Multimorbidity Profiles in German Centenarians: A Latent Class Analysis of Health Insurance Data
| Autor: | Petra von Berenberg, Paul Gellert, Adelheid Kuhlmey, Dagmar Dräger, Thomas Zahn, Julia Neuwirth |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Lung Diseases
Male Gerontology media_common.quotation_subject Myocardial Infarction Diabetes Complications German 03 medical and health sciences Health services 0302 clinical medicine Germany Rheumatic Diseases Diabetes Mellitus Health insurance Humans Multimorbidity Medicine 030212 general & internal medicine Sex Distribution media_common Aged 80 and over Heart Failure Peripheral Vascular Diseases Community and Home Care 030505 public health business.industry Arthritis Longevity Long-Term Care language.human_language Latent class model Hospitalization Cerebrovascular Disorders Latent Class Analysis language Dementia Female Kidney Diseases Geriatrics and Gerontology 0305 other medical science business |
| Zdroj: | Journal of Aging and Health. 31:580-594 |
| ISSN: | 1552-6887 0898-2643 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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