Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Department of Biostatistics, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA.
Int J Obes (Lond). 2019 Oct;43(10):1940-1950. doi: 10.1038/s41366-019-0354-8. Epub 2019 Mar 29.
BACKGROUND/OBJECTIVES: The waist-to-height ratio (WHtR) estimates cardiometabolic risk in youth without need for growth charts by sex and age. Questions remain about whether waist circumference measured per protocol of the National Health and Nutrition Examination Survey (WHtR) or World Health Organization (WHtR) can better predict blood pressures and lipid parameters in youth.
PARTICIPANTS/METHODS: WHtR was measured under both anthropometric protocols among participants in the SEARCH Study, who were recently diagnosed with diabetes (ages 5-19 years; N = 2 773). Biomarkers were documented concurrently with baseline anthropometry and again ~7 years later (ages 10-30 years; N = 1 712). For prediction of continuous biomarker outcomes, baseline WHtR or WHtR entered semiparametric regression models employing restricted cubic splines. To predict binary biomarkers (high-risk group defined as the most adverse quartile) linear WHtR or WHtR terms entered logistic models. Model covariates included demographic characteristics, pertinent medication use, and (for prospective predictions) the follow-up time since baseline. We used measures of model fit, including the adjusted-R and the area under the receiver operator curves (AUC) to compare WHtR and WHtR.
For the concurrent biomarkers, the proportion of variation in each outcome explained by full regression models ranged from 23 to 46%; for the prospective biomarkers, the proportions varied from 11 to 30%. Nonlinear relationships were recognized with the lipid outcomes, both at baseline and at follow-up. In full logistic models, the AUCs ranged from 0.75 (diastolic pressure) to 0.85 (systolic pressure) at baseline, and from 0.69 (triglycerides) to 0.78 (systolic pressure) at the prospective follow-up. To predict baseline elevations of the triglycerides/HDL cholesterol ratio, the AUC was 0.816 for WHtR compared with 0.810 for WHtR (p = 0.003), but otherwise comparisons between alternative WHtR protocols were not significantly different.
Among youth with recently diagnosed diabetes, measurements of WHtR by either waist circumference protocol similarly helped estimate current and prospective cardiometabolic risk biomarkers.
背景/目的：腰高比（WHtR）可估算无需按性别和年龄绘制生长图表的青年人群的心血管代谢风险。目前仍存在一些疑问，即按照国家健康和营养检查调查（WHtR）或世界卫生组织（WHtR）协议测量的腰围，是否能更好地预测青年人群的血压和血脂参数。
参与者/方法：在 SEARCH 研究中，根据最近被诊断患有糖尿病的参与者（年龄 5-19 岁；N=2773）的两种人体测量协议测量 WHtR。同时记录基线人体测量学和 7 年后（年龄 10-30 岁；N=1712）的生物标志物。为了预测连续生物标志物结果，在采用限制性立方样条的半参数回归模型中纳入基线 WHtR 或 WHtR。对于预测二分类生物标志物（高风险组定义为最不利的四分位数），线性 WHtR 或 WHtR 项则纳入逻辑回归模型。模型协变量包括人口统计学特征、相关药物使用以及（对于前瞻性预测）自基线以来的随访时间。我们使用模型拟合指标（包括调整后的 R 和接收者操作特征曲线下面积[AUC]）来比较 WHtR 和 WHtR。
对于同时性生物标志物，各结局的全回归模型解释的变异比例范围为 23%-46%；对于前瞻性生物标志物，比例范围为 11%-30%。在基线和随访时，血脂结局均存在非线性关系。在全逻辑回归模型中，AUC 范围为基线时舒张压为 0.75，收缩压为 0.85，前瞻性随访时为 0.69（甘油三酯），收缩压为 0.78。在预测基线时甘油三酯/高密度脂蛋白胆固醇比值升高时，WHtR 的 AUC 为 0.816，而 WHtR 的 AUC 为 0.810（p=0.003），但其他替代 WHtR 方案之间的比较无显著差异。
在近期被诊断患有糖尿病的青年人群中，按照腰围协议测量的 WHtR 同样有助于评估当前和前瞻性心血管代谢风险生物标志物。
