What Cut-Point in Gait Speed Best Discriminates Community-Dwelling Older Adults With Mobility Complaints From Those Without? A Pooled Analysis From the Sarcopenia Definitions and Outcomes Consortium

Author:

Cawthon Peggy M12ORCID,Patel Sheena M1,Kritchevsky Stephen B3ORCID,Newman Anne B4,Santanasto Adam4ORCID,Kiel Douglas P5,Travison Thomas G5ORCID,Lane Nancy6,Cummings Steven R12,Orwoll Eric S7,Duchowny Kate A2,Kwok Timothy8,Hirani Vasant9,Schousboe John1011,Karlsson Magnus K12,Mellström Dan1314ORCID,Ohlsson Claes1314ORCID,Ljunggren Östen15,Xue Qian-Li16ORCID,Shardell Michelle17ORCID,Jordan Joanne M18,Pencina Karol M5,Fielding Roger A19,Magaziner Jay17,Correa-de-Araujo Rosaly20,Bhasin Shalender21ORCID,Manini Todd M22

Affiliation:

1. California Pacific Medical Center Research Institute, San Francisco, USA

2. Department of Epidemiology and Biostatistics, University of California San Francisco, USA

3. Sticht Center for Healthy Aging and Alzheimer’s Prevention, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA

4. Department of Epidemiology, University of Pittsburgh, Pennsylvania, USA

5. Marcus Institute for Aging Research, Hebrew SeniorLife, Department of Medicine Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA

6. Center for Musculoskeletal Health and Department of Internal Medicine, University of California Medical Center, Sacramento, USA

7. Bone and Mineral Unit, Oregon Health & Science University, Portland, USA

8. Department of Medicine & Therapeutics and School of Public Health, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong

9. Charles Perkins Centre, University of Sydney, Australia

10. HealthPartners Institute, Bloomington, Minnesota, USA

11. Division of Health Policy and Management, University of Minnesota, Minneapolis, USA

12. Clinical and Molecular Osteoporosis Research Unit, Department of Orthopedics and Clinical Sciences in Malmo, Skane University Hospital, Lund University, Sweden

13. Centre for Bone and Arthritis Research, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, The Sahlgrenska Academy, University of Gothenburg, Sweden

14. Department of Drug Treatment, Sahlgrenska University Hospital, Region Västra Götaland, Gothenburg, Sweden

15. Department of Medical Sciences, Uppsala University, Sweden

16. Division of Geriatric Medicine and Gerontology and Center on Aging and Health, Johns Hopkins Medical Institute, Baltimore, Maryland, USA

17. Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, USA

18. Thurston Arthritis Research Center, School of Medicine, University of North Carolina, Chapel Hill, USA

19. Nutrition, Exercise, Physiology, and Sarcopenia Laboratory, Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, Massachusetts, USA

20. The National Institute on Aging, Bethesda, Maryland, USA

21. Boston Claude D. Pepper Older Americans Independence Center, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA

22. University of Florida, Gainesville, USA

Abstract

Abstract Background Cut-points to define slow walking speed have largely been derived from expert opinion. Methods Study participants (13 589 men and 5043 women aged ≥65years) had walking speed (m/s) measured over 4–6 m (mean ± SD: 1.20 ± 0.27 m/s in men and 0.94 ± 0.24 m/s in women.) Mobility limitation was defined as any self-reported difficulty with walking approximately 1/4 mile (prevalence: 12.6% men, 26.4% women). Sex-stratified classification and regression tree (CART) models with 10-fold cross-validation identified walking speed cut-points that optimally discriminated those who reported mobility limitation from those who did not. Results Among 5043 women, CART analysis identified 2 cut-points, classifying 4144 (82.2%) with walking speed ≥0.75 m/s, which we labeled as “fast”; 478 (9.5%) as “intermediate” (walking speed ≥0.62 m/s but <0.75 m/s); and 421 (8.3%) as “slow” (walking speed <0.62 m/s). Among 13 589 men, CART analysis identified 3 cut-points, classifying 10 001 (73.6%) with walking speed ≥1.00 m/s (“very fast”); 2901 (21.3%) as “fast” (walking speed ≥0.74 m/s but <1.00 m/s); 497 (3.7%) as “intermediate” (walking speed ≥0.57 m/s but <0.74 m/s); and 190 (1.4%) as “slow” (walking speed <0.57 m/s). Prevalence of self-reported mobility limitation was lowest in the “fast” or “very fast” (11% for men and 19% for women) and highest in the “slow” (60.5% in men and 71.0% in women). Rounding the 2 slower cut-points to 0.60 m/s and 0.75 m/s reclassified very few participants. Conclusions Cut-points in walking speed of approximately 0.60 m/s and 0.75 m/s discriminate those with self-reported mobility limitation from those without.

Funder

National Institute on Aging

Foundation for the National Institutes of Health

California Pacific Medical Center Foundation

Publisher

Oxford University Press (OUP)

Subject

Geriatrics and Gerontology,Aging

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