Skip to main content
PMC home page
Journal of Human Kinetics logoLink to Journal of Human Kinetics
. 2020 Aug 31;74:51–58. doi: 10.2478/hukin-2020-0013

The Effects of Low-Load Vs. High-Load Resistance Training on Muscle Fiber Hypertrophy: A Meta-Analysis

Jozo Grgic 1,*
PMCID: PMC7706639  PMID: 33312275

Abstract

The aim of this meta-analysis was to explore the effects of low-load vs. high-load resistance training on type I and type II muscle fiber hypertrophy. Searches for studies were performed through ten databases. Studies were included if they: (a) compared the effects of low-load vs. high-load resistance training (performed to momentary muscular failure); and, (b) assessed muscle fiber hypertrophy. A random-effects meta-analysis was performed to analyze the data. Ten study groups were included in the analysis. In the meta-analysis for the effects of low-load vs. high-load resistance training on type I muscle fiber hypertrophy, there was no significant difference between the training conditions (standardized mean difference: 0.28; 95% confidence interval: –0.27, 0.82; p = 0.316; I2 = 18%; 95% prediction interval: –0.71, 1.28). In the meta-analysis for the effects of low-load vs. high-load resistance training on type II muscle fiber hypertrophy, there was no significant difference between the training conditions (standardized mean difference: 0.30; 95% confidence interval: –0.05, 0.66; p = 0.089; I2 = 0%; 95% prediction interval: –0.28, 0.88). In this meta-analysis, there were no significant differences between low-load and high-load resistance training on hypertrophy of type I or type II muscle fibers. The 95% confidence and prediction intervals were very wide, suggesting that the true effect in the population and the effect reported in a future study conducted on this topic could be in different directions and anywhere from trivial to very large. Therefore, there is a clear need for future research on this topic.

Key words: loading zones, intensity, volume, cross-sectional area, CSA

Introduction

Skeletal muscle hypertrophy is one of the central adaptations to resistance training (American College of Sports Medicine, 2009). According to Haun et al. (2019), muscle hypertrophy can be assessed at the whole-muscle level (macroscopic methods) or the muscle fiber level (microscopic methods). Some of the methods used to measure muscle size at the whole-muscle level include B-mode ultrasound, computed tomography, and magnetic resonance imaging (Haun et al., 2019). Hypertrophy at the muscle fiber level is evaluated using muscle biopsy samples and commonly analyzed according to type I and type II muscle fibers.

When prescribing resistance exercise, one of the most important variables is the external load. Current resistance training guidelines recommend loads of 70% to 85% of one-repetition maximum (1RM) as ideal for muscle hypertrophy (American College of Sports Medicine, 2009). However, recent research has established that both low-load and high-load resistance training may produce similar muscle hypertrophy at the whole muscle level when the training is performed to momentary muscular failure (Schoenfeld et al., 2017; Schoenfeld et al., 2020). Despite these established effects, there is also a lack of consensus regarding the effects of low vs. high-load resistance training on muscle hypertrophy assessed at the muscle fiber level (Grgic and Schoenfeld, 2018).

As compared to high-load training, some authors have hypothesized that low-load resistance training may produce greater

hypertrophy of type I muscle fibers (Grgic et al., 2018a; Ogborn and Schoenfeld, 2014). In contrast, high-load training is suggested to predominantly impact type II muscle fiber hypertrophy (Folland and Williams, 2007). Grgic and Schoenfeld (2018) recently performed a narrative review on this topic. They concluded that while there is some evidence that low and high-load training may indeed produce different muscle fiber hypertrophy effects, the findings between studies remain highly inconsistent.

In a narrative review, there is no statistical mechanism for assessing the dispersion in effect size from study to study (Borenstein et al., 2009). A meta-analysis, however, incorporates all of the effect sizes from individual studies in a single statistical model and can isolate and quantify the true dispersion (Borenstein et al., 2009). Therefore, by using a meta-analysis, we might be able to provide greater clarity to this topic. Accordingly, the present paper aimed to perform a meta-analysis on the effects of low-load vs. high-load resistance training on type I and type II muscle fiber hypertrophy.

