Prevalence and patterns of multimorbidity in the Jamaican population: A comparative analysis of latent variable models

Background Evidence suggests that the single-disease paradigm does not accurately reflect the individual experience, with increasing prevalence of chronic disease multimorbidity, and subtle yet important differences in types of co-occurring diseases. Knowledge of multimorbidity patterns can aid clarification of individual-level burden and needs, to inform prevention and treatment strategies. This study aimed to estimate the prevalence of multimorbidity in Jamaica, identify population subgroups with similar and distinct disease profiles, and examine consistency in patterns identified across statistical techniques. Methods Latent class analysis (LCA) was used to examine multimorbidity patterns in a sample of 2,551 respondents aged 15–74 years, based on data from the nationally representative Jamaica Health and Lifestyle Survey 2007/2008 and self-reported presence/absence of 11 chronic conditions. Secondary analyses compared results with patterns identified using exploratory factor analysis (EFA). Results Nearly one-quarter of the sample (24.1%) were multimorbid (i.e. had ≥2 diseases), with significantly higher burden in females compared to males (31.6% vs. 16.1%; p