Multimorbidity and the risk of depression: a systematic review of cohort studies.

Abstract

Background: Multimorbidity has been associated with an increased risk of depression. In this systematic review, we aimed to evaluate longitudinal evidence on the association between multimorbidity, including specific multimorbidity patterns, and the risk of developing depression.

Methods: We searched Web of Science, PubMed, Embase, PsycINFO, China National Knowledge Infrastructure, and Wanfang from database inception to 31 December 2025. Cohort studies examining the association between multimorbidity or multimorbidity patterns and incident depression or depressive symptoms were included. Two reviewers independently screened studies, extracted data, and assessed study quality using the Newcastle-Ottawa Scale. We employed a narrative synthesis approach and presented the results using descriptive forest plots and harvest plots.

Results: A total of 17 longitudinal cohort studies were included, conducted in accordance with PRISMA guidelines, with generally high overall quality. Multimorbidity was consistently associated with an increased risk of depression, and the risk generally increased with the number of chronic conditions. This association was relatively stable across genders and populations in different countries. Associations varied across multimorbidity patterns. Cardiovascular-metabolic and respiratory-related patterns showed the most consistent associations with depression, whereas evidence for other patterns was limited and less consistent. Cardiovascular-metabolic multimorbidity showed a cumulative effect. Increasing multimorbidity trajectories may also be associated with subsequent depression risk.

Conclusions: Multimorbidity was longitudinally associated with an increased risk of incident depression or depressive symptoms, and this association appeared to vary according to disease burden, multimorbidity patterns, and changes in multimorbidity over time. Cardiovascular-metabolic patterns, respiratory-related patterns, and rapid trajectories of multimorbidity may represent potential high-risk features requiring further validation. Future research should standardise definitions and pattern identification methods, and further investigate dynamic processes and underlying mechanisms to inform early identification, risk stratification, and future intervention development for depression.

Registration: PROSPERO: CRD420261302076.