A Prediction Model for Prediabetes Risk in Middle-Aged and Elderly Populations: A Prospective Cohort Study in China

Background. To investigate indicators for prediabetes risk and construct a prediction model for prediabetes incidences in China. Methods. In this study, 551 adults aged 40–70 years had normal glucose tolerance (NGT) and normal hemoglobin A1c (HbA1c) levels at baseline. Baseline data including demogr...

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Main Authors: Jiahua Wu, Jiaqiang Zhou, Xueyao Yin, Yixin Chen, Xihua Lin, Zhiye Xu, Hong Li
Format: Article
Language:English
Published: Wiley 2021-01-01
Series:International Journal of Endocrinology
Online Access:http://dx.doi.org/10.1155/2021/2520806
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author Jiahua Wu
Jiaqiang Zhou
Xueyao Yin
Yixin Chen
Xihua Lin
Zhiye Xu
Hong Li
author_facet Jiahua Wu
Jiaqiang Zhou
Xueyao Yin
Yixin Chen
Xihua Lin
Zhiye Xu
Hong Li
author_sort Jiahua Wu
collection DOAJ
description Background. To investigate indicators for prediabetes risk and construct a prediction model for prediabetes incidences in China. Methods. In this study, 551 adults aged 40–70 years had normal glucose tolerance (NGT) and normal hemoglobin A1c (HbA1c) levels at baseline. Baseline data including demographic information, anthropometric measurements, and metabolic profile measurements were collected. The associations between possible indicators and prediabetes were assessed by the Cox proportional-hazards model. The predictive values were evaluated by the area under the receiver operating characteristic (ROC) curve (AUC). Results. During an average of 3.35 years of follow-up, the incidence of prediabetes was found to be 19.96% (n = 110). In the univariate analyses, fasting plasma glucose (FPG), fasting serum insulin (FINS), 2 h plasma glucose (2hPG), HbA1c, serum uric acid (SUA), waist circumference (WC), smoking, and family history of diabetes (FHD) were found to be significantly correlated with prediabetes. In the multivariable analyses, WC (hazard ratio (HR): 1.032; 95% confidence interval (CI): 1.010, 1.053; p=0.003), FHD (HR: 1.824; 95% CI: 1.250, 2.661; p=0.002), HbA1c (HR: 1.825; 95% CI: 1.227, 2.714; p=0.003), and FPG (HR: 2.284; 95% CI: 1.556, 3.352; p<0.001) were found to be independent risk factors for prediabetes. A model that encompassed WC, FHD, HbA1c, and FPG for predicting prediabetes exhibited the largest discriminative ability (AUC: 0.702). Conclusions. WC, FHD, HbA1c, and FPG are independently correlated with the risk of prediabetes. Furthermore, the combination of these predictors enhances the predictive accuracy of prediabetes.
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spelling doaj-art-5271e1a426d1404db8120b776d1ce27d2025-02-03T01:04:24ZengWileyInternational Journal of Endocrinology1687-83452021-01-01202110.1155/2021/2520806A Prediction Model for Prediabetes Risk in Middle-Aged and Elderly Populations: A Prospective Cohort Study in ChinaJiahua Wu0Jiaqiang Zhou1Xueyao Yin2Yixin Chen3Xihua Lin4Zhiye Xu5Hong Li6Department of EndocrinologyDepartment of EndocrinologyDepartment of EndocrinologyDepartment of EndocrinologyDepartment of EndocrinologyDepartment of EndocrinologyDepartment of EndocrinologyBackground. To investigate indicators for prediabetes risk and construct a prediction model for prediabetes incidences in China. Methods. In this study, 551 adults aged 40–70 years had normal glucose tolerance (NGT) and normal hemoglobin A1c (HbA1c) levels at baseline. Baseline data including demographic information, anthropometric measurements, and metabolic profile measurements were collected. The associations between possible indicators and prediabetes were assessed by the Cox proportional-hazards model. The predictive values were evaluated by the area under the receiver operating characteristic (ROC) curve (AUC). Results. During an average of 3.35 years of follow-up, the incidence of prediabetes was found to be 19.96% (n = 110). In the univariate analyses, fasting plasma glucose (FPG), fasting serum insulin (FINS), 2 h plasma glucose (2hPG), HbA1c, serum uric acid (SUA), waist circumference (WC), smoking, and family history of diabetes (FHD) were found to be significantly correlated with prediabetes. In the multivariable analyses, WC (hazard ratio (HR): 1.032; 95% confidence interval (CI): 1.010, 1.053; p=0.003), FHD (HR: 1.824; 95% CI: 1.250, 2.661; p=0.002), HbA1c (HR: 1.825; 95% CI: 1.227, 2.714; p=0.003), and FPG (HR: 2.284; 95% CI: 1.556, 3.352; p<0.001) were found to be independent risk factors for prediabetes. A model that encompassed WC, FHD, HbA1c, and FPG for predicting prediabetes exhibited the largest discriminative ability (AUC: 0.702). Conclusions. WC, FHD, HbA1c, and FPG are independently correlated with the risk of prediabetes. Furthermore, the combination of these predictors enhances the predictive accuracy of prediabetes.http://dx.doi.org/10.1155/2021/2520806
spellingShingle Jiahua Wu
Jiaqiang Zhou
Xueyao Yin
Yixin Chen
Xihua Lin
Zhiye Xu
Hong Li
A Prediction Model for Prediabetes Risk in Middle-Aged and Elderly Populations: A Prospective Cohort Study in China
International Journal of Endocrinology
title A Prediction Model for Prediabetes Risk in Middle-Aged and Elderly Populations: A Prospective Cohort Study in China
title_full A Prediction Model for Prediabetes Risk in Middle-Aged and Elderly Populations: A Prospective Cohort Study in China
title_fullStr A Prediction Model for Prediabetes Risk in Middle-Aged and Elderly Populations: A Prospective Cohort Study in China
title_full_unstemmed A Prediction Model for Prediabetes Risk in Middle-Aged and Elderly Populations: A Prospective Cohort Study in China
title_short A Prediction Model for Prediabetes Risk in Middle-Aged and Elderly Populations: A Prospective Cohort Study in China
title_sort prediction model for prediabetes risk in middle aged and elderly populations a prospective cohort study in china
url http://dx.doi.org/10.1155/2021/2520806
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