The First Clinical Medical School, Shandong University of Traditional Chinese Medicine, Shandong, China.
Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China.
J Clin Hypertens (Greenwich). 2023 Oct;25(10):957-964. doi: 10.1111/jch.14710. Epub 2023 Aug 23.
Increasing attention has been paid to the association between lean body mass (LBM) and hypertension in recent years, but the previous findings have often been contradictory. Therefore, the authors investigated the association between LBM and hypertension through a cross-sectional study in the United States. To investigate the relationship between LBM and hypertension, the authors conducted weighted multivariable logistic regression models. The authors used the restricted cubic spline regression model to determine if there was a nonlinear correlation. In order to locate the inflection point, the authors built a two-part linear regression model using a recursive method. In the full adjustment model, LBM was positively associated with hypertension, with ORs (95% CI) of 1.19 (1.02, 1.38). In the further linear trend test, the ORs (95% CI) for Q2, Q3, and Q4 were 0.76 (0.60, 0.95), 0.62 (0.47, 0.80), and 0.66 (0.48, 0.91), respectively, compared to Q1, which suggested that the association between LBM and hypertension might be non-linear. The authors performed the restricted cubic spline curve to confirm this non-linear relationship and found the inflection point of 43.21 kg with an opposite relationship in which LBM and hypertension exhibited a negative correction of 0.66 (0.50, 0.86) before the inflection point and a positive correlation of 1.20 (1.03, 1.39) after the inflection point. Our study highlighted a non-linear association between LBM and hypertension in the general US population.
近年来，人们越来越关注瘦体重（LBM）与高血压之间的关系，但之前的研究结果往往相互矛盾。因此，作者通过在美国进行的一项横断面研究来探讨 LBM 与高血压之间的关系。为了研究 LBM 与高血压之间的关系，作者进行了加权多变量逻辑回归模型分析。作者使用受限立方样条回归模型来确定是否存在非线性相关性。为了找到拐点，作者使用递归法构建了一个两部分线性回归模型。在全调整模型中，LBM 与高血压呈正相关，比值比（95%可信区间）为 1.19（1.02，1.38）。在进一步的线性趋势检验中，Q2、Q3 和 Q4 的比值比（95%可信区间）分别为 0.76（0.60，0.95）、0.62（0.47，0.80）和 0.66（0.48，0.91），与 Q1 相比，这表明 LBM 与高血压之间的关系可能是非线性的。作者进行了受限立方样条曲线分析来证实这种非线性关系，并发现拐点为 43.21kg，拐点前 LBM 和高血压呈负相关，校正比值比为 0.66（0.50，0.86），拐点后呈正相关，校正比值比为 1.20（1.03，1.39）。我们的研究强调了一般美国人群中 LBM 与高血压之间的非线性关系。
