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Climacteric. 2016 Oct;19(5):463-70. doi: 10.1080/13697137.2016.1200548. Epub 2016 Jun 29.

World-wide architecture of osteoporosis research: density-equalizing mapping studies and gender analysis.

Author information

1
a Department of Obstetrics and Gynecology, Keck School of Medicine , University of Southern California , Los Angeles , California , USA ;
2
b Institute of Occupational Medicine, Social Medicine and Environmental Medicine, Goethe-University , Frankfurt , Germany.

Abstract

OBJECTIVE:

While research activities on osteoporosis grow constantly, no concise description of the global research architecture exists. Hence, we aim to analyze and depict the world-wide scientific output on osteoporosis combining bibliometric tools, density-equalizing mapping projections and gender analysis.

METHOD:

Using the NewQIS platform, we analyzed all osteoporosis-related publications authored from 1900 to 2012 and indexed by the Web of Science. Bibliometric details were analyzed related to quantitative and semi-qualitative aspects.

RESULTS:

The majority of 57 453 identified publications were original research articles. The USA and Western Europe dominated the field regarding cooperation activity, publication and citation performance. Asia, Africa and South America played a minimal role. Gender analysis revealed a dominance of male scientists in almost all countries except Brazil.

CONCLUSION:

Although the scientific performance on osteoporosis is increasing world-wide, a significant disparity in terms of research output was visible between developed and low-income countries. This finding is particularly concerning since epidemiologic evaluations of future osteoporosis prevalences predict enormous challenges for the health-care systems in low-resource countries. Hence, our study underscores the need to address these disparities by fostering future research endeavors in these nations with the aim to successfully prevent a growing global burden related to osteoporosis.

KEYWORDS:

Osteoporosis; density-equalizing mapping; gender analysis; research architecture; scientometrics

PMID:
27352827
DOI:
10.1080/13697137.2016.1200548
[Indexed for MEDLINE]

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