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Examining variation in the measurement of multimorbidity in research: a systematic review of 566 studies

Iris Szu-Szu Ho, Amaya Azcoaga-Lorenzo, Ashley Akbari Orcid Logo, Corri Black, Jim Davies, Peter Hodgins, Kamlesh Khunti, Umesh Kadam, Ronan Lyons Orcid Logo, Colin McCowan, Stewart Mercer, Krishnarajah Nirantharakumar, Bruce Guthrie

The Lancet Public Health, Volume: 6, Issue: 8, Pages: e587 - e597

Swansea University Authors: Ashley Akbari Orcid Logo, Ronan Lyons Orcid Logo

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DOI (Published version): 10.1016/s2468-2667(21)00107-9

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BackgroundA systematic understanding of how multimorbidity has been constructed and measured is unavailable. This review aimed to examine the definition and measurement of multimorbidity in peer-reviewed studies internationally.MethodsWe systematically reviewed studies on multimorbidity, via a searc...

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Published in: The Lancet Public Health
ISSN: 2468-2667
Published: Elsevier BV 2021
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fullrecord <?xml version="1.0"?><rfc1807><datestamp>2022-07-05T15:41:41.9869822</datestamp><bib-version>v2</bib-version><id>57182</id><entry>2021-06-22</entry><title>Examining variation in the measurement of multimorbidity in research: a systematic review of 566 studies</title><swanseaauthors><author><sid>aa1b025ec0243f708bb5eb0a93d6fb52</sid><ORCID>0000-0003-0814-0801</ORCID><firstname>Ashley</firstname><surname>Akbari</surname><name>Ashley Akbari</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>83efcf2a9dfcf8b55586999d3d152ac6</sid><ORCID>0000-0001-5225-000X</ORCID><firstname>Ronan</firstname><surname>Lyons</surname><name>Ronan Lyons</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2021-06-22</date><deptcode>HDAT</deptcode><abstract>BackgroundA systematic understanding of how multimorbidity has been constructed and measured is unavailable. This review aimed to examine the definition and measurement of multimorbidity in peer-reviewed studies internationally.MethodsWe systematically reviewed studies on multimorbidity, via a search of nine bibliographic databases (Ovid [PsycINFO, Embase, Global Health, and MEDLINE], Web of Science, the Cochrane Library, CINAHL Plus, Scopus, and ProQuest Dissertations &amp; Theses Global), from inception to Jan 21, 2020. Reference lists and tracked citations of retrieved articles were hand-searched. Eligible studies were full-text articles measuring multimorbidity for any purpose in community, primary care, care home, or hospital populations receiving a non-specialist service. Abstracts, qualitative research, and case series were excluded. Two reviewers independently reviewed the retrieved studies with conflicts resolved by discussion or a third reviewer, and a single researcher extracted data from published papers. To assess our objectives of how multimorbidity has been measured and examine variation in the chronic conditions included (in terms of number and type), we used descriptive analysis (frequencies, cross-tabulation, and negative binomial regression) to summarise the characteristics of multimorbidity studies and measures (study setting, source of morbidity data, study population, primary study purpose, and multimorbidity measure type). This systematic review is registered with PROSPERO, CRD420201724090.Findings566 studies were included in our review, of which 206 (36&#xB7;4%) did not report a reference definition for multimorbidity and 73 (12&#xB7;9%) did not report the conditions their measure included. The number of conditions included in measures ranged from two to 285 (median 17 [IQR 11&#x2013;23). 452 (79&#xB7;9%) studies reported types of condition within a single multimorbidity measure; most included at least one cardiovascular condition (441 [97&#xB7;6%] of 452 studies), metabolic and endocrine condition (440 [97&#xB7;3%]), respiratory condition (422 [93&#xB7;4%]), musculoskeletal condition (396 [87&#xB7;6%]), or mental health condition (355 [78&#xB7;5%]) in their measure of multimorbidity. Chronic infections (123 [27&#xB7;2%]), haematological conditions (110 [24&#xB7;3%]), ear, nose, and throat conditions (107 [23&#xB7;7%]), skin conditions (70 [15&#xB7;5%]), oral conditions (19 [4&#xB7;2%]), and congenital conditions (14 [3&#xB7;1%]) were uncommonly included. Only eight individual conditions