In the dose-response model, there was a trend for 2-3 sets per exercise to be associated with a greater ES than 1 set per exercise (difference = 0.09 ± 0.05; CI: −0.02, 0.20; p = 0.09). The difference was significant when considering the Hochberg-adjusted permutation test p value (p = 0.009). There was also a trend for 4-6 sets per exercise to be associated with a greater ES compared with 1 set per exercise (difference = 0.20 ± 0.11; CI: −0.04, 0.43; p = 0.096). The difference was significant when considering the Hochberg-adjusted permutation test p value (p = 0.008). There was no significant difference between 2-3 sets per exercise and 4-6 sets per exercise (difference = 0.10 ± 0.10; CI: −0.09, 0.30; p = 0.29). There was a tendency for increasing ESs for an increasing number of sets. The mean ES for 1-set per exercise was 0.24 ± 0.03 (CI: 0.18, 0.31; Figure 2). The mean ES for 2-3 sets per exercise was 0.34 ± 0.03 (CI: 0.27, 0.41; Figure 2). The mean ES for 4-6 sets per exercise was 0.44 ± 0.09 (CI: 0.26, 0.62; Figure 2).
There was no significant relationship between treatment effect and sample size (slope of line = −0.002 ± 0.002; p = 0.32), indicating no evidence of publication bias.
The purpose of this meta-analysis was to determine whether multiple sets per exercise are associated with greater muscle hypertrophy than a single set per exercise in a resistance training program. Multiple sets per exercise were associated with significantly greater ESs in both the full and reduced statistical models. The mean ES for a single set per exercise was 0.25, whereas the mean ES for multiple sets was 0.35. Thus, multiple sets were associated with 40% greater hypertrophy-related ESs than a single set. According to Cohen's classifications for ESs (<0.41 = small; 0.41-0.70 = moderate; >0.70 = large) (9), both estimates are consistent with small treatment effects. In a previous meta-analysis on strength using an identical statistical model (23), 1 set per exercise was associated with a moderate treatment effect (mean ES = 0.54), whereas multiple sets were associated with a large treatment effect (mean ES = 0.80; Figure 3). The differences in ES estimates for strength vs. hypertrophy are consistent with the observation that changes in muscle size are often smaller and slower than changes in strength (28), particularly in untrained subjects (6 of the 8 studies in the current analysis involved untrained subjects). The observed ES difference for sex (a decrease of 0.28 for mixed groups compared with male groups) is consistent with the observation that women experience smaller changes in muscle size compared with men (17).
In a previous meta-analysis on strength using an identical statistical model, a 46% greater ES was observed for multiple sets compared with single sets (23) (Figure 3). A 40% greater ES was observed in this study. This indicates that the greater strength gains observed with multiple sets are in part because of greater muscle hypertrophy. It is known that mechanical loading stimulates protein synthesis in skeletal muscle (39), and increasing loads result in greater responses until a plateau is reached (24). It is likely that protein synthesis responds in a similar manner to the number of sets (i.e., an increasing response as the number of sets are increased, until a plateau is reached), although there is no research examining this. The results of this study support this hypothesis; there was a trend for an increasing ES for an increasing number of sets. The response appeared to start to level off around 4-6 sets, as the difference between 2-3 sets and 4-6 sets was smaller than the difference between 1 set and 2-3 sets. Also, the difference between 1 set and 2-3 sets was nearly significant (and the permutation test p value was significant), whereas the difference between 2-3 sets and 4-6 sets was not. However, only 2 studies in this analysis involved 4-6 sets per exercise. Thus, the statistical power to detect differences is low, and definitive conclusions cannot be made. These results are similar to a previous meta-analysis on strength, where there was an increasing response to an increasing number of sets, with an apparent plateau around 4-6 sets per exercise (23) (Figure 4).
It has been proposed that the majority of initial strength gains in untrained subjects are because of neural adaptations rather than hypertrophy (28). The results of this analysis suggest that some of the initial strength gains are because of hypertrophy. Given the insensitivity and variability of hypertrophy measurements, it is likely that hypertrophy occurs in untrained subjects but is difficult to detect. This is supported by research that shows increases in protein synthesis in response to resistance training in untrained subjects (24). Recent evidence also shows measurable hypertrophy after only 3 weeks of resistance exercise (38).
To examine the effects of potential outliers on the outcome, a sensitivity analysis was performed. The magnitude of the difference between single and multiple sets was consistent regardless of which study was removed. However, the removal of the study by Rønnestad et al. (35) affected the width of the CI, and the significant effect of multiple sets turned into a strong trend. However, this is likely because of loss of statistical power, given that the magnitude of the estimate remained similar, the permutation test p value remained significant, and the analysis consisted of only 8 studies.
