W Jack Rejeski1, Julia Rushing2, Jack M Guralnik3, Edward H Ip2, Abby C King4, Todd M Manini5, Anthony P Marsh6, Mary M McDermott7, Roger A Fielding8, Anne B Newman9, Catrine Tudor-Locke10, Thomas M Gill11. 1. Department of Health & Exercise Science, Wake Forest University, Winston-Salem, North Carolina. rejeski@wfu.edu. 2. Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, North Carolina. 3. Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore. 4. Department of Health Research and Policy and the Stanford Prevention Research Center, Department of Medicine, Stanford University School of Medicine, California. 5. Department of Aging & Geriatric Research, College of Medicine, University of Florida, Gainesville. 6. Department of Health & Exercise Science, Wake Forest University, Winston-Salem, North Carolina. 7. Department of Internal Medicine, Northwestern University, Chicago, Illinois. 8. Nutrition, Exercise Physiology, and Sarcopenia Laboratory, Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, Massachusetts. 9. Department of Epidemiology, University of Pittsburgh, Pennsylvania. 10. Pennington Biomedical Research Center, Baton Rouge, Louisiana. 11. Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut.
Abstract
BACKGROUND: The assessment of mobility is essential to both aging research and clinical geriatric practice. A newly developed self-report measure of mobility, the mobility assessment tool-short form (MAT-sf), uses video animations as an innovative method to improve measurement accuracy/precision. The primary aim of the current study was to evaluate whether MAT-sf scores can be used to identify risk for major mobility disability (MMD). METHODS: This article is based on data collected from the Lifestyle Interventions and Independence for Elders study and involved 1,574 older adults between the ages of 70-89. The MAT-sf was administered at baseline; MMD, operationalized as failure to complete the 400-m walk ≤ 15 minutes, was evaluated at 6-month intervals across a period of 42 months. The outcome of interest was the first occurrence of MMD or incident MMD. RESULTS: After controlling for age, sex, clinic site, and treatment arm, baseline MAT-sf scores were found to be effective in identifying risk for MMD (p < .0001). Partitioning the MAT-sf into four groups revealed that persons with scores <40, 40-49, 50-59, and 60+ had failure rates across 42 months of follow-up of 66%, 52%, 35%, and 22%, respectively. CONCLUSIONS: The MAT-sf is a quick and efficient way of identifying older adults at risk for MMD. It could be used to clinically identify older adults that are in need of intervention for MMD and provides a simple means for monitoring the status of patients' mobility, an important dimension of functional health.
BACKGROUND: The assessment of mobility is essential to both aging research and clinical geriatric practice. A newly developed self-report measure of mobility, the mobility assessment tool-short form (MAT-sf), uses video animations as an innovative method to improve measurement accuracy/precision. The primary aim of the current study was to evaluate whether MAT-sf scores can be used to identify risk for major mobility disability (MMD). METHODS: This article is based on data collected from the Lifestyle Interventions and Independence for Elders study and involved 1,574 older adults between the ages of 70-89. The MAT-sf was administered at baseline; MMD, operationalized as failure to complete the 400-m walk ≤ 15 minutes, was evaluated at 6-month intervals across a period of 42 months. The outcome of interest was the first occurrence of MMD or incident MMD. RESULTS: After controlling for age, sex, clinic site, and treatment arm, baseline MAT-sf scores were found to be effective in identifying risk for MMD (p < .0001). Partitioning the MAT-sf into four groups revealed that persons with scores <40, 40-49, 50-59, and 60+ had failure rates across 42 months of follow-up of 66%, 52%, 35%, and 22%, respectively. CONCLUSIONS: The MAT-sf is a quick and efficient way of identifying older adults at risk for MMD. It could be used to clinically identify older adults that are in need of intervention for MMD and provides a simple means for monitoring the status of patients' mobility, an important dimension of functional health.
Authors: W Jack Rejeski; Lawrence R Brawley; Walter T Ambrosius; Peter H Brubaker; Brian C Focht; Capri G Foy; Lesley D Fox Journal: Health Psychol Date: 2003-07 Impact factor: 4.267
Authors: Robert T Mankowski; Stephen D Anton; Robert Axtell; Shyh-Huei Chen; Roger A Fielding; Nancy W Glynn; Fang-Chi Hsu; Abby C King; Andrew S Layne; Christiaan Leeuwenburgh; Todd M Manini; Anthony P Marsh; Marco Pahor; Catrine Tudor-Locke; David E Conroy; Thomas W Buford Journal: J Am Geriatr Soc Date: 2017-08-11 Impact factor: 5.562
Authors: Heidi D Klepin; Janet A Tooze; Jack Rejeski; Shannon Mihalko; Timothy S Pardee; Wendy Demark-Wahnefried; Bayard L Powell; Ann M Geiger; Stephen Kritchevsky Journal: J Geriatr Oncol Date: 2022-05 Impact factor: 3.929
Authors: Kathryn E Callahan; Laura Lovato; Michael E Miller; Anthony P Marsh; Roger A Fielding; Thomas M Gill; Erik J Groessl; Jack Guralnik; Abby C King; Stephen B Kritchevsky; Mary M McDermott; Todd Manini; Anne B Newman; W Jack Rejeski Journal: J Am Geriatr Soc Date: 2018-10-03 Impact factor: 5.562
Authors: Sunghye Kim; Anthony P Marsh; Lauren Rustowicz; Catherine Roach; Xiaoyan I Leng; Stephen B Kritchevsky; W Jack Rejeski; Leanne Groban Journal: Anesthesiology Date: 2016-04 Impact factor: 7.892
Authors: Blake R Neyland; Christina E Hugenschmidt; Robert G Lyday; Jonathan H Burdette; Laura D Baker; W Jack Rejeski; Michael E Miller; Stephen B Kritchevsky; Paul J Laurienti Journal: Brain Sci Date: 2021-01-17
Authors: Sunghye Kim; Michael E Miller; Marina Lin; W Jack Rejeski; Stephen B Kritchevsky; Anthony P Marsh; Leanne Groban Journal: Eur Rev Aging Phys Act Date: 2018-04-26 Impact factor: 3.878
Authors: Janet Withall; Colin J Greaves; Janice L Thompson; Jolanthe L de Koning; Jessica C Bollen; Sarah J Moorlock; Kenneth R Fox; Max J Western; Tristan Snowsill; Antonieta Medina-Lara; Rosina Cross; Peter Ladlow; Gordon Taylor; Vasiliki Zisi; James Clynes; Selena Gray; Sandra Agyapong-Badu; Jack M Guralnik; W Jack Rejeski; Afroditi Stathi Journal: J Gerontol A Biol Sci Med Sci Date: 2020-11-13 Impact factor: 6.053