Abstract
Purpose
We investigated the research conducted on osteoporosis at EMRI to provide practical implications and suggestions for the development of future research.
Methods
We searched osteoporosis and related concepts, as well as various forms of affiliations to EMRI to find published documents indexed in Web of Science, PubMed, and Scopus databases until January 27, 2020. The main purpose and scopes of the studies were classified into seven main study areas. Co-authorship relations were examined using the VOSviewer and keyword analysis was carried out by the ScientoPy.
Results
A total 201 papers on the subject of osteoporosis with organizational affiliation to EMRI were found after initial screening and removing duplicates. A time trend analysis of publications showed a growing trend of EMRI’s publication in the field of osteoporosis since 2014. A total of 558 independent authors participated in osteoporosis-related research at EMRI, and the average contribution of authors was 6.72 per papers. The Co-authorship network for authors contributing in at least five publications, showed 4 main clusters of independent authors. The co-occurrence network of keywords included three large and intertwined clusters including the epidemiology of osteoporosis and its resulting fractures and risk factors, bone markers and monitoring the effectiveness of treatment with them, and nutrition and supplements in the field of osteoporosis and fractures.
Conclusion
EMRI has significantly contributed in osteoporosis science and related subjects during recent years, especially in public health aspects of osteoporosis and its risk factors and consequences. More attention should be paid to other areas such clinical and basic science studies.
Keywords: Osteoporosis, Metabolic bone diseases, Bibliometrics, Osteoporosis research center, Endocrinology and metabolism research institute
Introduction
Endocrinology and Metabolism Research Institute (EMRI) affiliated to Tehran University of Medical Sciences is a pioneering scientific and educational research body in Iran with a mission to combine clinical care, research and education in the field of endocrine and metabolic disorders. Over a quarter-century of experience, the institute has aimed to conduct basic and applied research and to provide training and prevention and treatment strategies in areas related to non-communicable diseases, especially osteoporosis, diabetes, thyroid and metabolic disorders [1].
As one of the most common metabolic bone diseases in Iran [2], osteoporosis has become one of the most important concerns of EMRI. In this regard, EMRI started its activities in the field of osteoporosis in 1999 in osteoporosis research group and has continued these activities since 2010 as the Osteoporosis Research Center (ORC). As a result of ORC’s efforts, the Institute was designed as a WHO Collaborating Center for Research and Education on Osteoporosis Management since 2007 till 2023 [3]. EMRI is also working closely with the International Osteoporosis Foundation (IOF) on conducting educational and research activities in the field of osteoporosis, and has been working with the foundation since 2004 as a full member of the IOF’ Committee of National Societies and the regional advisory committee (RAC) in the Middle East and North Africa (MENA) [4].
In this study, we investigated the research conducted on osteoporosis so far at EMRI in order to outline the strengths and weaknesses of these researches and to provide practical implications and suggestions for the development of future research strategies in EMRI.
Method
This research uses the scientometrics analysis to study the bibliographic data of EMRI on osteoporosis. The study included all the papers with at least one affiliation of EMRI published in osteoporosis field indexed in WoS, PubMed and Scopus databases. For this purpose, in this study, a search strategy containing “osteoporosis” and related concepts, as well as various forms of affiliations to EMRI was carried out to search data until January 27, 2020 in Web of Science, PubMed, and Scopus databases. The search strategy is given in Table 3.
Table 3.
