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The Impact of Different Insulin-Related Measures on the Risk of Prediabetes Among the Chinese Han Population

INTRODUCTION: Diabetes mellitus (DM) has a serious impact on people’s lives in the world. Interventions that affect risk factors for prediabetes can prevent and reduce diabetes occurrence. Proinsulin (PI), true insulin (TI), and proinsulin to insulin ratio (PI/TI) are risk factors for diabetes. The...

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Autores principales: Quan, Huibiao, Fang, Tuanyu, Lin, Leweihua, Lin, Lu, Ou, Qianying, Zhang, Huachuan, Chen, Kaining, Zhou, Zhiguang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Healthcare 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8342746/
https://www.ncbi.nlm.nih.gov/pubmed/34236576
http://dx.doi.org/10.1007/s13300-021-01102-1
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author Quan, Huibiao
Fang, Tuanyu
Lin, Leweihua
Lin, Lu
Ou, Qianying
Zhang, Huachuan
Chen, Kaining
Zhou, Zhiguang
author_facet Quan, Huibiao
Fang, Tuanyu
Lin, Leweihua
Lin, Lu
Ou, Qianying
Zhang, Huachuan
Chen, Kaining
Zhou, Zhiguang
author_sort Quan, Huibiao
collection PubMed
description INTRODUCTION: Diabetes mellitus (DM) has a serious impact on people’s lives in the world. Interventions that affect risk factors for prediabetes can prevent and reduce diabetes occurrence. Proinsulin (PI), true insulin (TI), and proinsulin to insulin ratio (PI/TI) are risk factors for diabetes. The roles of these indicators in prediabetes are unclear. This study aimed to evaluate the impact of PI, TI, PI/TI, 2-h proinsulin (2hPI), 2-h true insulin (2hTI), and 2hPI/2hTI on the risk of prediabetes among the Chinese Han population. METHODS: This cross-sectional study recruited 1688 subjects including 718 prediabetes cases and 970 non-prediabetes controls from Hainan Affiliated Hospital of Hainan Medical University. The cases involved 292 men and 426 women. The controls involved 324 men and 646 women. The mean age was 53.62 ± 12.43 years in the prediabetes group and 44.24 ± 12.87 years in the non-prediabetes group. RESULTS: Our results showed that PI, TI, PI/TI, 2hPI, 2hTI, and 2hPI/2hTI were significantly correlated with prediabetes (all p < 0.05). Logistic regression analysis revealed that PI (OR 1.022, 95% CI 1.014–1.031, p = 0.00011), TI (OR 1.005, 95% CI 1.003–1.007, p = 0.00012), PI/TI (OR 1.517, 95% CI 1.080–2.131, p = 0.016), and 2hTI (OR 1.000, 95% CI 1.000–1.001, p = 0.002) were significantly associated with an increased risk of prediabetes. Receiver operating characteristic curve (ROC) analysis indicated that the area under the ROC curve (AUC) of the combination (PI + TI + PI/TI + 2hPI + 2hTI + 2hPI/2hTI) in diagnosing prediabetes was 0.627, which was larger than the diagnostic value of HOMA-IR (AUC 0.614) and HOMA-β (AUC 0.387). CONCLUSIONS: Our study showed that PI, TI, PI/TI, and 2hTI could significantly enhance the risk of prediabetes in the Chinese Han population, which suggested that PI, TI, PI/TI, and 2hTI might be available risk factors for prediabetes.
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spelling pubmed-83427462021-08-20 The Impact of Different Insulin-Related Measures on the Risk of Prediabetes Among the Chinese Han Population Quan, Huibiao Fang, Tuanyu Lin, Leweihua Lin, Lu Ou, Qianying Zhang, Huachuan Chen, Kaining Zhou, Zhiguang Diabetes Ther Original Research INTRODUCTION: Diabetes mellitus (DM) has a serious impact on people’s lives in the world. Interventions that affect risk factors for prediabetes can prevent and reduce diabetes occurrence. Proinsulin (PI), true insulin (TI), and proinsulin to insulin ratio (PI/TI) are risk factors for diabetes. The roles of these indicators in prediabetes are unclear. This study aimed to evaluate the impact of PI, TI, PI/TI, 2-h proinsulin (2hPI), 2-h true insulin (2hTI), and 2hPI/2hTI on the risk of prediabetes among the Chinese Han population. METHODS: This cross-sectional study recruited 1688 subjects including 718 prediabetes cases and 970 non-prediabetes controls from Hainan Affiliated Hospital of Hainan Medical University. The cases involved 292 men and 426 women. The controls involved 324 men and 646 women. The mean age was 53.62 ± 12.43 years in the prediabetes group and 44.24 ± 12.87 years in the non-prediabetes group. RESULTS: Our results showed that PI, TI, PI/TI, 2hPI, 2hTI, and 2hPI/2hTI were significantly correlated with prediabetes (all p < 0.05). Logistic regression analysis revealed that PI (OR 1.022, 95% CI 1.014–1.031, p = 0.00011), TI (OR 1.005, 95% CI 1.003–1.007, p = 0.00012), PI/TI (OR 1.517, 95% CI 1.080–2.131, p = 0.016), and 2hTI (OR 1.000, 95% CI 1.000–1.001, p = 0.002) were significantly associated with an increased risk of prediabetes. Receiver operating characteristic curve (ROC) analysis indicated that the area under the ROC curve (AUC) of the combination (PI + TI + PI/TI + 2hPI + 2hTI + 2hPI/2hTI) in diagnosing prediabetes was 0.627, which was larger than the diagnostic value of HOMA-IR (AUC 0.614) and HOMA-β (AUC 0.387). CONCLUSIONS: Our study showed that PI, TI, PI/TI, and 2hTI could significantly enhance the risk of prediabetes in the Chinese Han population, which suggested that PI, TI, PI/TI, and 2hTI might be available risk factors for prediabetes. Springer Healthcare 2021-07-08 2021-08 /pmc/articles/PMC8342746/ /pubmed/34236576 http://dx.doi.org/10.1007/s13300-021-01102-1 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by-nc/4.0/Open Access This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Original Research
Quan, Huibiao
Fang, Tuanyu
Lin, Leweihua
Lin, Lu
Ou, Qianying
Zhang, Huachuan
Chen, Kaining
Zhou, Zhiguang
The Impact of Different Insulin-Related Measures on the Risk of Prediabetes Among the Chinese Han Population
title The Impact of Different Insulin-Related Measures on the Risk of Prediabetes Among the Chinese Han Population
title_full The Impact of Different Insulin-Related Measures on the Risk of Prediabetes Among the Chinese Han Population
title_fullStr The Impact of Different Insulin-Related Measures on the Risk of Prediabetes Among the Chinese Han Population
title_full_unstemmed The Impact of Different Insulin-Related Measures on the Risk of Prediabetes Among the Chinese Han Population
title_short The Impact of Different Insulin-Related Measures on the Risk of Prediabetes Among the Chinese Han Population
title_sort impact of different insulin-related measures on the risk of prediabetes among the chinese han population
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8342746/
https://www.ncbi.nlm.nih.gov/pubmed/34236576
http://dx.doi.org/10.1007/s13300-021-01102-1
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