Tao Shiyi, Yu Lintong, Li Jun, Huang Xuanchun, Xue Tiantian, Yang Deshuang, Tan Yuqing
Department of Cardiology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Graduate School, Beijing University of Chinese Medicine, Beijing, China.
Front Psychiatry. 2024 Oct 10;15:1441119. doi: 10.3389/fpsyt.2024.1441119. eCollection 2024.
Emerging studies reveal a shared pathophysiological underpinning for metabolic problems and mental illnesses. The present study aimed to determine the association between atherogenic index of plasma (AIP) and the incidence of major depressive disorder (MDD).
7,951 subjects of US adults were collected from the National Health and Nutrition Examination Survey (NHANES) 2005-2018. MDD was evaluated through the Patient Health Questionnaire (PHQ-9). Multivariate logistic regression, sensitivity analysis, and spline smoothing plot method were used to identify the relationship between AIP and MDD. The cut-off point was calculated using recursive partitioning analysis when segmenting effects emerged. The area under the receiver operating characteristic (ROC) curve (AUC) and Hosmer-Lemeshow test were conducted to evaluate the performance of AIP in identifying MDD. Subgroup analyses and interaction tests were used to explore whether the association was stable in different populations.
A positive correlation between AIP and PHQ-9 score and MDD was both observed in 7,951 subjects included in the study, with a significant threshold of -0.42 determined using recursive partitioning analysis. In the fully adjusted model, a positive association between AIP and PHQ-9 score and MDD was observed (β=0.46, 95% CI 0.140.78; OR=1.42, 95% CI 1.041.93). Individuals in the highest AIP quartile had a 0.39-unit higher PHQ-9 score (β=0.39, 95% CI 0.120.66) and a significantly 33% greater risk of MDD than those in the lowest AIP quartile (OR=1.33, 95% CI 1.021.73). Spline smoothing plot analysis further confirmed the positive and non-linear association between AIP and PHQ-9 and MDD. ROC analysis (AUC=0.771) and the Hosmer-Lemeshow test (χ = 14.239, =0.076) suggested an excellent performance and goodness-of-fit of the relatively optimal model. DCA and CIC analysis also revealed a favorable overall net benefit and clinical impact of the model. Subgroup analyses and interaction tests revealed that the association between AIP and PHQ-9 score and MDD remained consistent across different subgroups and was not modified by other covariates, and this positive correlation was more pronounced in those with diabetes or hypertension.
An elevated AIP is linked to a higher chance of MDD, especially in those with diabetes or hypertension. Resolving dyslipidemia and managing comorbidities may help reduce the likelihood of developing MDD.
新兴研究揭示了代谢问题和精神疾病之间共同的病理生理基础。本研究旨在确定血浆致动脉粥样硬化指数(AIP)与重度抑郁症(MDD)发病率之间的关联。
从2005 - 2018年美国国家健康与营养检查调查(NHANES)中收集了7951名美国成年人受试者。通过患者健康问卷(PHQ - 9)评估MDD。采用多因素逻辑回归、敏感性分析和样条平滑图方法来确定AIP与MDD之间的关系。当出现分段效应时,使用递归划分分析计算截断点。进行受试者工作特征(ROC)曲线下面积(AUC)和Hosmer - Lemeshow检验以评估AIP在识别MDD方面的性能。采用亚组分析和交互作用检验来探讨这种关联在不同人群中是否稳定。
在纳入研究的7951名受试者中均观察到AIP与PHQ - 9评分及MDD呈正相关,通过递归划分分析确定的显著阈值为 - 0.42。在完全调整模型中,观察到AIP与PHQ - 9评分及MDD呈正相关(β = 0.46,95%CI 0.140.78;OR = 1.42,95%CI 1.041.93)。AIP最高四分位数组的个体PHQ - 9评分比最低四分位数组高0.39个单位(β = 0.39,95%CI 0.120.66),MDD风险比最低四分位数组显著高33%(OR = 1.33,95%CI 1.021.73)。样条平滑图分析进一步证实了AIP与PHQ - 9及MDD之间的正相关和非线性关联。ROC分析(AUC = 0.771)和Hosmer - Lemeshow检验(χ² = 14.239,P = 0.076)表明相对最优模型具有良好的性能和拟合优度。决策曲线分析(DCA)和一致性指数(CIC)分析也显示该模型具有良好的总体净效益和临床影响。亚组分析和交互作用检验显示,AIP与PHQ - 9评分及MDD之间的关联在不同亚组中保持一致且不受其他协变量影响,这种正相关在糖尿病或高血压患者中更为明显。
AIP升高与MDD发生几率增加相关,尤其是在糖尿病或高血压患者中。解决血脂异常和管理合并症可能有助于降低发生MDD的可能性。