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Grip strength in healthy caucasian adults: reference values
Christian M Günther1, Alexander Bürger, Markus Rickert
1Department of Orthopaedics, Klinikum Grosshadern, Ludwig-Maximilian-University Munich, Munich, Germany.
The Journal of Hand Surgery
|April 15, 2008
Summary
This study provides updated handgrip strength reference data for adults, finding that gender and age are key predictors. Regression equations are offered for more accurate strength predictions in clinical and software applications.
Area of Science:
- Physiology
- Anthropometry
- Biostatistics
Background:
- Establishing accurate reference data for handgrip strength is crucial for clinical assessments and performance evaluations.
- Previous reference data may not encompass the wide age and gender spectrum of current populations.
- Understanding factors influencing handgrip strength is essential for interpreting individual results.
Purpose of the Study:
- To update reference data for handgrip strength in healthy adults across a broad age range (20-95 years).
- To identify and analyze anthropometric and demographic factors influencing handgrip strength.
- To develop prediction equations for estimating handgrip strength.
Main Methods:
- A cross-sectional study involving 769 healthy adults (403 women, 366 men).
- Standardized measurement of handgrip strength using a digital hydraulic dynamometer.
- Analysis of correlations between grip strength and anthropometric variables (e.g., forearm circumference, hand size, body mass), gender, and age.
Main Results:
- Mean handgrip strength was significantly lower in women (approx. 27-29 kg) compared to men (approx. 47-49 kg).
- Hand strength peaked around age 35 and declined thereafter, with comparable development in both genders.
- Forearm circumference, hand size, and body mass positively correlated with grip strength; gender and age were the strongest predictors.
Conclusions:
- Gender- and age-adjusted reference values are recommended for accurate interpretation of handgrip strength.
- Anthropometric characteristics should be considered alongside grip strength measurements.
- Generated regression equations can enhance the accuracy of strength predictions in clinical settings and software applications.
