Literature DB >> 29298301

Mapping of global scientific research in comorbidity and multimorbidity: A cross-sectional analysis.

Ferrán Catalá-López1,2,3, Adolfo Alonso-Arroyo4,5, Matthew J Page6, Brian Hutton3,7, Rafael Tabarés-Seisdedos1, Rafael Aleixandre-Benavent5,8.   

Abstract

BACKGROUND: The management of comorbidity and multimorbidity poses major challenges to health services around the world. Analysis of scientific research in comorbidity and multimorbidity is limited in the biomedical literature. This study aimed to map global scientific research in comorbidity and multimorbidity to understand the maturity and growth of the area during the past decades. METHODS AND
FINDINGS: This was a cross-sectional analysis of the Web of Science. Searches were run from inception until November 8, 2016. We included research articles or reviews with no restrictions by language or publication date. Data abstraction was done by one researcher. A process of standardization was conducted by two researchers to unify different terms and grammatical variants and to remove typographical, transcription, and/or indexing errors. All potential discrepancies were resolved via discussion. Descriptive analyses were conducted (including the number of papers, citations, signatures, most prolific authors, countries, journals and keywords). Network analyses of collaborations between countries and co-words were presented. During the period 1970-2016, 85994 papers (64.0% in 2010-2016) were published in 3500 journals. There was wide diversity in the specialty of the journals, with psychiatry (16558 papers; 19.3%), surgery (9570 papers; 11.1%), clinical neurology (9275 papers; 10.8%), and general and internal medicine (7622 papers; 8.9%) the most common. PLOS One (1223 papers; 1.4%), the Journal of Affective Disorders (1154 papers; 1.3%), the Journal of Clinical Psychiatry (727 papers; 0.8%), the Journal of the American Geriatrics Society (634 papers; 0.7%) and Obesity Surgery (588 papers; 0.7%) published the largest number of papers. 168 countries were involved in the production of papers. The global productivity ranking was headed by the United States (37624 papers), followed by the United Kingdom (7355 papers), Germany (6899 papers) and Canada (5706 papers). Twenty authors who published 100 or more papers were identified; the most prolific authors were affiliated with Harvard Medical School, State University of New York Upstate Medical University, National Taiwan Normal University and China Medical University. The 50 most cited papers ("citation classics" with at least 1000 citations) were published in 20 journals, led by JAMA Psychiatry (11 papers) and JAMA (10 papers). The most cited papers provided contributions focusing on methodological aspects (e.g. Charlson Comorbidity Index, Elixhauser Comorbidity Index, APACHE prognostic system), but also important studies on chronic diseases (e.g. epidemiology of mental disorders and its correlates by the U.S. National Comorbidity Survey, Fried's frailty phenotype or the management of obesity).
CONCLUSIONS: Ours is the first analysis of global scientific research in comorbidity and multimorbidity. Scientific production in the field is increasing worldwide with research leadership of Western countries, most notably, the United States.

Entities:  

Mesh:

Year:  2018        PMID: 29298301      PMCID: PMC5751979          DOI: 10.1371/journal.pone.0189091

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

Over the last three to four decades, substantial progress has been made toward reducing mortality and extending life expectancy worldwide [1,2]. Although health seems to have improved globally, more people than ever are spending more time with functional health loss and disability [3,4]. In many countries and regions, the management of multiple chronic diseases in a given patient at the same time (the so-called, “comorbidity” or “multimorbidity”) poses major challenges to health services [5-9]. People with two or more chronic (physical or mental) diseases are more likely to have poor health outcomes, more complex clinical management and increased healthcare costs [8,9]. Analysis of scientific research in comorbidity and multimorbidity is limited in the biomedical literature [10-16]. For example, Fortin et al. [12] previously investigated the characteristics of the publications on multimorbidity (or comorbidity) and compared the number of publications on it with the number of publications on three common chronic conditions (asthma, hypertension, and diabetes). A restricted search of MEDLINE in 2002 identified 353 papers on multimorbidity and comorbidity for the period 1990–2002. The number and diversity of articles were both insufficient to provide relevant data to inform evidence-based care of people affected by multiple chronic conditions [12]. The scientific landscape has changed considerably in the subsequent years, including the launch of important initiatives for the clinical management of multiple chronic diseases [17-20], but also the proliferation of open-access journals to disseminate research findings [5,7,21-25]. Considering research is needed to increase knowledge in a changing research area, this study aimed to map global scientific research in comorbidity and multimorbidity to understand maturity and growth during the past decades.

Methods

Search strategy

We conducted a cross-sectional analysis of the Web of Science, Science Citation Index-Expanded (SCI-E) database, from inception to November 8th 2016. The Web of Science has been considered the world’s leading taxonomic reference for citation analysis and prior to 2004, the only data source on citations available [26]. The search strategy for this study was designed by two senior health information specialists (AA-A, RA-B) and a clinical epidemiologist (FC-L), based on a previously published strategy [13]. The search strategy was constructed by using a combination of the following terms related to comorbidity and multimorbidity (see Box 1 for terminology): comorbidit* OR co-morbidit* OR multimorbidit* OR multi-morbidit* OR multidisease* OR multi-disease* OR multipatholog* OR multi-patholog* OR polimorbidit* OR poli-morbidit* OR polipatholog* OR poli-patholog* OR pluripatholog* OR pluri-patholog* (full strategy is available in S1 Table). We included two types of papers: research articles or reviews on comorbidity or multimorbidity of any type (physical or mental). Meeting abstracts, proceedings paper (journals, book-based), editorials, book chapters, corrections, retracted publications and other items (e.g. notes, news, etc…) were excluded. No restrictions in languages or publication date were applied to the database search.

Box 1. Terminology

The terms of “comorbidity” and “multimorbidity” are often used interchangeably. Many possible definitions and interpretations of the concepts of “comorbidity” and “multimorbidity” have been reported in the biomedical literature [9-11]. For example, Valderas and colleagues [9] reviewed the definitions of “comorbidity (and multimorbidity)” and their relationship to related constructs. A brief overview of common terms follows. Comorbidity. A widely accepted definition of “comorbidity” is the occurrence or the existence of any distinct additional medical condition to an index disease [31]. In general, the role of coexisting conditions is of less importance and one does not assume an interaction between the multiple conditions. The nature of the conditions that co-occur have variously included (physical or mental) diseases, disorders, conditions, illnesses, or health problems. Comorbidity was first included as a MeSH term in 1989 [9,10]. Multimorbidity. Most authors define “multimorbidity” as the co-occurrence of two or more medical conditions in an individual without any reference to an index disease [6,9-11]. Therefore, in multimorbidity, no index disease is defined and all conditions (or “morbidities”) are regarded of equal importance. Multimorbidity constitutes a more generic, patient-centered concept, whereas comorbidity is an index disease-based concept [11]. At present, no MeSH term exists for multimorbidity. Some authors have introduced other terms to describe the same or closely related concepts. Examples of alternative terms are: “multipathology”, “polymorbidity”, “polipathology”, and “pluripathology” [10,13,51]. Case example. Consider a 58-year-old woman with coronary artery disease, hypertension, and major depression. Her mental health professional, focusing on the major depression, would consider her coronary artery disease and hypertension as comorbidities. Her primary care physician might describe her as having multimorbidity, giving equal attention to her coronary artery disease, hypertension and major depression.