Methods

Search strategy

The search for the studies was performed through ten databases, including Academic Search Elite, CINAHL, ERIC, PsycINFO, OpenDissertations, Open Access Theses and Dissertations, PubMed/MEDLINE, Scopus, SPORTDiscus, and Web of Science databases. In all of these databases, the following search syntax was used: ("high-load" OR "high load" OR "low load" OR "low-load" OR "high repetition" OR "low repetition" OR "higher-repetition" OR "lower-repetition" OR "exercise load" OR "training load" OR "traditional muscular endurance" OR "traditional muscular strength") AND ("cross-sectional area" OR "CSA" OR "muscle fiber" OR "muscle fibre" OR "type I" OR "type II" OR "type IIa" OR "type IIx" OR "muscle biopsy" OR "muscle biopsies" OR "hypertrophy"). After the initial search, secondary searches were conducted. These searches consisted of: (a) checking the reference list of all studies included in the review; (b) screening the studies that cited the included studies (i.e., forward citation tracking), through Scopus and Google Scholar databases; and (c) examining the reference list of previous related reviews (Schoenfeld et al., 2016; Schoenfeld et al., 2017). The search for studies was conducted on February 1st, 2020.

Inclusion criteria

This review included studies that satisfied the following criteria: (a) published in English; (b) compared the effects of low-load (defined as all loads ≤60% of 1RM) vs. high-load (defined as loads >60% of 1RM) resistance training; (c) the training sets were performed to momentary muscular failure; (d) included humans as study participants; and (e) assessed muscle hypertrophy at the muscle fiber level. All studies that did not satisfy these criteria were excluded from the review. The most common reason for exclusion was the lack of muscle hypertrophy assessment at the muscle fiber level.

Data extraction

From all included studies, the following data were extracted: (a) details of the sample (i.e., sample size, sex, and participants’ training status); (b) description of low-load and high-load resistance training programs; (c) site of the muscle biopsy assessment; and (d) pre and post-intervention mean ± standard deviation (SD) of type I and type II muscle fiber cross-sectional area. In one case, relevant data was reported in a figure; for this study (Lim et al., 2019), the data was extracted using the WebPlotDigitizer software (2010-2019 Ankit Rohatgi). For studies that reported standard errors, the data were converted to SDs.

Methodological quality

The methodological quality of included studies was assessed using the Downs and Black (2000) checklist. This checklist evaluates several aspects of the study design, with items 1-10, 11-13, 14-26, and 27 referring to reporting, external validity, internal validity, and statistical power, respectively. As performed in other reviews (Davies et al., 2017; Grgic et al., 2018b) that focused on the effects of resistance training on muscular adaptations, two additional items were included on the checklist (item 28 and item 29). Item 28 referred to reporting of training adherence while item 29 was related to the supervision of the exercise programs. The maximum score on the checklist was 29 points. Studies were rated as being of “good quality” (>20 points), “moderate quality” (11-20 points), or “poor quality” (<11 points).

Statistical analysis

Meta-analyses were performed based on standardized mean differences (SMD; Hedge’s g). SMDs and 95% confidence intervals (CIs) were calculated using the pre- and post-intervention mean and SD of the muscle fiber cross-sectional data and the number of participants in each group. Two separate analyses were performed: (1) for type I fiber cross-sectional area; and, (2) for type II fiber cross-sectional area. For studies that presented data on different subtypes of type II muscle fibers (i.e., IIa and IIx), SMDs and variances were calculated for each outcome separately and the average values were used for the analysis. The interpretation of SMD was based on the following classification: small (≤0.2); medium (0.2-0.5); large (0.5-0.8); and very large (>0.8). Heterogeneity was explored using the I2 statistic with values ≤50%, 50-75%, and >75% indicating low, moderate, and high levels of heterogeneity, respectively. Meta-analyses were performed using the random-effects model. The statistical significance threshold was set at p < 0.05. 95% prediction intervals were calculated using: (a) the number of included studies; (b) the upper limit of the 95% CI; and (c) the tau-squared values. Prediction intervals denote the range in which the SMD of a future study conducted on the topic will likely be. All analyses were performed using the Comprehensive Meta-analysis software, version 2 (Biostat Inc., Englewood, NJ, USA).

