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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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer Healthcare
2021
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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. |
format | Online Article Text |
id | pubmed-8342746 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Healthcare |
record_format | MEDLINE/PubMed |
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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