Data extraction

For each included paper, data on the year of publication, the journal title, subject category, keywords, and the authors’ names, institutional affiliation(s), and country was downloaded online through the SCI-E from the Web of Science by one researcher (AA-A) in November 2016. A second researcher (FC-L) verified the data to minimize potential information errors. The SCI-E platform is a database that contains all the above information, including the full addresses of all authors of every paper. We also used the SCI-E to determine the extent to which each paper had been cited in the scientific peer-review literature using the “times cited” number (that is, the number of times a publication has been cited by other publications). A process of standardization was conducted by two researchers to bring together the different names of an author or country, and keywords. Specifically, one researcher (AA-A) checked the names by which an individual author appeared in two or more different forms (for example, “Ronald C. Kessler” or “Ronald Kessler” or “Ron Kessler”), using coincidence in that author’s place(s) of work as the basic criterion for normalization (for example, Harvard University, United States), and a second researcher (FC-L) verified data. We used both ‘‘author keywords” and ‘‘keyword plus,” which are automatically assigned by the Web of Science from the titles of the references of the articles because this approach has proven to be highly effective in representing the conceptual content of articles. To ensure consistency in the data, one researcher (RA-B) corrected keywords unifying grammatical variants and using only one keyword developed names of the same concept (for example, “diabetes mellitus” or “diabetes” or “adult diabetes” or “diabetes type 2” or “type 2 juvenile diabetes”). In addition, the same researcher (RA-B) removed typographical, transcription and/or indexing errors, and a second researcher (FC-L) verified data. All potential discrepancies were resolved via discussion. All these data were entered into a Microsoft Access® (Microsoft, Seattle, WA, United States) database.

Data analysis

In this paper, we analyzed data including the number of papers, citations, signatures of authors, collaboration index (which is the mean number of author’s signatures per paper), countries, journals and keywords. Data were summarized as frequencies and percentages for categorical items. We have presented in tables the most prolific authors and countries (> 100 papers), and the most cited papers (>1000 citations). We have presented network graphs (or diagrams) to represent data visualization of the structure of the most intense scientific collaboration between countries applying a threshold of 50 papers in collaboration. In order to depict the frequency of the most frequently used keywords, a word cloud was created using Wordle (http://www.wordle.net/), which is free-software that generates “word clouds” from text that the user provides and places more emphasis on words that appear with greater frequency in the source text. We identified the most frequently used keywords per journal subject category. We also presented the “co-words network” of keywords representing the co-occurrence phenomenon of highly frequent words in the papers. The co-words network reflects the relation among multiple terms, and so is effective in mapping the associations between keywords in textual data [27]. We used Pajek [28], a software package for large network analysis that is free for non-commercial use, to construct network graphs. PRISMA checklist [29,30] (http://www.prisma-statement.org/) guided the reporting of the present analysis (and is available in S1 Checklist).

Results

A total of 85994 papers (76350 articles and 9644 reviews) were identified and included in the analyses (Fig 1). Table 1 details the general characteristics of the papers.
Fig 1

Selection of papers.

Flowchart.

Table 1

General characteristics of the sample of study.

CharacteristicCategoryNumberPercent
Total number of papers85994100.0
Year of publication
1970–197930.0
1980–1989520.1
1990–199941794.9
2000–20092671931.0
2010–2016a5504164.0
Number of authors
147305.5
2–31895322.0
4–63506240.8
7–102058323.9
>1066667.8
Number of subject categoryb
15035458.6
25274830.7
379039.2
412001.4
51630.2
Main subject categoryb
Psychiatry1655819.3
Surgery957011.1
Clinical Neurology927510.8
Medicine, General & Internal76228.9
Cardiac & Cardiovascular Systems50985.9
Country of first author (top-10)
United States3317138.6
Germany54086.3
United Kingdom49455.8
Canada42214.9
Italy41074.8
Spain30703.6
Australia29983.5
The Netherlands27663.2
France27373.2
Taiwan (Republic of China)20342.4

aNovember 8th, 2016.

bSubject category according to Journal Citation Report.

Selection of papers.

Flowchart. aNovember 8th, 2016. bSubject category according to Journal Citation Report.

Publication trend

The number of papers increased exponentially over the study period (Fig 2). Approximately two-thirds of the papers have been published since 2010. The first paper was published in 1970 by Prof. Alvan R. Feinstein [31] providing the seminal definition of comorbidity referring to “any distinct clinical entity that has co-existed or that may occur during the clinical course of a patient who has the index disease under study.”
Fig 2

Number of papers by year of publication.

Note: Data for 2016 up to November 8th.

Number of papers by year of publication.

Note: Data for 2016 up to November 8th.

Journals and subject categories

3500 journals published 85994 papers. 596 (17.0%) journals published only one paper, 344 (9.8%) journals published two, 220 (6.3%) journals published three, and 2340 (66.8%) published four or more papers. PLOS One (n = 1223; 1.4%) and the Journal of Affective Disorders (n = 1154; 1.3%) published the largest number of papers, followed by the Journal of Clinical Psychiatry (n = 727; 0.8%), the Journal of the American Geriatrics Society (n = 634; 0.7%) and Obesity Surgery (n = 588; 0.7%). Most papers were classified in one (n = 50354; 58.6%) or two (n = 52748; 30.7%) journal’s subject categories. There was wide diversity in journal’s subject categories, with psychiatry, surgery, clinical neurology, and general and internal medicine the most common (Table 1).

Authors and countries

Most papers were written by 4 or more authors (72.5%; n = 62311) and only 5.5% (n = 4730) of papers were written by one author. The first authors of the papers were based most commonly in North America and Europe; first authors from the United States were responsible for 38.6% (n = 33171) of the papers (Table 1). We identified 20 authors who published 100 or more papers (Table 2). The most prolific authors were Ronald C Kessler with 331 (from Harvard Medical School, United States), Joseph Biederman with 248 (from Harvard Medical School, United States), Stephen V Faraone with 227 (from State University of New York Upstate Medical University, United States), Chia-Hung Kao with 223 (from National Taiwan Normal University, Taiwan) and Cheng-Li Lin with 193 papers (from China Medical University, China).
Table 2

Most productive authors.

