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中国东部成年人新型和传统人体测量学指标的比较:哪种指标是代谢肥胖正常体重表型的最佳指标?

Comparison of novel and traditional anthropometric indices in Eastern-China adults: which is the best indicator of the metabolically obese normal weight phenotype?

机构信息

Department of Non-Communicable Chronic Disease Prevention, Nanjing Municipal Center for Disease Control and Prevention, Nanjing, 210003, China.

出版信息

BMC Public Health. 2024 Aug 13;24(1):2192. doi: 10.1186/s12889-024-19638-9.

Abstract

BACKGROUND

People with the metabolically obese normal weight (MONW) phenotype have been confirmed to significantly increase the risk of unfavorable health consequences. This study aimed to investigate the relationships between traditional and novel anthropometric indices with the MONW phenotype and compare the predictive ability of different anthropometric indices in identifying individuals with the MONW phenotype.

METHODS

This cross-sectional study involved a total of 26,332 participants aged 18 years or older with a normal weight from Nanjing, China. Sociodemographic information, biochemical measurements, and anthropometric indices were collected. The novel body fat anthropometric indices included body shape index (ABSI), body roundness index (BRI), abdominal volume index (AVI), weight-adjusted-waist index (WWI), body adiposity index (BAI), conicity index (CI), waist-hip-height ratio (WHHR), as well as traditional indices such as waist circumference (WC), hip circumference (HC), body mass index (BMI), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR).The prevalence ratio (PR) from modified poisson regression and area under the receiver-operating characteristic curve (AUC) were conducted to compare the association and predictive capacity of different obesity indicators for the MONW phenotype. All analyses were stratified by sex.

RESULTS

Modified poisson regression analyses revealed that weight, WC, HC, BMI, WHR, WHtR, ABSI, BRI, AVI, WWI, BAI, CI, and WHHR were independently associated with higher risk of the MONW phenotype, regardless of whether they were treated as a continuous or categorical variable (P < 0.05). Notably, BRI demonstrated the strongest association in both men (highest quartile VS lowest quartile; PR = 3.14, 95%CI, 2.49, 3.96; P < 0.001) and women (PR = 4.63, 95%CI, 3.81, 5.62; P < 0.001). Receiver operating characteristic analysis indicated that AUC for the different anthropometric indices ranged from 0.50 to 0.80. BRI and WHtR had the largest AUC in both males (both AUC = 0.733; 95% CI, 0.717, 0.750) and females (both AUC = 0.773; 95% CI, 0.761, 0.786). The optimal cut-off points for BRI, determined by maximizing the Youden's index, were 3.102 (sensitivity: 63.2%, specificity: 36.2%) in males and 3.136 (sensitivity: 68.9%, specificity: 44.2%) in females. Moreover, BRI and WHtR exhibited the highest diagnostic accuracy in younger age groups, specifically those aged 18-34 in both sexes.

CONCLUSIONS

BRI emerged as the optimal predictor and independent determinant of the MONW phenotype, regardless of gender. This association was particularly pronounced in young individuals.

摘要

背景

代谢正常体重肥胖(MONW)表型的人已被证实会显著增加不良健康后果的风险。本研究旨在探讨传统和新型人体测量指标与 MONW 表型的关系,并比较不同人体测量指标在识别 MONW 表型个体方面的预测能力。

方法

本横断面研究共纳入来自中国南京的 26332 名 18 岁及以上的正常体重成年人。收集社会人口统计学信息、生化测量值和人体测量指标。新型体脂人体测量指标包括身体形状指数(ABSI)、身体圆度指数(BRI)、腹部体积指数(AVI)、体重调整腰围指数(WWI)、体脂指数(BAI)、锥形指数(CI)、腰围-臀围比(WHHR)以及传统指标如腰围(WC)、臀围(HC)、体重指数(BMI)、腰围-臀围比(WHR)和腰围-身高比(WHtR)。采用修正泊松回归分析比较不同肥胖指标与 MONW 表型的关联和预测能力,并计算优势比(PR)和受试者工作特征曲线下面积(AUC)。所有分析均按性别分层。

结果

修正泊松回归分析显示,体重、WC、HC、BMI、WHR、WHtR、ABSI、BRI、AVI、WWI、BAI、CI 和 WHHR 均与 MONW 表型的发生风险呈独立相关,无论它们被视为连续变量还是分类变量(P<0.05)。值得注意的是,BRI 在男性(最高四分位数 VS 最低四分位数;PR=3.14,95%CI,2.49,3.96;P<0.001)和女性(PR=4.63,95%CI,3.81,5.62;P<0.001)中均显示出最强的相关性。受试者工作特征分析表明,不同人体测量指标的 AUC 值范围为 0.50 至 0.80。BRI 和 WHtR 在男性(AUC 均为 0.733;95%CI,0.717,0.750)和女性(AUC 均为 0.773;95%CI,0.761,0.786)中均具有最大的 AUC。通过最大化 Youden 指数确定的 BRI 的最佳截断值为男性 3.102(敏感性:63.2%,特异性:36.2%),女性 3.136(敏感性:68.9%,特异性:44.2%)。此外,BRI 和 WHtR 在年轻人群中(男性和女性均为 18-34 岁)具有最高的诊断准确性。

结论

BRI 是 MONW 表型的最佳预测指标和独立决定因素,无论性别如何。这种关联在年轻个体中更为明显。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78ad/11321156/3222958269f8/12889_2024_19638_Fig1_HTML.jpg

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