Results

Search results and study characteristics

The primary search resulted in 1849 references. Of this number of search results, a total of 50 full-text papers were read, and five studies (Campos et al., 2002; Lim et al., 2019; Mitchell et al., 2012; Morton et al., 2016; Schuenke et al., 2012), with a total of 10 study groups were included in the review. Secondary search resulted in another 3131 results; however, no additional studies were included. The flow diagram of the search process is presented in Figure 1.

Figure 1.

Figure 1

Open in a new tab

Flow diagram of the search and study selection process

The pooled number of participants in all included studies was 120. Study samples ranged from 14 to 49 participants (median: 17 participants). Four studies included only males as study participants, while one study utilized a sample comprising of females (Table 1). Four studies included untrained participants; only one included resistance-trained individuals. The training program in the included studies lasted from 6 to 12 weeks. In all studies, muscle biopsy samples were taken from the quadriceps muscle. The included studies are summarized in Table 1.

Table 1.

Summary of the studies included in the review

Study Participants Training programs Resistance Duration of the
exercise(s) used in the training program training; weekly training frequency
Campos et al. (2002) 16 young untrained men Low-load: 2 sets per exercise performed for 20 to 28 RM Leg press, squat, and leg extension 8 weeks; 2-3 times per week
High-load: 4 sets per exercise performed for 3 to 5 RM
Lim et al. (2019) 14 young untrained men Low-load: 3 sets per exercise with 30% 1RM Leg press, leg extension, and leg curl 10 weeks; 3 times per week
High-load: 3 sets per exercise with 80% 1RM
Mitchell et al. (2012) 12 young untrained men Low-load: 3 sets per exercise with 30% 1RM Leg extension 12 weeks; 3 times per week
High-load: 3 sets per exercise with 80% 1RM
Morton et al. (2016) 49 young resistance- trained men Low-load: 3 sets per exercise with 30% to 50% 1RM Seated row, bench and shoulder press, front plank, bicep curls, triceps 12 weeks; 3 times per week
High-load: 3 sets per exercise with 75% to 90% 1RM extension, pull downs, leg press, curl, and extension
Schuenke et al. (2012) 17 young untrained women Low-load: 3 sets per exercise performed for 20 to 30 RM High-load: 3 sets per exercise performed for 6 to Leg press, squat, and leg extension 6 weeks; 2-3 times per week
10 RM
RM: repetition maximum
Open in a new tab

Methodological quality

The number of points scored on the Downs and Black checklist varied from 19 to 25. Four studies were classified as being of good methodological quality, and one study was classified as being of moderate methodological quality (Mitchell et al., 2012).

Meta-analysis results

A total of ten study groups were included in the meta-analysis. In the meta-analysis for the effects of low-load vs. high-load resistance training on type I muscle fiber hypertrophy, there was no significant difference between the training conditions (SMD: 0.28; 95% CI: –0.27, 0.82; p = 0.316; I2 = 18%; Figure 2). The 95% prediction intervals ranged from –0.71 to 1.28. In the meta-analysis for the effects of low-load vs. high-load resistance training on type II muscle fiber hypertrophy, there was no significant difference between the training conditions (SMD: 0.30; 95% CI: –0.05, 0.66; p = 0.089; I2 = 0%; Figure 3). The 95% prediction intervals ranged from –0.28 to 0.88.

Figure 2.

Figure 2

Open in a new tab

The forest plot is presenting the results of the meta-analysis on the effects of low-load vs. high-load resistance training on type I muscle fiber hypertrophy. The squares denote standardized mean difference (Hedges’s g) while the lines denote their respective 95% confidence intervals (CI)

Figure 3.

Figure 3

Open in a new tab

The forest plot is presenting the results of the meta-analysis on the effects of low-load vs. high-load resistance training on type II muscle fiber hypertrophy. The squares denote standardized mean difference (Hedges’s g) while the lines denote their respective 95% confidence intervals (CI)

Discussion

In this meta-analysis, there were no significant differences between low-load and high-load resistance training on hypertrophy of type I or type II muscle fibers. Even though it might be tempting to conclude that these results indicate that muscle fiber hypertrophy is not resistance training load-dependent, non-significant test results are generally not indicative of the absence of a true effect in the population (Lakens, 2017). In both performed analyses, the 95% CIs were wide, suggesting that the true effect in the population could be in different directions and anywhere from trivial to very large. Additionally, for type I muscle fiber hypertrophy, 95% predication intervals ranged from –0.71 to 1.28, suggesting that the next new observation on this topic will likely fall within this very wide range. Therefore, given the width of the 95% confidence and prediction intervals, there is a clear need for future research on this topic.

