The Role of HMB Supplementation in Enhancing the Effects of Resistance Training in Older Adults: A Systematic Review and Meta-Analysis on Muscle Quality, Body Composition, and Physical Function

Abstract

Background/objectives: Resistance training (RT) is a key strategy to counteract age-related declines in muscle strength and physical function. β-hydroxy-β-methylbutyrate (HMB) has been proposed as a complementary supplement to enhance these adaptations. However, the additional effects of RT plus HMB (RT+HMB) compared with RT alone remain unclear. This systematic review and meta-analysis evaluated the effects of RT+HMB versus RT alone on body composition, muscle quality (MQ), and physical function in older adults.

Methods: Following PRISMA guidelines (PROSPERO: CRD420251144810), six databases (PubMed, Scopus, Cochrane Library, CINAHL, Web of Science, and ScienceDirect) were searched up to July 2025. Randomized controlled trials comparing RT+HMB with RT alone were included. Methodological quality was assessed with the PEDro scale and risk of bias using Cochrane RoB 2. Pooled standardized mean differences (SMDs) with 95% confidence intervals (CIs) were calculated.

Results: Ten trials (n = 596) met inclusion criteria. RT+HMB produced modest and borderline significant improvements in handgrip strength (SMD 0.24; 95% CI 0.00-0.48; p = 0.05) and moderate benefits in Short Physical Performance Battery (SPPB) scores (SMD 0.54; 95% CI 0.12-0.95; p = 0.01). No significant effects were observed for gait speed, appendicular lean mass, MQ, fat mass, or body weight (p > 0.05). Five trials (50%) were rated at high risk of bias, limiting confidence in pooled estimates.

Conclusions: HMB supplementation combined with RT may yield modest improvements in functional performance, particularly handgrip strength and overall physical function, without statically significant effects in body composition and MQ. Further high-quality RCTs are warranted to confirm its clinical relevance.

Keywords: aging; body composition; resistance training; β-hydroxy β-methylbutyrate.

Figure 1

Prisma 2020 Flow Diagram.

Figure 2

Forest plot for MQ. The analysis includes the following studies: Yang et al., 2023 [42]; Ogawa et al., 2025 [48]; Stout et al., 2013 [44].

Figure 3

Forest plot for handgrip strength. The analysis includes the following studies: Stout et al., 2013 [44]; Rathmacher et al., 2020 [45]; Osuka et al., 2021 [47]; Ogawa et al., 2025 [48]; Yang et al., 2023 [42]; Meza et al., 2024 [46].

Figure 4

Forest plot for gait speed. The analysis includes the following studies: Meza et al., 2024 [46]; Ogawa et al., 2025 [48]; Yang et al., 2023 [42].

Figure 5

Forest plot for SPPB. The analysis includes the following studies: Deutz et al., 2013 [51]; Ogawa et al., 2025 [48]; Meza et al., 2024 [46].

Figure 6

Forest plot for Appendicular Lean Mass. The analysis includes the following studies: Ogawa et al., 2025 [48]; Osuka et al., 2021 [47]; Deutz et al., 2013 [51]; Rathmacher et al., 2020 [45]; Meza et al., 2024 [46].

Figure 7

Forest plot for fat mass. The analysis includes the following studies: Stout et al., 2013 [44]; Rathmacher et al., 2020 [45]; Meza et al., 2024 [46]; Deutz et al., 2013 [51].

Figure 8

Forest plot for body weight. The analysis includes the following studies: Stout et al., 2013 [44]; Osuka et al., 2021 [47]; Rathmacher et al., 2020 [45].

Figure 9

Risk of bias assessment for the included studies. D1–D5 represent bias from randomization, deviations from intervention, missing data, outcome measurement, and reporting. Judgments are classified qualitatively as Low (green), Some concerns (yellow), or High (red). No numerical score was applied, as the RoB 2 tool uses categorical rather than quantitative evaluation. The analysis includes the following studies: Yang et al., 2023 [42]; Meza et al., 2024 [46]; Ogawa et al., 2025 [48]; Ma et al., 2021 [49]; Osuka et al., 2021 [47]; Standley et al., 2017 [43]; Din et al., 2019 [50]; Deutz et al., 2013 [51]; Rathmacher et al., 2020 [45]; Stout et al., 2013 [44].