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10-year multimorbidity patterns among people with and without rheumatic and musculoskeletal diseases: an observational cohort study using linked electronic health records from Wales, UK

Farideh Jalali-najafabadi Orcid Logo, Rowena Bailey, Jane Lyons, Ashley Akbari Orcid Logo, Thamer Ba Dhafari, Narges Azadbakht, Jim Rafferty Orcid Logo, Alan Watkins Orcid Logo, Glen Philip Martin Orcid Logo, John Bowes, Ronan Lyons Orcid Logo, Anne Barton Orcid Logo, Niels Peek

BMJ Open, Volume: 14, Issue: 6, Start page: e079169

Swansea University Authors: Rowena Bailey, Jane Lyons, Ashley Akbari Orcid Logo, Jim Rafferty Orcid Logo, Alan Watkins Orcid Logo, Ronan Lyons Orcid Logo

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DOI (Published version): 10.1136/bmjopen-2023-079169

Abstract

Objectives To compare the patterns of multimorbidity between people with and without rheumatic and musculoskeletal diseases (RMDs) and to describe how these patterns change by age and sex over time, between 2010 and 2019.Participants 103 426 people with RMDs and 2.9 million comparators registered in...

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ISSN: 2044-6055 2044-6055
Published: BMJ 2024
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Each patient with an RMD aged 0&#x2013;100 years between January 2010 and December 2019 registered in Clinical Practice Research Welsh practices was matched with up to five comparators without an RMD, based on age, gender and GP code.Primary outcome measures The prevalence of 29 Elixhauser-defined comorbidities in people with RMDs and comparators categorised by age, gender and GP practices. Conditional logistic regression models were fitted to calculate differences (OR, 95%&#x2009;CI) in associations with comorbidities between cohorts.Results The most prevalent comorbidities were cardiovascular risk factors, hypertension and diabetes. Having an RMD diagnosis was associated with a significantly higher odds for many conditions including deficiency anaemia (OR 1.39, 95%&#x2009;CI (1.32 to 1.46)), hypothyroidism (OR 1.34, 95%&#x2009;CI (1.19 to 1.50)), pulmonary circulation disorders (OR 1.39, 95%&#x2009;CI 1.12 to 1.73) diabetes (OR 1.17, 95%&#x2009;CI (1.11 to 1.23)) and fluid and electrolyte disorders (OR 1.27, 95%&#x2009;CI (1.17 to 1.38)). RMDs have a higher proportion of multimorbidity (two or more conditions in addition to the RMD) compared with non-RMD group (81% and 73%, respectively in 2019) and the mean number of comorbidities was higher in women from the age of 25 and 50 in men than in non-RMDs group.Conclusion People with RMDs are approximately 1.5 times as likely to have multimorbidity as the general population and provide a high-risk group for targeted intervention studies. The individuals with RMDs experience a greater load of coexisting health conditions, which tend to manifest at earlier ages. This phenomenon is particularly pronounced among women. Additionally, there is an under-reporting of comorbidities in individuals with RMDs.</abstract><type>Journal Article</type><journal>BMJ Open</journal><volume>14</volume><journalNumber>6</journalNumber><paginationStart>e079169</paginationStart><paginationEnd/><publisher>BMJ</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>2044-6055</issnPrint><issnElectronic>2044-6055</issnElectronic><keywords/><publishedDay>19</publishedDay><publishedMonth>6</publishedMonth><publishedYear>2024</publishedYear><publishedDate>2024-06-19</publishedDate><doi>10.1136/bmjopen-2023-079169</doi><url/><notes/><college>COLLEGE NANME</college><department>Medical School</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>MEDS</DepartmentCode><institution>Swansea University</institution><apcterm>Another institution paid the OA fee</apcterm><funders>The datasets used in this study were supported by grants cofunded by Medical Research Council (MRC) and National Institute for Health Research (NIHR) (grant number: MR/S027750/1); and supported by Health Data Research UK (grant number: HDR- 9006), which receives its funding from the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation and the Wellcome Trust. This work was supported by the ADR Wales programme of work. The ADR Wales programme of work is aligned to the priority themes as identified in the Welsh Government&#x2019;s national strategy: Prosperity for All. ADR Wales brings together data science experts at Swansea University Medical School, staff from the Wales