我们的目的是调查胰岛素抵抗(IR)的影响,由胰岛素抵抗的稳态模型评估(HOMA-IR)确定,关于心脏代谢危险因素(CMRFs),并开发了基于人体测量学的中国青少年IR预测列线图。
数据来自分层整群抽样方法的横断面研究,在中国东北的青少年中进行。
共有882名青少年(12-16岁,包括468名男孩)。
所有参与者都接受了人体测量和生化检查。IR的阈值包括每个性别组(CutoffA)内体重指数(BMI)和空腹血糖(FPG)水平正常的青少年的HOMA-IR的第90百分位数,和所有同性参与者的第75百分位数(截止B)。
HOMA-IR与CMRF相关。IR,由截止时间A和B定义,与大多数CMRF显著相关,除了HDL-C水平下降。在诊断IR的这两个标准之间发现了极好的一致性(κ=0.825)。然而,IR使用截止值A,与心脏代谢风险更密切相关。IR的发生率,由截止值A定义,根据不同的BMI类别,为18.93%,从10.99%增加到43.87%。Further,基于人体测量学的红外预测模型,结合性,年龄,腰臀比,体重和BMI,被开发并作为列线图呈现。
青少年的IR与心脏代谢风险密切相关。我们开发了一种基于人体测量学的青少年IR预测列线图,这可能有助于健康咨询和自我风险评估。
We aimed to investigate the impact of insulin resistance (IR), as determined by the homeostasis model assessment of insulin resistance (HOMA-IR), on cardiometabolic risk factors (CMRFs), and develop an anthropometry-based predictive nomogram for IR among adolescents in China.
Data were acquired from a cross-sectional study with a stratified cluster sampling method, conducted among adolescents in Northeast China.
A total of 882 adolescents (aged 12-16 years, 468 boys) were included.
All participants underwent anthropometric and biochemical examinations. The thresholds of IR included the 90th percentile of the HOMA-IR for adolescents with a normal body mass index (BMI) and fasting plasma glucose (FPG) level within each sex group (Cutoff A), and the 75th percentile for all participants of the same sex (Cutoff B).
The HOMA-IR was associated with CMRFs. IR, as defined by both cutoffs A and B, was significantly associated with most CMRFs, except decreased HDL-C levels. Excellent concordance (κ = 0.825) was found between these two criteria in diagnosing IR. However, IR using cutoff A, was more closely associated with cardiometabolic risk. The incidence of IR, as defined by cutoff A, was 18.93% and increased from 10.99% to 43.87% based on the different BMI categories. Further, an anthropometry-based predictive model for IR, incorporating sex, age, waist-to-hip ratio, weight and BMI, was developed and presented as a nomogram.
IR among adolescents is strongly related to cardiometabolic risk. We developed an anthropometry-based predictive nomogram for IR among adolescents, which may facilitate health counselling and self-risk assessments.