Cardiometabolic Risk Clusters, Physical Activity, Digital Exclusion, and Depression Trajectories in Older Adults

Overview

This study analyzed data from two large longitudinal cohorts, ELSA and HRS, to investigate how clusters of cardiometabolic risk factors, physical activity levels, and digital exclusion relate to trajectories of depressive symptoms in adults aged 50 and above. It highlights the complex interplay between these factors and their influence on depression over time.

Background

Depression is a leading cause of disability worldwide, affecting over 300 million people and linked to significant healthcare costs and adverse health outcomes such as cardiovascular disease. Cardiometabolic risk factors like diabetes, obesity, and hypertension contribute to depression risk through inflammatory pathways. Physical activity and digital inclusion have protective effects against depressive symptoms, but their roles in the context of cardiometabolic risk clusters and depression trajectories remain unclear. Large-scale longitudinal studies like ELSA and HRS provide valuable data to explore these relationships in aging populations.

Data Highlights

The study utilized baseline data from wave 2 of ELSA (2004/2005) and wave 9 of HRS (2008/2009), with follow-up spanning multiple waves up to 2023. Initial samples included 9,432 ELSA and 17,217 HRS participants, with final analytical samples of 4,519 and 4,380 respectively after exclusions for age, missing data, and loss to follow-up. The cohorts are nationally representative of adults aged 50 and older in the UK and USA.

Key Findings

• Distinct clusters of cardiometabolic risk factors were identified using latent class analysis, revealing heterogeneous subgroups with varying depression risk profiles.
• Higher clustering of cardiometabolic risks was associated with increased trajectories of depressive symptoms over time.
• Physical activity was found to mediate and moderate the relationship between cardiometabolic risk clusters and depressive symptoms, with higher activity levels mitigating depression risk.
• Digital exclusion independently contributed to worse depressive symptom trajectories and moderated the impact of cardiometabolic risk on depression.
• The interplay between cardiometabolic risk, physical activity, and digital inclusion suggests multifactorial pathways influencing depression in older adults.

Clinical Implications

Clinicians should consider comprehensive assessments of cardiometabolic risk profiles in older adults when evaluating depression risk. Encouraging physical activity and addressing barriers to digital inclusion may serve as effective interventions to reduce depressive symptoms in this population. Integrating behavioral and social factors into depression management could improve therapeutic outcomes.

Conclusion

This study underscores the importance of recognizing heterogeneous cardiometabolic risk clusters and their interaction with physical activity and digital inclusion in shaping depressive symptom trajectories among older adults. Targeted interventions addressing these factors may help mitigate depression burden in aging populations.

References

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