Age, sex, and socioeconomic differences in multimorbidity measured in four ways: UK primary care cross-sectional analysis

Clare MacRae; Stewart W. Mercer; David Henderson; Megan McMinn; Daniel R. Morales; Emily Jefferson; Ronan A. Lyons; Jane Lyons; Chris Dibben; David A. McAllister; Bruce Guthrie

doi:10.3399/BJGP.2022.0405

Age, sex, and socioeconomic differences in multimorbidity measured in four ways: UK primary care cross-sectional analysis

Clare MacRae, Stewart W. Mercer, David Henderson, Megan McMinn, Daniel R. Morales, Emily Jefferson, Ronan A. Lyons, Jane Lyons, Chris Dibben, David A. McAllister, Bruce Guthrie

Population Health and Genomics

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25 Citations (Scopus)

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Abstract

Background: Multimorbidity poses major challenges to healthcare systems worldwide. Definitions with cut-offs in excess of ≥2 long-term conditions (LTCs) might better capture populations with complexity but are not standardised.

Aim: To examine variation in prevalence using different definitions of multimorbidity.

Design and Setting: Cross-sectional study of 1 168 620 people in England.

Method: Comparison of multimorbidity (MM) prevalence using four definitions: MM2+ (≥2 LTCs), MM3+ (≥3 LTCs), MM3+ from 3+ (≥3 LTCs from ≥3 International Classification of Diseases, 10th revision chapters), and mental-physical MM (≥2 LTCs where ≥1 mental health LTC and ≥1 physical health LTC are recorded). Logistic regression was used to examine patient characteristics associated with multimorbidity under all four definitions.

Results: MM2+ was most common (40.4%) followed by MM3+ (27.5%), MM3+ from 3+ (22.6%), and mental-physical MM (18.9%). MM2+, MM3+, and MM3+ from 3+ were strongly associated with oldest age (adjusted odds ratio [aOR] 58.09, 95% confidence interval [CI] = 56.13 to 60.14; aOR 77.69, 95% CI = 75.33 to 80.12; and aOR 102.06, 95% CI = 98.61 to 105.65; respectively), but mental-physical MM was much less strongly associated (aOR 4.32, 95% CI = 4.21 to 4.43). People in the most deprived decile had equivalent rates of multimorbidity at a younger age than those in the least deprived decile. This was most marked in mental-physical MM at 40-45 years younger, followed by MM2+ at 15-20 years younger, and MM3+ and MM3+ from 3+ at 10-15 years younger. Females had higher prevalence of multimorbidity under all definitions, which was most marked for mental-physical MM.

Conclusion: Estimated prevalence of multimorbidity depends on the definition used, and associations with age, sex, and socioeconomic position vary between definitions. Applicable multimorbidity research requires consistency of definitions across studies.

Original language	English
Article number	10.3399/BJGP.2022.0405
Pages (from-to)	e249-e256
Number of pages	8
Journal	British Journal of General Practice
Volume	73
Issue number	729
Early online date	30 Mar 2023
DOIs	https://doi.org/10.3399/BJGP.2022.0405
Publication status	Published - Apr 2023

Keywords

Female
Humans
Multimorbidity
Cross-Sectional Studies
Prevalence
Socioeconomic Factors
United Kingdom/epidemiology
Primary Health Care
epidemiology
multimorbidity
primary care
socioeconomic disparities

ASJC Scopus subject areas

Family Practice

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.3399/BJGP.2022.0405Licence: CC BY

Final Published VersionFinal published version, 158 KBLicence: CC BY

https://pubmed.ncbi.nlm.nih.gov/36997222/Licence: CC BY

Cite this

MacRae, C., Mercer, S. W., Henderson, D., McMinn, M., Morales, D. R., Jefferson, E., Lyons, R. A., Lyons, J., Dibben, C., McAllister, D. A., & Guthrie, B. (2023). Age, sex, and socioeconomic differences in multimorbidity measured in four ways: UK primary care cross-sectional analysis. British Journal of General Practice, 73(729), e249-e256. Article 10.3399/BJGP.2022.0405. https://doi.org/10.3399/BJGP.2022.0405