Search Strategy
| Database | Search Strategy | Execution Date | No. of Records |
|---|---|---|---|
| PubMed | (“Osteoporosis”[Mesh] OR Osteop*[TIAB] OR “Bone Density”[Mesh] OR “Bone Density” [TIAB] OR “Bone Densities” [TIAB] OR “Bone Mineral”[TIAB] OR “Bone Loss”[TIAB] OR “Bone health”[TIAB] OR “Bone Quality” [TIAB] OR “Bone Marker”[TIAB] OR “Bone Markers”[TIAB] OR “Bone Mass” [TIAB] OR “Bone Turnover”[TIAB] OR “bone turn-over”[TIAB] OR “Bone Resorption” [TIAB] OR “Bone Formation” [TIAB] OR Osteolysis[TIAB] OR ossification[TIAB] OR “osseous density”[TIAB] OR “skeletal mass” [TIAB] OR “Bone Diseases, Metabolic”[Mesh] OR (Bone[TIAB] AND Diseases[TIAB] AND Metabolic[TIAB]) OR “Bone Remodeling” [TIAB] OR “Bone Regeneration” [TIAB] OR “Densitometry”[Mesh] OR Densitometr*[TIAB]) AND (((Endocrino*[AD] AND (Metabolic[AD] OR Metab*[AD]) AND CLINIC*[AD] AND INSTITUTE[AD]) OR EMRI[AD]) AND (TUMS[AD] OR “Tehran University of Medical Sciences”[AD] OR “MED SCI UNIV TEHRAN”[AD] OR “MED UNIV TEHRAN” [AD] OR “SHARIATI HOSP”[AD] OR “TEHRAN MED SCI UNIV”[AD] OR “TEHRAN MED UNIV”[AD] OR “TEHRAN UNIV MED”[AD] OR “TEHRAN UNIV MED SCI”[AD] OR “UNIV TEHRAN MED SCI”[AD] OR “UNIV TEHRAN MED SCI HLTH SCI”[AD] OR “UNIV TEHRAN MED SCI HLTH SERV”[AD]) | 27 Jan 2020 | 68 |
|
Web of Science (Indexes: SCI-EXPANDED, SSCI, A&HCI, CPCI-S, CPCI-SSH, BKCI-S, BKCI-SSH, ESCI, CCR-EXPANDED, IC.) |
TS = (Osteop* OR (Bone NEAR/3 (Densit* OR Mineral OR Loss OR health* OR Quality OR Marker OR Mass OR Turnover OR turn-over OR Resorption OR Formation)) OR Osteolysis OR ossification OR (osseous NEAR/3 density) OR (skeletal NEAR/3 mass) OR (Bone NEAR/3 Diseases NEAR/3 Metabolic) OR” Bone Remodeling” OR” Bone Regeneration” OR Densitometr*) AND AD = (((Endocrino* SAME (Metabolic OR Metab) SAME CLIN* SAME INST*) OR EMRI) SAME (TUMS OR “Tehran University of Medical Sciences” OR “MED SCI UNIV TEHRAN” OR “MED UNIV TEHRAN” OR “SHARIATI HOSP” OR “TEHRAN MED SCI UNIV” OR “TEHRAN MED UNIV” OR “TEHRAN UNIV MED” OR “TEHRAN UNIV MED SCI” OR “UNIV TEHRAN MED SCI” OR “UNIV TEHRAN MED SCI HLTH SCI” OR “UNIV TEHRAN MED SCI HLTH SERV”)) | 27 Jan 2020 | 111 |
| Scopus | TITLE-ABS-KEY (osteop* OR (bone W/3 (densit* OR mineral OR loss OR health* OR quality OR marker OR mass OR turnover OR turn-over OR resorption OR formation)) OR osteolysis OR ossification OR (osseous W/3 density) OR (skeletal W/3 mass) OR (bone W/3 diseases W/3 metabolic) OR “Bone Remodeling” OR “Bone Regeneration” OR densitometr*) AND (AFFIL (((endocrino* AND (metabolic OR metab*) AND clin* AND inst*) OR emri) AND (tums OR “Tehran University of Medical Sciences” OR “MED SCI UNIV TEHRAN” OR “MED UNIV TEHRAN” OR “SHARIATI HOSP” OR “TEHRAN MED SCI UNIV” OR “TEHRAN MED UNIV” OR “TEHRAN UNIV MED” OR “TEHRAN UNIV MED SCI” OR “UNIV TEHRAN MED SCI” OR “UNIV TEHRAN MED SCI HLTH SCI” OR “UNIV TEHRAN MED SCI HLTH SERV”)) OR (AF-ID (“Tehran University of Medical Sciences Endocrinology and Metabolism Research Institute” 60,027,129))) | 27 Jan 2020 | 202 |
The inclusion criteria were studies with at least one author affiliated to EMRI or one of its affiliated research centers. Erratum papers and ambiguity in authenticity of EMRI affiliation of authors as well as the studies whose subject were irrelevant to osteoporosis were excluded. All bibliographic data from the three sources were imported to endnote. The matching of title, author, and source was used to find duplicate papers. After eliminating duplicates in the EndNote software, two researchers independently investigated the inclusion and exclusion criteria by reading the title, abstract and authors’ organizational affiliation of the papers. In case of any disagreement between the two researchers, a third person re-examined the papers to achieve a consensus.
