残余胆固醇升高与流行重度抑郁症的风险:一项基于全国人群的研究

IF 3.8 3区 医学 Q2 PSYCHIATRY Frontiers in Psychiatry Pub Date : 2024-11-14 eCollection Date: 2024-01-01 DOI:10.3389/fpsyt.2024.1495467
Shiyi Tao, Lintong Yu, Jun Li, Ji Wu, Deshuang Yang, Xuanchun Huang, Tiantian Xue
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引用次数: 0

摘要

背景:残余胆固醇(RC)因与多种疾病相关而受到越来越多的关注。然而,全面的基于人群的研究阐明RC与重度抑郁症(MDD)之间的关系是有限的。目前的研究旨在确定美国成年人RC和重度抑郁症之间的关系。方法:从2005-2018年国家健康与营养检查调查(NHANES)中获得具有完整RC和抑郁信息的美国成年人的横断面数据。使用患者健康问卷(PHQ-9)评估重度抑郁症。采用多变量logistic回归、敏感性分析和样条平滑图方法探讨RC与抑郁之间的关系。当出现分割效应时,采用递归分割分析法计算分界点。采用受试者工作特征曲线下面积(AUC)、校准曲线、Hosmer-Lemeshow检验、决策曲线分析(DCA)和临床影响曲线(CIC)评价RC识别MDD的效果。通过亚组分析和相互作用检验来探讨这种关联在不同人群中是否稳定。结果:共有9173名参与者被纳入研究,RC分数越高的参与者PHQ-9得分越高,MDD患病率也越高。在完全校正模型中,RC、PHQ-9评分与MDD均呈正相关(β=0.54, 95% CI 0.26~0.82;Or =1.43, 95% ci 1.15~1.78)。最高RC四分位数的受试者PHQ-9评分高出0.42个单位(β=0.42, 95% CI 0.15~0.69),患重度抑郁症的风险显著高于最低RC四分位数的受试者32% (OR=1.32, 95% CI 1.05~1.66)。样条平滑图分析进一步证实了RC与PHQ-9和MDD呈正非线性相关。ROC分析(AUC=0.762)、Hosmer-Lemeshow检验(χ2 = 6.258, P=0.618)和校正曲线均显示多元模型具有良好的拟合优度。DCA和CIC分析同样表明该模型具有积极的总体净效益和临床影响。亚组分析和相互作用试验表明,RC和抑郁之间的关系在亚组中保持稳定,不受除糖尿病、高血压或高脂血症以外的其他因素的影响。结论:在美国成年人中,尤其是糖尿病、高血压或高脂血症患者中,RC升高与MDD患病率升高相关。本研究结果提示,对RC水平和合并症的管理可能有助于减轻MDD的发生。
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Elevated remnant cholesterol and the risk of prevalent major depressive disorder: a nationwide population-based study.

Background: Remnant cholesterol (RC) has received increasing attention due to its association with a variety of diseases. However, comprehensive population-based studies elucidating the relationship between RC and major depressive disorder (MDD) are limited. The current study aimed to determine the association between RC and MDD in US adults.

Methods: Cross-sectional data of US adults with complete RC and depression information were obtained from the National Health and Nutrition Examination Survey (NHANES) 2005-2018. MDD was evaluated using the Patient Health Questionnaire (PHQ-9). Multivariate logistic regression, sensitivity analysis, and spline smoothing plot method were conducted to explore the relationship between RC and depression. The cut-off point was calculated using recursive partitioning analysis when segmenting effects emerged. The area under the receiver operating characteristic (ROC) curve (AUC), calibration curve, Hosmer-Lemeshow test, the decision curve analysis (DCA), and clinical impact curve (CIC) were employed to evaluate the performance of RC in identifying MDD. Subgroup analyses and interaction tests were performed to explore whether the association was stable in different populations.

Results: A total of 9,173 participants were enrolled and participants in the higher RC quartile tended to have a higher PHQ-9 score and prevalence of MDD. In the fully adjusted model, a positive association between RC and PHQ-9 score and MDD was both observed (β=0.54, 95% CI 0.26~0.82; OR=1.43, 95% CI 1.15~1.78). Participants in the highest RC quartile had a 0.42-unit higher PHQ-9 score (β=0.42, 95% CI 0.15~0.69) and a significantly 32% higher risk of MDD than those in the lowest RC quartile (OR=1.32, 95% CI 1.05~1.66). Spline smoothing plot analysis further confirmed the positive and non-linear association between RC and PHQ-9 and MDD. ROC analysis (AUC=0.762), the Hosmer-Lemeshow test (χ2 = 6.258, P=0.618), and calibration curve all indicated a high performance and goodness-of-fit of the multivariate model. DCA and CIC analysis similarly demonstrated a positive overall net benefit and clinical impact for the model. Subgroup analyses and interaction tests suggested that the relationship between RC and depression remained stable across subgroups and was unaffected by other factors other than diabetes, hypertension, or hyperlipidemia.

Conclusion: An elevated RC is associated with a higher risk of prevalent MDD among US adults, especially in those with diabetes, hypertension, or hyperlipidemia. The present results suggested that the management of RC levels and comorbidities may contribute to alleviating the occurrence of MDD.

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来源期刊
Frontiers in Psychiatry
Frontiers in Psychiatry Medicine-Psychiatry and Mental Health
CiteScore
6.20
自引率
8.50%
发文量
2813
审稿时长
14 weeks
期刊介绍: Frontiers in Psychiatry publishes rigorously peer-reviewed research across a wide spectrum of translational, basic and clinical research. Field Chief Editor Stefan Borgwardt at the University of Basel is supported by an outstanding Editorial Board of international researchers. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, clinicians and the public worldwide. The journal''s mission is to use translational approaches to improve therapeutic options for mental illness and consequently to improve patient treatment outcomes.
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