Suey S Y Yeung1, Esmee M Reijnierse2, Marijke C Trappenburg3, Jean-Yves Hogrel4, Jamie S McPhee5, Mathew Piasecki6, Sarianna Sipila7, Anu Salpakoski8, Gillian Butler-Browne4, Mati Pääsuke9, Helena Gapeyeva9, Marco V Narici10, Carel G M Meskers11, Andrea B Maier12. 1. Department of Human Movement Sciences, AgeAmsterdam, Faculty of Behavioural and Movement Sciences, Amsterdam Movement Sciences, Vrije Universiteit, Amsterdam, The Netherlands; Department of Medicine and Aged Care, AgeMelbourne, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, Australia. 2. Department of Medicine and Aged Care, AgeMelbourne, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, Australia. 3. Department of Internal Medicine, Section of Gerontology and Geriatrics, VU University Medical Center, Amsterdam, The Netherlands; Department of Internal Medicine, Amstelland Hospital, Amstelveen, The Netherlands. 4. Institute of Myology, Paris, France. 5. School of Healthcare Science, Manchester Metropolitan University, Manchester, United Kingdom. 6. MRC-ARUK Centre of Excellence for Musculoskeletal Ageing Research, Clinical Metabolic and Molecular Physiology, University of Nottingham, Royal Derby Hospital Centre, Derby, United Kingdom. 7. Gerontology Research Center, Faculty of Sport and Health Sciences, University of Jyvaskyla, Jyvaskyla, Finland. 8. Peurunka Oy, Laukaa, Finland. 9. Institute of Sport Sciences and Physiotherapy, University of Tartu, Tartu, Estonia. 10. Institute of Physiology, Department of Biomedical Sciences, University of Padova, Podavo, Italy. 11. Department of Human Movement Sciences, AgeAmsterdam, Faculty of Behavioural and Movement Sciences, Amsterdam Movement Sciences, Vrije Universiteit, Amsterdam, The Netherlands; Department of Rehabilitation Medicine, VU University Medical Center, Amsterdam, The Netherlands. 12. Department of Human Movement Sciences, AgeAmsterdam, Faculty of Behavioural and Movement Sciences, Amsterdam Movement Sciences, Vrije Universiteit, Amsterdam, The Netherlands; Department of Medicine and Aged Care, AgeMelbourne, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, Australia. Electronic address: andrea.maier@mh.org.au.
Abstract
OBJECTIVES: Dynapenia, low muscle strength, is predictive for negative health outcomes and is usually expressed as handgrip strength (HGS). Whether HGS can be a proxy for overall muscle strength and whether this depends on age and health status is controversial. This study assessed the agreement between HGS and knee extension strength (KES) in populations differing in age and health status. DESIGN: Data were retrieved from 5 cohorts. SETTING AND PARTICIPANTS: Community, geriatric outpatient clinics, and a hospital. Five cohorts (960 individuals, 49.8% male) encompassing healthy young and older individuals, geriatric outpatients, and older individuals post hip fracture were included. MEASURES: HGS and KES were measured according to the protocol of each cohort. Pearson correlation was performed to analyze the association between HGS and KES, stratified by sex. HGS and KES were standardized into sex-specific z scores. The agreement between standardized HGS and standardized KES at population level and individual level were assessed by intraclass correlation coefficients (ICC) and Bland-Altman analysis. RESULTS: Pearson correlation coefficients were low in healthy young (male: 0.36 to 0.45, female: 0.45) and healthy older individuals (male: 0.35 to 0.37, female: 0.44), and moderate in geriatric outpatients (male and female: 0.54) and older individuals post hip fracture (male: 0.44, female: 0.57) (P < .05, except for male older individuals post hip fracture [P = .07]). Intraclass correlation coefficient values were poor to moderate in all populations (ie, healthy young individuals [0.41, 0.45], healthy older individuals [0.37, 0.41, 0.44], geriatric outpatients [0.54], and older individuals post hip fracture [0.54]). Bland-Altman analysis showed that within the same population of age and health status, agreement between HGS and KES varied on individual level. CONCLUSIONS: At both population and individual level, HGS and KES showed a low to moderate agreement independently of age and health status. HGS alone should not be assumed a proxy for overall muscle strength.
OBJECTIVES: Dynapenia, low muscle strength, is predictive for negative health outcomes and is usually expressed as handgrip strength (HGS). Whether HGS can be a proxy for overall muscle strength and whether this depends on age and health status is controversial. This study assessed the agreement between HGS and knee extension strength (KES) in populations differing in age and health status. DESIGN: Data were retrieved from 5 cohorts. SETTING AND PARTICIPANTS: Community, geriatric outpatient clinics, and a hospital. Five cohorts (960 individuals, 49.8% male) encompassing healthy young and older individuals, geriatric outpatients, and older individuals post hip fracture were included. MEASURES: HGS and KES were measured according to the protocol of each cohort. Pearson correlation was performed to analyze the association between HGS and KES, stratified by sex. HGS and KES were standardized into sex-specific z scores. The agreement between standardized HGS and standardized KES at population level and individual level were assessed by intraclass correlation coefficients (ICC) and Bland-Altman analysis. RESULTS: Pearson correlation coefficients were low in healthy young (male: 0.36 to 0.45, female: 0.45) and healthy older individuals (male: 0.35 to 0.37, female: 0.44), and moderate in geriatric outpatients (male and female: 0.54) and older individuals post hip fracture (male: 0.44, female: 0.57) (P < .05, except for male older individuals post hip fracture [P = .07]). Intraclass correlation coefficient values were poor to moderate in all populations (ie, healthy young individuals [0.41, 0.45], healthy older individuals [0.37, 0.41, 0.44], geriatric outpatients [0.54], and older individuals post hip fracture [0.54]). Bland-Altman analysis showed that within the same population of age and health status, agreement between HGS and KES varied on individual level. CONCLUSIONS: At both population and individual level, HGS and KES showed a low to moderate agreement independently of age and health status. HGS alone should not be assumed a proxy for overall muscle strength.
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