Nanna Sklander Hansen1, Lars Ängquist2, Peter Lange1,3, Ramune Jacobsen4. 1. Department of Public Health, University of Copenhagen, Copenhagen, Denmark. 2. Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark. 3. Medical Department, Herlev-Gentofte Hospital, Hellerup, Denmark. 4. Department of Pharmacy, University of Copenhagen, Copenhagen, Denmark. ramune.jacobsen@sund.ku.dk.
Abstract
BACKGROUND: Individuals who share the same comorbidity profile are usually similar with regard to their disease severity, use of health care, and clinical outcomes. The identification of comorbidity clusters therefore bears prognostic information. The objective of this study was to identify and characterize comorbidity clusters in individuals with COPD in Denmark. METHODS: Data from the Danish national registers were used. The study population included all individuals ≥16 y old who lived in the Danish Capital Region on January 1, 2012, and were diagnosed with COPD (N = 70,274). Comorbid chronic conditions were identified using diagnostic algorithms. A 2-step cluster analysis was performed. RESULTS: 81% of subjects with COPD had chronic comorbidities; the most common was hypertension (47.6%), and the least common was anxiety (0.1%). Three comorbidity clusters were identified. Cluster 1 contained 16% of the studied individuals with COPD, with all having heart disease in addition to the remaining comorbidities. Cluster 2 contained 30% of the studied individuals with COPD, of whom approximately 1 in 3 suffered from allergies, while the rest had no comorbidities. Cluster 3 contained 54% of the studied individuals with COPD, where all comorbidities but heart disease were represented. Cluster 1 contained the highest proportion of individuals over the age of 65 y, as well as the individuals with the lowest education. After adjusting for sociodemographic characteristics, individuals in Cluster 1 had the highest rates of hospitalizations and bed days. CONCLUSIONS: The presence of heart disease in individuals with COPD is a strong prognostic factor for socioeconomic and health vulnerability.
BACKGROUND: Individuals who share the same comorbidity profile are usually similar with regard to their disease severity, use of health care, and clinical outcomes. The identification of comorbidity clusters therefore bears prognostic information. The objective of this study was to identify and characterize comorbidity clusters in individuals with COPD in Denmark. METHODS: Data from the Danish national registers were used. The study population included all individuals ≥16 y old who lived in the Danish Capital Region on January 1, 2012, and were diagnosed with COPD (N = 70,274). Comorbid chronic conditions were identified using diagnostic algorithms. A 2-step cluster analysis was performed. RESULTS: 81% of subjects with COPD had chronic comorbidities; the most common was hypertension (47.6%), and the least common was anxiety (0.1%). Three comorbidity clusters were identified. Cluster 1 contained 16% of the studied individuals with COPD, with all having heart disease in addition to the remaining comorbidities. Cluster 2 contained 30% of the studied individuals with COPD, of whom approximately 1 in 3 suffered from allergies, while the rest had no comorbidities. Cluster 3 contained 54% of the studied individuals with COPD, where all comorbidities but heart disease were represented. Cluster 1 contained the highest proportion of individuals over the age of 65 y, as well as the individuals with the lowest education. After adjusting for sociodemographic characteristics, individuals in Cluster 1 had the highest rates of hospitalizations and bed days. CONCLUSIONS: The presence of heart disease in individuals with COPD is a strong prognostic factor for socioeconomic and health vulnerability.
Authors: Elena Jurevičienė; Greta Burneikaitė; Laimis Dambrauskas; Vytautas Kasiulevičius; Edita Kazėnaitė; Rokas Navickas; Roma Puronaitė; Giedrė Smailytė; Žydrūnė Visockienė; Edvardas Danila Journal: Int J Environ Res Public Health Date: 2022-01-15 Impact factor: 3.390