were included by more than half of studies in the multimorbidity measure used (diabetes, stroke, cancer, chronic obstructive pulmonary disease, hypertension, coronary heart disease, chronic kidney disease, and heart failure), with individual mental health conditions under-represented. Of the 566 studies, 419 were rated to be of moderate risk of bias, 107 of high risk of bias, and 40 of low risk of bias according to the Effective Public Health Practice Project quality assessment tool.InterpretationMeasurement of multimorbidity is poorly reported and highly variable. Consistent reporting of measure definitions should be required by journals, and consensus studies are needed to define core and study-dependent conditions to include in measures of multimorbidity.</abstract><type>Journal Article</type><journal>The Lancet Public Health</journal><volume>6</volume><journalNumber>8</journalNumber><paginationStart>e587</paginationStart><paginationEnd>e597</paginationEnd><publisher>Elsevier BV</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>2468-2667</issnPrint><issnElectronic/><keywords/><publishedDay>1</publishedDay><publishedMonth>8</publishedMonth><publishedYear>2021</publishedYear><publishedDate>2021-08-01</publishedDate><doi>10.1016/s2468-2667(21)00107-9</doi><url/><notes>Supplementary appendix in article.</notes><college>COLLEGE NANME</college><department>Health Data Science</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>HDAT</DepartmentCode><institution>Swansea University</institution><apcterm>Other</apcterm><funders>This work was supported by supported by Health Data Research UK (HDR-UK; grant number CFC0110) 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. We would like to express our appreciation to members of the wider HDR-UK National Multimorbidity Resource for contribution to the conceptualisation of the study.</funders><lastEdited>2022-07-05T15:41:41.9869822</lastEdited><Created>2021-06-22T18:56:45.7352187</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>Iris Szu-Szu</firstname><surname>Ho</surname><order>1</order></author><author><firstname>Amaya</firstname><surname>Azcoaga-Lorenzo</surname><order>2</order></author><author><firstname>Ashley</firstname><surname>Akbari</surname><orcid>0000-0003-0814-0801</orcid><order>3</order></author><author><firstname>Corri</firstname><surname>Black</surname><order>4</order></author><author><firstname>Jim</firstname><surname>Davies</surname><order>5</order></author><author><firstname>Peter</firstname><surname>Hodgins</surname><order>6</order></author><author><firstname>Kamlesh</firstname><surname>Khunti</surname><order>7</order></author><author><firstname>Umesh</firstname><surname>Kadam</surname><order>8</order></author><author><firstname>Ronan</firstname><surname>Lyons</surname><orcid>0000-0001-5225-000X</orcid><order>9</order></author><author><firstname>Colin</firstname><surname>McCowan</surname><order>10</order></author><author><firstname>Stewart</firstname><surname>Mercer</surname><order>11</order></author><author><firstname>Krishnarajah</firstname><surname>Nirantharakumar</surname><order>12</order></author><author><firstname>Bruce</firstname><surname>Guthrie</surname><order>13</order></author></authors><documents><document><filename>57182__20375__03769d531fd84ff5bbc883f58c6ab72c.pdf</filename><originalFilename>57182.pdf</originalFilename><uploaded>2021-07-09T16:58:32.6991808</uploaded><type>Output</type><contentLength>900221</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>&#xA9; 2021 The Author(s). 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spelling 2022-07-05T15:41:41.9869822 v2 57182 2021-06-22 Examining variation in the measurement of multimorbidity in research: a systematic review of 566 studies aa1b025ec0243f708bb5eb0a93d6fb52 0000-0003-0814-0801 Ashley Akbari Ashley Akbari true false 83efcf2a9dfcf8b55586999d3d152ac6 0000-0001-5225-000X Ronan Lyons Ronan Lyons true false 2021-06-22 HDAT BackgroundA systematic understanding of how multimorbidity has been constructed and measured is unavailable. This review aimed to examine the definition and measurement of multimorbidity in peer-reviewed studies internationally.MethodsWe systematically reviewed studies on multimorbidity, via a search of nine bibliographic databases (Ovid [PsycINFO, Embase, Global Health, and MEDLINE], Web of Science, the Cochrane Library, CINAHL Plus, Scopus, and ProQuest Dissertations & Theses Global), from inception to Jan 21, 2020. Reference lists and tracked citations