Joint Modeling of Self-Rated Health and Changes in Physical Functioning
成果类型:
Article
署名作者:
Hubbard, Rebecca A.; Inoue, Lurdes Y. T.; Diehr, Paula
署名单位:
University of Washington; University of Washington Seattle; Fred Hutchinson Cancer Center; University of Washington; University of Washington Seattle
刊物名称:
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
ISSN/ISSBN:
0162-1459
DOI:
10.1198/jasa.2009.ap08423
发表日期:
2009
页码:
912-928
关键词:
markov-models
older-adults
disability
patterns
disease
transitions
predictors
mortality
survival
trajectories
摘要:
Self-rated health is an important indicator of future morbidity and mortality. Research has indicated that self-rated health is related to both levels of and changes in physical functioning. But no previous study has jointly modeled longitudinal functional Status and self-rated health trajectories. We propose a joint model for self-rated health and physical functioning that describes the relationship between perceptions of health and the rate of change of physical functioning or disability. Our joint model uses a non homogeneous, Markov process for discrete physical functioning states and connects this to a logistic regression model for healthy versus unhealthy self-rated health through parameters of the physical functioning model. We use simulation studies to establish finite-sample properties of our estimators and show that this model is robust to misspecification of the functional form of the relationship between self-rated health and rate of change of physical functioning, We also show that our joint model performs better than an empirical model based on observed changes in functional status. We apply our joint model to data from the Cardiovascular Health Study (CHS), a large multicenter longitudinal study of older adults. Our analysis indicates that self-rated health is associated both with level of functioning. as indicated by difficulty with activities of daily living (ADL) and instrumental activities of daily living (IADL). and with the risk of increasing difficulty with ADLs and IADLs.