Daniel O Clark1, Timothy E Stump2, Wanzhu Tu3, Douglas K Miller4. 1. Indiana University Center for Aging Research, Indianapolis IN, USA Regenstrief Institute, Inc., Indianapolis IN, USA Department of Medicine, Division of General Internal Medicine and Geriatrics, Indiana University School of Medicine, Indianapolis IN, USA daniclar@iupui.edu. 2. Division of Biostatistics, Indiana University School of Medicine, Indianapolis IN, USA. 3. Regenstrief Institute, Inc., Indianapolis IN, USA Division of Biostatistics, Indiana University School of Medicine, Indianapolis IN, USA. 4. Indiana University Center for Aging Research, Indianapolis IN, USA Regenstrief Institute, Inc., Indianapolis IN, USA Department of Medicine, Division of General Internal Medicine and Geriatrics, Indiana University School of Medicine, Indianapolis IN, USA.
Abstract
OBJECTIVES: Efforts to prevent activity of daily living (ADL) dependency may be improved through models that assess older adults' dependency risk. We evaluated whether cognition and gait speed measures improve the predictive validity of interview-based models. METHOD: Participants were 8,095 self-respondents in the 2006 Health and Retirement Survey who were aged 65 years or over and independent in five ADLs. Incident ADL dependency was determined from the 2008 interview. Models were developed using random 2/3rd cohorts and validated in the remaining 1/3rd. RESULTS: Compared to a c-statistic of 0.79 in the best interview model, the model including cognitive measures had c-statistics of 0.82 and 0.80 while the best fitting gait speed model had c-statistics of 0.83 and 0.79 in the development and validation cohorts, respectively. CONCLUSION: Two relatively brief models, one that requires an in-person assessment and one that does not, had excellent validity for predicting incident ADL dependency but did not significantly improve the predictive validity of the best fitting interview-based models.
OBJECTIVES: Efforts to prevent activity of daily living (ADL) dependency may be improved through models that assess older adults' dependency risk. We evaluated whether cognition and gait speed measures improve the predictive validity of interview-based models. METHOD:Participants were 8,095 self-respondents in the 2006 Health and Retirement Survey who were aged 65 years or over and independent in five ADLs. Incident ADL dependency was determined from the 2008 interview. Models were developed using random 2/3rd cohorts and validated in the remaining 1/3rd. RESULTS: Compared to a c-statistic of 0.79 in the best interview model, the model including cognitive measures had c-statistics of 0.82 and 0.80 while the best fitting gait speed model had c-statistics of 0.83 and 0.79 in the development and validation cohorts, respectively. CONCLUSION: Two relatively brief models, one that requires an in-person assessment and one that does not, had excellent validity for predicting incident ADL dependency but did not significantly improve the predictive validity of the best fitting interview-based models.
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