of retrieved articles were hand-searched. Eligible studies were full-text articles measuring multimorbidity for any purpose in community, primary care, care home, or hospital populations receiving a non-specialist service. Abstracts, qualitative research, and case series were excluded. Two reviewers independently reviewed the retrieved studies with conflicts resolved by discussion or a third reviewer, and a single researcher extracted data from published papers. To assess our objectives of how multimorbidity has been measured and examine variation in the chronic conditions included (in terms of number and type), we used descriptive analysis (frequencies, cross-tabulation, and negative binomial regression) to summarise the characteristics of multimorbidity studies and measures (study setting, source of morbidity data, study population, primary study purpose, and multimorbidity measure type). This systematic review is registered with PROSPERO, CRD420201724090.Findings566 studies were included in our review, of which 206 (36·4%) did not report a reference definition for multimorbidity and 73 (12·9%) did not report the conditions their measure included. The number of conditions included in measures ranged from two to 285 (median 17 [IQR 11–23). 452 (79·9%) studies reported types of condition within a single multimorbidity measure; most included at least one cardiovascular condition (441 [97·6%] of 452 studies), metabolic and endocrine condition (440 [97·3%]), respiratory condition (422 [93·4%]), musculoskeletal condition (396 [87·6%]), or mental health condition (355 [78·5%]) in their measure of multimorbidity. Chronic infections (123 [27·2%]), haematological conditions (110 [24·3%]), ear, nose, and throat conditions (107 [23·7%]), skin conditions (70 [15·5%]), oral conditions (19 [4·2%]), and congenital conditions (14 [3·1%]) were uncommonly included. Only eight individual conditions were included by more than half of studies in the multimorbidity measure used (diabetes, stroke, cancer, chronic obstructive pulmonary disease, hypertension, coronary heart disease, chronic kidney disease, and heart failure), with individual mental health conditions under-represented. Of the 566 studies, 419 were rated to be of moderate risk of bias, 107 of high risk of bias, and 40 of low risk of bias according to the Effective Public Health Practice Project quality assessment tool.InterpretationMeasurement of multimorbidity is poorly reported and highly variable. Consistent reporting of measure definitions should be required by journals, and consensus studies are needed to define core and study-dependent conditions to include in measures of multimorbidity. Journal Article The Lancet Public Health 6 8 e587 e597 Elsevier BV 2468-2667 1 8 2021 2021-08-01 10.1016/s2468-2667(21)00107-9 Supplementary appendix in article. COLLEGE NANME Health Data Science COLLEGE CODE HDAT Swansea University Other This work was supported by supported by Health Data Research UK (HDR-UK; grant number CFC0110) 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. We would like to express our appreciation to members of the wider HDR-UK National Multimorbidity Resource for contribution to the conceptualisation of the study. 2022-07-05T15:41:41.9869822 2021-06-22T18:56:45.7352187 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Medicine Iris Szu-Szu Ho 1 Amaya Azcoaga-Lorenzo 2 Ashley Akbari 0000-0003-0814-0801 3 Corri Black 4 Jim Davies 5 Peter Hodgins 6 Kamlesh Khunti 7 Umesh Kadam 8 Ronan Lyons 0000-0001-5225-000X 9 Colin McCowan 10 Stewart Mercer 11 Krishnarajah Nirantharakumar 12 Bruce Guthrie 13 57182__20375__03769d531fd84ff5bbc883f58c6ab72c.pdf 57182.pdf 2021-07-09T16:58:32.6991808 Output 900221 application/pdf Version of Record true © 2021 The Author(s). This is an Open Access article under the CC BY 4.0 license true eng https://creativecommons.org/licenses/by/4.0/
title Examining variation in the measurement of multimorbidity in research: a systematic review of 566 studies
spellingShingle Examining variation in the measurement of multimorbidity in research: a systematic review of 566 studies
Ashley Akbari
Ronan Lyons
title_short Examining variation in the measurement of multimorbidity in research: a systematic review of 566 studies
title_full Examining variation in the measurement of multimorbidity in research: a systematic review of 566 studies
title_fullStr Examining variation in the measurement of multimorbidity in research: a systematic review of 566 studies
