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Identifying obesity indicators which best correlate with type 2 diabetes in a Chinese population
BACKGROUND: Obesity has been shown to be a prognostic indicator of type 2 diabetes (T2D); however, the power of different obesity indicators in the detection of T2D remains controversial. This study evaluates the detecting power of body mass index (BMI), waist circumference (WC), waist-to-hip ratio...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3490952/ https://www.ncbi.nlm.nih.gov/pubmed/22937748 http://dx.doi.org/10.1186/1471-2458-12-732 |
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author | Xin, Zhong Liu, Chang Niu, Wen-Yan Feng, Jian-Ping Zhao, Lei Ma, Ya-Hong Hua, Lin Yang, Jin-Kui |
author_facet | Xin, Zhong Liu, Chang Niu, Wen-Yan Feng, Jian-Ping Zhao, Lei Ma, Ya-Hong Hua, Lin Yang, Jin-Kui |
author_sort | Xin, Zhong |
collection | PubMed |
description | BACKGROUND: Obesity has been shown to be a prognostic indicator of type 2 diabetes (T2D); however, the power of different obesity indicators in the detection of T2D remains controversial. This study evaluates the detecting power of body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR) and waist-to-height ratio (WHTR) for the presence of T2D in undiagnosed diabetics among the Chinese population. METHODS: Individuals were selected from an ongoing large-scale population-based Beijing Community Pre-Diabetes (BCPD) study cohort. The oral glucose tolerance tests (OGTT) were performed to diagnose diabetes. A total of 220 new cases of T2D and 1,868 normal blood glucose subjects were analyzed. ROC curve analyses were used to compare the association of different obesity indicators with T2D and determine the optimal cut-off points of the best predictor for identifying T2D in men and women. RESULTS: All indicators positively correlated with presence of T2D in both men and women. In women, WC, WHR and WHTR were similar, but were better in identifying T2D when compared to BMI (P < 0.0001, P=0.0016 and P=0.0001, respectively). In men, WC, WHTR and BMI were similar, but WC and WHTR were better than WHR (P=0.0234, P=0.0101, respectively). For women, 86 cm was the optimal WC cut-off point, and its sensitivity and specificity were 0.714 and 0.616; for men, the optimal cut-off point was 90 cm, and its sensitivity and specificity were 0.722 and 0.571. CONCLUSION: Compared with BMI, WHR and WHTR, WC is a simple and accurate measure for predicting T2D in the Chinese population. |
format | Online Article Text |
id | pubmed-3490952 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-34909522012-11-09 Identifying obesity indicators which best correlate with type 2 diabetes in a Chinese population Xin, Zhong Liu, Chang Niu, Wen-Yan Feng, Jian-Ping Zhao, Lei Ma, Ya-Hong Hua, Lin Yang, Jin-Kui BMC Public Health Research Article BACKGROUND: Obesity has been shown to be a prognostic indicator of type 2 diabetes (T2D); however, the power of different obesity indicators in the detection of T2D remains controversial. This study evaluates the detecting power of body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR) and waist-to-height ratio (WHTR) for the presence of T2D in undiagnosed diabetics among the Chinese population. METHODS: Individuals were selected from an ongoing large-scale population-based Beijing Community Pre-Diabetes (BCPD) study cohort. The oral glucose tolerance tests (OGTT) were performed to diagnose diabetes. A total of 220 new cases of T2D and 1,868 normal blood glucose subjects were analyzed. ROC curve analyses were used to compare the association of different obesity indicators with T2D and determine the optimal cut-off points of the best predictor for identifying T2D in men and women. RESULTS: All indicators positively correlated with presence of T2D in both men and women. In women, WC, WHR and WHTR were similar, but were better in identifying T2D when compared to BMI (P < 0.0001, P=0.0016 and P=0.0001, respectively). In men, WC, WHTR and BMI were similar, but WC and WHTR were better than WHR (P=0.0234, P=0.0101, respectively). For women, 86 cm was the optimal WC cut-off point, and its sensitivity and specificity were 0.714 and 0.616; for men, the optimal cut-off point was 90 cm, and its sensitivity and specificity were 0.722 and 0.571. CONCLUSION: Compared with BMI, WHR and WHTR, WC is a simple and accurate measure for predicting T2D in the Chinese population. BioMed Central 2012-09-01 /pmc/articles/PMC3490952/ /pubmed/22937748 http://dx.doi.org/10.1186/1471-2458-12-732 Text en Copyright ©2012 Xin et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Xin, Zhong Liu, Chang Niu, Wen-Yan Feng, Jian-Ping Zhao, Lei Ma, Ya-Hong Hua, Lin Yang, Jin-Kui Identifying obesity indicators which best correlate with type 2 diabetes in a Chinese population |
title | Identifying obesity indicators which best correlate with type 2 diabetes in a Chinese population |
title_full | Identifying obesity indicators which best correlate with type 2 diabetes in a Chinese population |
title_fullStr | Identifying obesity indicators which best correlate with type 2 diabetes in a Chinese population |
title_full_unstemmed | Identifying obesity indicators which best correlate with type 2 diabetes in a Chinese population |
title_short | Identifying obesity indicators which best correlate with type 2 diabetes in a Chinese population |
title_sort | identifying obesity indicators which best correlate with type 2 diabetes in a chinese population |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3490952/ https://www.ncbi.nlm.nih.gov/pubmed/22937748 http://dx.doi.org/10.1186/1471-2458-12-732 |
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