The review's main finding is that when the training is performed to muscular failure, there is not enough available data to conclude that low-load is more effective for muscle fiber hypertrophy than high-load, or vice-versa. However, we need to consider some associated physiological responses to resistance training when extrapolating the data to practice. According to Henneman's size principle, motor units are recruited in an orderly fashion (Henneman et al., 1965). At the beginning of a set with low-loads (e.g., 30% 1RM), lower threshold motor units associated with type I muscle fibers are recruited to lift the load (Duchateau et al., 2006). As these motor units fatigue, higher threshold motor units associated with type II muscle fibers will be recruited, ultimately resulting in the recruitment of the entire motor unit pool. When exercising with high-loads (e.g., 80% 1RM), the recruitment of all motor units occurs from the exercise's onset (Duchateau et al., 2006). Therefore, if the training is performed to muscular failure, the recruitment of high and low threshold motor units may be similar regardless of load used in training. Similar recruitment of motor units with low-load and high-load training may, over time, also result in comparable hypertrophy of muscle fibers. Furthermore, recent data reported similar hypertrophy of the soleus (a predominantly slow-twitch muscle) and the gastrocnemius (muscle with a similar composition of slow and fast-twitch fibers) when training with high-loads or low-loads (Schoenfeld et al., 2020). These results may be explained by the data from Morton et al. (2020), where no significant difference in glycogen depletion of type I and type II fibers and phosphorylation of relevant signaling proteins was found between low-load and high-load training. When considering the whole body of literature, it might be that the effects of high-load and low-load training on muscle fiber hypertrophy are similar in terms of their magnitude. Nevertheless, given the already identified limitations of the data (i.e., wide 95% CIs and prediction intervals), this topic needs to be further investigated.

In the analysis for type II muscle fiber hypertrophy, the pooled SMD favored high-loads, even though the effect was not statistically significant (p = 0.089). However, it is also worth noting that the data from Schuenke et al. (2012) impacted the pooled estimate in this analysis. Specifically, the SMD from this study amounted to 1.01, which is substantially higher than the effects observed in other studies. When this study was excluded from the analysis, the pooled estimate was reduced to 0.20 (95% CI: –0.18, 0.57; p = 0.310). This study differed from other research by the inclusion of females as study participants. All other included studies utilized samples comprised exclusively of males. Tentatively, these results may indicate that training with low and high-loads produces different effects on muscle fiber hypertrophy in females, but not in males. Instead of excluding females, future studies may consider including both sexes and plot the results separately to explore whether a sex difference exists to training with varying loads.

It needs to be mentioned that the results presented in this meta-analysis are specific to the lower-body musculature. Specifically, all studies collected muscle biopsy samples from the quadriceps femoris muscle group, which is the most common location because of its mixed fiber type composition, trainability, and accessibility (Staron et al., 2000). Therefore, while indicative, the results presented herein cannot necessarily be generalized to the upper-body musculature. Future research is needed to explore the effects of low-load and high-load resistance training on muscle fiber hypertrophy in the upper-body musculature.

Using the Downs and Black checklist, the included studies were classified as being of moderate or good methodological quality. Therefore, the pooled data presented in this meta-analysis are not confounded by the inclusion of studies that were of poor methodological quality. However, it also needs to be mentioned that adherence to the training programs was reported only in one study (Morton et al., 2016). Adherence to any training program is one of the critical variables that will determine its effectiveness (Gentil and Bottaro, 2013). In this context, one acute study reported that low-load training (20 to 25 RM) produced higher degrees of effort, discomfort, and displeasure, as compared to high-load training (8 to 12 RM) (Ribeiro et al., 2019). These differences in affective responses may impact long-term adherence of participants to the training program; therefore, future studies should ensure that adherence is reported.