AuthorAffiliation and countryTotal papersTotal citationsCitations per paperPapers in collaborationTotal signaturesCollaboration index (signatures per paper)
Ronald C KesslerHarvard Medical School, United States33181160245.2324338910.2
Joseph BiedermanHarvard Medical School and Massachusetts General Hospital, United States2481996480.524416856.8
Stephen V FaraoneState University of New York Upstate Medical University, United States2271692774.622617777.8
Chia-Hung KaoNational Taiwan Normal University, Taiwan (Republic of China)2236362.922313095.9
Cheng-Li LinChina Medical University Hospital, China Medical University, China1935502.819311325.9
Murray B SteinUniversity of California, United States1661059063.8161175510.6
Hans-Ulrich WittchenDresden University of Technology, Germany16224910153.815812147.5
Henrik Toft SørensenAarhus University Hospital, Denmark162329920.416210226.3
Kenneth S KendlerVirginia Commonwealth University, United States16019554122.2156174810.9
Dan J SteinUniversity of Cape Town, South Africa149577338.7147193713.0
Kathleen Ries MerikangasNational Institute of Mental Health (NIMH), United States13715240111.21328646.3
Fung-Chang SungChina Medical University, China1259777.81258887.1
Jitender SareenUniversity of Manitoba, Canada116414635.71156175.3
Ron de GraafNetherlands Institute of Mental Health and Addiction (NIMHA), Netherlands114805170.6114133111.7
Hagop S AkiskalUniversity of California, United States112702962.81087486.7
Jordi AlonsoIMIM Hospital del Mar Medical Research Institute, Spain111852776.8111171715.5
Tzeng-Ji ChenNational Yang-Ming University, Taipei Veterans General Hospital, Taiwan (Republic of China)1099048.310910519.6
Wayne J KatonUniversity of Washington, United States107940987.91037386.9
Josep M HaroParc Sanitari Sant Joan de Déu, Spain105841080.1105271225.8
Luigi FerrucciNational Institute on Aging (NIA), United States104430741.41049278.9
Overall, 168 countries worldwide were involved in the sample of papers. The productivity ranking for countries with respect to the number of papers (Table 3) was headed by the United States (37624 papers), followed by the United Kingdom (7355 papers), Germany (6899 papers) and Canada (5706 papers). Fig 3 shows a visual representation of the most intense collaborative network between 42 countries (with at least 50 papers in co-authorship), in which we can see the relationships of some countries with respect to others and the position that each occupies in the network.
Table 3

Productivity and patterns of collaboration by 50 top countries.

CountryTotal papersPapers per million inhabitantsTotal collaborationsTotal citationsCitations per paperPapers in collaboration (distinct country)Distinct countries of collaborationMain collaborator (and number of collaborations)
United States37624117.114296121107232.27905146Canada (1574)
United Kingdom7355112.9930118640225.33669130United States (1336)
Germany689984.7739516282923.62504126United States (999)
Canada5706159.2489316578429.12442118United States (1574)
Italy537388.4709412072822.52093122United States (1045)
Australia3979167.338098813222.21575117United States (639)
Spain388983.853917548719.41289122United States (569)
Netherlands3885229.4622611075628.51786116United States (728)
France374256.057478384622.41506125United States (634)
Taiwan/Republic of China217392.47562352610.834995United States (218)
Sweden2066210.834865382626.11167114United States (428)
Brazil19789.523562977315.1658119United States (374)
Switzerland1852223.536595631530.41190118Germany (454)
China17351.324582582814.9693111United States (422)
Denmark1689297.624984141624.5798110United States (378)
Japan157612.421562988819.0443109United States (313)
Belgium1264112.040363618428.685496Netherlands (405)
Turkey120315.3983106268.8171109United States (88)
South Korea114222.69251469812.9288103United States (220)
Israel1087129.719522602924.0445108United States (310)
Norway1024197.117962418523.6520107United States (185)
Austria1000116.125772336123.4597108Germany (319)
Finland923168.416182474026.8403110United Kingdom (158)
Greece73868.216311600821.7375112United States (137)
Poland66417.517461080616.327683United Kingdom (133)
India6520.5954927814.2207102United States (112)
New Zealand599130.313622344839.233995United States (168)
Ireland513110.510941268024.727694United Kingdom (144)
Singapore48287.1794934419.4219108United States (111)
Mexico4623.618361704836.9257112United States (207)
South Africa4378.014621369231.3316113United States (175)
Portugal41239.81406819219.9185108United Kingdom (92)
Hungary29530.0996715924.320081United States (93)
Czech Republic27225.8838565320.814276Italy (53)
Iran2723.4345321011.877105United States (31)
Russia2421.7809602324.9102111United Kingdom (43)
Serbia23032.448219048.384106Italy (30)
Argentina2245.2834836537.3115113United States (78)
Chile22412.541621209.510584United States (56)
Saudi Arabia2207.0448425019.314595United States (63)
Romania20910.51273522825.0119107Italy (68)
Croatia20749.034920309.86270Italy (22)
Thailand1842.739517679.611982United States (56)
Colombia1733.61316749743.3120109United States (95)
Egypt1651.8391179210.987103United States (27)
Nigeria1650.9767558333.87092United States (53)
Malaysia1464.822913229.16883Australia (23)
Slovenia13866.9630277020.18278Germany (44)
Lebanon12120.7992677056.010298United States (81)
Pakistan1180.6431485441.145108United States (23)

top-50 countries with at least 100 papers. Country inhabitants (year 2015) obtained from the World Bank (http://data.worldbank.org/).

Fig 3

Global collaborative network between countries.

Note: Most productive cluster of countries applying a threshold of 50 or more papers signed in co-authorship. Node sizes are proportional to the number of papers and line thicknesses are proportional to the number of collaborations. Node colors: America = red; Asia = yellow; Africa = green; Europe = blue; Oceania = purple.

Global collaborative network between countries.

Note: Most productive cluster of countries applying a threshold of 50 or more papers signed in co-authorship. Node sizes are proportional to the number of papers and line thicknesses are proportional to the number of collaborations. Node colors: America = red; Asia = yellow; Africa = green; Europe = blue; Oceania = purple. top-50 countries with at least 100 papers. Country inhabitants (year 2015) obtained from the World Bank (http://data.worldbank.org/).

Keywords

The most commonly used article/review keywords were “comorbidity” (9223 papers; 10.7%), followed by “depression” (n = 5853; 6.8%), “elderly” (n = 3077; 3.6%) and “mortality” (n = 2806; 3.3%) (Fig 4). The most frequently used keywords in the most common journal subject categories are shown in Table 4. Co-words analysis shows some associations of keywords forming triads (groupings of three terms), such as “comorbidity” and “depression” with either “anxiety/anxiety disorders”, “posttraumatic stress disorder”, “bipolar disorder”, “alcohol dependence”, “drug dependence” or “quality of life”; the associations of “diabetes mellitus” with “cardiovascular diseases”, “obesity”, or “hypertension”; and the association of “depression” with “bipolar disorder” and “suicide” (Fig 5).
Fig 4

Word cloud for the frequency of terms.

Note: Most frequently used keywords (at least 500 times).

Table 4

Most prolific journals and most commonly used keywords per journal subject category.

