Abstract
OBJECTIVE: Mood instability levels are high in depression, but temporal precedence and potential mechanisms are unknown. Hypotheses tested were as follows: (1) mood instability is associated with depression cross-sectionally, (2) mood instability predicts new onset and maintenance of depression prospectively and (3) the mood instability and depression link are mediated by sleep problems, alcohol abuse and life events.
METHOD: Data from the National Psychiatric Morbidity Survey 2000 at baseline (N = 8580) and 18-month follow-up (N = 2413) were used. Regression modeling controlling for socio-demographic factors, anxiety and hypomanic mood was conducted. Multiple mediational analyses were used to test our conceptual path model.
RESULTS: Mood instability was associated with depression cross-sectionally (odds ratio: 5.28; 95% confidence interval: [3.67, 7.59]; p < 0.001) and predicted depression inception (odds ratio: 2.43; 95% confidence interval: [1.03-5.76]; p = 0.042) after controlling for important confounders. Mood instability did not predict maintenance of depression. Sleep difficulties and severe problems with close friends and family significantly mediated the link between mood instability and new onset depression (23.05% and 6.19% of the link, respectively). Alcohol abuse and divorce were not important mediators in the model.
CONCLUSION: Mood instability is a precursor of a depressive episode, predicting its onset. Difficulties in sleep are a significant part of the pathway. Interventions targeting mood instability and sleep problems have the potential to reduce the risk of depression.
Original language | English |
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Pages (from-to) | 557-65 |
Number of pages | 9 |
Journal | Australian & New Zealand Journal of Psychiatry |
Volume | 49 |
Issue number | 6 |
Early online date | 7 Apr 2015 |
DOIs | |
Publication status | Published - Jun 2015 |
Keywords
- Cross-Sectional Studies
- Depressive Disorder/epidemiology
- Humans
- Interview, Psychological
- Mood Disorders/complications
- Prospective Studies
- Risk Factors