Conclusions

This review did not find significant differences between low-load vs. high-load resistance training on hypertrophy of type I or type II muscle fibers. Therefore, the main finding of this review is that when resistance training is performed to muscular failure, there is not enough available data to conclude that high-load or low-load outperforms the other regarding their effects on type I or type II muscle fiber hypertrophy. Given that the 95% confidence and prediction intervals were very wide, there is a clear need for future research on this topic.

References

  1. American College of Sports Medicine. American College of Sports Medicine position stand. Progression models in resistance training for healthy adults. Med Sci Sports Exerc. 2009;41(3):687–708. doi: 10.1249/MSS.0b013e3181915670. [DOI] [PubMed] [Google Scholar]
  2. Borenstein M, Hedges LV, Higgins JPT, Rothstein HR. Introduction to Meta-Analysis. West Sussex: John Wiley & Sons, Ltd; 385;; 2009. [Google Scholar]
  3. Campos GE, Luecke TJ, Wendeln HK, Toma K, Hagerman FC, Murray TF, Ragg KE, Ratamess NA, Kraemer WJ, Staron RS. Muscular adaptations in response to three different resistance-training regimens: specificity of repetition maximum training zones. Eur J Appl Physiol. 2002;88(1-2):50–60. doi: 10.1007/s00421-002-0681-6. [DOI] [PubMed] [Google Scholar]
  4. Davies TB, Kuang K, Orr R, Halaki M, Hackett D. Effect of movement velocity during resistance training on dynamic muscular strength: a systematic review and meta-analysis. Sports Med. 2017;47(8):1603–17. doi: 10.1007/s40279-017-0676-4. [DOI] [PubMed] [Google Scholar]
  5. Downs SH, Black N. The feasibility of creating a checklist for the assessment of the methodological quality both of randomised and non-randomised studies of health care interventions. J Epidemiol Commun Health. 1998;52(6):377–84. doi: 10.1136/jech.52.6.377. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Duchateau J, Semmler JG, Enoka RM. Training adaptations in the behavior of human motor units. J Appl Physiol. 2006;101(6):1766–75. doi: 10.1152/japplphysiol.00543.2006. [DOI] [PubMed] [Google Scholar]
  7. Folland JP, Williams AG. The adaptations to strength training: morphological and neurological contributions to increased strength. Sports Med. 2007;37(2):145–68. doi: 10.2165/00007256-200737020-00004. [DOI] [PubMed] [Google Scholar]
  8. Gentil P, Bottaro M. Effects of training attendance on muscle strength of young men after 11 weeks of resistance training. Asian J Sports Med. 2013;4(2):101–6. doi: 10.5812/asjsm.34489. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Grgic J, Homolak J, Mikulic P, Botella J, Schoenfeld BJ. Inducing hypertrophic effects of type I skeletal muscle fibers: A hypothetical role of time under load in resistance training aimed at muscular hypertrophy. Med Hypotheses. 2018a;112:40–2. doi: 10.1016/j.mehy.2018.01.012. [DOI] [PubMed] [Google Scholar]
  10. Grgic J, Schoenfeld BJ, Skrepnik M, Davies TB, Mikulic P. Effects of rest interval duration in resistance training on measures of muscular strength: a systematic review. Sports Med. 2018b;48(1):137–51. doi: 10.1007/s40279-017-0788-x. [DOI] [PubMed] [Google Scholar]
  11. Grgic J, Schoenfeld BJ. Are the Hypertrophic Adaptations to High and Low-Load Resistance Training Muscle Fiber Type Specific? Front Physiol. 2018;9:402. doi: 10.3389/fphys.2018.00402. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Haun CT, Vann CG, Roberts BM, Vigotsky AD, Schoenfeld BJ, Roberts MD. A Critical Evaluation of the Biological Construct Skeletal Muscle Hypertrophy: Size Matters but So Does the Measurement. Front Physiol. 2019;10:247. doi: 10.3389/fphys.2019.00247. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Henneman E, Somjen G, Carpenter DO. Functional significance of cell size in spinal motoneurons. J Neurophysiol. 1965;28:560–80. doi: 10.1152/jn.1965.28.3.560. [DOI] [PubMed] [Google Scholar]
