Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

A New Path to Address Multimorbidity? Longitudinal Analyses of Retirement Sequences and Chronic Diseases in Old Age

A New Path to Address Multimorbidity? Longitudinal Analyses of Retirement Sequences and Chronic... Chronic disease and multimorbidity are growing health challenges for aging populations, often coinciding with retirement. We examine late-life predictors of multimorbidity, focusing on the association between retirement sequences and number of chronic diseases. We modeled the number of chronic diseases as a function of six types of previously identified 10-year retirement sequences using Health and Retirement Study (HRS) data for 7,880 Americans observed between ages 60 to 61 and 70 to 71. Our results show that at baseline, the adjusted prevalence of multimorbidity was lowest in sequences characterized by late retirement from full-time work and highest in sequences characterized by early labor-force disengagement. Age increases in multimorbidity varied across retirement sequences, though overall differences in prevalence persisted at age 70 to 71. Earlier life disadvantages did not moderate these associations. Findings suggest further investigation of policies that target health limitations affecting work, promote continued beneficial employment opportunities, and ultimately leverage retirement sequences as a novel path to influence multimorbidity in old age. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Applied Gerontology SAGE

A New Path to Address Multimorbidity? Longitudinal Analyses of Retirement Sequences and Chronic Diseases in Old Age

Loading next page...
 
/lp/sage/a-new-path-to-address-multimorbidity-longitudinal-analyses-of-tapsm6JtIw
Publisher
SAGE
Copyright
© The Author(s) 2021
ISSN
0733-4648
eISSN
1552-4523
DOI
10.1177/07334648211031038
Publisher site
See Article on Publisher Site

Abstract

Chronic disease and multimorbidity are growing health challenges for aging populations, often coinciding with retirement. We examine late-life predictors of multimorbidity, focusing on the association between retirement sequences and number of chronic diseases. We modeled the number of chronic diseases as a function of six types of previously identified 10-year retirement sequences using Health and Retirement Study (HRS) data for 7,880 Americans observed between ages 60 to 61 and 70 to 71. Our results show that at baseline, the adjusted prevalence of multimorbidity was lowest in sequences characterized by late retirement from full-time work and highest in sequences characterized by early labor-force disengagement. Age increases in multimorbidity varied across retirement sequences, though overall differences in prevalence persisted at age 70 to 71. Earlier life disadvantages did not moderate these associations. Findings suggest further investigation of policies that target health limitations affecting work, promote continued beneficial employment opportunities, and ultimately leverage retirement sequences as a novel path to influence multimorbidity in old age.

Journal

Journal of Applied GerontologySAGE

Published: Jan 1, 2021

There are no references for this article.