Journal subject categoryTotal papersJournal nameTotal papersTotal papers
Psychiatry16558Journal of Affective Disorders1154Depression3290
Journal of Clinical Psychiatry727Bipolar disorder1295
Psychiatry Research528Attention deficit hyperactivity disorder1083
Surgery9570Obesity Surgery588Bariatric surgery570
Journal of Vascular Surgery489Morbid obesity414
Annals of Thoracic Surgery338Obesity356
Clinical Neurology9275Journal of Affective Disorders1154Depression1568
Epilepsy & Behavior370Bipolar disorder727
Journal of Nervous and Mental Disease365Epilepsy670
Medicine, General & Internal7622Medicine302Primary care341
Journal of General Internal Medicine282Depression326
BMJ Open272Diabetes mellitus318
Cardiac & Cardiovascular Systems5098Annals of Thoracic Surgery338Heart failure548
American Journal of Cardiology336Mortality326
International Journal of Cardiology269Atrial fibrillation226
Oncology4790Cancer370Elderly680
Journal of Clinical Oncology279Breast cancer460
Annals of Surgical Oncology154Chemotherapy391
Neurosciences4698Biological Psychiatry249Depression873
Encéphale244Bipolar disorder383
Bipolar Disorders184Attention deficit hyperactivity disorder311
Pharmacology & Pharmacy4223Drugs & Aging236Depression380
Clinical Therapeutics134Diabetes mellitus173
International Journal of Clinical Practice125Attention deficit hyperactivity disorder139
Urology & Nephrology4150Journal of Urology331Mortality327
Nephrology Dialysis Transplantation297Prostate cancer305
Urology247Hemodialysis287
Geriatrics & Gerontology3399Journal of the American Geriatrics Society634Elderly660
Drugs & Aging236Older adults435
Archives of Gerontology and Geriatrics203Depression278
Public, Environmental & Occupational Health3392Medical Care361Depression182
Journal of Clinical Epidemiology220Diabetes mellitus160
BMC Public Health220Epidemiology155
Respiratory System3003Annals of Thoracic Surgery338Chronic obstructive pulmonary disease622
Chest282Asthma160
Respiratory Medicine185Mortality155
Health Care Sciences & Services2907Medical Care361Quality of life188
Journal of General Internal Medicine282Depression154
BMC Health Services Research245Diabetes mellitus148
Psychology2788Psychological Medicine517Depression598
Depression and Anxiety407Epidemiology166
International Journal of Eating Disorders249Posttraumatic stress disorder144
Pediatrics2739Journal of the American Academy of Child and Adolescent Psychiatry376Attention deficit hyperactivity disorder330
Pediatrics167Children302
Journal of Child and Adolescent Psychopharmacology103Adolescent289
Endocrinology & Metabolism2517Diabetes Care185Diabetes mellitus359
Obesity137Obesity239
Osteoporosis International118Depression122
Peripheral Vascular Disease2446Journal of Vascular Surgery489Hypertension190
Annals of Vascular Surgery193Stroke159
Circulation192Mortality133
Psychology, Clinical2429Journal of Clinical Psychiatry727Depression374
Psychological Medicine517Anxiety disorders130
Depression and Anxiety407Eating disorders121
Gastroenterology & Hepatology2345Journal of Gastrointestinal Surgery186Colorectal Cancer144
World Journal of Gastroenterology161Mortality112
Diseases of the Colon & Rectum127Hepatitis C105
Orthopedics2300Spine306Mortality123
Clinical Orthopaedics and Related Research195Risk factors96
Journal of Bone and Joint Surgery164Hip fracture95
Infectious Diseases1792Clinical Infectious Diseases151HIV infection398
BMC Infectious Diseases129Mortality146
Infection Control and Hospital Epidemiology90Bacteremia104
Immunology1691Clinical Infectious Diseases151HIV infection239
Transplantation Proceedings134Asthma136
Biology of Blood and Marrow Transplantation112Influenza74
Rheumatology1610Journal of Rheumatology222Rheumatoid arthritis293
Rheumatology132Osteoarthritis91
BMC Musculoskeletal Disorders122Gout78
Gerontology1597Journal of the American Geriatrics Society634Elderly660
Journals of Gerontology Series A184Older adults435
International Journal of Geriatric Psychiatry156Depression278
Critical Care Medicine1589Chest282Mortality191
Critical Care Medicine183Intensive care156
Injury123Chronic obstructive pulmonary disease90
Fig 5

Co-words network of the author keywords.

Node sizes are proportional to the number of papers and line thicknesses are proportional to the number of co-occurrences of words. Node colors: blue = words related to general terms; green = words related to diseases/disorders, signs and symptoms; yellow = interventions.

Word cloud for the frequency of terms.

Note: Most frequently used keywords (at least 500 times).

Co-words network of the author keywords.

Node sizes are proportional to the number of papers and line thicknesses are proportional to the number of co-occurrences of words. Node colors: blue = words related to general terms; green = words related to diseases/disorders, signs and symptoms; yellow = interventions.

Most cited papers

Overall, included papers received 1.9 million citations, of which 40.9% citations (n = 808817) corresponded to 3596 (4.2%) papers with at least 100 citations. The most cited papers by number of citations (“citation classics” with at least 1000 citations) are listed in Table 5. All the 50 most cited papers were published in English. These most cited articles were published in 20 journals, led by the Archives of General Psychiatry (now, renamed JAMA Psychiatry) with 11 papers and followed by the Journal of the American Medical Association (JAMA) with 8 papers. The list of most cited papers (Table 4) contains contributions dealing with methodological aspects, but also important epidemiological studies on chronic non-communicable diseases, comorbidity and/or multimorbidity. Some of the methodological papers present the most commonly used measures of comorbidities in health services and outcomes research: the “Charlson Comorbidity Index” [32,33] and its various adaptations (papers number-1, number-4, number-17 and number-20 in Table 5) and the “Elixhauser Comorbidity Index” [34] (paper number-10). These comorbidity index measures capture the “comorbidity burden” that exists alongside a primary diagnosis and that may influence outcomes. The list of the most cited paper also reflects major advances in the description of the epidemiology of mental disorders and its correlates by the U.S. National Comorbidity Survey [35-40] (papers number-2, number-3, number-5, number-6, number-7 and number-15, among others in Table 5); the widely-used frailty phenotype framework proposed by Fried et al. [41] (paper number-8 in Table 5)–the concepts of “frailty” and “comorbidity/multimorbidity” are commonly used interchangeably to identify vulnerable older adults [42-44], but there is a growing consensus that these might be distinct clinical entities that are causally related [42,43]; the management of predisposing factors such as obesity and overweight [45-48] (papers number-9, number-12, number-18 and number-33); the importance of hospital volume to operative mortality associated with cardiovascular and cancer procedures [49] (paper number-13 in Table 5); and the development of the widely-used “Acute Physiology and Chronic Health Evaluation (APACHE) prognostic system” [50] (paper number-14 in Table 5) to quantify the severity of illness in the intensive care units.
Table 5

Most cited papers.