@article{6b0804ab27a346a09421f738abfb9c97,

title = "Age, sex, and socioeconomic differences in multimorbidity measured in four ways: UK primary care cross-sectional analysis",

abstract = "Background: Multimorbidity poses major challenges to healthcare systems worldwide. Definitions with cut-offs in excess of ≥2 long-term conditions (LTCs) might better capture populations with complexity but are not standardised.Aim: To examine variation in prevalence using different definitions of multimorbidity.Design and Setting: Cross-sectional study of 1 168 620 people in England.Method: Comparison of multimorbidity (MM) prevalence using four definitions: MM2+ (≥2 LTCs), MM3+ (≥3 LTCs), MM3+ from 3+ (≥3 LTCs from ≥3 International Classification of Diseases, 10th revision chapters), and mental-physical MM (≥2 LTCs where ≥1 mental health LTC and ≥1 physical health LTC are recorded). Logistic regression was used to examine patient characteristics associated with multimorbidity under all four definitions.Results: MM2+ was most common (40.4%) followed by MM3+ (27.5%), MM3+ from 3+ (22.6%), and mental-physical MM (18.9%). MM2+, MM3+, and MM3+ from 3+ were strongly associated with oldest age (adjusted odds ratio [aOR] 58.09, 95% confidence interval [CI] = 56.13 to 60.14; aOR 77.69, 95% CI = 75.33 to 80.12; and aOR 102.06, 95% CI = 98.61 to 105.65; respectively), but mental-physical MM was much less strongly associated (aOR 4.32, 95% CI = 4.21 to 4.43). People in the most deprived decile had equivalent rates of multimorbidity at a younger age than those in the least deprived decile. This was most marked in mental-physical MM at 40-45 years younger, followed by MM2+ at 15-20 years younger, and MM3+ and MM3+ from 3+ at 10-15 years younger. Females had higher prevalence of multimorbidity under all definitions, which was most marked for mental-physical MM.Conclusion: Estimated prevalence of multimorbidity depends on the definition used, and associations with age, sex, and socioeconomic position vary between definitions. Applicable multimorbidity research requires consistency of definitions across studies.",

keywords = "Female, Humans, Multimorbidity, Cross-Sectional Studies, Prevalence, Socioeconomic Factors, United Kingdom/epidemiology, Primary Health Care, epidemiology, multimorbidity, primary care, socioeconomic disparities",

author = "Clare MacRae and Mercer, {Stewart W.} and David Henderson and Megan McMinn and Morales, {Daniel R.} and Emily Jefferson and Lyons, {Ronan A.} and Jane Lyons and Chris Dibben and McAllister, {David A.} and Bruce Guthrie",

note = "Funding Information: Bruce Guthrie, Stewart W Mercer, Daniel R Morales, and Emily Jefferson received funding for this study from the Chief Scientist Office (reference: HIPS/18/30). Clare MacRae received funding for this study from an NHS Education for Scotland Academic Fellowship and Medical Research Council fellowship (reference: MR/W000253/1). The funders had no role in the development of study design, data collection and interpretation, or writing of the final report. The corresponding author had full data access and had final responsibility for submitting for publication. Copyright: {\textcopyright} 2023 The Authors.",

year = "2023",

month = apr,

doi = "10.3399/BJGP.2022.0405",

language = "English",

volume = "73",

pages = "e249--e256",

journal = "British Journal of General Practice",

issn = "0960-1643",

publisher = "Royal College of General Practitioners",

number = "729",

}

MacRae, C, Mercer, SW, Henderson, D, McMinn, M, Morales, DR , Jefferson, E, Lyons, RA, Lyons, J, Dibben, C, McAllister, DA & Guthrie, B 2023, 'Age, sex, and socioeconomic differences in multimorbidity measured in four ways: UK primary care cross-sectional analysis', British Journal of General Practice, vol. 73, no. 729, 10.3399/BJGP.2022.0405, pp. e249-e256. https://doi.org/10.3399/BJGP.2022.0405

TY - JOUR

T1 - Age, sex, and socioeconomic differences in multimorbidity measured in four ways

T2 - UK primary care cross-sectional analysis

AU - MacRae, Clare

AU - Mercer, Stewart W.

AU - Henderson, David

AU - McMinn, Megan

AU - Morales, Daniel R.

AU - Jefferson, Emily

AU - Lyons, Ronan A.

AU - Lyons, Jane

AU - Dibben, Chris

AU - McAllister, David A.

AU - Guthrie, Bruce

N1 - Funding Information: Bruce Guthrie, Stewart W Mercer, Daniel R Morales, and Emily Jefferson received funding for this study from the Chief Scientist Office (reference: HIPS/18/30). Clare MacRae received funding for this study from an NHS Education for Scotland Academic Fellowship and Medical Research Council fellowship (reference: MR/W000253/1). The funders had no role in the development of study design, data collection and interpretation, or writing of the final report. The corresponding author had full data access and had final responsibility for submitting for publication. Copyright: © 2023 The Authors.

