Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 549

The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.

Association Between Serum Uric Acid and Development of Type 2 Diabetes

Open access
Kodama, Satoru, Saito, Kazumi, Yachi, Yoko, Asumi, Mihoko, Sugawara, Ayumi, Totsuka, Kumiko, Saito, Aki, Sone, Hirohito·2009·Diabetes Care

Abstract

OBJECTIVE: To systematically evaluate the association between serum uric acid (SUA) level and subsequent development of type 2 diabetes. RESEARCH DESIGN AND METHODS: We searched Medline (31 March from 1966 to 2009) and Embase (31 March from 1980 to 2009) for observational cohort studies examining the association between SUA and the risk of type 2 diabetes by manual literature search. Relative risks (RRs) for each 1 mg/dl increase in SUA were pooled by using a random-effects model. The studies included were stratified into subgroups representing different study characteristics, and meta-regression analyses were performed to investigate the effect of these characteristics on the association between SUA level and type 2 diabetes risk. RESULTS: The search yielded 11 cohort studies (42,834 participants) that reported 3,305 incident cases of type 2 diabetes during follow-up periods ranging from 2.0 to 13.5 years. The pooled RR of a 1 mg/dl increase in SUA was 1.17 (95% CI 1.09–1.25). Study results were consistently significant (i.e., >1) across characteristics of participants and study design. Publication bias was both visually and statistically suggested (P = 0.03 for Egger's test, 0.06). Adjustment for publication bias attenuated the pooled RR per mg/dl increase in SUA (RR 1.11 [95% CI 1.03–1.20]), but the association remained statistically significant (P = 0.009). CONCLUSIONS: The current meta-analysis suggests that SUA level is positively associated with the development of type 2 diabetes regardless of various study characteristics. Further research should attempt to determine whether it is effective to utilize SUA level as a predictor of type 2 diabetes for its primary prevention.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.2337/dc09-0288

Cites

34 of 34 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 34 references

Cited by

See all 549

Metadata

Authors
Kodama, S., Saito, K., Yachi, Y., Asumi, M., Sugawara, A., Totsuka, K., Saito, A., & Sone, H.
Venue
Diabetes Care
Published
2009-06-23
Volume
32
Issue
9
Pages
1737-1742
ISSN
  • 0149-5992 (ISSN-L)
  • 1935-5548
OpenAlex
W2098458611
Cited by
549
References
34
FWCI
10.93
Type
journal article
Language
en
Open access
hybrid

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Association Between Serum Uric Acid and Development of Type 2 Diabetes. https://app.cochat.ai/papers/10.2337/dc09-0288
The paper
Kodama, S., Saito, K., Yachi, Y., Asumi, M., Sugawara, A., Totsuka, K., Saito, A., & Sone, H. (2009). Association Between Serum Uric Acid and Development of Type 2 Diabetes. Diabetes Care. https://doi.org/10.2337/dc09-0288

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.