RankPaperTotal citationsCitations/year
1.Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40:373–83.15049518.9
2.Kessler RC, McGonagle KA, Zhao S, Nelson CB, Hughes M, Eshleman S, Wittchen HU, Kendler KS. Lifetime and 12-month prevalence of DSM-III-R psychiatric disorders in the United States. Results from the National Comorbidity Survey. Arch Gen Psychiatry. 1994;51:8–19.7752352.4
3.Kessler RC, Berglund P, Demler O, Jin R, Merikangas KR, Walters EE. Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Arch Gen Psychiatry. 2005;62:593–602.5404491.3
4.Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol. 1992;45:613–9.4463186.0
5.Kessler RC, Sonnega A, Bromet E, Hughes M, Nelson CB. Posttraumatic stress disorder in the National Comorbidity Survey. Arch Gen Psychiatry. 1995;52:1048–60.4397209.4
6.Kessler RC, Chiu WT, Demler O, Merikangas KR, Walters EE. Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Arch Gen Psychiatry. 2005;62:617–27.4180380.0
7.Kessler RC, Berglund P, Demler O, Jin R, Koretz D, Merikangas KR, Rush AJ, Walters EE, Wang PS; National Comorbidity Survey Replication. The epidemiology of major depressive disorder: results from the National Comorbidity Survey Replication (NCS-R). JAMA. 2003;289:3095–105.3476267.4
8.Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, Seeman T, Tracy R, Kop WJ, Burke G, McBurnie MA; Cardiovascular Health Study Collaborative Research Group. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001;56:M146-56.3052203.5
9.Buchwald H, Avidor Y, Braunwald E, Jensen MD, Pories W, Fahrbach K, Schoelles K. Bariatric surgery: a systematic review and meta-analysis. JAMA. 2004;292:1724–37.2923243.6
10.Elixhauser A, Steiner C, Harris DR, Coffey RM. Comorbidity measures for use with administrative data. Med Care. 1998;36:8–27.2625145.8
11.Regier DA, Farmer ME, Rae DS, Locke BZ, Keith SJ, Judd LL, Goodwin FK. Comorbidity of mental disorders with alcohol and other drug abuse. Results from the Epidemiologic Catchment Area (ECA) Study. JAMA. 1990;264:2511–8.246294.7
12.Must A, Spadano J, Coakley EH, Field AE, Colditz G, Dietz WH. The disease burden associated with overweight and obesity. JAMA. 1999;282:1523–9.2409141.7
13.Birkmeyer JD, Siewers AE, Finlayson EV, Stukel TA, Lucas FL, Batista I, Welch HG, Wennberg DE. Hospital volume and surgical mortality in the United States. N Engl J Med. 2002;346:1128–37.2341167.2
14.Knaus WA, Wagner DP, Draper EA, Zimmerman JE, Bergner M, Bastos PG, Sirio CA, Murphy DJ, Lotring T, Damiano A, et al. The APACHE III prognostic system. Risk prediction of hospital mortality for critically ill hospitalized adults. Chest. 1991;100:1619–36.215586.2
15.Kessler RC, Andrews G, Colpe LJ, Hiripi E, Mroczek DK, Normand SL, Walters EE, Zaslavsky AM. Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychol Med. 2002;32:959–76.2064147.4
16.Hoge CW, Castro CA, Messer SC, McGurk D, Cotting DI, Koffman RL. Combat duty in Iraq and Afghanistan, mental health problems, and barriers to care. N Engl J Med. 2004;351:13–22.2013167.8
17.Quan H, Sundararajan V, Halfon P, Fong A, Burnand B, Luthi JC, Saunders LD, Beck CA, Feasby TE, Ghali WA. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care. 2005;43:1130–9.1825165.9
18.Haslam DW, James WP. Obesity. Lancet. 2005 Oct 1;366(9492):1197–209.1787162.5
19.DiMatteo MR, Lepper HS, Croghan TW. Depression is a risk factor for noncompliance with medical treatment: meta-analysis of the effects of anxiety and depression on patient adherence. Arch Intern Med. 2000;160:2101–7.1525138.6
20.Charlson M, Szatrowski TP, Peterson J, Gold J. Validation of a combined comorbidity index. J Clin Epidemiol. 1994;47:1245–51.151368.8
21.Bousquet J, Khaltaev N, Cruz AA, Denburg J, Fokkens WJ, Togias A, Zuberbier T, Baena-Cagnani CE, Canonica GW, van Weel C, et al. Allergic Rhinitis and its Impact on Asthma (ARIA) 2008 update (in collaboration with the World Health Organization, GA(2)LEN and AllerGen). Allergy. 2008;63 Suppl 86:8–160.1505188.1
22.Meyer IH. Prejudice, social stress, and mental health in lesbian, gay, and bisexual populations: conceptual issues and research evidence. Psychol Bull. 2003;129:674–97.1501115.5
23.Spitzer RL, Kroenke K, Williams JB, Löwe B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med. 2006;166:1092–7.1433143.3
24.Costello EJ, Mustillo S, Erkanli A, Keeler G, Angold A. Prevalence and development of psychiatric disorders in childhood and adolescence. Arch Gen Psychiatry. 2003;60:837–44.1417109.0
25.Trivedi MH, Rush AJ, Wisniewski SR, Nierenberg AA, Warden D, Ritz L, Norquist G, Howland RH, Lebowitz B, McGrath PJ, Shores-Wilson K, et al. Evaluation of outcomes with citalopram for depression using measurement-based care in STAR*D: implications for clinical practice. Am J Psychiatry. 2006;163:28–40.1394139.4
26.Vestbo J, Hurd SS, Agustí AG, Jones PW, Vogelmeier C, Anzueto A, Barnes PJ, Fabbri LM, Martinez FJ, Nishimura M, et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. Am J Respir Crit Care Med. 2013;187:347–65.1365455.0
