Frailty and depression: A latent trait analysis

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DESCRIPTION (provided by applicant): This project aims to understand the structural and temporal associations between frailty and depression, and to describe the combined role of these constructs within the aging process. Frailty is common in later life, affecting between 10.9 and 20.3% of older adults, and this syndrome increases vulnerability to a host of common poor health outcomes such as falls, hospitalization, disability, nursing home entry and mortality. Identifying frailty is thus important as it may serve as a vital indicator for timely intervention nd prevention of disease and disability. However, understanding and identification of this syndrome is hindered by lack of unified conceptual and operational definitions. Confusion in defining frailt is caused, in part, by lack of knowledge regarding how and why frailty is related to other common syndromes in later life, such as depression. This project seeks funding support for research on elucidating relationships between frailty and depression in order to develop a better conceptual understanding of frailty and to improve the clinical usefulness of its identification. The proposed research will use publically available data from the Health and Retirement Study (HRS), spanning 5 follow-up waves over a 10-year period (2000 to 2010). The HRS is a large, prospective, population-based sample of approximately 20,000 older adults with comprehensive measurements of physical functioning and mental health. The HRS data provides a unique opportunity to evaluate and compare competing models of comorbidity between frailty and depression. Data from HRS participants aged 65 years and older and without major disease or functional limitation will be compiled and analyzed. Using latent trait analysis and structural equation modeling, we will assess competing models for the association between depression and frailty. We expect to provide better understanding of the relationships between depression and frailty by building and testing competing structural models of their comorbidity. By evaluating competing models, we expect to identify factors which differentially influence the syndromes of frailty and depression and those which predict their comorbidity. This study will provide a rich understanding of how the conditions of frailty and depression are related, explore differences in the factors which predict these conditions, and determine whether frailty and depression are jointly related to prediction of key health outcomes. By clarifying the joint influence of depression and frailty in predicting poor health outcomes over time, we expect to inform the development of better, more accurate conceptual and operational definitions of frailty, which account for the intersection of physical and mental health. An improved understanding of these relationships will help guide research to development of more accurate and comprehensive definitions of frailty. Accounting for the interrelationships between frailty and depression, and refinement of the operational definition of frailty will facilitate improved identification of frail individuals and development of more effective prevention and intervention strategies.