetition maximum in free weight exercises in trained and untrained men. J Strength Cond Res 20: 819–823, 2006.
37. Siahkouhian M, Hedayatneja M. Correlations of anthropometric and body composition variables with the performance of young elite weightlifters. J Hum Kinetics 25: 125–131, 2010.
38. Spiering BA, Kraemer WJ, Anderson JM, Armstrong LE, Nindl BC, Volek JS, Maresh CM. Resistance exercise biology: Manipulation of resistance exercise programme variables determines the responses of cellular and molecular signalling pathways. Sports Med 38: 527–540, 2008.
39. Wilborn CD, Kerksick CM, Campbell BI, Taylor LW, Marcello BM, Rasmussen CJ, Greenwood MC, Almada A, Kreider RB. Effects of Zinc Magnesium Aspartate (ZMA) supplementation on training adaptations and Markers of Anabolism and Catabolism. J Int Soc Sports Nutr 1: 12–20, 2004.
40. Wilborn CD, Taylor LW, Campbell BI, Kerksick C, Rasmussen CJ, Greenwood M, Kreider RB. Effects of methoxyisoflavone, ecdysterone, and sulfo-polysaccharide supplementation on training adaptations in resistance-trained males. J Int Soc Sports Nutr 3: 19–27, 2006.
muscle endurance; bench press; leg press; resistance training; volume
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