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Original Article Inverted U-Shaped Associations Between Glycemic Biomed Environ Sci, 2021; 34(1): 9-18 9 Original Article Inverted U-Shaped Associations between Glycemic Indices and Serum Uric Acid Levels in the General Chinese Population: Findings from the China Cardiometabolic Disease and Cancer Cohort (4C) Study* ZHU Yuan Yue1,2,&, ZHENG Rui Zhi1,2,&, WANG Gui Xia3,&, CHEN Li4,&, SHI Li Xin5, SU Qing6, XU Min1,2, XU Yu1,2, CHEN Yu Hong1,2, YU Xue Feng7, YAN Li8, WANG Tian Ge1,2, ZHAO Zhi Yun1,2, QIN Gui Jun9, WAN Qin10, CHEN Gang11, GAO Zheng Nan12, SHEN Fei Xia13, LUO Zuo Jie14, QIN Ying Fen14, HUO Ya Nan15, LI Qiang16, YE Zhen17, ZHANG Yin Fei18, LIU Chao19, WANG You Min20, WU Sheng Li21, YANG Tao22, DENG Hua Cong23, ZHAO Jia Jun24, CHEN Lu Lu25, MU Yi Ming26, TANG Xu Lei27, HU Ru Ying17, WANG Wei Qing1,2, NING Guang1,2, LI Mian1,2,#, LU Jie Li1,2,#, and BI Yu Fang1,2,# 1. Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; 2. Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; 3. The First Hospital of Jilin University, Changchun 130021, Jinlin, China; 4. Qilu Hospital of Shandong University, Jinan 250012, Shandong, China; 5. Affiliated Hospital of Guiyang Medical College, Guiyang 550004, Guizhou, China; 6. Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai 200092, China; 7. Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China; 8. Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, Guangdong, China; 9. The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan, China; 10. The Affiliated Hospital of Southwest Medical University, Luzhou 646099, Sichuan, China; 11. Fujian Provincial Hospital, Fujian Medical University, Fuzhou 350001, Fujian, China; 12. Dalian Municipal Central Hospital, Dalian 116003, Liaoning, China; 13. The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang, China; 14. The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi, China; 15. Jiangxi Provincial People’s Hospital Affiliated to Nanchang University, Nanchang 330006, Jiangxi, China; 16. The Second Affiliated Hospital of Harbin Medical University, Harbin 150086, Heilongjiang, China; 17. Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, Zhejiang, China; 18. Central Hospital of Shanghai Jiading District, Shanghai 201800, China; 19. Jiangsu Province Hospital on Integration of Chinese and Western Medicine, Nanjing 210028, Jiangsu, China; 20. The First Affiliated Hospital of Anhui Medical University, Hefei 230022, Anhui, China; 21. Karamay Municipal People’s Hospital, Karamay 830054, Xinjiang, China; 22. The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China; 23. The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China; 24. Shandong Provincial Hospital affiliated to Shandong University, Jinan 250021, Shandong, China; 25. Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, Hubei, China; 26. Chinese People’s Liberation Army General Hospital, Beijing 100853, China; 27. The First Hospital of Lanzhou University, Lanzhou 730000, Gansu, China *This work is supported by grants from the Ministry of Science and Technology of the People’s Republic of China [grant nos. 2016YFC1305600, 2016YFC1305202, 2016YFC1304904, 2017YFC1310700, and 2018YFC1311800]; the National Natural Science Foundation of China [grant nos. 81970706, 81970691, 81970728, and 81800683]. &These authors contributed equally to this work. #Correspondence should be addressed to LI Mian, MD, PhD, E-mail: [email protected]; LU Jie Li, MD, PhD, E-mail: [email protected]; BI Yu Fang, MD, PhD, Tel: 86-21-64370045, Fax: 86-21-64373514, E-mail: [email protected] Biographical notes of the first authors: ZHU Yuan Yue, female, born in 1995, MD, majoring in clinical epidemiology of diabetes and metabolic diseases; ZHENG Rui Zhi, male, born in 1987, PhD, majoring in epidemiology of metabolic disease; WANG Gui Xia, female, born in 1963, Professor, majoring in diagnosis and treatment of metabolic diseases; CHEN Li, female, born in 1958, Professor, majoring in diagnosis and treatment of endocrine diseases. 