PDF(Pubmed)
Abstract：
To predict the optimal cut-off values for screening and predicting metabolic syndrome(MetS) in a middle-aged and elderly Chinese population using 13 obesity and lipid-related indicators, and to identify the most suitable predictors.
The data for this cross-sectional investigation came from the China Health and Retirement Longitudinal Study (CHARLS), including 9457 middle-aged and elderly people aged 45-98 years old. We examined 13 indicators, including waist circumference (WC), body mass index (BMI), waist-height ratio (WHtR), visceral adiposity index (VAI), a body shape index (ABSI), body roundness index (BRI), lipid accumulation product index (LAP), conicity index (CI), Chinese visceral adiposity index (CVAI), triglyceride-glucose index (TyG-index) and their combined indices (TyG-BMI, TyG-WC, TyG-WHtR). The receiver operating characteristic curve (ROC) was used to determine the usefulness of indicators for screening for MetS in the elderly and to determine their cut-off values, sensitivity, specificity, and area under the curve (AUC). Association analysis of 13 obesity-related indicators with MetS was performed using binary logistic regression analysis.
A total of 9457 middle-aged and elderly Chinese were included in this study, and the overall prevalence of the study population was 41.87% according to the diagnostic criteria of NCEP ATP III. According to age and gender, the percentage of males diagnosed with MetS was 30.67% (45-54 years old: 30.95%, 55-64 years old: 41.02%, 65-74 years old: 21.19%, ≥ 75 years old: 6.84%). The percentage of females diagnosed with MetS was 51.38% (45-54 years old: 31.95%, 55-64 years old: 39.52%, 65-74 years old: 20.43%, ≥ 75 years old: 8.10%). The predictive power of Tyg-related parameters was more prominent in both sexes. In addition, LAP and CVAI are also good at predicting MetS. ABSI had a poor prediction ability.
Among the middle-aged and elderly population in China, after adjusting for confounding factors, all the indicators except ABSI had good predictive power. The predictive power of Tyg-related parameters was more prominent in both sexes. In addition, LAP and CVAI are also good at predicting MetS.
The data for this cross-sectional investigation came from the China Health and Retirement Longitudinal Study (CHARLS), including 9457 middle-aged and elderly people aged 45-98 years old. We examined 13 indicators, including waist circumference (WC), body mass index (BMI), waist-height ratio (WHtR), visceral adiposity index (VAI), a body shape index (ABSI), body roundness index (BRI), lipid accumulation product index (LAP), conicity index (CI), Chinese visceral adiposity index (CVAI), triglyceride-glucose index (TyG-index) and their combined indices (TyG-BMI, TyG-WC, TyG-WHtR). The receiver operating characteristic curve (ROC) was used to determine the usefulness of indicators for screening for MetS in the elderly and to determine their cut-off values, sensitivity, specificity, and area under the curve (AUC). Association analysis of 13 obesity-related indicators with MetS was performed using binary logistic regression analysis.
A total of 9457 middle-aged and elderly Chinese were included in this study, and the overall prevalence of the study population was 41.87% according to the diagnostic criteria of NCEP ATP III. According to age and gender, the percentage of males diagnosed with MetS was 30.67% (45-54 years old: 30.95%, 55-64 years old: 41.02%, 65-74 years old: 21.19%, ≥ 75 years old: 6.84%). The percentage of females diagnosed with MetS was 51.38% (45-54 years old: 31.95%, 55-64 years old: 39.52%, 65-74 years old: 20.43%, ≥ 75 years old: 8.10%). The predictive power of Tyg-related parameters was more prominent in both sexes. In addition, LAP and CVAI are also good at predicting MetS. ABSI had a poor prediction ability.
Among the middle-aged and elderly population in China, after adjusting for confounding factors, all the indicators except ABSI had good predictive power. The predictive power of Tyg-related parameters was more prominent in both sexes. In addition, LAP and CVAI are also good at predicting MetS.
摘要：
■使用13项肥胖和血脂相关指标预测中国中老年人群代谢综合征（MetS）筛查和预测的最佳临界值，并确定最合适的预测因子。
■这项横断面调查的数据来自中国健康与退休纵向研究（CHARLS），其中包括9457名45-98岁的中老年人。我们检查了13个指标，包括腰围（WC），体重指数（BMI），腰高比（WHtR），内脏肥胖指数（VAI），身体形状指数(ABSI)，身体圆度指数（BRI），脂质积累产物指数（LAP），锥度指数(CI)，中国内脏肥胖指数（CVAI），甘油三酯-葡萄糖指数(TyG-指数)及其组合指数(TyG-BMI，TyG-WC,TyG-WHtR）。受试者工作特征曲线（ROC）用于确定老年人MetS筛查指标的有用性，并确定其临界值，灵敏度,特异性，和曲线下面积(AUC)。采用二元logistic回归分析13项肥胖相关指标与MetS的相关性。
■本研究共纳入了9457名中老年人，根据NCEPATPIII的诊断标准，研究人群的总体患病率为41.87％。根据年龄和性别,诊断为MetS的男性百分比为30.67％（45-54岁：30.95％，55-64岁：41.02%，65-74岁：21.19%，≥75岁：6.84%）。诊断为MetS的女性比例为51.38％（45-54岁：31.95％，55-64岁：39.52%，65-74岁：20.43%，≥75岁：8.10%）。Tyg相关参数的预测能力在两种性别中都更为突出。此外,LAP和CVAI也擅长预测MetS。ABSI的预测能力较差。
■在中国中老年人群中，在对混杂因素进行调整后，除ABSI外,所有指标均具有良好的预测能力.Tyg相关参数的预测能力在两种性别中都更为突出。此外,LAP和CVAI也擅长预测MetS。
■这项横断面调查的数据来自中国健康与退休纵向研究（CHARLS），其中包括9457名45-98岁的中老年人。我们检查了13个指标，包括腰围（WC），体重指数（BMI），腰高比（WHtR），内脏肥胖指数（VAI），身体形状指数(ABSI)，身体圆度指数（BRI），脂质积累产物指数（LAP），锥度指数(CI)，中国内脏肥胖指数（CVAI），甘油三酯-葡萄糖指数(TyG-指数)及其组合指数(TyG-BMI，TyG-WC,TyG-WHtR）。受试者工作特征曲线（ROC）用于确定老年人MetS筛查指标的有用性，并确定其临界值，灵敏度,特异性，和曲线下面积(AUC)。采用二元logistic回归分析13项肥胖相关指标与MetS的相关性。
■本研究共纳入了9457名中老年人，根据NCEPATPIII的诊断标准，研究人群的总体患病率为41.87％。根据年龄和性别,诊断为MetS的男性百分比为30.67％（45-54岁：30.95％，55-64岁：41.02%，65-74岁：21.19%，≥75岁：6.84%）。诊断为MetS的女性比例为51.38％（45-54岁：31.95％，55-64岁：39.52%，65-74岁：20.43%，≥75岁：8.10%）。Tyg相关参数的预测能力在两种性别中都更为突出。此外,LAP和CVAI也擅长预测MetS。ABSI的预测能力较差。
■在中国中老年人群中，在对混杂因素进行调整后，除ABSI外,所有指标均具有良好的预测能力.Tyg相关参数的预测能力在两种性别中都更为突出。此外,LAP和CVAI也擅长预测MetS。
