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Int. J. Environ. Res. Public Health 2016, 13(9), 879; doi:10.3390/ijerph13090879

Atherogenic Index of Plasma Predicts Hyperuricemia in Rural Population: A Cross-Sectional Study from Northeast China

Department of Cardiology, the First Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang 110001, China
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Academic Editor: Paul B. Tchounwou
Received: 4 July 2016 / Revised: 25 August 2016 / Accepted: 31 August 2016 / Published: 2 September 2016
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Abstract

We aimed to determine the association of atherogenic index of plasma (AIP) with hyperuricemia (HUA) in the rural population of northeast China. This cross-sectional study was conducted in the rural areas of northeast China from January 2012 to August 2013, and the final analysis included data obtained form 5253 men and 6092 women. 1104 participants (9.7%) suffered from HUA. Spearman rank test showed that AIP was positively correlated with uric acid in both sexes (r = 0.310 for men and r = 0.347 for women, both p < 0.001). AIP was classified into three groups: the low (<0.11), the intermediate (0.11–0.21) and the increased (>0.21) risk. The prevalence of HUA increased with AIP. Multivariate logistic regression analysis showed that, compared to the low AIP group, participants in increased AIP group had a 2.536-fold risk for HUA (2.164-fold in male and 2.960-fold in female) after adjustment for covariates. Results of receiver operating characteristic curves showed that the area under the curve (95% confidence intervals) was 0.686 (0.665–0.707) for male and 0.730 (0.706–0.755) for female. We indicated that increased AIP was associated with higher serum uric acid levels and could be identified as an independent risk factor of HUA in the rural population of northeast China. View Full-Text
Keywords: atherogenic index of plasma; hyperuricemia; rural population atherogenic index of plasma; hyperuricemia; rural population
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MDPI and ACS Style

Chang, Y.; Li, Y.; Guo, X.; Guo, L.; Sun, Y. Atherogenic Index of Plasma Predicts Hyperuricemia in Rural Population: A Cross-Sectional Study from Northeast China. Int. J. Environ. Res. Public Health 2016, 13, 879.

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