Department of Community Medicine, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia.
School of Public Health, Dow University of Health Sciences (DUHS), Karachi, Pakistan.
Front Endocrinol (Lausanne). 2023 Oct 9;14:1223424. doi: 10.3389/fendo.2023.1223424. eCollection 2023.
Anthropometric indices are affordable and non-invasive methods for screening metabolic syndrome (MetS). However, determining the most effective index for screening can be challenging.
To investigate the accuracy of anthropometric indices as a screening tool for predicting MetS among apparently healthy individuals in Karachi, Pakistan.
A community-based cross-sectional survey was conducted in Karachi, Pakistan, from February 2022 to August 2022. A total of 1,065 apparently healthy individuals aged 25 years and above were included. MetS was diagnosed using International Diabetes Federation guidelines. Anthropometric indices were defined based on body mass index (BMI), neck circumference (NC), mid-upper arm circumference (MUAC), waist circumference (WC), waist to height ratio (WHtR), conicity index, reciprocal ponderal index (RPI), body shape index (BSI), and visceral adiposity index (VAI). The analysis involved the utilization of Pearson's correlation test and independent t-test to examine inferential statistics. The receiver operating characteristic (ROC) analysis was also applied to evaluate the predictive capacities of various anthropometric indices regarding metabolic risk factors. Moreover, the area under the curve (AUC) was computed, and the chosen anthropometric indices' optimal cutoff values were determined.
All anthropometric indices, except for RPI in males and BSI in females, were significantly higher in MetS than those without MetS. VAI [AUC 0.820 (95% CI 0.78-0.86)], WC [AUC 0.751 (95% CI 0.72-0.79)], WHtR [AUC 0.732 (95% CI 0.69-0.77)], and BMI [AUC 0.708 (95% CI 0.66-0.75)] had significantly higher AUC for predicting MetS in males, whereas VAI [AUC 0.693 (95% CI 0.64-0.75)], WHtR [AUC 0.649 (95% CI 0.59-0.70)], WC [AUC 0.646 (95% CI 0.59-0.61)], BMI [AUC 0.641 (95% CI 0.59-0.69)], and MUAC [AUC 0.626 (95% CI 0.57-0.68)] had significantly higher AUC for predicting MetS in females. The AUC of NC for males was 0.656 (95% CI 0.61-0.70), while that for females was 0.580 (95% CI 0.52-0.64). The optimal cutoff points for all anthropometric indices exhibited a high degree of sensitivity and specificity in predicting the onset of MetS.
BMI, WC, WHtR, and VAI were the most important anthropometric predictors for MetS in apparently healthy individuals of Pakistan, while BSI was found to be the weakest indicator.
人体测量学指数是一种经济实惠且非侵入性的方法，可用于筛查代谢综合征（MetS）。然而，确定最有效的指数来进行筛查可能具有挑战性。
研究人体测量学指数作为一种筛查工具，用于预测巴基斯坦卡拉奇地区看似健康人群中的代谢综合征。
本研究是一项在巴基斯坦卡拉奇进行的基于社区的横断面调查，时间为 2022 年 2 月至 2022 年 8 月。共纳入了 1065 名年龄在 25 岁及以上的看似健康的个体。代谢综合征的诊断采用国际糖尿病联合会的指南。根据体重指数（BMI）、颈围（NC）、中上臂围（MUAC）、腰围（WC）、腰高比（WHtR）、锥度指数、倒数体重指数（RPI）、身体形状指数（BSI）和内脏脂肪指数（VAI）来定义人体测量学指数。分析包括使用 Pearson 相关检验和独立 t 检验来进行推断统计学检验。还应用了受试者工作特征（ROC）分析来评估各种人体测量学指数对代谢风险因素的预测能力。此外，计算了曲线下面积（AUC），并确定了所选人体测量学指数的最佳截断值。
除了男性的 RPI 和女性的 BSI 之外，所有人体测量学指数在代谢综合征患者中均显著高于无代谢综合征患者。在男性中，VAI [AUC 0.820（95%CI 0.78-0.86）]、WC [AUC 0.751（95%CI 0.72-0.79）]、WHtR [AUC 0.732（95%CI 0.69-0.77）]和 BMI [AUC 0.708（95%CI 0.66-0.75）]对预测代谢综合征具有更高的 AUC，而 VAI [AUC 0.693（95%CI 0.64-0.75）]、WHtR [AUC 0.649（95%CI 0.59-0.70）]、WC [AUC 0.646（95%CI 0.59-0.61）]、BMI [AUC 0.641（95%CI 0.59-0.69）]和 MUAC [AUC 0.626（95%CI 0.57-0.68）]对预测女性代谢综合征具有更高的 AUC。男性 NC 的 AUC 为 0.656（95%CI 0.61-0.70），而女性 NC 的 AUC 为 0.580（95%CI 0.52-0.64）。所有人体测量学指数的最佳截断点在预测代谢综合征的发生方面均表现出较高的敏感性和特异性。
BMI、WC、WHtR 和 VAI 是巴基斯坦看似健康人群中代谢综合征最重要的人体预测指标，而 BSI 则是最弱的指标。
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