Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Shanxi University of Chinese Medicine, Shanxi, China.
Nutr Metab Cardiovasc Dis. 2024 Oct;34(10):2409-2419. doi: 10.1016/j.numecd.2024.06.003. Epub 2024 Jun 13.
Our aim was to explore the potential relationship between SII and obesity, as well as abdominal obesity.
We utilized a weighted multivariable logistic regression model to investigate the relationship between SII and obesity, as well as abdominal obesity. Generalized additive models were employed to test for non-linear associations. Subsequently, we constructed a two-piecewise linear regression model and conducted a recursive algorithm to calculate inflection points. Additionally, subgroup analyses and interaction tests were performed. A total of 7,880 U.S. adult participants from NHANES 2011-2018 were recruited for this study. In the regression model adjusted for all confounding variables, the odds ratios (95% confidence intervals) for the association between SII/100 and obesity, as well as abdominal obesity, were 1.03 (1.01, 1.06) and 1.04 (1.01, 1.08) respectively. There was a non-linear and reverse U-shaped association between SII/100 and obesity, as well as abdominal obesity, with inflection points at 7.32 and 9.98 respectively. Significant positive correlations were observed before the inflection points, while significant negative correlations were found after the inflection points. There was a statistically significant interaction in the analysis of age, hypertension, and diabetes. Moreover, a notable interaction is observed between SII/100 and abdominal obesity within non-Hispanic Asian populations.
In adults from the United States, there is a positive correlation between SII and the high risk of obesity, as well as abdominal obesity. Further large-scale prospective studies are needed to analyze the role of SII in obesity and abdominal obesity.
本研究旨在探讨血小板/淋巴细胞比值(SII)与肥胖和腹型肥胖之间的潜在关系。
我们采用加权多变量逻辑回归模型来研究 SII 与肥胖和腹型肥胖之间的关系。采用广义加性模型来检验非线性关联。随后,我们构建了两段线性回归模型,并进行递归算法计算拐点。此外,还进行了亚组分析和交互检验。共纳入了来自 NHANES 2011-2018 年的 7880 名美国成年参与者。在调整所有混杂因素的回归模型中,SII/100 与肥胖和腹型肥胖的比值比(95%置信区间)分别为 1.03(1.01,1.06)和 1.04(1.01,1.08)。SII/100 与肥胖和腹型肥胖之间存在非线性和反向 U 形关联,拐点分别为 7.32 和 9.98。在拐点之前观察到显著的正相关,而在拐点之后观察到显著的负相关。在分析年龄、高血压和糖尿病时存在统计学显著的交互作用。此外,在非西班牙裔亚裔人群中,SII/100 与腹型肥胖之间存在显著的交互作用。
在美国成年人中,SII 与肥胖和腹型肥胖的高风险呈正相关。需要进一步开展大规模前瞻性研究来分析 SII 在肥胖和腹型肥胖中的作用。