Peggy M Cawthon1,2, Sheena M Patel1, Stephen B Kritchevsky3, Anne B Newman4, Adam Santanasto4, Douglas P Kiel5, Thomas G Travison5, Nancy Lane6, Steven R Cummings1,2, Eric S Orwoll7, Kate A Duchowny2, Timothy Kwok8, Vasant Hirani9, John Schousboe10,11, Magnus K Karlsson12, Dan Mellström13,14, Claes Ohlsson13,14, Östen Ljunggren15, Qian-Li Xue16, Michelle Shardell17, Joanne M Jordan18, Karol M Pencina5, Roger A Fielding19, Jay Magaziner17, Rosaly Correa-de-Araujo20, Shalender Bhasin21, Todd M Manini22. 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
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.
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.
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Authors: Shalender Bhasin; Thomas G Travison; Todd M Manini; Sheena Patel; Karol M Pencina; Roger A Fielding; Jay M Magaziner; Anne B Newman; Douglas P Kiel; Cyrus Cooper; Jack M Guralnik; Jane A Cauley; Hidenori Arai; Brian C Clark; Francesco Landi; Laura A Schaap; Suzette L Pereira; Daniel Rooks; Jean Woo; Linda J Woodhouse; Ellen Binder; Todd Brown; Michelle Shardell; Quian-Li Xue; Ralph B DʼAgostino; Denise Orwig; Greg Gorsicki; Rosaly Correa-De-Araujo; Peggy M Cawthon Journal: J Am Geriatr Soc Date: 2020-03-09 Impact factor: 5.562
Authors: Stephanie A Studenski; Katherine W Peters; Dawn E Alley; Peggy M Cawthon; Robert R McLean; Tamara B Harris; Luigi Ferrucci; Jack M Guralnik; Maren S Fragala; Anne M Kenny; Douglas P Kiel; Stephen B Kritchevsky; Michelle D Shardell; Thuy-Tien L Dam; Maria T Vassileva Journal: J Gerontol A Biol Sci Med Sci Date: 2014-05 Impact factor: 6.053