Then, the full-text of papers, deemed relevant to the inclusion criteria of the present research, were studied by one researcher and the main purposes and scopes of the studies were determined and classified into seven main study areas. Some papers were categorized into more than one category because they belonged to more than one area at the same time.
The bibliographic data of these papers were also used to the co-authorship network analysis using the VOSviewer v1.6.15. VOSviewer is a freely available computer software used for constructing and visualizing bibliometric networks. It can construct bibliometric network at the levels of countries, organizations, journals, researchers, or individual publications. These networks can be constructed based on citation, bibliographic coupling, co-citation, or co-authorship relations. It also offers text mining feature to visualize co-occurrence networks of keywords [5]. In this study we used VOSviewer to visualize co-authorship and co-word occurrence networks. To do this, the keywords of the papers were first unified in terms of different forms of writing, then the keywords presented in at least 7 papers were extracted, and their co-occurrence network was visualized. The same was done to visualize co-author network. First, we uniformed different forms of author names, and then the co-authorship network for authors contributing in at least five publications was visualized using VOSviewer. We also used ScientoPy v2.0.3 to analyze the trend of keyword presence in studies. ScientoPy is an open-source python script for scientometrics literature review. It can automatically generate and reports the top topics (based on authors or index keywords), authors, and countries from bibliographic data [6].
Results
Our search of the three Web of Science, Scopus, and PubMed databases retrieved 111, 201, and 67 papers, respectively. Out of 379 retrieved documents, 133 duplicate papers were removed from the collection and finally 246 papers were included for further screening. Then, by studying the title,abstract and authors’ organizational affiliation of the papers of the papers by two independent researchers, the papers that had the inclusion criteria were selected and the others were excluded from the study (45 papers). Thus, 201 papers on the subject of osteoporosis with organizational affiliation to EMRI were found in the aforementioned databases (Fig. 1).
Fig. 1.
PRISMA flow diagram
A time trend analysis of publication showed that EMRI’s growth in the researches in the field of osteoporosis has accelerated since 2014 (Fig. 2).
Fig. 2.
Frequency of published papers by EMRI in the field of osteoporosis by the year of publication (2004–2019)
Furthermore, a review of the authors showed that a total of 558 independent authors participated in research in the field of osteoporosis at EMRI, and the average contribution of authors was 6.72 per paper. Among these authors, “Larijani B” with 144, “Hosseinnejad A” with 48 and “Khashayar P” with 38 papers were the most prolific contributors in this field. A list of the 10 most prolific authors in the field of osteoporosis is given in Table 1.
Table 1.
Top 10 Prolific authors of EMRI in the field of osteoporosis (2004–2019)
| Rank | Authors | No. of Records | % of 201 |
|---|---|---|---|
| 1 | Larijani, B. | 144 | 71.6 |
| 2 | Hossein-Nezhad, A. | 48 | 23.9 |
| 3 | Khashayar, P. | 38 | 18.9 |
| 4 | Maghbooli, Z. | 30 | 14.9 |
| 5 | Heshmat, R. | 29 | 14.4 |
| 6 | Keshtkar, A. | 29 | 14.4 |
| 7 | Soltani, A. | 22 | 10.9 |
| 8 | Ostovar, A. | 17 | 8.5 |
| 9 | Nabipour, I. | 17 | 8.5 |
| 10 | Razi, F. | 16 | 8.0 |
The Co-authorship network for authors contributing in at least five publications shows 4 main clusters of independent authors (Fig. 3). In this network, “Larijani B” plays an outstanding role of intermediary node with a large number of direct links with other clusters of this collection. Succeeding to him, “Khashayar P”, “Heshmat R”, “Hosseinnejad A” and “Keshtkar A” had the highest total link strength in this network, which means that these researchers had the highest level of co-authorship in the collection [7].