  14. Lakens D. Equivalence Tests: A Practical Primer for t Tests, Correlations, and Meta-Analyses. Soc Psychol Personal Sci. 2017;8(4):355–62. doi: 10.1177/1948550617697177. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Lim C, Kim HJ, Morton RW, Harris R, Phillips SM, Jeong TS, Kim CK. Resistance Exercise-induced Changes in Muscle Phenotype Are Load Dependent. Med Sci Sports Exerc. 2019;51(12):2578–85. doi: 10.1249/MSS.0000000000002088. [DOI] [PubMed] [Google Scholar]
  16. Mitchell CJ, Churchward-Venne TA, West DW, Burd NA, Breen L, Baker SK, Phillips SM. Resistance exercise load does not determine training-mediated hypertrophic gains in young men. J Appl Physiol. 2012;113(1):71–7. doi: 10.1152/japplphysiol.00307.2012. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Morton RW, Oikawa SY, Wavell CG, Mazara N, McGlory C, Quadrilatero J, Baechler BL, Baker SK, Phillips SM. Neither load nor systemic hormones determine resistance training-mediated hypertrophy or strength gains in resistance-trained young men. J Appl Physiol. 2016;121(1):129–38. doi: 10.1152/japplphysiol.00154.2016. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Morton RW, Sonne MW, Farias Zuniga A, Mohammad IYZ, Jones A, McGlory C, Keir PJ, Potvin JR, Phillips SM. Muscle fibre activation is unaffected by load and repetition duration when resistance exercise is performed to task failure. J Physiol. 2019;597(17):4601–13. doi: 10.1113/JP278056. [DOI] [PubMed] [Google Scholar]
  19. Ogborn D, Schoenfeld BJ. The role of fiber types in muscle hypertrophy: implications for loading strategies. Strength Cond J. 2014;36(2):20–5. [Google Scholar]
  20. Ribeiro AS, Dos Santos ED, Nunes JP, Schoenfeld BJ. Acute Effects of Different Training Loads on Affective Responses in Resistance-trained Men. Int J Sports Med. 2019;40(13):850–5. doi: 10.1055/a-0997-6680. [DOI] [PubMed] [Google Scholar]
  21. Schoenfeld BJ, Grgic J, Ogborn D, Krieger JW. Strength and Hypertrophy Adaptations Between Low- vs. High-Load Resistance Training: A Systematic Review and Meta-analysis. J Strength Cond Res. 2017;31(12):3508–23. doi: 10.1519/JSC.0000000000002200. [DOI] [PubMed] [Google Scholar]
  22. Schoenfeld BJ, Vigotsky AD, Grgic J, Haun C, Contreras B, Delcastillo K, Francis A, Cote G, Alto A. Do the anatomical and physiological properties of a muscle determine its adaptive response to different loading protocols? Physiol Rep. 2020;8(9):e14427. doi: 10.14814/phy2.14427. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Schoenfeld BJ, Wilson JM, Lowery RP, Krieger JW. Muscular adaptations in low- versus high-load resistance training: A meta-analysis. Eur J Sport Sci. 2016;16(1):1–10. doi: 10.1080/17461391.2014.989922. [DOI] [PubMed] [Google Scholar]
  24. Schuenke MD, Herman JR, Gliders RM, Hagerman FC, Hikida RS, Rana SR, Ragg KE, Staron RS. Early-phase muscular adaptations in response to slow-speed versus traditional resistance-training regimens. Eur J Appl Physiol. 2012;112(10):3585–95. doi: 10.1007/s00421-012-2339-3. [DOI] [PubMed] [Google Scholar]
  25. Staron RS, Hagerman FC, Hikida RS, Murray TF, Hostler DP, Crill MT, Ragg KE, Toma K. Fiber type composition of the vastus lateralis muscle of young men and women. J Histochem Cytochem. 2000;48(5):623–9. doi: 10.1177/002215540004800506. [DOI] [PubMed] [Google Scholar]

Articles from Journal of Human Kinetics are provided here courtesy of Academy of Physical Education in Katowice, Poland

RESOURCES