Identifying longitudinal clusters of multimorbidity in an urban setting: A population-based cross-sectional study.
Clustering
Correspondence analysis
LTC, long term conditions
Long term conditions
MCA, multiple correspondence analysis
Multimorbidity
QOF, quality outcomes framework
UK, United Kingdom
WSS/BSS, ratio of within- to between- sum of squares
Journal
The Lancet regional health. Europe
ISSN: 2666-7762
Titre abrégé: Lancet Reg Health Eur
Pays: England
ID NLM: 101777707
Informations de publication
Date de publication:
Apr 2021
Apr 2021
Historique:
entrez:
24
9
2021
pubmed:
25
9
2021
medline:
25
9
2021
Statut:
epublish
Résumé
Globally, there is increasing research on clusters of multimorbidity, but few studies have investigated multimorbidity in urban contexts characterised by a young, multi-ethnic, deprived populations. This study identified clusters of associative multimorbidity in an urban setting. This is a population-based retrospective cross-sectional study using electronic health records of all adults aged 18 years and over, registered between April 2005 to May 2020 in general practices in one inner London borough. Multiple correspondence analysis and cluster analysis was used to identify groups of multimorbidity from 32 long-term conditions (LTCs). The population included 41 general practices with 826,936 patients registered between 2005 and 2020, with mean age 40 (SD15·6) years. The prevalence of multimorbidity was 21% ( Mental health problems, pain, and at-risk behaviours leading to cardiovascular diseases are the important clusters identified in this young, urban population. Impact on Urban Health, United Kingdom.
Sections du résumé
BACKGROUND
BACKGROUND
Globally, there is increasing research on clusters of multimorbidity, but few studies have investigated multimorbidity in urban contexts characterised by a young, multi-ethnic, deprived populations. This study identified clusters of associative multimorbidity in an urban setting.
METHODS
METHODS
This is a population-based retrospective cross-sectional study using electronic health records of all adults aged 18 years and over, registered between April 2005 to May 2020 in general practices in one inner London borough. Multiple correspondence analysis and cluster analysis was used to identify groups of multimorbidity from 32 long-term conditions (LTCs).
RESULTS
RESULTS
The population included 41 general practices with 826,936 patients registered between 2005 and 2020, with mean age 40 (SD15·6) years. The prevalence of multimorbidity was 21% (
INTERPRETATION
CONCLUSIONS
Mental health problems, pain, and at-risk behaviours leading to cardiovascular diseases are the important clusters identified in this young, urban population.
FUNDING
BACKGROUND
Impact on Urban Health, United Kingdom.
Identifiants
pubmed: 34557797
doi: 10.1016/j.lanepe.2021.100047
pii: S2666-7762(21)00024-7
pmc: PMC8454750
doi:
Types de publication
Journal Article
Langues
eng
Pagination
100047Informations de copyright
© 2021 The Author(s).
Déclaration de conflit d'intérêts
The authors declare no conflict of interest.
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