Fig. 3.
Co-authorship network of researchers in the field of osteoporosis at EMRI. (The size of the nodes is based on the number of papers by the author and the size of the lines is based on the strength of the link) (2004–2019)
The co-occurrence network of keywords presenting in at least 7 documents is shown in Fig. 4 which includes three large and intertwined clusters:
Cluster 1: Green. The cluster has 18 keywords, and keywords such as “Osteoporosis”, “Osteopenia”, “Bone Density”, “Hip Fracture” and “Risk Factors” indicate documents on the epidemiology of osteoporosis and its resulting fractures and risk factors.
Cluster 2: Red. The cluster includes 23 keywords, it is the largest cluster in the network, and keywords such as “osteocalcin”, “alkaline phosphatase”, “osteolysis”, and “Bone turn over” indicate studies on bone markers and monitoring the effectiveness of treatment with them.
Cluster 3: Blue. This cluster with 12 keywords such as “Calcium”, “Phosphorus” and “Vitamin blood level” includes studies on nutrition and supplements in the field of osteoporosis and fractures.
Fig. 4.
Co-occurrence network of keywords in papers published by EMRI in the field of osteoporosis (2004–2019)
Also, the trend of widely used keywords in the EMRI documents on osteoporosis was depicted using the ScientoPy software (Fig. 5). Common descriptor keywords such as study type (“systematic review”, “meta-analysis”, cross-sectional study, etc.) and demographic descriptors (“male”, “female”, “child”, “adult”, etc.) and the word “osteoporosis” were excluded from keywords trend. Since the word “osteoporosis” was in almost all papers, it was excluded from top keywords to make other keywords clearer.
Fig. 5.
Time trend of top 20 keywords used in published papers by EMRI in the field of osteoporosis (2004–2019)
Table 2 shows the frequency distribution of the papers in each study area. Most studies investigated the risk factors for osteoporosis. After that, diagnostic studies, estimates of incidence and prevalence, and primary prevention of osteoporosis were in the following rank orders. The lowest numbers of the papers were related to the risk assessment studies of osteoporotic fractures, human studies related to osteoporosis treatment, and laboratory and animal studies in the field of osteoporosis.
Table 2.
Frequency distribution of EMRI’s papers on osteoporosis based on their main study area (2004–2019)
| Row | Main area | No. of documents (%) |
|---|---|---|
| 1 | Human studies of osteoporosis risk factors | 115 (56.9) |
| 2 | Human studies of osteoporosis diagnosis | 53 (26.2) |
| 3 | Estimating osteoporosis incidence or prevalence | 52 (25.7) |
| 4 | Primary prevention in osteoporosis | 46 (22.8) |
| 5 | In vitro and animal studies | 34 (16.8) |
| 6 | Human studies of osteoporosis treatment | 32 (15.8) |
| 7 | Osteoporotic fractures risk assessment | 28 (13.9) |
Figure 6 shows the time trend of changes in the number of papers in the seven areas during 2004–2019. The main areas of the first studies on osteoporosis at EMRI were diagnosis and risk factors. During 2006–2007, most of the papers were related to estimating the incidence and prevalence of osteoporosis. Every year since 2008, except for 2011, the largest portion of papers examined the osteoporosis risk factors. In 2011, the largest numbers of papers were for the treatment of osteoporosis by conducting human studies. In Vitro and animal studies in 2015 and 2017, and, primary prevention studies in 2016 were ranked second in terms of frequency. The number of papers related to the diagnosis of osteoporosis and the studies on estimate osteoporosis incidence and prevalence have re-increased since 2018 and 2019 respectively.
Fig. 6.
