Li Sen, Jia Zhaoqi, Zhang Zhang, Li Yuxin, Ding Yining, Qin Zongshi, Guo Shuzhen
School of Life Sciences, Beijing University of Chinese Medicine, Beijing, China.
Peking University Clinical Research Institute, Peking University, Beijing, China.
Gen Psychiatr. 2023 Aug 14;36(4):e101063. doi: 10.1136/gpsych-2023-101063. eCollection 2023.
The comorbidity of cardiovascular disease (CVD) and depression has been well established, as depression usually presents simultaneously with CVD risk factors. However, the potential association between cumulative exposure to CVD risk and depression remains unclear, so we conducted the current investigation. To our knowledge, this is the first study that employs the cumulative risk model to examine the effect of CVD risk factors on depression using nationally representative population and gender, age and CVD status-stratified subpopulations.
To systematically study the possible individual and cumulative effect of 18 CVD risk factors on depression.
A cross-sectional, secondary analysis investigated associations between 18 CVD risk factors and depression. The interaction effect between CVD risk factors and age, gender and CVD status was also examined. Enrolment included 20 816 participants from the US National Health and Nutrition Examination Survey 2005-2016. Participants with Patient Health Questionnaire-9 scores over 15 or who were using an antidepressant were considered depressive; 18 known cardiovascular risk factors were incorporated in the present study.
At the individual risk factor level, smoking, drinking, living alone, sleep quality, body mass index, waist circumference and diabetes status had differential associations with depression risk according to the gender, age or CVD status of the participants. Most importantly, gender-stratified cumulative risk analysis indicated that similar depression risk was found in both genders with a small number of CVD risk factors (odds ratio (OR)=1.32; 95% confidence interval (CI): 0.87 to 1.99), but females had a significantly higher depression risk compared with males under high cumulative risk exposure (OR=2.86; 95% CI: 1.79 to 4.59).
Clarifying the association of numerous CVD risk factors with depression according to gender, age and overall CVD status may be beneficial for risk stratification and the prevention of depression in clinical practice. Moreover, the observed novel evidence of high cumulative risk exposure-mediated gender disparities in depression risk may shed light on the underlying mechanism of females' greater vulnerability to depression.
心血管疾病（CVD）与抑郁症的共病现象已得到充分证实，因为抑郁症通常与CVD危险因素同时出现。然而，累积暴露于CVD风险与抑郁症之间的潜在关联仍不明确，因此我们进行了本次调查。据我们所知，这是第一项采用累积风险模型，利用具有全国代表性的人群以及按性别、年龄和CVD状态分层的亚人群，来研究CVD危险因素对抑郁症影响的研究。
系统研究18种CVD危险因素对抑郁症可能产生的个体和累积影响。
一项横断面的二次分析研究了18种CVD危险因素与抑郁症之间的关联。还考察了CVD危险因素与年龄、性别及CVD状态之间的交互作用。研究纳入了2005 - 2016年美国国家健康与营养检查调查中的20816名参与者。患者健康问卷-9得分超过15分或正在使用抗抑郁药的参与者被视为患有抑郁症；本研究纳入了18种已知的心血管危险因素。
在个体危险因素层面，根据参与者的性别、年龄或CVD状态，吸烟、饮酒、独居、睡眠质量、体重指数、腰围和糖尿病状态与抑郁症风险存在不同的关联。最重要的是，按性别分层的累积风险分析表明，在少数CVD危险因素的情况下，两性的抑郁症风险相似（优势比（OR）=1.32；95%置信区间（CI）：0.87至1.99），但在高累积风险暴露下，女性的抑郁症风险显著高于男性（OR = 2.86；95% CI：1.79至4.59）。
根据性别、年龄和整体CVD状态阐明众多CVD危险因素与抑郁症的关联，可能有助于临床实践中的风险分层和抑郁症预防。此外，观察到的高累积风险暴露介导的抑郁症风险性别差异的新证据，可能有助于揭示女性更易患抑郁症的潜在机制。
