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Disaggregating Activities of Daily Living Limitations for Predicting Nursing Home Admission
Author(s) -
Fong Joelle H.,
Mitchell Olivia S.,
Koh Benedict S. K.
Publication year - 2015
Publication title -
health services research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.706
H-Index - 121
eISSN - 1475-6773
pISSN - 0017-9124
DOI - 10.1111/1475-6773.12235
Subject(s) - activities of daily living , medicine , nursing homes , bathing , gerontology , explanatory power , predictive power , proportional hazards model , physical therapy , nursing , epistemology , philosophy , surgery , pathology
Objective To examine whether disaggregated activities of daily living ( ADL ) limitations better predict the risk of nursing home admission compared to conventionally used ADL disability counts. Data Sources We used panel data from the Health and Retirement Study ( HRS ) for years 1998–2010. The HRS is a nationally representative survey of adults older than 50 years ( n = 18,801). Study Design We fitted Cox regressions in a continuous time survival model with age at first nursing home admission as the outcome. Time‐varying ADL disability types were the key explanatory variables. Principal Findings Of the six ADL limitations, bathing difficulty emerged as the strongest predictor of subsequent nursing home placement across cohorts. Eating and dressing limitations were also influential in driving admissions among more recent cohorts. Using simple ADL counts for analysis yielded similar adjusted R 2 s; however, the amount of explained variance doubled when we allowed the ADL disability measures to time‐vary rather than remain static. Conclusions Looking beyond simple ADL counts can provide health professionals insights into which specific disability types trigger long‐term nursing home use. Functional disabilities measured closer in time carry more prognostic power than static measures.