Framework for a Short Muscle Function Battery Using Electronic Handgrip Dynamometry and Accelerometry in Older Adults - 07/04/25

Doi : 10.1016/j.tjfa.2025.100045

Ryan McGrath ^1,^2,^3,^4,^5,^⁎ , Grant R. Tomkinson ⁴, Sarah Andrew ^1,², Joshua Batesole ^1,², Chloe Carling ¹, Bryan K. Christensen ², Samantha FitzSimmons ^1,², Halli Heimbuch ^1,², Tyler Hoang ², Donald Jurivich ³, Jacob Kieser ^1,², Kelly Knoll ^1,², Peyton Lahr ^1,², Matthew Langford ^1,², Michaela Mastrud ¹, Megan Orr ⁶, Yeong Rhee ², Kyle J. Hackney ²
¹ Healthy Aging North Dakota (HAND), North Dakota State University, Fargo, ND, USA
² Department of Health, Nutrition, and Exercise Sciences, North Dakota State University, Fargo, ND, USA;
³ Department of Geriatrics, University of North Dakota, Grand Forks, ND, USA
⁴ Alliance for Research in Exercise, Nutrition, and Activity (ARENA), Allied Health and Human Performance, University of South Australia, Adelaide, South Australia, Australia
⁵ Fargo VA Healthcare System, Fargo, ND, USA
⁶ Department of Statistics, North Dakota State University, Fargo, ND, USA

^⁎Corresponding author: Ryan McGrath, North Dakota State University, 1805 NDSU Research Park Dr. N., Fargo, ND 58102, Phone: 701-231-6043, Fax: 701-231-8872North Dakota State University1805 NDSU Research Park Dr. N.FargoND58102

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ABSTRACT

Background

Electronic handgrip dynamometry and accelerometry enables novel opportunities to collect additional attributes of muscle function beyond just maximal strength, but some muscle function attributes may already be related, which may warrant discerning these attributes into a short muscle function battery (SMFB).

Objectives

We sought to determine the multivariate relationships between maximal strength, asymmetry, submaximal control, rate of force development, bimanual coordination, fatigability, and contractile steadiness in older adults.

Design

A cross-sectional design was used for this investigation.

Setting

Laboratory.

Participants

The analytic sample included 121 generally healthy older adults aged 70.7±4.7 years.

Measurements

Electronic handgrip dynamometry and accelerometry measured strength, asymmetry, submaximal control, rate of force development, bimanual coordination, fatigability, and contractile steadiness. The handgrip variables were standardized before they were included in a factor analysis. Factors with eigenvalues >1.0 were kept. Items within a factor with a loading |>0.30| were similarly retained.

Results

There were 3 factors retained with eigenvalues of 1.88, 1.56, and 1.10. The first factor (functional strength), which explained 39.9% of the variance, included strength, submaximal control, and rate of force development. Factor 2(lateral function), which explained 35.8% of the variance, included asymmetry and bimanual coordination. The third factor (muscle endurance), which explained 24.3% of the variance, included fatigability and contractile steadiness.

Conclusions

Our findings suggest the surfacing of themes in the additional muscle function measures, thereby providing framework for a SMFB. More research is needed for electronic handgrip dynamometry and accelerometry derived muscle function on health before consideration of implementation in clinical practice.

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Keywords : Aging, Geriatrics, Muscle Strength, Muscle Strength Dynamometer, Muscle Weakness