Han Sibo, Zhang Yingqi, Wu Bingxin, Chen Qingyun, Han Zhengyuan, Chen Jingmin, Li Peishan, Xu Meimei
Second Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China.
The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, China.
Front Public Health. 2025 Mar 19;13:1534302. doi: 10.3389/fpubh.2025.1534302. eCollection 2025.
This research is aimed at investigating the association between the cardiometabolic index (CMI) and depressive symptoms in Chinese population of middle and older age, using data derived from the CHARLS study.
Using data from 7,800 participants in the 2011-2012 wave of the CHARLS cohort, this cross-sectional analysis concentrated on examining the association between CMI and depressive symptoms, assessed through CESD-10 scores. The study utilized multivariate logistic regression, multiple linear regression, and restricted cubic spline (RCS) models to investigate the link between CMI and depression, with subgroup analyses offering further insights. Sensitivity analyses included propensity score matching and data from 8,457 participants in the 2015-2016 CHARLS wave.
In fully adjusted models, higher CMI was significantly associated with an elevated risk of depression, with participants having a CMI ≥ 0.594 showing a 162% higher risk compared to those with lower CMI. The RCS analysis identified a threshold at CMI = 0.594, where participants with CMI ≥ 0.594 had a 162% elevated possibility of depression in comparison to those with CMI < 0.594 [OR = 2.62, 95% CI: 2.36-2.91]. Sensitivity analyses, including propensity score matching and data from the 2015-2016 CHARLS wave, confirmed the robustness of the findings.
Our analysis demonstrates that elevated CMI levels are independently correlated with a heightened likelihood of experiencing depressive symptoms, highlighting the significance of metabolic interventions in mitigating depressive tendencies in middle-aged and older individuals.
本研究旨在利用中国健康与养老追踪调查(CHARLS)研究的数据,调查中国中老年人群中心血管代谢指数(CMI)与抑郁症状之间的关联。
本横断面分析使用了CHARLS队列2011 - 2012年波次中7800名参与者的数据,重点研究CMI与通过CESD - 10评分评估的抑郁症状之间的关联。该研究采用多变量逻辑回归、多元线性回归和受限立方样条(RCS)模型来研究CMI与抑郁之间的联系,并通过亚组分析提供进一步的见解。敏感性分析包括倾向得分匹配以及2015 - 2016年CHARLS波次中8457名参与者的数据。
在完全调整模型中,较高的CMI与抑郁风险升高显著相关,CMI≥0.594的参与者相比CMI较低的参与者,抑郁风险高出162%。RCS分析确定CMI = 0.594为一个阈值,与CMI < 0.594的参与者相比,CMI≥0.594的参与者患抑郁症的可能性高出162%[比值比(OR)= 2.62,95%置信区间(CI):2.36 - 2.91]。包括倾向得分匹配和2015 - 2016年CHARLS波次数据在内的敏感性分析证实了研究结果的稳健性。
我们的分析表明,升高的CMI水平与出现抑郁症状的可能性增加独立相关,突出了代谢干预在减轻中老年个体抑郁倾向方面的重要性。