Predictive value of sarcopenia components for all-cause mortality: findings from population-based cohorts

Leo D Westbury; Nicholas C Harvey; Charlotte Beaudart; Olivier Bruyère; Jane A Cauley; Peggy Cawthon; Alfonso J Cruz-Jentoft; Elizabeth M Curtis; Kristine Ensrud; Roger A Fielding; Helena Johansson; John A Kanis; Magnus K Karlsson; Nancy E Lane; Laetitia Lengelé; Mattias Lorentzon; Eugene McCloskey; Dan Mellström; Anne B Newman; Claes Ohlsson; Eric Orwoll; Jean-Yves Reginster; Eva Ribom; Björn E Rosengren; John T Schousboe; Elaine M Dennison; Cyrus Cooper; and the International Musculoskeletal Ageing Network

doi:10.1007/s40520-024-02783-x

Predictive value of sarcopenia components for all-cause mortality: findings from population-based cohorts

Aging Clin Exp Res. 2024 Jun 6;36(1):126. doi: 10.1007/s40520-024-02783-x.

Authors

Leo D Westbury¹, Nicholas C Harvey^{2

3}, Charlotte Beaudart⁴, Olivier Bruyère⁵, Jane A Cauley⁶, Peggy Cawthon^{7

8}, Alfonso J Cruz-Jentoft⁹, Elizabeth M Curtis¹, Kristine Ensrud^{10

11}, Roger A Fielding¹², Helena Johansson^{13

14}, John A Kanis^{13

15}, Magnus K Karlsson¹⁶, Nancy E Lane¹⁷, Laetitia Lengelé¹⁸, Mattias Lorentzon^{13

19}, Eugene McCloskey^{13

20}, Dan Mellström²¹, Anne B Newman⁶, Claes Ohlsson^{22

23}, Eric Orwoll²⁴, Jean-Yves Reginster²⁵, Eva Ribom²⁶, Björn E Rosengren¹⁶, John T Schousboe^{27

28}, Elaine M Dennison^{1

29

30}, Cyrus Cooper^{1

29

31}; and the International Musculoskeletal Ageing Network

Affiliations

¹ MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, UK.
² MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, UK. nch@mrc.soton.ac.uk.
³ NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK. nch@mrc.soton.ac.uk.
⁴ Department of Biomedical Sciences, Clinical Pharmacology and Toxicology Research Unit, Namur Research Institute for Life Sciences (NARILIS), Faculty of Medicine, University of Namur, 5000, Namur, Belgium.
⁵ Division of Epidemiology, Public Health and Health Economics, Department of Public Health, University of Liège, Liège, Belgium.
⁶ Department of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.
⁷ Research Institute, California Pacific Medical Center, San Francisco, California, USA.
⁸ Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA.
⁹ Servicio de Geriatría, Hospital Universitario Ramón y Cajal (IRYCIS), Madrid, Spain.
¹⁰ Medicine and Epidemiology & Community Health, University of Minnesota, Minnesota, USA.
¹¹ Center for Care Delivery and Outcomes Research, Minneapolis VA Health Care System, Minneapolis, MN, USA.
¹² Nutrition, Exercise Physiology, and Sarcopenia Laboratory, Jean Mayer USDA Human Nutrition Research Center On Aging, Tufts University, Boston, USA.
¹³ Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia.
¹⁴ Sahlgrenska Osteoporosis Centre, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden.
¹⁵ Centre for Metabolic Bone Diseases, University of Sheffield, Sheffield, UK.
¹⁶ Clinical and Molecular Osteoporosis Research Unit, Department of Clinical Sciences Malmo, Lund University and Department of Orthopedics, Skane University Hospital, Malmo, Sweden.
¹⁷ Division of Rheumatology, Department of Internal Medicine, UC Davis Health, 4625 Second Avenue, Sacramento, CA, 95917, USA.
¹⁸ Metabolism and Nutrition Research Group, Louvain Drug Research Institute, UCLouvain, Université catholique de Louvain, 1200 Sint-Lambrechts-Woluwe, Belgium.
¹⁹ Center for Osteoporosis Research, Institute of Medicine, Sahlgrenska Academy, Sahlgrenska University Hospital, Mölndal, Sweden.
²⁰ Centre for Integrated Research in Musculoskeletal Ageing (CIMA), Mellanby Centre for Bone Research, University of Sheffield, Sheffield, UK.
²¹ Centre for Bone and Arthritis Research (CBAR), Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
²² Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
²³ Region Västra Götaland, Sahlgrenska University Hospital, Department of Drug Treatment, Gothenburg, Sweden.
²⁴ Oregon Health & Science University, Portland, Oregon, USA.
²⁵ Protein Research Chair, Biochemistry Department, College of Science, King Saud University, Riyadh, Kingdom of Saudi Arabia.
²⁶ Department of Surgical Sciences, University of Uppsala, Uppsala, Sweden.
²⁷ Park Nicollet Clinic and HealthPartners Institute, Bloomington, Minnesota, USA.
²⁸ University of Minnesota, Minneapolis, Minnesota, USA.
²⁹ NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK.
³⁰ Victoria University of Wellington, Wellington, New Zealand.
³¹ NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK.

Abstract

Background: Low grip strength and gait speed are associated with mortality. However, investigation of the additional mortality risk explained by these measures, over and above other factors, is limited.

Aim: We examined whether grip strength and gait speed improve discriminative capacity for mortality over and above more readily obtainable clinical risk factors.

Methods: Participants from the Health, Aging and Body Composition Study, Osteoporotic Fractures in Men Study, and the Hertfordshire Cohort Study were analysed. Appendicular lean mass (ALM) was ascertained using DXA; muscle strength by grip dynamometry; and usual gait speed over 2.4-6 m. Verified deaths were recorded. Associations between sarcopenia components and mortality were examined using Cox regression with cohort as a random effect; discriminative capacity was assessed using Harrell's Concordance Index (C-index).

Results: Mean (SD) age of participants (n = 8362) was 73.8(5.1) years; 5231(62.6%) died during a median follow-up time of 13.3 years. Grip strength (hazard ratio (95% CI) per SD decrease: 1.14 (1.10,1.19)) and gait speed (1.21 (1.17,1.26)), but not ALM index (1.01 (0.95,1.06)), were associated with mortality in mutually-adjusted models after accounting for age, sex, BMI, smoking status, alcohol consumption, physical activity, ethnicity, education, history of fractures and falls, femoral neck bone mineral density (BMD), self-rated health, cognitive function and number of comorbidities. However, a model containing only age and sex as exposures gave a C-index (95% CI) of 0.65(0.64,0.66), which only increased to 0.67(0.67,0.68) after inclusion of grip strength and gait speed.

Conclusions: Grip strength and gait speed may generate only modest adjunctive risk information for mortality compared with other more readily obtainable risk factors.

Keywords: Ageing; Epidemiology; Mortality; Osteoporosis; Sarcopenia.

MeSH terms

Aged
Aged, 80 and over
Cohort Studies
Female
Hand Strength* / physiology
Humans
Male
Mortality
Predictive Value of Tests
Risk Factors
Sarcopenia* / mortality
Sarcopenia* / physiopathology
Walking Speed* / physiology

Abstract

MeSH terms

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