PY - 2023/4

Y1 - 2023/4

N2 - Background: Multimorbidity poses major challenges to healthcare systems worldwide. Definitions with cut-offs in excess of ≥2 long-term conditions (LTCs) might better capture populations with complexity but are not standardised.Aim: To examine variation in prevalence using different definitions of multimorbidity.Design and Setting: Cross-sectional study of 1 168 620 people in England.Method: Comparison of multimorbidity (MM) prevalence using four definitions: MM2+ (≥2 LTCs), MM3+ (≥3 LTCs), MM3+ from 3+ (≥3 LTCs from ≥3 International Classification of Diseases, 10th revision chapters), and mental-physical MM (≥2 LTCs where ≥1 mental health LTC and ≥1 physical health LTC are recorded). Logistic regression was used to examine patient characteristics associated with multimorbidity under all four definitions.Results: MM2+ was most common (40.4%) followed by MM3+ (27.5%), MM3+ from 3+ (22.6%), and mental-physical MM (18.9%). MM2+, MM3+, and MM3+ from 3+ were strongly associated with oldest age (adjusted odds ratio [aOR] 58.09, 95% confidence interval [CI] = 56.13 to 60.14; aOR 77.69, 95% CI = 75.33 to 80.12; and aOR 102.06, 95% CI = 98.61 to 105.65; respectively), but mental-physical MM was much less strongly associated (aOR 4.32, 95% CI = 4.21 to 4.43). People in the most deprived decile had equivalent rates of multimorbidity at a younger age than those in the least deprived decile. This was most marked in mental-physical MM at 40-45 years younger, followed by MM2+ at 15-20 years younger, and MM3+ and MM3+ from 3+ at 10-15 years younger. Females had higher prevalence of multimorbidity under all definitions, which was most marked for mental-physical MM.Conclusion: Estimated prevalence of multimorbidity depends on the definition used, and associations with age, sex, and socioeconomic position vary between definitions. Applicable multimorbidity research requires consistency of definitions across studies.

AB - Background: Multimorbidity poses major challenges to healthcare systems worldwide. Definitions with cut-offs in excess of ≥2 long-term conditions (LTCs) might better capture populations with complexity but are not standardised.Aim: To examine variation in prevalence using different definitions of multimorbidity.Design and Setting: Cross-sectional study of 1 168 620 people in England.Method: Comparison of multimorbidity (MM) prevalence using four definitions: MM2+ (≥2 LTCs), MM3+ (≥3 LTCs), MM3+ from 3+ (≥3 LTCs from ≥3 International Classification of Diseases, 10th revision chapters), and mental-physical MM (≥2 LTCs where ≥1 mental health LTC and ≥1 physical health LTC are recorded). Logistic regression was used to examine patient characteristics associated with multimorbidity under all four definitions.Results: MM2+ was most common (40.4%) followed by MM3+ (27.5%), MM3+ from 3+ (22.6%), and mental-physical MM (18.9%). MM2+, MM3+, and MM3+ from 3+ were strongly associated with oldest age (adjusted odds ratio [aOR] 58.09, 95% confidence interval [CI] = 56.13 to 60.14; aOR 77.69, 95% CI = 75.33 to 80.12; and aOR 102.06, 95% CI = 98.61 to 105.65; respectively), but mental-physical MM was much less strongly associated (aOR 4.32, 95% CI = 4.21 to 4.43). People in the most deprived decile had equivalent rates of multimorbidity at a younger age than those in the least deprived decile. This was most marked in mental-physical MM at 40-45 years younger, followed by MM2+ at 15-20 years younger, and MM3+ and MM3+ from 3+ at 10-15 years younger. Females had higher prevalence of multimorbidity under all definitions, which was most marked for mental-physical MM.Conclusion: Estimated prevalence of multimorbidity depends on the definition used, and associations with age, sex, and socioeconomic position vary between definitions. Applicable multimorbidity research requires consistency of definitions across studies.

KW - Female

KW - Humans

KW - Multimorbidity

KW - Cross-Sectional Studies

KW - Prevalence

KW - Socioeconomic Factors

KW - United Kingdom/epidemiology

KW - Primary Health Care

KW - epidemiology

KW - multimorbidity

KW - primary care

KW - socioeconomic disparities

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U2 - 10.3399/BJGP.2022.0405

DO - 10.3399/BJGP.2022.0405

M3 - Article

C2 - 36997222

SN - 0960-1643

VL - 73

SP - e249-e256

JO - British Journal of General Practice

JF - British Journal of General Practice

IS - 729

M1 - 10.3399/BJGP.2022.0405

ER -

Age, sex, and socioeconomic differences in multimorbidity measured in four ways: UK primary care cross-sectional analysis

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

Other files and links

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Multimorbidity and Clinical Guidelines: Using Epidemiology to Quantify the Applicability of Trial Evidence to Inform Guideline Development (Joint with University of Edinburgh and University of Glasgow)

Health Informatics Centre

Cite this

Age, sex, and socioeconomic differences in multimorbidity measured in four ways: UK primary care cross-sectional analysis

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

Other files and links

Fingerprint

Projects

Multimorbidity and Clinical Guidelines: Using Epidemiology to Quantify the Applicability of Trial Evidence to Inform Guideline Development (Joint with University of Edinburgh and University of Glasgow)

Equipment

Health Informatics Centre

Cite this