27.Hudson JI, Hiripi E, Pope HG Jr, Kessler RC. The prevalence and correlates of eating disorders in the National Comorbidity Survey Replication. Biol Psychiatry. 2007;61:348–58.1344149.3
28.Kessler RC, Adler L, Barkley R, Biederman J, Conners CK, Demler O, Faraone SV, Greenhill LL, Howes MJ, Secnik K, et al. The prevalence and correlates of adult ADHD in the United States: results from the National Comorbidity Survey Replication. Am J Psychiatry. 2006;163:716–23.1336133.6
29.Vos T, Flaxman AD, Naghavi M, Lozano R, Michaud C, Ezzati M, Shibuya K, Salomon JA, Abdalla S, Aboyans V, et al. Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380:2163–96.1306326.5
30.Ozer EJ, Best SR, Lipsey TL, Weiss DS. Predictors of posttraumatic stress disorder and symptoms in adults: a meta-analysis. Psychol Bull. 2003;129:52–73.128298.6
31.Grant BF, Stinson FS, Dawson DA, Chou SP, Dufour MC, Compton W, Pickering RP, Kaplan K. Prevalence and co-occurrence of substance use disorders and independent mood and anxiety disorders: results from the National Epidemiologic Survey on Alcohol and Related Conditions. Arch Gen Psychiatry. 2004;61:807–16.1275106.3
32.Lasser K, Boyd JW, Woolhandler S, Himmelstein DU, McCormick D, Bor DH. Smoking and mental illness: A population-based prevalence study. JAMA. 2000;284:2606–10.127579.7
33.Dietz WH. Health consequences of obesity in youth: childhood predictors of adult disease. Pediatrics. 1998;101:518–25.127170.6
34.Demyttenaere K, Bruffaerts R, Posada-Villa J, Gasquet I, Kovess V, Lepine JP, Angermeyer MC, Bernert S, de Girolamo G, Morosini P, et al. Prevalence, severity, and unmet need for treatment of mental disorders in the World Health Organization World Mental Health Surveys. JAMA. 2004;291:2581–90.1265105.4
35.Hagan PG, Nienaber CA, Isselbacher EM, Bruckman D, Karavite DJ, Russman PL, Evangelista A, Fattori R, Suzuki T, Oh JK, et al. The International Registry of Acute Aortic Dissection (IRAD): new insights into an old disease. JAMA. 2000;283:897–903.120075.0
36.Pories WJ, Swanson MS, MacDonald KG, Long SB, Morris PG, Brown BM, Barakat HA, deRamon RA, Israel G, Dolezal JM, et al. Who would have thought it? An operation proves to be the most effective therapy for adult-onset diabetes mellitus. Ann Surg. 1995;222:339–50.118356.3
37.Sheline YI, Wang PW, Gado MH, Csernansky JG, Vannier MW. Hippocampal atrophy in recurrent major depression. Proc Natl Acad Sci U S A. 1996;93:3908–13.117959.0
38.Kessler RC, Crum RM, Warner LA, Nelson CB, Schulenberg J, Anthony JC. Lifetime co-occurrence of DSM-III-R alcohol abuse and dependence with other psychiatric disorders in the National Comorbidity Survey. Arch Gen Psychiatry. 1997;54:313–21.114260.1
39.Weissman MM, Bland RC, Canino GJ, Faravelli C, Greenwald S, Hwu HG, Joyce PR, Karam EG, Lee CK, Lellouch J, et al. Cross-national epidemiology of major depression and bipolar disorder. JAMA. 1996;276:293–9.113356.7
40.Kessler RC, Borges G, Walters EE. Prevalence of and risk factors for lifetime suicide attempts in the National Comorbidity Survey. Arch Gen Psychiatry. 1999;56:617–26.111265.4
41.Kessler RC, Barker PR, Colpe LJ, Epstein JF, Gfroerer JC, Hiripi E, Howes MJ, Normand SL, Manderscheid RW, Walters EE, et al. Screening for serious mental illness in the general population. Arch Gen Psychiatry. 2003;60:184–9.110885.2
42.Blazer DG, Kessler RC, McGonagle KA, Swartz MS. The prevalence and distribution of major depression in a national community sample: the National Comorbidity Survey. Am J Psychiatry. 1994;151:979–86.109649.8
43.Wang PS, Lane M, Olfson M, Pincus HA, Wells KB, Kessler RC. Twelve-month use of mental health services in the United States: results from the National Comorbidity Survey Replication. Arch Gen Psychiatry. 2005;62:629–40.109399.4
44.Sullivan PF, Neale MC, Kendler KS. Genetic epidemiology of major depression: review and meta-analysis. Am J Psychiatry. 2000;157:1552–62.108968.1
45.Kessler RC, McGonagle KA, Swartz M, Blazer DG, Nelson CB. Sex and depression in the National Comorbidity Survey. I: Lifetime prevalence, chronicity and recurrence. J Affect Disord. 1993;29:85–96.107646.8
46.Moussavi S, Chatterji S, Verdes E, Tandon A, Patel V, Ustun B. Depression, chronic diseases, and decrements in health: results from the World Health Surveys. Lancet. 2007;370:851–8.1065118.3
47.Romano PS, Roos LL, Jollis JG. Adapting a clinical comorbidity index for use with ICD-9-CM administrative data: differing perspectives. J Clin Epidemiol. 1993;46:1075–9.106146.1
48.Browning JD, Horton JD. Molecular mediators of hepatic steatosis and liver injury. J Clin Invest. 2004;114:147–52.103286.0
49Bair MJ, Robinson RL, Katon W, Kroenke K. Depression and pain comorbidity: a literature review. Arch Intern Med. 2003;163:2433–45.102278.6
50.Hasin DS, Stinson FS, Ogburn E, Grant BF. Prevalence, correlates, disability, and comorbidity of DSM-IV alcohol abuse and dependence in the United States: results from the National Epidemiologic Survey on Alcohol and Related Conditions. Arch Gen Psychiatry. 2007;64:830–42.1004111.6

