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01.12.2018 | Research article | Ausgabe 1/2018 Open Access

BMC Geriatrics 1/2018

Using different anthropometric indices to assess prediction ability of type 2 diabetes in elderly population: a 5 year prospective study

Zeitschrift:
BMC Geriatrics > Ausgabe 1/2018
Autoren:
Jing Yang, Fei Wang, Jing Wang, Xu Han, Hua Hu, Caizheng Yu, Jing Yuan, Ping Yao, Xiaoping Miao, Sheng Wei, Youjie Wang, Weihong Chen, Yuan Liang, Huan Guo, Xiaomin Zhang, Dan Zheng, Yuhan Tang, Handong Yang, Meian He
Wichtige Hinweise

Electronic supplementary material

The online version of this article (https://​doi.​org/​10.​1186/​s12877-018-0912-2) contains supplementary material, which is available to authorized users.

Abstract

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.
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