Time trend of changes in the frequency of EMRI’s publications on osteoporosis based on their main study area (2004–2019)
Discussion
Our study shows a significant contribution of EMRI in some important areas of osteoporosis research during the last 15 years. The number of papers published by the investigators affiliated to EMRI has dramatically increased since 2014. Fluctuations in the number of published papers during the last 15 years reflect the changes in research infrastructures, manpower, and conducted research projects in EMRI. Epidemiology of osteoporosis and its risk factors in Iran, bone turnover markers and their role in treatment monitoring, and dietary factors of osteoporosis, including calcium and vitamin D are among the most frequent subjects investigated by researchers in EMRI.
Although a growing trend of sevenfold compared to its first year is observed in the osteoporosis scientific production of EMRI, it has been accompanied by ups and downs. However, by increasing its scientific collaboration, EMRI is on the path to maturity. Today, group collaboration has become a necessity in scientific research, and depicting the relationships that govern the social networks of scientists (communication and collaboration networks) is a way to show how science is advancing in a scientific field [8]. Also, identifying the status of collaboration between authors plays an important role in future planning and research policies of a specific field and can be effective in revealing the shortcomings and deterrents of group collaboration [9].
Although the report of 150 years of Nature has marked an average of 16 authors per paper in medical and health sciences field [10], this number is 6.72 among EMRI authors. The reason for this noticeable difference in the number of authors seems to be the complexity and breadth of studies in the Nature journal, which demonstrates the need for broader group collaboration. On the other hand, this number of authors indicates that EMRI members understand the effects of group collaboration and are aware of the fact that great work with low-collaborating members cannot be achieved [11]. Therefore, researchers should be encouraged to communicate more with each other to increase the number of collaborations between network members.
In this study, the network of cooperation between EMRI authors was depicted so that the authors could increase their contact circles by observing the current situation and by expanding their participation in scientific discourses, they could expand their working groups and scientific networks [12]
Based on the findings of the present study, EMRI has mainly focused so far on the public health aspects of osteoporosis and its risk factors and consequences fully in line with its commitments as a WHO Collaborating Center. The studies conducted by researchers at EMRI have also provided evidence for well-informed health policymaking at the Ministry of Health and Medical Education. Iranian Multicenter Osteoporosis Studies [13–19] and the vitamin D fortification study [20] are some examples of these studies directly translated into public health interventions at the primary health care level. However, there are other areas that should be addressed more strongly at EMRI.
The mission of Osteoporosis Research Center (ORC) of EMRI is to extend its research activities in the three following areas: i) epidemiological studies and applied health system research, ii) clinical studies including randomized controlled trials of newly developed drugs, iii) basic science research [1]. Besides, it has been planned to contribute in the development of new health technologies related to osteoporosis including diagnostic devices and screening tools and techniques.
To achieve the goals and objectives of EMRI in the field of osteoporosis research and technology, ORC has set several strategies for the next 5 years. Strengthening Iranian Osteoporosis Research Network, extending international collaborations with distinguished institutes engaged in osteoporosis research and related international organizations such as WHO and International Osteoporosis Foundation (IOF), providing financial resources through applying for national and international grants, and building necessary research infrastructures including bio-bank and clinical settings are among the main ones.
Our study had some limitations. We did not consider citations of papers because our PubMed collection didn’t had citation data. Level of evidence (meta-analysis, randomized controlled trials, etc.) was not categorized in our study while describing the level of evidence could be more useful. Although a broad range of keywords were used in our search strategy (see Table 3), some papers may have been missed.
Conclusion
In summary, EMRI has significantly contributed in osteoporosis science and related subjects during recent years, especially in public health aspects of osteoporosis and its risk factors and consequences. More attention should be paid to other areas such clinical and basic science studies.
Acknowledgments
Authors are thankful to the Deputy of Research of EMRI for the support and guidance in conducting this study.
Availability of data and material
All data used in this research are available at Web of Science, PubMed, and Scopus databases.
Appendix
Funding information
This study was supported by Deputy of Research of EMRI.
Compliance with ethical standards
Conflicts of interest/competing interests
KK, NF, FH, MS, NM, BL, and AO are affiliated to EMRI.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
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Data Availability Statement
All data used in this research are available at Web of Science, PubMed, and Scopus databases.