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Related Experiment Video

Updated: Dec 29, 2025

Lower Limb Biomechanical Analysis of Healthy Participants
06:36

Lower Limb Biomechanical Analysis of Healthy Participants

Published on: April 15, 2020

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Lower-limb muscle strength: normative data from an observational population-based study.

Julie A Pasco1,2,3,4, Amanda L Stuart5, Kara L Holloway-Kew5

  • 1School of Medicine, Deakin University, Geelong, VIC, 3220, Australia. julie.pasco@deakin.edu.au.

BMC Musculoskeletal Disorders
|February 10, 2020
PubMed
Summary
This summary is machine-generated.

Muscle strength and quality decline with age in adults. This study provides normative data for lower-limb muscle function in men and women aged 20-97 years to help identify dynapenia and poor muscle quality.

Keywords:
DynapeniaHand-held dynamometryManual muscle testReference valuesSarcopeniaSpecific force

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Area of Science:

  • Gerontology
  • Musculoskeletal Health
  • Biogerontology

Background:

  • Muscle deterioration with age or disease requires reference data for quantification.
  • Normative data for lower-limb muscle strength and quality are presented.
  • The study included 573 males and 923 females aged 20-97 years from the Geelong Osteoporosis Study.

Purpose of the Study:

  • To establish normative reference data for lower-limb muscle strength and quality.
  • To provide benchmarks for assessing muscle deterioration in adults.
  • To aid in the identification of age-related muscle dysfunction.

Main Methods:

  • Cross-sectional study design.
  • Muscle strength measured using a hand-held dynamometer (HHD).
  • Leg lean mass assessed by dual-energy x-ray absorptiometry (DXA); muscle quality calculated as strength/mass.

Main Results:

  • Both muscle strength and quality decreased with increasing age in males and females.
  • Age accounted for a significant portion of the variance in muscle strength (12.9-25.3% in males, 20.8-24.6% in females).
  • Means, standard deviations, and T-score cutpoints ( -2.0 and -1.0) for muscle strength and quality are reported by age-decade.

Conclusions:

  • The generated normative data are valuable for quantifying dynapenia and poor muscle quality.
  • These data assist in assessing muscle dysfunction in the general adult population.
  • Useful for identifying individuals with frailty, sarcopenia, and other age-related muscle issues.