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Cited by 477

The DOI matches its Crossref record; 66 of the 66 references it cites were found in a registry or an index.

Epidemiology of Gout

Open access
Roddy, Edward, Choi, Hyon K.·2014·Rheumatic Disease Clinics of North America

Abstract

Synopsis Gout is the most prevalent inflammatory arthritis in men. The findings of several epidemiological studies from a diverse range of countries suggest that the prevalence of gout has risen over the last few decades. Whilst incidence data are scarce, data from the US suggests that the incidence of gout is also rising. Evidence from prospective epidemiological studies has confirmed dietary factors (animal purines, alcohol and fructose), obesity, the metabolic syndrome, hypertension, diuretic use, and chronic kidney disease as clinically relevant risk factors for hyperuricemia and gout. Low-fat dairy products, coffee, and vitamin C appear to have a protective effect. Further prospective studies are required to examine other proposed risk factors for hyperuricaemia and gout such as the use of β-blockers and angiotension-II receptor antagonists (other than losartan), obstructive sleep apnoea, and osteoarthritis, and putative protective factors such as calcium-channel blockers and losartan.

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Registry

Crossref · 10.1016/j.rdc.2014.01.001

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Metadata

Authors
Roddy, E., & Choi, H. K.
Venue
Rheumatic Disease Clinics of North America
Publisher
Elsevier BV
Published
2014-05
Volume
40
Issue
2
Pages
155-175
ISSN
0889-857X (ISSN-L)
OpenAlex
W1987339529
Cited by
477
References
66
FWCI
39.74
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Epidemiology of Gout. https://app.cochat.ai/papers/10.1016/j.rdc.2014.01.001
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Roddy, E., & Choi, H. K. (2014). Epidemiology of Gout. Rheumatic Disease Clinics of North America. https://doi.org/10.1016/j.rdc.2014.01.001

Data sources

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.