Relationship between traditional and non-traditional obesity parameters and diabetes and early-onset diabetes: an analysis based on a large cohort

传统和非传统肥胖参数与糖尿病及早发性糖尿病的关系:基于大型队列的分析

阅读:2

Abstract

BACKGROUND: Diabetes mellitus (DM), especially early-onset DM, poses a growing global health challenge. While body mass index (BMI) is commonly used to assess obesity, it does not adequately capture fat distribution or metabolic risk. Alternative indices such as waist-to-height ratio (WHtR) and conicity index (CI) may better predict diabetes risk, particularly in younger populations. METHODS: This cohort study included 15,453 participants for overall DM risk analysis (mean follow-up: 6.04 years, range: 0.45-12.96) and 5,584 participants under age 40 for early-onset DM (mean follow-up: 3.38 years, range: 0.47-12.32). Ten obesity-related indices were evaluated. Cox regression models estimated the association between each index and the incidence of DM and early-onset DM. Time-dependent receiver operating characteristic (ROC) curves and C-index are used to assess discriminatory performance. RESULTS: During follow-up, 373 cases of DM and 29 cases of early-onset DM were identified. WHtR showed the strongest association with DM risk (HR per SD=1.39; 95% CI: 1.24-1.56), while CI had the strongest association with early-onset DM (HR per SD=2.63; 95% CI: 1.88-3.66). The cardiovascular metabolic index (CMI) had the highest area under the ROC curve (AUC) for assessing short-term DM risk, while lipid accumulation products (LAP) had the highest AUC value for medium- to long-term DM risk. WHtR had the highest AUC of 0.80 in assessing the risk of early-onset DM. CONCLUSIONS: Several non-traditional obesity indices, particularly WHtR, CI, CMI, and LAP, are superior to BMI in assessing the risk of DM or early-onset DM. These indices may offer valuable tools for early detection and personalized prevention strategies in clinical practice.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。