TY - JOUR
T1 - Patterns of Multimorbidity in Middle-Aged and Older Adults: An Analysis of the UK Biobank Data
AU - Zemedikun, Dawit
PY - 2018/7
Y1 - 2018/7
N2 - Objective: To assess the prevalence, disease clusters, and patterns of multimorbidity using a novel 2-stage approach in middle-aged and older adults from the United Kingdom.
Patients and Methods: Data on 36 chronic conditions from 502,643 participants aged 40 to 69 years with baseline measurements between March 13, 2006, and October 1, 2010, from the UK Biobank were extracted. We combined cluster analysis and association rule mining to assess patterns of multimorbidity
overall and by age, sex, and ethnicity. A maximum of 3 clusters and 30 disease patterns were mined. Comparisons were made using lift as the main measure of association.
Results: Ninety-five thousand seven hundred-ten participants (19%) had 2 or more chronic conditions. The first cluster included only myocardial infarction and angina (lift¼13.3), indicating that the likelihood of co-occurrence of these conditions is 13 times higher than in isolation. The second cluster consisted of 26 conditions, including cardiovascular, musculoskeletal, respiratory, and neurodegenerative diseases. The strongest association was found between heart failure and atrial fibrillation (lift¼23.6). Diabetes was at the center of this cluster with strong associations with heart failure, chronic kidney disease, liver failure, and stroke (lift>2). The third cluster contained 8 highly prevalent conditions, including cancer, hypertension, asthma, and depression, and the strongest association was observed between anxiety and depression (lift¼5.0).
Conclusion: Conditions such as diabetes, hypertension, and asthma are the epicenter of disease clusters for multimorbidity. A more integrative multidisciplinary approach focusing on better management and
prevention of these conditions may help prevent other conditions in the clusters.
AB - Objective: To assess the prevalence, disease clusters, and patterns of multimorbidity using a novel 2-stage approach in middle-aged and older adults from the United Kingdom.
Patients and Methods: Data on 36 chronic conditions from 502,643 participants aged 40 to 69 years with baseline measurements between March 13, 2006, and October 1, 2010, from the UK Biobank were extracted. We combined cluster analysis and association rule mining to assess patterns of multimorbidity
overall and by age, sex, and ethnicity. A maximum of 3 clusters and 30 disease patterns were mined. Comparisons were made using lift as the main measure of association.
Results: Ninety-five thousand seven hundred-ten participants (19%) had 2 or more chronic conditions. The first cluster included only myocardial infarction and angina (lift¼13.3), indicating that the likelihood of co-occurrence of these conditions is 13 times higher than in isolation. The second cluster consisted of 26 conditions, including cardiovascular, musculoskeletal, respiratory, and neurodegenerative diseases. The strongest association was found between heart failure and atrial fibrillation (lift¼23.6). Diabetes was at the center of this cluster with strong associations with heart failure, chronic kidney disease, liver failure, and stroke (lift>2). The third cluster contained 8 highly prevalent conditions, including cancer, hypertension, asthma, and depression, and the strongest association was observed between anxiety and depression (lift¼5.0).
Conclusion: Conditions such as diabetes, hypertension, and asthma are the epicenter of disease clusters for multimorbidity. A more integrative multidisciplinary approach focusing on better management and
prevention of these conditions may help prevent other conditions in the clusters.
UR - https://doi.org/10.1016/j.mayocp.2018.02.012
U2 - 10.1016/j.mayocp.2018.02.012
DO - 10.1016/j.mayocp.2018.02.012
M3 - Article
SN - 0025-6196
SP - 857
EP - 866
JO - Mayo Clinic Proceedings
JF - Mayo Clinic Proceedings
M1 - 93(7)
ER -