Institute of Social and Economic Research, Data and Methods (WISERD) at Cardiff University and specialist teams within the Welsh Government to develop new evidence which supports Prosperity for All by using the SAIL Databank at Swansea University, to link and analyse anonymised data. ADR Wales is part of the Economic and Social Research Council (part of UK Research and Innovation) funded ADR UK (grant ES/S007393/1). This research was partially funded by the NIHR&#x2019;s Manchester Biomedical Research Centre. The views expressed are those of the author(s) and not necessarily those of the NHS, the National Institute for Health research or the Department of Health and Social Care. The work is supported by the Centre for Genetics and Genomics Versus Arthritis (UK grant number 21754). AB is an NIHR Senior Investigator. FJ- n&#x2019;s research is supported by an MRC/University of Manchester Skills Development Fellowship (grant number MR/R016615).</funders><projectreference/><lastEdited>2024-07-04T12:19:01.5614650</lastEdited><Created>2024-06-23T11:38:39.6138898</Created><path><level id="1">Faculty of Medicine, Health and Life Sciences</level><level id="2">Swansea University Medical School - Medicine</level></path><authors><author><firstname>Farideh</firstname><surname>Jalali-najafabadi</surname><orcid>0000-0003-4895-4578</orcid><order>1</order></author><author><firstname>Rowena</firstname><surname>Bailey</surname><order>2</order></author><author><firstname>Jane</firstname><surname>Lyons</surname><orcid/><order>3</order></author><author><firstname>Ashley</firstname><surname>Akbari</surname><orcid>0000-0003-0814-0801</orcid><order>4</order></author><author><firstname>Thamer Ba</firstname><surname>Dhafari</surname><order>5</order></author><author><firstname>Narges</firstname><surname>Azadbakht</surname><order>6</order></author><author><firstname>Jim</firstname><surname>Rafferty</surname><orcid>0000-0002-1667-7265</orcid><order>7</order></author><author><firstname>Alan</firstname><surname>Watkins</surname><orcid>0000-0003-3804-1943</orcid><order>8</order></author><author><firstname>Glen Philip</firstname><surname>Martin</surname><orcid>0000-0002-3410-9472</orcid><order>9</order></author><author><firstname>John</firstname><surname>Bowes</surname><order>10</order></author><author><firstname>Ronan</firstname><surname>Lyons</surname><orcid>0000-0001-5225-000X</orcid><order>11</order></author><author><firstname>Anne</firstname><surname>Barton</surname><orcid>0000-0003-3316-2527</orcid><order>12</order></author><author><firstname>Niels</firstname><surname>Peek</surname><order>13</order></author></authors><documents><document><filename>66849__30820__68e06cb4cccb4a5f99c4d64611ea41d1.pdf</filename><originalFilename>66849.VoR.pdf</originalFilename><uploaded>2024-07-04T12:17:05.8693831</uploaded><type>Output</type><contentLength>4280710</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license.</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language><licence>https://creativecommons.org/licenses/by/4.0/</licence></document></documents><OutputDurs/></rfc1807>
spelling 2024-07-04T12:19:01.5614650 v2 66849 2024-06-23 10-year multimorbidity patterns among people with and without rheumatic and musculoskeletal diseases: an observational cohort study using linked electronic health records from Wales, UK 455e2c1e6193448f6269b9e72acaf865 Rowena Bailey Rowena Bailey true false 1b74fa5125a88451c52c45bcf20e0b47 Jane Lyons Jane Lyons true false aa1b025ec0243f708bb5eb0a93d6fb52 0000-0003-0814-0801 Ashley Akbari Ashley Akbari true false 52effe759a718bd36eb12cdd10fe1a09 0000-0002-1667-7265 Jim Rafferty Jim Rafferty true false 81fc05c9333d9df41b041157437bcc2f 0000-0003-3804-1943 Alan Watkins Alan Watkins true false 83efcf2a9dfcf8b55586999d3d152ac6 0000-0001-5225-000X Ronan Lyons Ronan Lyons true false 2024-06-23 MEDS Objectives To compare the patterns of multimorbidity between people with and without rheumatic and musculoskeletal diseases (RMDs) and to describe how these patterns change by age and sex over time, between 2010 and 2019.Participants 103 426 people with RMDs and 2.9 million comparators registered in 395 Wales general practices (GPs). Each patient with an RMD aged 0–100 years between January 2010 and December 2019 registered in Clinical Practice Research Welsh practices was matched with up to five comparators without an RMD, based on age, gender and GP code.Primary outcome measures The prevalence of 29 Elixhauser-defined comorbidities in people with RMDs