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Multimorbidity patterns and their associations with patient-perceived treatment burden: A latent class analysis of
Marie Hauge Pedersen1,2, Mathias Lasgaard1,3, Camilla Palmhøj Nielsen1,2
1DEFACTUM - Public Health Research, Central Denmark Region, Aarhus, Denmark.
Objectives:
To identify population groups with distinct multimorbidity patterns and to examine their associations with high treatment burden.
Methods:
Latent class analysis was conducted using cross-sectional, self-reported data on 16 long-term conditions from Danish adults aged 25 years and older in treatment (N = 14,344), drawn from the Danish National Health Survey. Treatment burden was assessed using the Multimorbidity Treatment Burden Questionnaire, and associations between identified multimorbidity patterns and high treatment burden (score ≥22) were examined using a bias-adjusted three-step approach.
Results:
Eight latent classes were identified: 1 Hypertension (31% of the study population); 2 Mental health disorders (21%); 3 Musculoskeletal disorders (17%); 4 Complex cardiometabolic- musculoskeletal disorders (10%); 5 Complex headache-mental-back-disorders (7%); 6 Asthma- allergy (6%); 7 Cataract- respiratory disorders (5%); and 8 Complex respiratory- musculoskeletal disorders (3%). Overall, 13% experienced a high treatment burden. This proportion varied from 0.5% in Class 3 to 48% in Class 5, with the highest proportions associated with Classes 4 (27%), 5 (48%), and 8 (26%). The three complex multimorbidity groups averaged more than four conditions per individual and, compared to Class 1, were associated with a non-Danish background, being temporarily or permanently out of work, low social support, and difficulties engaging with healthcare providers. The prevalence of high treatment burden and the strength of its association with disease patterns decreased with age, while no substantial differences were observed across sexes.
Conclusion:
Specific multimorbidity patterns were strongly associated with high treatment burden. These findings may inform healthcare planning, resource allocation, and tailored interventions to reduce treatment burden.
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