The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
High Serum Uric Acid and Increased Risk of Type 2 Diabetes: A Systemic Review and Meta-Analysis of Prospective Cohort Studies
Open accessAbstract
OBJECTIVE: Current evidence suggests high serum uric acid may increase the risk of type 2 diabetes, but the association is still uncertain. The aim of the study was to evaluate the association between serum uric acid and future risk of type 2 diabetes by conducting a meta-analysis of prospective cohort studies. DESIGN AND METHODS: We conducted a systematic literature search of the PubMed database through April 2012. Prospective cohort studies were included in meta-analysis that reported the multivariate adjusted relative risks (RRs) and the corresponding 95% confidence intervals (CIs) for the association between serum uric acid and risk of type 2 diabetes. We used both fix-effects and random-effects models to calculate the overall effect estimate. The heterogeneity across studies was tested by both Q statistic and I(2) statistic. Begg's funnel plot and Egger's regression test were used to assess the potential publication bias. RESULTS: We retrieved 7 eligible articles derived from 8 prospective cohort studies, involving a total of 32016 participants and 2930 incident type 2 diabetes. The combined RR of developing type 2 diabetes for the highest category of serum uric acid level compared with the lowest was 1.56(95% CI, 1.39-1.76). Dose-response analysis showed the risk of type 2 diabetes was increased by 6% per 1 mg/dl increment in serum uric acid level (RR 1.06, 95% CI: 1.04-1.07). The result from each subgroup showed a significant association between serum uric acid and risk of type 2 diabetes. In sensitive analysis, the combined RR was consistent every time omitting any one study. Little evidence of heterogeneity and publication bias was observed. CONCLUSIONS: Our meta-analysis of prospective cohort studies provided strong evidence that high level of serum uric acid is independent of other established risk factors, especially metabolic syndrome components, for developing type 2 diabetes in middle-aged and older people.
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Meta-analysis of Observational Studies in Epidemiology<SUBTITLE>A Proposal for Reporting</SUBTITLE>
Stroup, D. F. (2000) · JAMA · doi:10.1001/jama.283.15.2008 · Cited by 20,623
Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement
Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2010) · International Journal of Surgery · doi:10.1016/j.ijsu.2010.02.007 · Cited by 12,156
Methods for Trend Estimation from Summarized Dose-Response Data, with Applications to Meta-Analysis
Greenland, S., & Longnecker, M. P. (1992) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a116237 · Cited by 2,353
Perry, I. J., Wannamethee, S. G., Walker, M. K., Thomson, A. G., Whincup, P. H., & Shaper, A. G. (1995) · BMJ · doi:10.1136/bmj.310.6979.560 · Cited by 532
Plasma uric acid and the risk of type 2 diabetes in a Chinese community
Chien, K.-L., Chen, M.-F., Hsu, H.-C., Chang, W.-T., Su, T.-C., Lee, Y.-T., & Hu, F. B. (2008) · Clinical Chemistry · doi:10.1373/clinchem.2007.095190 · Cited by 172
Cited by
Guo, P., Furnary, T., Vasiliou, V., Yan, Q., Nyhan, K., Jones, D. P., Johnson, C. H., & Liew, Z. (2022) · Environment International · doi:10.1016/j.envint.2022.107159 · Cited by 145
Navaeian, M., Asadian, S., Ahmadpour Yazdi, H., & Gheibi, N. (2021) · Molecular Biology Reports · doi:10.1007/s11033-021-06270-8 · Cited by 14
Metadata
- Authors
- Lv, Q., Meng, X.-F., He, F.-F., Chen, S., Su, H., Xiong, J., Gao, P., Tian, X.-J., Liu, J.-S., Zhu, Z.-H., Huang, K., & Zhang, C.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2013-02-20
- Volume
- 8
- Issue
- 2
- Pages
- e56864
- ISSN
- 1932-6203 (ISSN-L)
- OpenAlex
- W1984782606
- Cited by
- 364
- References
- 5
- FWCI
- 2.88
- Type
- journal article
- Language
- en
- Open access
- gold
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