Publication bias represents the problem where studies showing statistically significant results are more likely to be published than studies that fail to show significant results (e.g., studies showing a significant difference between 1 set and multiple sets per exercise may be more likely to be published) (4). Thus, meta-analyses of published studies may overestimate the magnitude of a treatment effect (4). Analyses can be performed to detect the presence of publication bias; one analysis involves examining the relationship between sample size and treatment effect (25). The existence of a significant relationship suggests that publication bias may be present. However, no such relationship was observed in the current study. Two previous meta-analyses on the effects of multiple vs. single sets on strength also failed to observe any evidence of publication bias (23,44). Also, only 2 of the 8 studies in this analysis reported significant differences in hypertrophy-related measures when comparing single with multiple sets (26,35). This strongly suggests that publication bias is not present, because if it were, most of the studies would report significant differences. In fact, even though only 2 of the 8 studies reported significant differences, the mean study-level ES favored the multiple-set group in all 8 studies (Table 1). This indicates that many of these studies are underpowered to detect differences.
There are a number of strengths to the current study design. First, strict inclusion criteria were used; only studies comparing single with multiple sets while holding all other variables constant were included. Second, the multilevel model allowed for the simultaneous modeling of the variation between studies, between treatment groups, and between ESs within each treatment group. Third, both standard and permutation test p values were used to protect against spurious findings, a common problem with metaregression (13). Finally, a sensitivity analysis was performed, and this indicated the mean difference between single and multiple sets to be reasonably consistent across the removal of individual studies.
A primary limitation of this analysis is the small number of studies. Thus, the statistical power of the analysis is limited. This was evident as the removal of the study by Rønnestad et al. (35) affected the p value and CIs. This was also evident by the observed trends that did not quite reach statistical significance (although they were significant according to permutation tests). The small number of studies also limited the number of predictors that could be included in the statistical model. Thus, interactions between set volume and factors such as training experience could not be explored, as had been done in a previous meta-analysis on strength (23). Also, the majority of studies in this analysis compared 1 set with 3 sets per exercise; only 2 studies in this analysis incorporated ≥4 sets per exercise. This limits the statistical power to compare 3 sets with greater set volumes, as the SE for the 4-6 set category was large. Given that the ES for 4-6 sets (0.44) is considered a moderate effect, whereas the ES for 2-3 sets (0.34) is considered a small effect according to Cohen's classifications (9), more research involving ≥4 sets is needed to clarify whether this is a chance difference or a true difference. Another limitation is that meta-regression, like epidemiological research, can only support observational associations and cannot demonstrate causation (42). A final limitation is the availability of data (42). Some studies, despite meeting the design criteria (comparison of single vs. multiple sets while keeping other variables constant), were excluded because hypertrophy was not measured. Because an analysis can only be undertaken for trials where all information is available, bias can be introduced in the results (42). However, most of the excluded studies reported greater strength gains in the multiple-set groups. Given the relationship between strength and muscle size, the consistency of the mean difference during the sensitivity analysis, the fact that the study-level ES favored the multiple-set group in all 8 studies, and the lack of evidence of publication bias, it is unlikely that the addition of more studies would alter the results, other than improving statistical power.
Multiple sets per exercise were associated with significantly greater changes in muscle size than a single set per exercise during a resistance exercise program. Specifically, hypertrophy-related ESs were 40% greater with multiple sets compared with single sets. This was true regardless of subject training status or training program duration. There was a trend for an increasing hypertrophic response to an increasing number of sets. Thus, individuals interested in achieving maximal hypertrophy should do a minimum of 2-3 sets per exercise. It is possible that 4-6 sets could give an even greater response, but the small number of studies incorporating volumes of ≥4 sets limits the statistical power and the ability to form any definitive conclusions. If time is a limiting factor, then single sets can produce hypertrophy, but improvements may not be optimal. More research is necessary to compare the effects of 2-3 sets per exercise to ≥4 sets. Future research should also focus on the effects of resistance training volume on protein synthesis and other cellular and molecular changes that may impact hypertrophy. Finally, resistance training studies comparing hypertrophic responses between treatments should include sufficient numbers of subjects to obtain adequate statistical power to detect differences; studies should also report power analyses.
The author thanks Dr. Dan Wagman for his help in obtaining some articles. There were no financial or personal conflicts of interest and no external funding for this study. The results of this study do not constitute endorsement by the National Strength and Conditioning Association.
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