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Association between social isolation and depression: Evidence from longitudinal and Mendelian randomization analyses
Shuai Zhu1, Xiangjie Kong1, Fulei Han1
1Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China.
Journal of Affective Disorders
|January 14, 2024
Summary
Social isolation and depression in older adults have a reciprocal relationship, meaning each condition can worsen the other. Interventions should address both mental health and social connection to improve well-being.
Area of Science:
- Gerontology
- Psychiatry
- Epidemiology
Background:
- Growing evidence suggests a link between social isolation and depression.
- The precise nature and causality of this association remain unclear.
- This study investigates the potential bidirectional relationship between social isolation and depression.
Purpose of the Study:
- To examine the temporal relationship between social isolation and depressive symptoms in older adults.
- To assess the causal link between social isolation and depression using genetic data.
Main Methods:
- Cross-lagged panel model (CLPM) analysis of the English Longitudinal Study of Aging (ELSA) data (n=6787).
- Two-sample bidirectional Mendelian randomization (MR) using genome-wide association study data for social isolation phenotypes (n=448,858-487,647) and depression (n=215,644-2,113,907).
Main Results:
- CLPM revealed significant positive associations in both directions: social isolation predicting depressive symptoms (β=0.037) and depressive symptoms predicting social isolation (β=0.039).
- Bidirectional MR confirmed a positive association between genetically predicted loneliness and social isolation with depression (OR=1.88) and vice versa (OR=1.16).
Conclusions:
- Findings indicate a bidirectional relationship between social isolation and depression in older adults.
- Interventions should consider the reciprocal impact on mental health and social connection.
- Addressing both aspects may be crucial for improving well-being in older populations.
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