and comparators categorised by age, gender and GP practices. Conditional logistic regression models were fitted to calculate differences (OR, 95% CI) in associations with comorbidities between cohorts.Results The most prevalent comorbidities were cardiovascular risk factors, hypertension and diabetes. Having an RMD diagnosis was associated with a significantly higher odds for many conditions including deficiency anaemia (OR 1.39, 95% CI (1.32 to 1.46)), hypothyroidism (OR 1.34, 95% CI (1.19 to 1.50)), pulmonary circulation disorders (OR 1.39, 95% CI 1.12 to 1.73) diabetes (OR 1.17, 95% CI (1.11 to 1.23)) and fluid and electrolyte disorders (OR 1.27, 95% CI (1.17 to 1.38)). RMDs have a higher proportion of multimorbidity (two or more conditions in addition to the RMD) compared with non-RMD group (81% and 73%, respectively in 2019) and the mean number of comorbidities was higher in women from the age of 25 and 50 in men than in non-RMDs group.Conclusion People with RMDs are approximately 1.5 times as likely to have multimorbidity as the general population and provide a high-risk group for targeted intervention studies. The individuals with RMDs experience a greater load of coexisting health conditions, which tend to manifest at earlier ages. This phenomenon is particularly pronounced among women. Additionally, there is an under-reporting of comorbidities in individuals with RMDs. Journal Article BMJ Open 14 6 e079169 BMJ 2044-6055 2044-6055 19 6 2024 2024-06-19 10.1136/bmjopen-2023-079169 COLLEGE NANME Medical School COLLEGE CODE MEDS Swansea University Another institution paid the OA fee The datasets used in this study were supported by grants cofunded by Medical Research Council (MRC) and National Institute for Health Research (NIHR) (grant number: MR/S027750/1); and supported by Health Data Research UK (grant number: HDR- 9006), which receives its funding from the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation and the Wellcome Trust. This work was supported by the ADR Wales programme of work. The ADR Wales programme of work is aligned to the priority themes as identified in the Welsh Government’s national strategy: Prosperity for All. ADR Wales brings together data science experts at Swansea University Medical School, staff from the Wales Institute of Social and Economic Research, Data and Methods (WISERD) at Cardiff University and specialist teams within the Welsh Government to develop new evidence which supports Prosperity for All by using the SAIL Databank at Swansea University, to link and analyse anonymised data. ADR Wales is part of the Economic and Social Research Council (part of UK Research and Innovation) funded ADR UK (grant ES/S007393/1). This research was partially funded by the NIHR’s Manchester Biomedical Research Centre. The views expressed are those of the author(s) and not necessarily those of the NHS, the National Institute for Health research or the Department of Health and Social Care. The work is supported by the Centre for Genetics and Genomics Versus Arthritis (UK grant number 21754). AB is an NIHR Senior Investigator. FJ- n’s research is supported by an MRC/University of Manchester Skills Development Fellowship (grant number MR/R016615). 2024-07-04T12:19:01.5614650 2024-06-23T11:38:39.6138898 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Medicine Farideh Jalali-najafabadi 0000-0003-4895-4578 1 Rowena Bailey 2 Jane Lyons 3 Ashley Akbari 0000-0003-0814-0801 4 Thamer Ba Dhafari 5 Narges Azadbakht 6 Jim Rafferty 0000-0002-1667-7265 7 Alan Watkins 0000-0003-3804-1943 8 Glen Philip Martin 0000-0002-3410-9472 9 John Bowes 10 Ronan Lyons 0000-0001-5225-000X 11 Anne Barton 0000-0003-3316-2527 12 Niels Peek 13 66849__30820__68e06cb4cccb4a5f99c4d64611ea41d1.pdf 66849.VoR.pdf 2024-07-04T12:17:05.8693831 Output 4280710 application/pdf Version of Record true This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license. true eng https://creativecommons.org/licenses/by/4.0/
title 10-year multimorbidity patterns among people with and without rheumatic and musculoskeletal diseases: an observational cohort study using linked electronic health records from Wales, UK
spellingShingle 10-year multimorbidity patterns among people with and without rheumatic and musculoskeletal diseases: an observational cohort study using linked electronic health records from Wales, UK
Rowena Bailey
Jane Lyons
Ashley Akbari
Jim Rafferty
Alan Watkins
Ronan Lyons
