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.

Aim: To investigate the association of erectile dysfunction (ED) and osteoporosis in all-aged (18-87 years) males, and by comparing models with or without ED, explore the ability of ED to assess the prevalence of osteoporosis. Methods: We performed a cross-sectional study in Southern China based on the community population from March to July 2015 and 998 eligible individuals ages form 18 to 87 years were included. The diagnosis of ED was based on self-reporting and osteoporosis was defined as a bone mineral density (BMD) of 2.5 standard deviations or below (T score ≤−2.5). Odds ratios (OR) and 95% confidence intervals (95%CI) were calculated in logistic regression model. Lasso regression model was used for feature selection. Receiver operating characteristics (ROC) curve analysis was used to evaluate the ability of the different models to assess the prevalence of osteoporosis. Results: The prevalence of osteoporosis was 1.70-fold higher in the ED group compared with the non-ED group (OR: 1.70, 95%CI: 0.99-2.87, P=0.051) after adjustment in total population. AUC in model with biochemical indices including low density lipoprotein cholesterol (LDL-C) and fasting plasma glucose (FPG), further plus ED was 0.73 (95% CI: 0.68-0.79), which was significantly higher than model only with non-invasive basic clinical parameters (AUC: 0.70, 95% CI: 0.65-0.80). Model included only biochemical indices evaluated the AUC from 0.70 to 0.72 (P=0.050), and further plus ED can significantly evaluated the ability of diagnosis osteoporosis (P=0.017). Conclusions: We found that patients with ED had an increased risk of osteoporosis among the all-age (18-87 years) male population, and the diagnosis ability for osteoporosis significantly evaluated when plus ED. For assessing osteoporosis in male population, the information about ED should be collected.