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Age, sex, and socioeconomic differences in multimorbidity measured in four ways: UK primary care cross-sectional analysis
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 m...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Royal College of General Practitioners
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9923763/ https://www.ncbi.nlm.nih.gov/pubmed/36997222 http://dx.doi.org/10.3399/BJGP.2022.0405 |
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author | MacRae, Clare Mercer, Stewart W Henderson, David McMinn, Megan Morales, Daniel R Jefferson, Emily Lyons, Ronan A Lyons, Jane Dibben, Chris McAllister, David A Guthrie, Bruce |
author_facet | MacRae, Clare Mercer, Stewart W Henderson, David McMinn, Megan Morales, Daniel R Jefferson, Emily Lyons, Ronan A Lyons, Jane Dibben, Chris McAllister, David A Guthrie, Bruce |
author_sort | MacRae, Clare |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9923763 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Royal College of General Practitioners |
record_format | MEDLINE/PubMed |
spelling | pubmed-99237632023-02-14 Age, sex, and socioeconomic differences in multimorbidity measured in four ways: UK primary care cross-sectional analysis MacRae, Clare Mercer, Stewart W Henderson, David McMinn, Megan Morales, Daniel R Jefferson, Emily Lyons, Ronan A Lyons, Jane Dibben, Chris McAllister, David A Guthrie, Bruce Br J Gen Pract Research 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. Royal College of General Practitioners 2023-01-10 /pmc/articles/PMC9923763/ /pubmed/36997222 http://dx.doi.org/10.3399/BJGP.2022.0405 Text en © The Authors https://creativecommons.org/licenses/by/4.0/This article is Open Access: CC BY 4.0 licence (http://creativecommons.org/licences/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ). |
spellingShingle | Research MacRae, Clare Mercer, Stewart W Henderson, David McMinn, Megan Morales, Daniel R Jefferson, Emily Lyons, Ronan A Lyons, Jane Dibben, Chris McAllister, David A Guthrie, Bruce Age, sex, and socioeconomic differences in multimorbidity measured in four ways: UK primary care cross-sectional analysis |
title | Age, sex, and socioeconomic differences in multimorbidity measured in four ways: UK primary care cross-sectional analysis |
title_full | Age, sex, and socioeconomic differences in multimorbidity measured in four ways: UK primary care cross-sectional analysis |
title_fullStr | Age, sex, and socioeconomic differences in multimorbidity measured in four ways: UK primary care cross-sectional analysis |
title_full_unstemmed | Age, sex, and socioeconomic differences in multimorbidity measured in four ways: UK primary care cross-sectional analysis |
title_short | Age, sex, and socioeconomic differences in multimorbidity measured in four ways: UK primary care cross-sectional analysis |
title_sort | age, sex, and socioeconomic differences in multimorbidity measured in four ways: uk primary care cross-sectional analysis |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9923763/ https://www.ncbi.nlm.nih.gov/pubmed/36997222 http://dx.doi.org/10.3399/BJGP.2022.0405 |
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