title_short 10-year multimorbidity patterns among people with and without rheumatic and musculoskeletal diseases: an observational cohort study using linked electronic health records from Wales, UK
title_full 10-year multimorbidity patterns among people with and without rheumatic and musculoskeletal diseases: an observational cohort study using linked electronic health records from Wales, UK
title_fullStr 10-year multimorbidity patterns among people with and without rheumatic and musculoskeletal diseases: an observational cohort study using linked electronic health records from Wales, UK
title_full_unstemmed 10-year multimorbidity patterns among people with and without rheumatic and musculoskeletal diseases: an observational cohort study using linked electronic health records from Wales, UK
title_sort 10-year multimorbidity patterns among people with and without rheumatic and musculoskeletal diseases: an observational cohort study using linked electronic health records from Wales, UK
author_id_str_mv 455e2c1e6193448f6269b9e72acaf865
1b74fa5125a88451c52c45bcf20e0b47
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52effe759a718bd36eb12cdd10fe1a09
81fc05c9333d9df41b041157437bcc2f
83efcf2a9dfcf8b55586999d3d152ac6
author_id_fullname_str_mv 455e2c1e6193448f6269b9e72acaf865_***_Rowena Bailey
1b74fa5125a88451c52c45bcf20e0b47_***_Jane Lyons
aa1b025ec0243f708bb5eb0a93d6fb52_***_Ashley Akbari
52effe759a718bd36eb12cdd10fe1a09_***_Jim Rafferty
81fc05c9333d9df41b041157437bcc2f_***_Alan Watkins
83efcf2a9dfcf8b55586999d3d152ac6_***_Ronan Lyons
author Rowena Bailey
Jane Lyons
Ashley Akbari
Jim Rafferty
Alan Watkins
Ronan Lyons
author2 Farideh Jalali-najafabadi
Rowena Bailey
Jane Lyons
Ashley Akbari
Thamer Ba Dhafari
Narges Azadbakht
Jim Rafferty
Alan Watkins
Glen Philip Martin
John Bowes
Ronan Lyons
Anne Barton
Niels Peek
format Journal article
container_title BMJ Open
container_volume 14
container_issue 6
container_start_page e079169
publishDate 2024
institution Swansea University
issn 2044-6055
2044-6055
doi_str_mv 10.1136/bmjopen-2023-079169
publisher BMJ
college_str Faculty of Medicine, Health and Life Sciences
hierarchytype
hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str Swansea University Medical School - Medicine{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Medicine
document_store_str 1
active_str 0
description Objectives To compare the patterns of multimorbidity between people with and without rheumatic and musculoskeletal diseases (RMDs) and to describe how these patterns change by age and sex over time, between 2010 and 2019.Participants 103 426 people with RMDs and 2.9 million comparators registered in 395 Wales general practices (GPs). Each patient with an RMD aged 0–100 years between January 2010 and December 2019 registered in Clinical Practice Research Welsh practices was matched with up to five comparators without an RMD, based on age, gender and GP code.Primary outcome measures The prevalence of 29 Elixhauser-defined comorbidities in people with RMDs and comparators categorised by age, gender and GP practices. Conditional logistic regression models were fitted to calculate differences (OR, 95% CI) in associations with comorbidities between cohorts.Results The most prevalent comorbidities were cardiovascular risk factors, hypertension and diabetes. Having an RMD diagnosis was associated with a significantly higher odds for many conditions including deficiency anaemia (OR 1.39, 95% CI (1.32 to 1.46)), hypothyroidism (OR 1.34, 95% CI (1.19 to 1.50)), pulmonary circulation disorders (OR 1.39, 95% CI 1.12 to 1.73) diabetes (OR 1.17, 95% CI (1.11 to 1.23)) and fluid and electrolyte disorders (OR 1.27, 95% CI (1.17 to 1.38)). RMDs have a higher proportion of multimorbidity (two or more conditions in addition to the RMD) compared with non-RMD group (81% and 73%, respectively in 2019) and the mean number of comorbidities was higher in women from the age of 25 and 50 in men than in non-RMDs group.Conclusion People with RMDs are approximately 1.5 times as likely to have multimorbidity as the general population and provide a high-risk group for targeted intervention studies. The individuals with RMDs experience a greater load of coexisting health conditions, which tend to manifest at earlier ages. This phenomenon is particularly pronounced among women. Additionally, there is an under-reporting of comorbidities in individuals with RMDs.
published_date 2024-06-19T14:34:32Z
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score 11.04748

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