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Using different anthropometric indices to assess prediction ability of type 2 diabetes in elderly population: a 5 year prospective study
BACKGROUND: Emerging studies have investigated the association between different anthropometric indices with diabetes risk but the results were inconsistent. The aims of the study were to examine the associations of different anthropometric indices with incident diabetes risk and whether novel anthr...
Autores principales: | , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6142386/ https://www.ncbi.nlm.nih.gov/pubmed/30223783 http://dx.doi.org/10.1186/s12877-018-0912-2 |
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author | Yang, Jing Wang, Fei Wang, Jing Han, Xu Hu, Hua Yu, Caizheng Yuan, Jing Yao, Ping Miao, Xiaoping Wei, Sheng Wang, Youjie Chen, Weihong Liang, Yuan Guo, Huan Zhang, Xiaomin Zheng, Dan Tang, Yuhan Yang, Handong He, Meian |
author_facet | Yang, Jing Wang, Fei Wang, Jing Han, Xu Hu, Hua Yu, Caizheng Yuan, Jing Yao, Ping Miao, Xiaoping Wei, Sheng Wang, Youjie Chen, Weihong Liang, Yuan Guo, Huan Zhang, Xiaomin Zheng, Dan Tang, Yuhan Yang, Handong He, Meian |
author_sort | Yang, Jing |
collection | PubMed |
description | BACKGROUND: Emerging studies have investigated the association between different anthropometric indices with diabetes risk but the results were inconsistent. The aims of the study were to examine the associations of different anthropometric indices with incident diabetes risk and whether novel anthropometric indices improve diabetes prediction beyond traditional indices among elderly Chinese. METHODS: Nine thousand nine hundred sixty-two elderly individuals (age ≥ 60 years old) derived from the prospective Dongfeng-Tongji cohort were included. Hazard ratio (HR) and corresponding 95% confidence interval (CI) were evaluated by Cox proportional hazard model to examine the associations between traditional anthropometric indices (body mass index [BMI], waist circumference [WC], waist-to-height ratio [WHtR]), novel anthropometric indices (visceral adiposity index [VAI], a body shape index [ABSI], body roundness index [BRI]) and diabetes risk. Receiver operating characteristic (ROC) curve and area under curve (AUC) were applied to compare the novel anthropometric indices with the traditional indices in diabetes prediction. RESULTS: During mean 4.6 years of follow-up, 614 incident cases of type 2 diabetes (T2D) were identified. Significant positive associations were detected between BMI, WC, WHtR, VAI and BRI and incident T2D risk. For ABSI, no significant association was observed in either men or women. BMI was the strongest predictor in diabetes in men (AUC = 0.655) comparable with the other anthropometric indices (P < 0.05). Similar as men, BMI was the strongest predictor (AUC = 0.635) in women. Except for WC, the AUC of BMI was larger than WHtR, VAI, and BRI. In contrast, ABSI was not a good predictor in either men (AUC = 0.507) or women (AUC = 0.503). CONCLUSIONS: In elderly Chinese, BMI, WC, WHtR, VAI and BRI were positively associated with incident T2D risk. Among them, BMI was the strongest predictor in both men and women. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12877-018-0912-2) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6142386 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-61423862018-09-20 Using different anthropometric indices to assess prediction ability of type 2 diabetes in elderly population: a 5 year prospective study Yang, Jing Wang, Fei Wang, Jing Han, Xu Hu, Hua Yu, Caizheng Yuan, Jing Yao, Ping Miao, Xiaoping Wei, Sheng Wang, Youjie Chen, Weihong Liang, Yuan Guo, Huan Zhang, Xiaomin Zheng, Dan Tang, Yuhan Yang, Handong He, Meian BMC Geriatr Research Article BACKGROUND: Emerging studies have investigated the association between different anthropometric indices with diabetes risk but the results were inconsistent. The aims of the study were to examine the associations of different anthropometric indices with incident diabetes risk and whether novel anthropometric indices improve diabetes prediction beyond traditional indices among elderly Chinese. METHODS: Nine thousand nine hundred sixty-two elderly individuals (age ≥ 60 years old) derived from the prospective Dongfeng-Tongji cohort were included. Hazard ratio (HR) and corresponding 95% confidence interval (CI) were evaluated by Cox proportional hazard model to examine the associations between traditional anthropometric indices (body mass index [BMI], waist circumference [WC], waist-to-height ratio [WHtR]), novel anthropometric indices (visceral adiposity index [VAI], a body shape index [ABSI], body roundness index [BRI]) and diabetes risk. Receiver operating characteristic (ROC) curve and area under curve (AUC) were applied to compare the novel anthropometric indices with the traditional indices in diabetes prediction. RESULTS: During mean 4.6 years of follow-up, 614 incident cases of type 2 diabetes (T2D) were identified. Significant positive associations were detected between BMI, WC, WHtR, VAI and BRI and incident T2D risk. For ABSI, no significant association was observed in either men or women. BMI was the strongest predictor in diabetes in men (AUC = 0.655) comparable with the other anthropometric indices (P < 0.05). Similar as men, BMI was the strongest predictor (AUC = 0.635) in women. Except for WC, the AUC of BMI was larger than WHtR, VAI, and BRI. In contrast, ABSI was not a good predictor in either men (AUC = 0.507) or women (AUC = 0.503). CONCLUSIONS: In elderly Chinese, BMI, WC, WHtR, VAI and BRI were positively associated with incident T2D risk. Among them, BMI was the strongest predictor in both men and women. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12877-018-0912-2) contains supplementary material, which is available to authorized users. BioMed Central 2018-09-17 /pmc/articles/PMC6142386/ /pubmed/30223783 http://dx.doi.org/10.1186/s12877-018-0912-2 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Yang, Jing Wang, Fei Wang, Jing Han, Xu Hu, Hua Yu, Caizheng Yuan, Jing Yao, Ping Miao, Xiaoping Wei, Sheng Wang, Youjie Chen, Weihong Liang, Yuan Guo, Huan Zhang, Xiaomin Zheng, Dan Tang, Yuhan Yang, Handong He, Meian Using different anthropometric indices to assess prediction ability of type 2 diabetes in elderly population: a 5 year prospective study |
title | Using different anthropometric indices to assess prediction ability of type 2 diabetes in elderly population: a 5 year prospective study |
title_full | Using different anthropometric indices to assess prediction ability of type 2 diabetes in elderly population: a 5 year prospective study |
title_fullStr | Using different anthropometric indices to assess prediction ability of type 2 diabetes in elderly population: a 5 year prospective study |
title_full_unstemmed | Using different anthropometric indices to assess prediction ability of type 2 diabetes in elderly population: a 5 year prospective study |
title_short | Using different anthropometric indices to assess prediction ability of type 2 diabetes in elderly population: a 5 year prospective study |
title_sort | using different anthropometric indices to assess prediction ability of type 2 diabetes in elderly population: a 5 year prospective study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6142386/ https://www.ncbi.nlm.nih.gov/pubmed/30223783 http://dx.doi.org/10.1186/s12877-018-0912-2 |
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