Deepika R Laddu1, Betsy C Wertheim2, David O Garcia3, Nancy F Woods4, Michael J LaMonte5, Bertha Chen6, Hoda Anton-Culver7, Oleg Zaslavsky4, Jane A Cauley8, Rowan Chlebowski9, JoAnn E Manson10, Cynthia A Thomson2,3, Marcia L Stefanick6,11. 1. Department of Physical Therapy, University of Illinois at Chicago, Chicago, Illinois. 2. University of Arizona Cancer Center, Tucson, Arizona. 3. Department of Health Promotion Sciences, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, Arizona. 4. School of Nursing, University of Washington, Seattle, Washington. 5. Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo-State University of New York, Buffalo, New York. 6. Department of Obstetrics and Gynecology, School of Medicine, Stanford University, Palo Alto, California. 7. Department of Epidemiology, University of California, Irvine, Irvine, California. 8. Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania. 9. Los Angeles Medical Center, Los Angeles Biomedical Research Institute at Harbor-University of California, Torrance, California. 10. Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts. 11. Stanford Prevention Research Center, School of Medicine, Stanford University, Palo Alto, California.
Abstract
OBJECTIVES: To compare the value of clinically measured gait speed with that of the self-reported Medical Outcomes Study 36-item Short-Form Survey Physical Function Index (SF-36 PF) in predicting future preclinical mobility disability (PCMD) in older women. DESIGN: Prospective cohort study. SETTING: Forty clinical centers in the United States. PARTICIPANTS: Women aged 65 to 79 enrolled in the Women's Health Initiative Clinical Trials with gait speed and SF-36 assessed at baseline (1993-1998) and follow-up Years 1, 3, and 6 (N = 3,587). MEASUREMENTS: Women were categorized as nondecliners or decliners based on changes (from baseline to Year 1) in gait speed and SF-36 PF scores. Logistic regression models were used to estimate incident PCMD (gait speed <1.0 m/s) at Years 3 and 6. Area under the receiver operating characteristic curve (AUC) was used to compare the predictive value of SF-36 PF with that of measured gait speed. RESULTS: Slower baseline gait speed and lower SF-36 PF scores were associated with higher adjusted odds of PCMD at Years 3 and 6 (all P < .001). For gait speed, decliners were 2.59 times as likely to have developed PCMD as nondecliners by Year 3 and 2.35 times as likely by Year 6. Likewise, for SF-36, decliners were 1.42 times as likely to have developed PCMD by Year 3 and 1.49 times as likely by Year 6. Baseline gait speed (AUC = 0.713) was nonsignificantly better than SF-36 (AUC = 0.705) at predicting PCMD over 6 years (P = .21); including measures at a second time point significantly improved model discrimination for predicting PCMD (all P < .001). CONCLUSION: Gait speed identified PCMD risk in older women better than the SF-36 PF did, although the results may be limited given that gait speed served as a predictor and to define the PCMD outcome. Nonetheless, monitoring trajectories of change in mobility are better predictors of future mobility disability than single measures.
OBJECTIVES: To compare the value of clinically measured gait speed with that of the self-reported Medical Outcomes Study 36-item Short-Form Survey Physical Function Index (SF-36 PF) in predicting future preclinical mobility disability (PCMD) in older women. DESIGN: Prospective cohort study. SETTING: Forty clinical centers in the United States. PARTICIPANTS: Women aged 65 to 79 enrolled in the Women's Health Initiative Clinical Trials with gait speed and SF-36 assessed at baseline (1993-1998) and follow-up Years 1, 3, and 6 (N = 3,587). MEASUREMENTS: Women were categorized as nondecliners or decliners based on changes (from baseline to Year 1) in gait speed and SF-36 PF scores. Logistic regression models were used to estimate incident PCMD (gait speed <1.0 m/s) at Years 3 and 6. Area under the receiver operating characteristic curve (AUC) was used to compare the predictive value of SF-36 PF with that of measured gait speed. RESULTS: Slower baseline gait speed and lower SF-36 PF scores were associated with higher adjusted odds of PCMD at Years 3 and 6 (all P < .001). For gait speed, decliners were 2.59 times as likely to have developed PCMD as nondecliners by Year 3 and 2.35 times as likely by Year 6. Likewise, for SF-36, decliners were 1.42 times as likely to have developed PCMD by Year 3 and 1.49 times as likely by Year 6. Baseline gait speed (AUC = 0.713) was nonsignificantly better than SF-36 (AUC = 0.705) at predicting PCMD over 6 years (P = .21); including measures at a second time point significantly improved model discrimination for predicting PCMD (all P < .001). CONCLUSION: Gait speed identified PCMD risk in older women better than the SF-36 PF did, although the results may be limited given that gait speed served as a predictor and to define the PCMD outcome. Nonetheless, monitoring trajectories of change in mobility are better predictors of future mobility disability than single measures.
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