Journal of aging and health · 2017
Multimorbidity Profiles in German Centenarians: A Latent Class Analysis of Health Insurance Data.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Gellert Paul, von Berenberg Petra, Zahn Thomas, Neuwirth Julia, Kuhlmey Adelheid, Dräger Dagmar
Аннотация
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.
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.
Предметные рубрики MeSH
Aged, 80 and overArthritisCerebrovascular DisordersDementiaDiabetes ComplicationsDiabetes MellitusFemaleGermanyHeart FailureHospitalizationHumansKidney DiseasesLatent Class AnalysisLong-Term CareLung DiseasesMaleMultimorbidityMyocardial InfarctionPeripheral Vascular DiseasesRheumatic DiseasesSex Distribution