10 Biomed Environ Sci, 2021; 34(1): 9-18 Abstract Objective The relationship between serum uric acid (SUA) levels and glycemic indices, including plasma glucose (FPG), 2-hour postload glucose (2h-PG), and glycated hemoglobin (HbA1c), remains inconclusive. We aimed to explore the associations between glycemic indices and SUA levels in the general Chinese population. Methods The current study was a cross-sectional analysis using the first follow-up survey data from The China Cardiometabolic Disease and Cancer Cohort Study. A total of 105,922 community-dwelling adults aged ≥ 40 years underwent the oral glucose tolerance test and uric acid assessment. The nonlinear relationships between glycemic indices and SUA levels were explored using generalized additive models. Results A total of 30,941 men and 62,361 women were eligible for the current analysis. Generalized additive models verified the inverted U-shaped association between glycemic indices and SUA levels, but with different inflection points in men and women. The thresholds for FPG, 2h-PG, and HbA1c for men and women were 6.5/8.0 mmol/L, 11.0/14.0 mmol/L, and 6.1/6.5, respectively (SUA levels increased with increasing glycemic indices before the inflection points and then eventually decreased with further increases in the glycemic indices). Conclusion An inverted U-shaped association was observed between major glycemic indices and uric acid levels in both sexes, while the inflection points were reached earlier in men than in women. Key words: Cross-sectional study; Serum uric acid; Glycemic index; Glycemic status Biomed Environ Sci, 2021; 34(1): 9-18 doi: 10.3967/bes2021.003 ISSN: 0895-3988 www.besjournal.com (full text) CN: 11-2816/Q Copyright ©2021 by China CDC INTRODUCTION across the full spectrum of glucose tolerance in the general population. However, the exact association of ric acid is the final oxidation product of glycemic indices with SUA levels and the risk of purine metabolism. Overproduction or hyperuricemia needs to be elucidated further. Udecreased excretion of serum uric acid Considering the challenge posed by the increasing (SUA) can lead to hyperuricemia, which is strongly prevalence of hyperuricemia and diabetes, a associated with several cardiometabolic diseases[1]. comprehensive description of the association between Notably, recent studies have revealed that glycemic indices and hyperuricemia may be important hyperuricemia is related to an increased risk of for the improvement of public health. Therefore, this diabetes[2-4]. However, only a few studies have cross-sectional study, which included a large sample of evaluated the impact of glucose tolerance or serum participants with a full spectrum of glycemic status, glucose levels on the prevalence of hyperuricemia[5]. aimed to investigate the association between glycemic Several epidemiological studies investigating the indices and hyperuricemia prevalence as well as SUA relationship between glycemic indices and SUA levels levels. have been conducted but reported inconsistent results. For example, a U-shaped relationship was found METHODS between fasting plasma glucose (FPG) and SUA levels in individuals with normal glucose tolerance (NGT)[6], Study Population but a linearly negative relationship was observed between these variables in diabetic patients[7]. A recent The present study was a cross-sectional analysis study showed that the association dynamically of the first follow-up survey for The China changed according to the levels of glucose tolerance[8], Cardiometabolic Disease and Cancer Cohort Study which was confirmed by several other studies[9,10]. The (4C study) during in 2014–2015. The design and controversial conclusions might be attributable to the methodology of the 4C study have been previously heterogeneity in ethnicities and glycemic status of the described in detail elsewhere[11,12]. Among 105,922 participants. To date, few studies have evaluated the adults who underwent SUA and glycemic tests, 7,945 relationship between glycemic indices and SUA levels who used hypoglycemic or hypouricemic drugs were Glycemic indices and serum uric acid levels 11 excluded. As the use of diuretics might affect the eGFR = 141 × min (SCr/k, 1)α × max (SCr/k, 1)−1.209 × metabolism of uric acid[13], 282 individuals 0.993Age (men) (1) undergoing diuretic treatment were excluded. eGFR = 141 × min (SCr/k, 1)α × max (SCr/k, 1)−1.209 × Furthermore, 4,393 individuals with end-stage 0.993Age × 1.018 (women)[15] (2) kidney disease were excluded. Finally, 93,302 Definitions and Diagnostic Criteria individuals (30,941 men and 62,361 women) were included in the current analysis. Glycemic status was defined as follows: NGT, The study protocol was approved by the prediabetes, and diabetes, according to the Institutional Review Board of Ruijin Hospital, recommendations of the 2020 American Diabetes Shanghai Jiao Tong University
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