Most cited (top-50) papers with at least 1000 citations.

Most cited (top-50) papers with at least 1000 citations.

Discussion

In this cross-sectional analysis, we analyzed the global scientific research in comorbidity and multimorbidity for the period 1970–2016. We have identified the most productive investigators and countries, most common subjects and keywords, most prolific journals and “citation classics” in comorbidity and multimorbidity based on publications in multiple specialties and disciplines. The most striking results are the increasing number of published articles in recent years, with approximately two-thirds of the papers published since 2010. To the best of our knowledge, this is the first comprehensive global mapping analysis of scientific publications in comorbidity and multimorbidity. This analysis complements and expands the perspective of previous studies that analyzed some characteristics of articles in comorbidity [10,12], the diversity of terms used in the literature referring to the presence of multiple concurrent diseases [10,12,51], or reviews on the implications and the understanding of research needs and treatment impact [52,53]. In line with previous research in other areas [54-57], the global productivity of scientific papers is dominated by the United States (as a central hub of knowledge), followed by other nodes in Western Europe (such as the United Kingdom, Germany and Italy) and Canada. The large number of publications on comorbidity and multimorbidity from these countries reflects the importance that Western societies devote to research as the basis for socio-economic and technological development, but also reflects the interest in understanding and addressing important challenges of population aging and increased complexity of chronicity. Ageing of the world's population is increasing the number of people living with sequelae of multiple diseases, with an increasing trend in low-income countries [1-4]. As might be expected, the scientific community captured is centered on a nucleus of scientists and researchers from academia, medical and health research centers from North America and Western Europe, but also from Australia and Taiwan (Republic of China). Specifically, the most intense global collaborations took place between authors and institutions from the United States, the United Kingdom and Canada. Perhaps, the very limited participation of low and middle income-based researchers and institutions in research on comorbidity and multimorbidity could warrant further pragmatic action given that the epidemiological transition (e.g. replacement of infectious diseases by chronic diseases) imposes more constraints to deal with the burden of multiple chronic diseases in a poor environment characterized by ill-health systems [3,4,58-60]. Papers on comorbidity and multimorbidity were published most often in journals devoted to neuropsychiatry and neurosciences. Psychiatry has become one of the fastest growing medical disciplines [61]. In fact, the publication activity and interest of comorbidity and multimorbidity in people with mental disorders seems to be increasing [62,63]. Our analysis revealed that nearly 20% of all scientific production was published in journals belonging to psychiatry and mental health. This large relative productivity in psychiatry may be explained by the important role of comorbidity and its implications for theories of etiology, prevention and treatment of mental disorders [63]. Within psychiatry, comorbidity has been traditionally used to refer to the overlap of two or more psychiatric disorders [64]. Similarly, comorbidity (and multimorbidity) between mental disorders and substance use disorders [65-67], cardiovascular diseases [68-70], cancer [71,72] or other chronic disorders [6,73] has gained prominence within the past few decades. Our analyses suggest that other medical disciplines with a large number of papers on comorbidity and multimorbidity, including surgery [74,75], clinical neurology [76-78], general and internal medicine [3,4,79,80], cardiology [81] and oncology [82], focus on those conditions with a high global burden of disease. The subject analysis has revealed that the keywords’ prioritization in comorbidity and multimorbidity depends on the addressed subject area. For example, “Depression” is the most commonly used keyword in the subject categories of Psychiatry, Clinical Neurology, Neurosciences, Psychology; but also in General and Internal Medicine, Geriatrics and Gerontology, Pharmacology, Endocrinology, Public, Environmental and Occupational Health, and Health Care Sciences and Services. Depression is a common mental disorder that occurs in people of all ages across all world regions and represents a leading cause of disease burden [3,4,78]. Despite existing evidence of the effectiveness of multiple interventions, traditional approaches to the management of the depressive disorders (such as medication alone and brief psychotherapy) have contributed to large treatment gaps [83-86]. In this respect, the complex pathogenesis implicates factors of diverse nature that should be considered in research. For example, integrating the management of depressive disorders with other common mental disorders (e.g. anxiety disorders and bipolar disorder) or other chronic conditions (e.g. cancer, diabetes and diseases of the cardiorespiratory system) through transdiagnostic interventions [83]. The topic analysis of the most cited papers (“citation classics”) allowed us to determine which topics have attracted the most interest in the research on comorbidity and multimorbidity. These include landmark methodological developments in measuring comorbidity (such as Charlson’s index, Elixhauser’s index and their modifications) [32-34] and descriptive epidemiological studies measuring the burden of comorbidity [35-40], among others. However, important knowledge gaps in comorbidity and multimorbidity remain. The limitations of clinical practice guidelines and treatment for single diseases are well recognized in the biomedical literature, along with the call to make better use of the best evidence base [87,88]. Clinical trials are usually conducted in homogeneous populations, which prevents us from knowing whether treatment effects in people with multiple chronic diseases are equivalent to those in patients with single diseases [89,90]. The evidence base for interventions to improve outcomes for people with multimorbidity therefore remains limited; however, emerging evidence is being generated to support disease management policies in primary care and community settings [53]. The consideration of people with multimorbidity is essential in future study design and evaluations of health services and technologies. To be of value, it is important that research includes the evaluation of the benefits of multiple approaches for multiple coexisting diseases (e.g. patient-, family- and population-centered), and that generalizability and applicability problems be explicitly addressed [87-91]. There are several limitations to our study. We characterized knowledge structures generated by papers included in the Web of Science database, integrating subject categories of journals, keywords of papers and network analyses. However, these methods represent a scoping approach which could be complemented further by more detailed analyses, for example analyzing the content and reporting quality of papers in evidence syntheses (including systematic reviews of the literature [92]). We only analyzed research articles and review articles. Undoubtedly, there are other important reports (e.g. health policy reports, meeting abstracts and letters/correspondence [93]) that also merit consideration in global debates and discussions in comorbidity and multimorbidity. The validity of keywords mapping and the results of the co-word analyses depend on the definitions of words chosen to conceptualize the papers by the authors or database indexers to categorize papers. The growing interest in comorbidity and multimorbidity by health care providers has resulted in more research on these issues, which may have led to a proliferation of different terms for the same concepts. For example, the traditional (and widely accepted) term “comorbidity” is associated with high volume of papers but may lack specificity, whereas the more recently introduced term of “multimorbidity” is associated with low number of papers (see S1 Table). As Almirall and Fortin stated “[t]he use of clearly defined terms in the literature is recommended until a general consensus on the terminology of multiple coexistent diseases is reached” across multiple disciplines [51]. Given the dynamic nature of the field, it will be interesting to see whether the growth trend remains in the coming years, and how the characteristics of the field changes of time (e.g. by means of longitudinal network analyses).

Conclusion

The global analysis presented in this study provides compelling evidence of the scientific growth of research on comorbidity and multimorbidity. Scientific research in this field is increasingly published in biomedical journals, with research leadership of Western countries, most notably, the United States. This study contributes to a better understanding in this challenging field and identifies the main areas of research, the publication sources chosen for their scientific dissemination and the major scientific leaders. Advances in several subjects and research areas will allow for use of new theories and models to fundamentally changes in the management of people with multiple chronic diseases.

Reporting checklist.

(DOCX) Click here for additional data file.

Search strategy and results.

(DOCX) Click here for additional data file.
  86 in total

1.  Hospital volume and surgical mortality in the United States.

Authors:  John D Birkmeyer; Andrea E Siewers; Emily V A Finlayson; Therese A Stukel; F Lee Lucas; Ida Batista; H Gilbert Welch; David E Wennberg
Journal:  N Engl J Med       Date:  2002-04-11       Impact factor: 91.245

2.  Managing patients with multimorbidity in primary care.

Authors:  Emma Wallace; Chris Salisbury; Bruce Guthrie; Cliona Lewis; Tom Fahey; Susan M Smith
Journal:  BMJ       Date:  2015-01-20

3.  Consideration of multiple chronic diseases in randomized controlled trials.

Authors:  Alejandro R Jadad; Matthew J To; Mohamed Emara; Jennifer Jones
Journal:  JAMA       Date:  2011-12-28       Impact factor: 56.272

4.  Frailty in older adults: evidence for a phenotype.

Authors:  L P Fried; C M Tangen; J Walston; A B Newman; C Hirsch; J Gottdiener; T Seeman; R Tracy; W J Kop; G Burke; M A McBurnie
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2001-03       Impact factor: 6.053

5.  Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication.

Authors:  Ronald C Kessler; Patricia Berglund; Olga Demler; Robert Jin; Kathleen R Merikangas; Ellen E Walters
Journal:  Arch Gen Psychiatry       Date:  2005-06

6.  The epidemiology of major depressive disorder: results from the National Comorbidity Survey Replication (NCS-R).

Authors:  Ronald C Kessler; Patricia Berglund; Olga Demler; Robert Jin; Doreen Koretz; Kathleen R Merikangas; A John Rush; Ellen E Walters; Philip S Wang
Journal:  JAMA       Date:  2003-06-18       Impact factor: 56.272

Review 7.  Cardiovascular risk assessment in patients with a severe mental illness: a systematic review and meta-analysis.

Authors:  Quintí Foguet-Boreu; Maria Isabel Fernandez San Martin; Gemma Flores Mateo; Edurne Zabaleta Del Olmo; Luís Ayerbe García-Morzon; Maria Perez-Piñar López; Luis Miguel Martin-López; Javier Montes Hidalgo; Concepción Violán
Journal:  BMC Psychiatry       Date:  2016-05-12       Impact factor: 3.630

8.  Climate Change Research in View of Bibliometrics.

Authors:  Robin Haunschild; Lutz Bornmann; Werner Marx
Journal:  PLoS One       Date:  2016-07-29       Impact factor: 3.240

9.  Global, regional, and national age-sex specific mortality for 264 causes of death, 1980-2016: a systematic analysis for the Global Burden of Disease Study 2016.

Authors: 
Journal:  Lancet       Date:  2017-09-16       Impact factor: 79.321

10.  Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-years for 32 Cancer Groups, 1990 to 2015: A Systematic Analysis for the Global Burden of Disease Study.

