Ethnic differences in early onset multimorbidity and associations with health service use, long-term prescribing, years of life lost, and mortality: an observational study using person-level clustering in the UK Clinical Practice Research Datalink

BackgroundThe population prevalence of multimorbidity (the existence of at least 2 or more long-term conditions (LTCs) in an individual) is increasing among young adults, particularly in minority ethnic groups and individuals living in socioeconomically deprived areas. In this study, we applied a data-driven approach to identify clusters of individuals who had an early onset multimorbidity in an ethnically and socioeconomically diverse population. We identified associations between clusters and a range of health outcomes. Methods and findingsWe analysed the electronic health records from 837,869 individuals in England with early onset multimorbidity (aged between 16 and 39 years old when the second LTC was recorded) using linked primary and secondary care data between 2010 and 2020 from the Clinical Practice Research Datalink GOLD (CPRD GOLD). A total of 204 LTCs were included. Latent class analysis stratified by ethnicity unveiled 4 clusters of multimorbidity in White groups and 3 clusters in South Asian and Black groups. We found that early onset multimorbidity is the most common form of multimorbidity among minority ethnic (59% and 56%, in the South Asian and Black populations, respectively) in the UK compared to the White population (42%). At the end of the study, 4% of the White early onset multimorbidity population had died compared to 2% of the South Asian and Black populations, however, the latter groups died younger and lost more years of life. The three ethnic groups displayed a cluster of individuals with increased rates of primary care consultations, hospitalisations, long-term prescribing, and odds of mortality. These presented a combination of physical and mental health conditions that are common across all groups (hypertension, depression and painful conditions being the leading conditions). However, they also presented exclusive LTCs and had different sociodemographic profiles: Whites were mostly men (54%), South Asian and Black groups were more socioeconomically deprived than White groups, with a consistent deprivation gradient across all multimorbidity clusters. In White groups, the highest risk cluster was more socioeconomically deprived than the lowest risk cluster. ConclusionsThese findings emphasise the need to identify, prevent and manage multimorbidity early in the life course. Our work provides additional insights into the need to ensure healthcare improvements are equitable and reach those from socioeconomically deprived and diverse groups who are disproportionately and more severely affected by multimorbidity.