Abstract
Background
The concurrence of several chronic conditions is a rising concern that poses a serious burden on ageing populations. Analysing how these conditions appear together and how they change through time may provide useful information to design successful multimorbidity-management programs.
Objective
To identify multimorbidity patterns and their related characteristics from a longitudinal perspective.
Subjects
25,931 older adults aged 50+ drawn from the Survey of Health, Ageing and Retirement in Europe (SHARE), a population-based longitudinal European study.
Methods
A sex-stratified Latent Transition Analysis (LTA) was conducted to fit latent classes based on 15 self-reported chronic conditions across three time points. Health-related and socioeconomic variables were assessed as covariates of those patterns.
Results
We identified four time-constant latent classes for each sex:
A “severely impaired” class (with a weighted prevalence of 7.24% for females and 3.30% for males at the first time point),
A “metabolic” class (26.15% and 23.82%),
A “healthy” class (50.92% and 54.32%).
The fourth class was named “osteoarticular” for females (15.70%) and “articular-COPD-ulcer” for males (18.56%).
Age, smoking, material deprivation, and high body mass index were associated with worse health patterns, whereas education, employment, and physical activity were related to less multimorbid classes. Few class changes were detected when modelling transitions.
Conclusions
We reported information on multimorbidity classes and their characteristics that may help to develop targeted health strategies. Within a four-year time window, the identified latent classes remained consistent across time points.