title_full_unstemmed Examining variation in the measurement of multimorbidity in research: a systematic review of 566 studies
title_sort Examining variation in the measurement of multimorbidity in research: a systematic review of 566 studies
author_id_str_mv aa1b025ec0243f708bb5eb0a93d6fb52
83efcf2a9dfcf8b55586999d3d152ac6
author_id_fullname_str_mv aa1b025ec0243f708bb5eb0a93d6fb52_***_Ashley Akbari
83efcf2a9dfcf8b55586999d3d152ac6_***_Ronan Lyons
author Ashley Akbari
Ronan Lyons
author2 Iris Szu-Szu Ho
Amaya Azcoaga-Lorenzo
Ashley Akbari
Corri Black
Jim Davies
Peter Hodgins
Kamlesh Khunti
Umesh Kadam
Ronan Lyons
Colin McCowan
Stewart Mercer
Krishnarajah Nirantharakumar
Bruce Guthrie
format Journal article
container_title The Lancet Public Health
container_volume 6
container_issue 8
container_start_page e587
publishDate 2021
institution Swansea University
issn 2468-2667
doi_str_mv 10.1016/s2468-2667(21)00107-9
publisher Elsevier BV
college_str Faculty of Medicine, Health and Life Sciences
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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
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description BackgroundA systematic understanding of how multimorbidity has been constructed and measured is unavailable. This review aimed to examine the definition and measurement of multimorbidity in peer-reviewed studies internationally.MethodsWe systematically reviewed studies on multimorbidity, via a search of nine bibliographic databases (Ovid [PsycINFO, Embase, Global Health, and MEDLINE], Web of Science, the Cochrane Library, CINAHL Plus, Scopus, and ProQuest Dissertations & Theses Global), from inception to Jan 21, 2020. Reference lists and tracked citations of retrieved articles were hand-searched. Eligible studies were full-text articles measuring multimorbidity for any purpose in community, primary care, care home, or hospital populations receiving a non-specialist service. Abstracts, qualitative research, and case series were excluded. Two reviewers independently reviewed the retrieved studies with conflicts resolved by discussion or a third reviewer, and a single researcher extracted data from published papers. To assess our objectives of how multimorbidity has been measured and examine variation in the chronic conditions included (in terms of number and type), we used descriptive analysis (frequencies, cross-tabulation, and negative binomial regression) to summarise the characteristics of multimorbidity studies and measures (study setting, source of morbidity data, study population, primary study purpose, and multimorbidity measure type). This systematic review is registered with PROSPERO, CRD420201724090.Findings566 studies were included in our review, of which 206 (36·4%) did not report a reference definition for multimorbidity and 73 (12·9%) did not report the conditions their measure included. The number of conditions included in measures ranged from two to 285 (median 17 [IQR 11–23). 452 (79·9%) studies reported types of condition within a single multimorbidity measure; most included at least one cardiovascular condition (441 [97·6%] of 452 studies), metabolic and endocrine condition (440 [97·3%]), respiratory condition (422 [93·4%]), musculoskeletal condition (396 [87·6%]), or mental health condition (355 [78·5%]) in their measure of multimorbidity. Chronic infections (123 [27·2%]), haematological conditions (110 [24·3%]), ear, nose, and throat conditions (107 [23·7%]), skin conditions (70 [15·5%]), oral conditions (19 [4·2%]), and congenital conditions (14 [3·1%]) were uncommonly included. Only eight individual conditions were included by more than half of studies in the multimorbidity measure used (diabetes, stroke, cancer, chronic obstructive pulmonary disease, hypertension, coronary heart disease, chronic kidney disease, and heart failure), with individual mental health conditions under-represented. Of the 566 studies, 419 were rated to be of moderate risk of bias, 107 of high risk of bias, and 40 of low risk of bias according to the Effective Public Health Practice Project quality assessment tool.InterpretationMeasurement of multimorbidity is poorly reported and highly variable. Consistent reporting of measure definitions should be required by journals, and consensus studies are needed to define core and study-dependent conditions to include in measures of multimorbidity.
published_date 2021-08-01T04:12:43Z
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