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Glucose metabolism indices and the development of chronic kidney disease: a cohort study of middle-aged and elderly Chinese persons
  • +16
  • Lili You,
  • Qiling Feng,
  • Kan Sun,
  • Diaozhu Lin,
  • Chulin Huang,
  • Chaogang Chen,
  • Chuan Wang,
  • Guojuan Lao,
  • Shengneng Xue,
  • Juying Tang,
  • Na Li,
  • Yiqin Qi,
  • Wanting Feng,
  • Feng Li,
  • Chuan Yang,
  • Mingtong Xu,
  • Yan Li,
  • Li Yan,
  • Meng Ren
Lili You
Sun Yat-sen Memorial Hospital, Sun Yat-sen University

Corresponding Author:[email protected]

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Qiling Feng
Sun Yat-sen Memorial Hospital, Sun Yat-sen University
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Kan Sun
Sun Yat-sen Memorial Hospital, Sun Yat-sen University
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Diaozhu Lin
Sun Yat-sen Memorial Hospital, Sun Yat-sen University
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Chulin Huang
Sun Yat-Sen Memorial Hospital
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Chaogang Chen
Sun Yat-sen Memorial Hospital, Sun Yat-sen University
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Chuan Wang
Sun Yat-sen Memorial Hospital, Sun Yat-sen University
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Guojuan Lao
Sun Yat-Sen Memorial Hospital
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Shengneng Xue
Sun Yat-sen Memorial Hospital, Sun Yat-sen University
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Juying Tang
Sun Yat-sen Memorial Hospital, Sun Yat-sen University
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Na Li
Sun Yat-Sen Memorial Hospital
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Yiqin Qi
Sun Yat-sen Memorial Hospital, Sun Yat-sen University
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Wanting Feng
Sun Yat-sen Memorial Hospital, Sun Yat-sen University
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Feng Li
Sun Yat-sen Memorial Hospital, Sun Yat-sen University
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Chuan Yang
Sun Yat-sen Memorial Hospital, Sun Yat-sen University
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Mingtong Xu
Sun Yat-sen Memorial Hospital, Sun Yat-sen University
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Yan Li
Sun Yat-sen Memorial Hospital, Sun Yat-sen University
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Li Yan
Sun Yat-sen Memorial Hospital, Sun Yat-sen University
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Meng Ren
Sun Yat-sen Memorial Hospital, Sun Yat-sen University
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Abstract

Background Chronic kidney disease (CKD) has become a major global health issue, and abnormalities of glucose metabolism are a risk factor responsible for development of CKD. We aimed to investigate associations between glucose metabolism indices and CKD in a Chinese population, and determine which index is superior for predicting incident CKD. Methods This community-based population study included 5232 subjects aged ≥40 years without baseline CKD. CKD was defined as an estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2 or urinary albumin-to-creatinine ration (UACR) ≥30 mg/g. We examined the associations of glucose metabolism indices, including fasting plasma glucose (FPG), 2-hour (2h) oral glucose tolerance test (OGTT), haemoglobin A1c (HbA1c), fasting insulin level, homeostasis model assessment of insulin resistance (HOMA-IR), and HOMA-β and the development of CKD. Results With an average follow-up of 3.6 years, 6.4% of the subjects developed CKD. Pearson’s correlation analysis revealed that FPG, HbA1c, fasting insulin, and HOMA-IR were all significantly correlated with UACR and eGFR. The association persisted in multivariate linear regression analysis adjusted for age and sex. Compared with other glucose indices, HOMA-IR exhibited the strongest associations with CKD in COX multivariate regression analysis (HR = 1.17, 95% CI: 1.04-1.31). Conclusion HOMA-IR is superior to other routine indices of glucose metabolism for predicting the development of CKD in middle-aged Chinese persons. Screening with HOMA-IR may help prevent the development of CKD in the general population.