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<p>Accurate strength assessment requires consideration of individual anthropometric and demographic differences. Traditional absolute and body mass-normalized measures often fail to capture inter-individual variability, thereby limiting the precision of strength testing and classification. This study aimed to investigate the influence of age, body mass, height, and anthropometric characteristics on strength capacity and to systematically integrate these variables into a classification framework. A total of 393 individuals (197 females, 196 males), aged 16–64 years and ranging from beginners to elite powerlifters, were recruited. One-repetition maximum (1-RM) strength was assessed in the bench press (BP), back squat (SQ), and deadlift (DL). Age, height, body mass, and selected anthropometric variables including arm and leg lengths, were recorded. Multiple regression analyses were used to quantify the influence of these variables on 1-RM performance. Based on significant predictors, individualized z-scores were computed to standardize 1-RM values relative to relevant anthropometric and demographic factors. The applicability of these z-scores to interval-based classification frameworks was evaluated. Age, body mass, and height were identified as significant determinants of maximal strength across all 3 exercises. Incorporation of these variables into z-score calculation enabled a more precise and individualized assessment of strength performance. Attempts to apply z-scores to interval-based classification frameworks revealed substantial within-category heterogeneity, indicating that such frameworks are unsuitable for accurate strength classification. This study establishes an anthropometry- and demography-adjusted framework for strength assessment in BP, SQ, and DL among healthy adults aged 16–64 years. Standardized z-scores provide a biologically meaningful alternative to conventional normalization methods. The proposed z-score framework provides a reproducible, data-driven tool for individualized strength assessment in the BP, SQ and DL, with direct applications in sport science research, performance monitoring, and strength-based rehabilitation for healthy adults aged 16–64 years.</p>

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Normalization of muscle strength measures in barbell exercises by sex, age, and anthropometry: notes on allometry

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月6日

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  • Eduard Isenmann,
  • Stephan Geisler,
  • Tim Havers,
  • Simon Gavanda,
  • Patrick Diel,
  • Steffen Held,
  • Ulrich Flenker

摘要

Accurate strength assessment requires consideration of individual anthropometric and demographic differences. Traditional absolute and body mass-normalized measures often fail to capture inter-individual variability, thereby limiting the precision of strength testing and classification. This study aimed to investigate the influence of age, body mass, height, and anthropometric characteristics on strength capacity and to systematically integrate these variables into a classification framework. A total of 393 individuals (197 females, 196 males), aged 16–64 years and ranging from beginners to elite powerlifters, were recruited. One-repetition maximum (1-RM) strength was assessed in the bench press (BP), back squat (SQ), and deadlift (DL). Age, height, body mass, and selected anthropometric variables including arm and leg lengths, were recorded. Multiple regression analyses were used to quantify the influence of these variables on 1-RM performance. Based on significant predictors, individualized z-scores were computed to standardize 1-RM values relative to relevant anthropometric and demographic factors. The applicability of these z-scores to interval-based classification frameworks was evaluated. Age, body mass, and height were identified as significant determinants of maximal strength across all 3 exercises. Incorporation of these variables into z-score calculation enabled a more precise and individualized assessment of strength performance. Attempts to apply z-scores to interval-based classification frameworks revealed substantial within-category heterogeneity, indicating that such frameworks are unsuitable for accurate strength classification. This study establishes an anthropometry- and demography-adjusted framework for strength assessment in BP, SQ, and DL among healthy adults aged 16–64 years. Standardized z-scores provide a biologically meaningful alternative to conventional normalization methods. The proposed z-score framework provides a reproducible, data-driven tool for individualized strength assessment in the BP, SQ and DL, with direct applications in sport science research, performance monitoring, and strength-based rehabilitation for healthy adults aged 16–64 years.