Background: Research on the relationship between creatinine to body weight ratios (Cre/BW ratios) and the prevalence of diabetes is still lacking. The intention of this research was to explore the potential relationship between Cre/BW ratio and diabetes prevalence in Chinese adults.Methods: This retrospective study was conducted on 199 526 patients in the Chinese Rich Healthcare Group from 2010 to 2016. The participants were divided into four groups on the basis of the quartiles of the Cre/BW ratios. Multivariate multiple imputation and dummy variables were used to handle missing values. Multivariate regression analysis was applied to detect the relationship between Cre/BW and diabetes. A smoothing plot was also used to identify whether there were nonlinear relationships.Results: After handling missing values and adjusting for potential confounders, the multivariate Cox regression analysis results showed that Cre/BW was inversely correlated with diabetes risk (hazard ratio [HR]: 0.268; 95% confidence interval [CI]: 0.229-0.314, p < 0.00001). For men, the HR of incident diabetes was 0.255 (95% CI: 0.212-0.307) and for women it was 0.297 (95% CI: 0.218-0.406). Moreover, sensitivity analysis confirmed the stability of the results. Furthermore, the smoothing plot revealed that there was a saturation effect between Cre/BW and the incidence of diabetes. Conclusions: This study demonstrated that increased Cre/BW is negatively correlated with diabetes in Chinese adults. It also found that Cre/BW has a nonlinear relationship with the incidence of diabetes.
BackgroundThe Metabolic score of insulin resistance (METS-IR) has recently been accepted as a reliable alternative to insulin resistance (IR), which was demonstrated to be consistent with the hyperinsulinemic-euglycemic clamp. Few pieces of research have focused on the relationship between METS-IR and diabetes in Chinese. The purpose of this research was to explore the effect of METS-IR on new-onset diabetes in a large multicenter Chinese study.MethodsAt the baseline of this retrospective longitudinal research, 116855 participators were included in the Chinese cohort study administered from 2010 to 2016. The subjects were stratified by quartiles of METS-IR. To assess the effect of METS-IR on incident diabetes, the Cox regression model was constructed in this study. Stratification analysis and interaction tests were applied to detect the potential effect of METS-IR and incident diabetes among multiple subgroups. To verify whether there was a dose-response relationship between METS-IR and diabetes, a smooth curve fitting was performed. In addition, to further determine the performance of METS -IR in predicting incident diabetes, the receiver operating characteristic curve (ROC) was conducted.ResultsThe average age of the research participators was 44.08 ± 12.93 years, and 62868 (53.8%) were men. METS-IR were significant relationship with new-onset diabetes after adjusting for possible variables (Hazard ratio [HR]: 1.077; 95% confidence interval [CI]: 1.073-1.082, P < 0.0001), the onset risk for diabetes in Quartile 4 group was 6.261-fold higher than those in Quartile 1 group. Moreover, stratified analyses and interaction tests showed that interaction was detected in the subgroup of age, body mass index, systolic blood pressure, diastolic blood pressure, and fasting plasma glucose, there was no significant interaction between males and females. Furthermore, a dose-response correlation was detected between METS-IR and incident diabetes, the nonlinear relationship was revealed and the inflection point of METS-IR was calculated to be 44.43. When METS-IR≥44.43, compared with METS-IR < 44.43, the trend was gradually saturated, with log-likelihood ratio test P < 0.001. Additionally, the area under receiver operating characteristic of the METS-IR in predicting incident diabetes was 0.729, 0.718, and 0.720 at 3, 4, and 5 years, respectively.ConclusionsMETS-IR was correlated with incident diabetes significantly, and showed a nonlinear relationship. This study also found that METS-IR had good discrimination of diabetes.
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