Department of Psychiatry, McGill University, Montreal, Quebec, Canada.
Douglas Research Centre, Montreal, Quebec, Canada.
Psychiatry Clin Neurosci. 2024 Nov;78(11):703-711. doi: 10.1111/pcn.13728. Epub 2024 Sep 2.
The current study aims to characterize the longitudinal patterns of depression subtypes and investigate the associations among the stability of depression subtypes, COVID-19-related stressors, and depression severity.
The study utilized data from the Canadian Longitudinal Study on Aging, which is a national, long-term study of Canadian adults aged 45 and older (n = 12,957). Latent profile analysis was used to identify latent depression subtypes. Latent transition analysis was then applied to assess the stability of these subtypes over time. Hierarchical multivariate linear regression was used to explore the relationships among these identified depression subtypes, COVID-19-related stressors, and depression severity among males and females, respectively.
Distinct depression subtypes were identified. Except for atypical depression, other depression subtypes showed greater stability over time. We also found that melancholic depression (B = 9.432) and typical depression (B = 6.677) were strongly associated with depression severity during the pandemic. Health-related stressors (B = 0.840), conflict (B = 3.639), difficulties accessing resources (B = 0.927), separation from family (B = 0.840), and caregiving experience (B = 0.764), were significantly associated with increased depression severity. Sex-specific analyses also revealed differences in the associations between stressors and depression severity between males and females.
This study contributes valuable insights into the latent clustering of depression subtypes and their stability. Stressors were associated with increased depression severity, with distinct associations observed among males and females. These findings have implications for targeted early interventions and integrated clinical management strategies by providing the evidence base for tailored mental health care during and after the pandemic.
本研究旨在描述抑郁亚型的纵向模式,并探讨抑郁亚型的稳定性、与 COVID-19 相关压力源以及抑郁严重程度之间的关联。
本研究利用了加拿大老龄化纵向研究的数据,这是一项针对 45 岁及以上加拿大成年人的全国性长期研究(n=12957)。使用潜在剖面分析来识别潜在的抑郁亚型。然后应用潜在转变分析来评估这些亚型随时间的稳定性。分层多元线性回归用于分别探讨这些确定的抑郁亚型、与 COVID-19 相关的压力源与男性和女性抑郁严重程度之间的关系。
确定了不同的抑郁亚型。除了非典型抑郁外,其他抑郁亚型在随时间推移表现出更高的稳定性。我们还发现,在大流行期间,忧郁性抑郁(B=9.432)和典型抑郁(B=6.677)与抑郁严重程度密切相关。健康相关压力源(B=0.840)、冲突(B=3.639)、资源获取困难(B=0.927)、与家人分离(B=0.840)和照顾经历(B=0.764)与抑郁严重程度显著相关。性别特异性分析还揭示了压力源与男性和女性抑郁严重程度之间的关联存在差异。
本研究为抑郁亚型的潜在聚类及其稳定性提供了有价值的见解。压力源与抑郁严重程度增加有关,在男性和女性中观察到不同的关联。这些发现为在大流行期间和之后提供了针对特定人群的早期干预和综合临床管理策略的证据基础,对有针对性的心理健康护理具有重要意义。