Chronic condition patterns in the US population and their association with health related quality of life.

This study aims to identify chronic disease patterns and their relationship to health-related quality of life (HRQL) in the US population. This cross-sectional study used data from 86,745 participants aged 18 years and older of the Medical Expenditure Panel Survey (MEPS) 2010-2015, we employed latent class analysis (LCA) to identify subgroups of participants with different combinations of 23 chronic conditions which had medical utilization during the past 12 months. Derived chronic condition latent classes were used to predict the 12-Item Short Form Survey physical component score (PCS), mental component score (MCS) in addition to overall HRQL (SF-6D) while controlling for covariates. LCA identified five unique multi-morbidity groups: "healthy" (62.5%), "vascular risk" (18.9%), "anxiety" (12.2%), "heart disease" (2.9%), and "severely-impaired" (3.5%). Covariate-adjusted mean SF-6D scores varied significantly among classes: healthy (0.85), vascular risk (0.77), anxiety (0.67), heart disease group (0.65), and severely-impaired (0.56). The anxiety group, proportionately younger and female, had high PCS (46.3) but low MCS (41.9). The heart disease group, although older and in poor physical health (PCS = 33.2), had higher MCS scores (46.9). Our results demonstrate multi-morbidity significantly impacts HRQL. The relationship between physical and mental health functioning varied across different multi-morbidity groups, and the discordance was more pronounced in younger ages and females. Our research also identified an older age group that was mentally robust and maintained a strong HRQL. Findings can inform the development of targeted interventions to improve physical and mental health functioning in vulnerable populations.