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dc.contributor.authorEto, Fen_US
dc.contributor.authorSamuel, Men_US
dc.contributor.authorHenkin, Ren_US
dc.contributor.authorMahesh, Men_US
dc.contributor.authorAhmad, Ten_US
dc.contributor.authorAngdembe, Aen_US
dc.contributor.authorHamish McAllister-Williams, Ren_US
dc.contributor.authorMissier, Pen_US
dc.contributor.authorJ Reynolds, Nen_US
dc.contributor.authorR Barnes, Men_US
dc.contributor.authorHull, Sen_US
dc.contributor.authorFiner, Sen_US
dc.contributor.authorMathur, Ren_US
dc.date.accessioned2024-01-03T14:34:15Z
dc.date.available2023-09-17en_US
dc.date.issued2023-10en_US
dc.identifier.urihttps://qmro.qmul.ac.uk/xmlui/handle/123456789/93337
dc.description.abstractBACKGROUND: The 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 FINDINGS: Using linked primary and secondary care data from the Clinical Practice Research Datalink GOLD (CPRD GOLD), we conducted a cross-sectional study of 837,869 individuals with early onset multimorbidity (aged between 16 and 39 years old when the second LTC was recorded) registered with an English general practice between 2010 and 2020. The study population included 777,906 people of White ethnicity (93%), 33,915 people of South Asian ethnicity (4%), and 26,048 people of Black African/Caribbean ethnicity (3%). A total of 204 LTCs were considered. Latent class analysis stratified by ethnicity identified 4 clusters of multimorbidity in White groups and 3 clusters in South Asian and Black groups. We found that early onset multimorbidity was more common among South Asian (59%, 33,915) and Black (56% 26,048) groups compared to the White population (42%, 777,906). Latent class analysis revealed physical and mental health conditions that were common across all ethnic groups (i.e., hypertension, depression, and painful conditions). However, each ethnic group also presented exclusive LTCs and different sociodemographic profiles: In White groups, the cluster with the highest rates/odds of the outcomes was predominantly male (54%, 44,150) and more socioeconomically deprived than the cluster with the lowest rates/odds of the outcomes. On the other hand, South Asian and Black groups were more socioeconomically deprived than White groups, with a consistent deprivation gradient across all multimorbidity clusters. At the end of the study, 4% (34,922) of the White early onset multimorbidity population had died compared to 2% of the South Asian and Black early onset multimorbidity populations (535 and 570, respectively); however, the latter groups died younger and lost more years of life. The 3 ethnic groups each displayed a cluster of individuals with increased rates of primary care consultations, hospitalisations, long-term prescribing, and odds of mortality. Study limitations include the exclusion of individuals with missing ethnicity information, the age of diagnosis not reflecting the actual age of onset, and the exclusion of people from Mixed, Chinese, and other ethnic groups due to insufficient power to investigate associations between multimorbidity and health-related outcomes in these groups. CONCLUSIONS: These findings emphasise the need to identify, prevent, and manage multimorbidity early in the life course. Our work provides additional insights into the excess burden of early onset multimorbidity in those from socioeconomically deprived and diverse groups who are disproportionately and more severely affected by multimorbidity and highlights the need to ensure healthcare improvements are equitable.en_US
dc.format.extente1004300 - ?en_US
dc.languageengen_US
dc.relation.ispartofPLoS Meden_US
dc.rightsAttribution 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/*
dc.subjectYoung Adulten_US
dc.subjectHumansen_US
dc.subjectMaleen_US
dc.subjectAdolescenten_US
dc.subjectAdulten_US
dc.subjectFemaleen_US
dc.subjectMultimorbidityen_US
dc.subjectCross-Sectional Studiesen_US
dc.subjectCluster Analysisen_US
dc.subjectUnited Kingdomen_US
dc.subjectPatient Acceptance of Health Careen_US
dc.titleEthnic differences in early onset multimorbidity and associations with health service use, long-term prescribing, years of life lost, and mortality: A cross-sectional study using clustering in the UK Clinical Practice Research Datalink.en_US
dc.typeArticle
dc.identifier.doi10.1371/journal.pmed.1004300en_US
pubs.author-urlhttps://www.ncbi.nlm.nih.gov/pubmed/37889900en_US
pubs.issue10en_US
pubs.notesNot knownen_US
pubs.publication-statusPublished onlineen_US
pubs.volume20en_US
dcterms.dateAccepted2023-09-17en_US
rioxxterms.funderDefault funderen_US
rioxxterms.identifier.projectDefault projecten_US
qmul.funderMultimorbidity clusters, trajectories and genetic risk, in British south Asians::Medical Research Councilen_US


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Attribution 3.0 United States
Except where otherwise noted, this item's license is described as Attribution 3.0 United States