LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Multimorbidity Profiles in German Centenarians: A Latent Class Analysis of Health Insurance Data

Photo from wikipedia

Objectives: Multimorbidity in centenarians is common; although investigations of the prevalence of morbidity in centenarians are accumulating, research on profiles of co-occurrence of morbidities is still sparse. Our aim was… Click to show full abstract

Objectives: Multimorbidity in centenarians is common; although investigations of the prevalence of morbidity in centenarians are accumulating, research on profiles of co-occurrence of morbidities is still sparse. Our aim was to explore profiles of comorbidities in centenarians. Method: Health insurance data from 1,121 centenarians comprising inpatient and outpatient diagnoses from the past 5 years (2009-2013) were analyzed using latent class analysis with adjustments for sex, age, hospitalization, and long-term care. Results: Four distinct comorbidity profiles emerged from the data: 36% of centenarians were categorized as “age-associated”; 18% had a variety of comorbidities but were not diabetic were labeled “multimorbid without diabetes”; 9% were labeled “multimorbid with diabetes”; and 36% “low morbidity.” Conclusion: Patterns of comorbidities describe the complexity of geriatric multimorbidity more appropriately than an approach focused on a single disease. The profiles described by this specific research may inform clinicians and health care planners for the oldest old.

Keywords: insurance data; class analysis; latent class; health insurance; multimorbidity; health

Journal Title: Journal of Aging and Health
Year Published: 2019

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.