Am J Epidemiol. 2022 Mar 24;191(5):886-899. doi: 10.1093/aje/kwab298.
Visceral adipose tissue (VAT) is a strong prognostic factor for cardiovascular disease and a potential target for cardiovascular risk stratification. Because VAT is difficult to measure in clinical practice, we estimated prediction models with predictors routinely measured in general practice and VAT as outcome using ridge regression in 2,501 middle-aged participants from the Netherlands Epidemiology of Obesity study, 2008-2012. Adding waist circumference and other anthropometric measurements on top of the routinely measured variables improved the optimism-adjusted R2 from 0.50 to 0.58 with a decrease in the root-mean-square error (RMSE) from 45.6 to 41.5 cm2 and with overall good calibration. Further addition of predominantly lipoprotein-related metabolites from the Nightingale platform did not improve the optimism-corrected R2 and RMSE. The models were externally validated in 370 participants from the Prospective Investigation of Vasculature in Uppsala Seniors (PIVUS, 2006-2009) and 1,901 participants from the Multi-Ethnic Study of Atherosclerosis (MESA, 2000-2007). Performance was comparable to the development setting in PIVUS (R2 = 0.63, RMSE = 42.4 cm2, calibration slope = 0.94) but lower in MESA (R2 = 0.44, RMSE = 60.7 cm2, calibration slope = 0.75). Our findings indicate that the estimation of VAT with routine clinical measurements can be substantially improved by incorporating waist circumference but not by metabolite measurements.
内脏脂肪组织(VAT)是心血管疾病的一个强有力的预后因素,也是心血管风险分层的一个潜在目标。由于 VAT 在临床实践中难以测量,我们使用岭回归在 2008-2012 年荷兰肥胖症流行病学研究中对 2501 名中年参与者进行了研究,这些参与者的预测因子是常规测量的预测因子,而 VAT 是结果。在常规测量变量的基础上增加腰围和其他人体测量学测量值,可将乐观调整后的 R2 从 0.50 提高到 0.58,将均方根误差(RMSE)从 45.6 降低到 41.5 cm2,并且整体校准效果良好。进一步增加来自 Nightingale 平台的主要脂蛋白相关代谢物并不能提高校正后的 R2 和 RMSE。这些模型在 370 名来自乌普萨拉老年人血管前瞻性研究(PIVUS,2006-2009 年)和 1901 名来自动脉粥样硬化多民族研究(MESA,2000-2007 年)的参与者中进行了外部验证。在 PIVUS 中的表现与开发环境相当(R2 = 0.63,RMSE = 42.4 cm2,校准斜率 = 0.94),但在 MESA 中较低(R2 = 0.44,RMSE = 60.7 cm2,校准斜率 = 0.75)。我们的研究结果表明,通过纳入腰围,而不是通过代谢物测量,可以大大提高常规临床测量中 VAT 的估计值。