Zhou Yulin, Hou Yanan, Xiang Jiali, Dai Huajie, Li Mian, Wang Tiange, Wang Shuangyuan, Lin Hong, Lu Jieli, Xu Yu, Chen Yuhong, Wang Weiqing, Bi Yufang, Xu Min, Zhao Zhiyun
Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, 200025, Shanghai, China.
Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Nutr Metab (Lond). 2021 Dec 7;18(1):103. doi: 10.1186/s12986-021-00629-1.
We aimed to define refined body shapes by using multiple anthropometric traits that represent fat distribution, and evaluate their associations with risk of insulin resistance (IR) and cardiometabolic disorders in a Chinese population.
We performed a cross-sectional analysis in 6570 community-based participants aged ≥ 40 years. Four body circumferences (neck, waist, hip, and thigh) and their ratios were put simultaneously into an open-source Waikato Environment for Knowledge Analysis platform to select the worthiest indicators in determining IR. The ratio of the top 3 fat distribution indicators was used to define the refined body shapes.
We defined 8 distinct body shapes based on sex-specific combinations of waist-to-hip ratio (WHR), waist-to-thigh ratio (WTR), and waist-to-neck ratio (WNR), which differed in participants' distribution and risk of IR and related cardiometabolic disorders. In women, as compared to the low WHR-low WTR-low WNR shape, all body shapes were significantly associated with IR and related cardiometabolic disorders; while in men, the low WHR-high WTR-high WNR shape and the higher WHR related shapes were significantly associated with IR and related cardiometabolic disorders. Stratified by WHR, the results were consistent in women; however, no significant associations were detected in men.
We defined 8 distinct body shapes by taking WHR, WTR, and WNR, simultaneously into account, which differed in association with the risk of IR and related cardiometabolic disorders in women. This study suggests that body shapes defined by multiple anthropometric traits could provide a useful, convenient, and easily available method for identifying cardiometabolic risk.
我们旨在通过使用代表脂肪分布的多种人体测量特征来定义精细的体型,并评估它们与中国人群胰岛素抵抗(IR)和心脏代谢紊乱风险的关联。
我们对6570名年龄≥40岁的社区参与者进行了横断面分析。将四个身体周长(颈部、腰部、臀部和大腿)及其比率同时输入到开源的怀卡托知识分析环境平台中,以选择在确定IR方面最有价值的指标。使用前3个脂肪分布指标的比率来定义精细的体型。
我们根据腰臀比(WHR)、腰大腿比(WTR)和腰颈比(WNR)的性别特异性组合定义了8种不同的体型,这些体型在参与者的IR分布和风险以及相关心脏代谢紊乱方面存在差异。在女性中,与低WHR-低WTR-低WNR体型相比,所有体型均与IR及相关心脏代谢紊乱显著相关;而在男性中,低WHR-高WTR-高WNR体型和较高WHR相关体型与IR及相关心脏代谢紊乱显著相关。按WHR分层,女性的结果一致;然而,在男性中未检测到显著关联。
我们同时考虑WHR、WTR和WNR定义了8种不同的体型,这些体型与女性IR及相关心脏代谢紊乱风险的关联有所不同。本研究表明,由多种人体测量特征定义的体型可为识别心脏代谢风险提供一种有用、便捷且易于获得的方法。