Authors:  Christina Fitzmaurice; Christine Allen; Ryan M Barber; Lars Barregard; Zulfiqar A Bhutta; Hermann Brenner; Daniel J Dicker; Odgerel Chimed-Orchir; Rakhi Dandona; Lalit Dandona; Tom Fleming; Mohammad H Forouzanfar; Jamie Hancock; Roderick J Hay; Rachel Hunter-Merrill; Chantal Huynh; H Dean Hosgood; Catherine O Johnson; Jost B Jonas; Jagdish Khubchandani; G Anil Kumar; Michael Kutz; Qing Lan; Heidi J Larson; Xiaofeng Liang; Stephen S Lim; Alan D Lopez; Michael F MacIntyre; Laurie Marczak; Neal Marquez; Ali H Mokdad; Christine Pinho; Farshad Pourmalek; Joshua A Salomon; Juan Ramon Sanabria; Logan Sandar; Benn Sartorius; Stephen M Schwartz; Katya A Shackelford; Kenji Shibuya; Jeff Stanaway; Caitlyn Steiner; Jiandong Sun; Ken Takahashi; Stein Emil Vollset; Theo Vos; Joseph A Wagner; Haidong Wang; Ronny Westerman; Hajo Zeeb; Leo Zoeckler; Foad Abd-Allah; Muktar Beshir Ahmed; Samer Alabed; Noore K Alam; Saleh Fahed Aldhahri; Girma Alem; Mulubirhan Assefa Alemayohu; Raghib Ali; Rajaa Al-Raddadi; Azmeraw Amare; Yaw Amoako; Al Artaman; Hamid Asayesh; Niguse Atnafu; Ashish Awasthi; Huda Ba Saleem; Aleksandra Barac; Neeraj Bedi; Isabela Bensenor; Adugnaw Berhane; Eduardo Bernabé; Balem Betsu; Agnes Binagwaho; Dube Boneya; Ismael Campos-Nonato; Carlos Castañeda-Orjuela; Ferrán Catalá-López; Peggy Chiang; Chioma Chibueze; Abdulaal Chitheer; Jee-Young Choi; Benjamin Cowie; Solomon Damtew; José das Neves; Suhojit Dey; Samath Dharmaratne; Preet Dhillon; Eric Ding; Tim Driscoll; Donatus Ekwueme; Aman Yesuf Endries; Maryam Farvid; Farshad Farzadfar; Joao Fernandes; Florian Fischer; Tsegaye Tewelde G/Hiwot; Alemseged Gebru; Sameer Gopalani; Alemayehu Hailu; Masako Horino; Nobuyuki Horita; Abdullatif Husseini; Inge Huybrechts; Manami Inoue; Farhad Islami; Mihajlo Jakovljevic; Spencer James; Mehdi Javanbakht; Sun Ha Jee; Amir Kasaeian; Muktar Sano Kedir; Yousef S Khader; Young-Ho Khang; Daniel Kim; James Leigh; Shai Linn; Raimundas Lunevicius; Hassan Magdy Abd El Razek; Reza Malekzadeh; Deborah Carvalho Malta; Wagner Marcenes; Desalegn Markos; Yohannes A Melaku; Kidanu G Meles; Walter Mendoza; Desalegn Tadese Mengiste; Tuomo J Meretoja; Ted R Miller; Karzan Abdulmuhsin Mohammad; Alireza Mohammadi; Shafiu Mohammed; Maziar Moradi-Lakeh; Gabriele Nagel; Devina Nand; Quyen Le Nguyen; Sandra Nolte; Felix A Ogbo; Kelechi E Oladimeji; Eyal Oren; Mahesh Pa; Eun-Kee Park; David M Pereira; Dietrich Plass; Mostafa Qorbani; Amir Radfar; Anwar Rafay; Mahfuzar Rahman; Saleem M Rana; Kjetil Søreide; Maheswar Satpathy; Monika Sawhney; Sadaf G Sepanlou; Masood Ali Shaikh; Jun She; Ivy Shiue; Hirbo Roba Shore; Mark G Shrime; Samuel So; Samir Soneji; Vasiliki Stathopoulou; Konstantinos Stroumpoulis; Muawiyyah Babale Sufiyan; Bryan L Sykes; Rafael Tabarés-Seisdedos; Fentaw Tadese; Bemnet Amare Tedla; Gizachew Assefa Tessema; J S Thakur; Bach Xuan Tran; Kingsley Nnanna Ukwaja; Benjamin S Chudi Uzochukwu; Vasiliy Victorovich Vlassov; Elisabete Weiderpass; Mamo Wubshet Terefe; Henock Gebremedhin Yebyo; Hassen Hamid Yimam; Naohiro Yonemoto; Mustafa Z Younis; Chuanhua Yu; Zoubida Zaidi; Maysaa El Sayed Zaki; Zerihun Menlkalew Zenebe; Christopher J L Murray; Mohsen Naghavi
Journal:  JAMA Oncol       Date:  2017-04-01       Impact factor: 31.777

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  7 in total

1.  Prevalence and comorbidity of attention deficit hyperactivity disorder in Spain: study protocol for extending a systematic review with updated meta-analysis of observational studies.

Authors:  Ferrán Catalá-López; Manuel Ridao; Amparo Núñez-Beltrán; Ricard Gènova-Maleras; Adolfo Alonso-Arroyo; Rafael Aleixandre-Benavent; Miguel A Catalá; Rafael Tabarés-Seisdedos
Journal:  Syst Rev       Date:  2019-02-11

Review 2.  Chronic obstructive pulmonary disease and rheumatic diseases: A systematic review on a neglected comorbidity.

Authors:  Irini Gergianaki; Ioanna Tsiligianni
Journal:  J Comorb       Date:  2019-01-07

3.  Science maps for exploration, navigation, and reflection-A graphic approach to strategic thinking.

Authors:  Flemming Skov
Journal:  PLoS One       Date:  2021-12-31       Impact factor: 3.240

4.  Multimorbidity patterns of chronic conditions and geriatric syndromes in older patients from the MoPIM multicentre cohort study.

Authors:  Marisa Baré; Susana Herranz; Albert Roso-Llorach; Rosa Jordana; Concepción Violán; Marina Lleal; Pere Roura-Poch; Marta Arellano; Rafael Estrada; Gloria Julia Nazco
Journal:  BMJ Open       Date:  2021-11-15       Impact factor: 2.692

5.  Effects of goal-oriented care for adults with multimorbidity: A systematic review and meta-analysis.

Authors:  Angelo Barbato; Barbara D'Avanzo; Michela Cinquini; Andrea Veronica Fittipaldo; Alessandro Nobili; Laura Amato; Simona Vecchi; Graziano Onder
Journal:  J Eval Clin Pract       Date:  2022-03-30       Impact factor: 2.336

6.  Examine the association between key determinants identified by the chronic disease indicator framework and multimorbidity by rural and urban settings.

Authors:  John S Moin; Richard H Glazier; Kerry Kuluski; Alex Kiss; Ross E G Upshur
Journal:  J Multimorb Comorb       Date:  2021-06-30

7.  Reporting guidelines for health research: protocol for a cross-sectional analysis of the EQUATOR Network Library.

Authors:  Ferrán Catalá-López; Adolfo Alonso-Arroyo; Matthew J Page; Brian Hutton; Manuel Ridao; Rafael Tabarés-Seisdedos; Rafael Aleixandre-Benavent; David Moher
Journal:  BMJ Open       Date:  2019-03-04       Impact factor: 2.692

  7 in total

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