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Danger and loss events and the incidence of anxiety and depressive disorders: a prospective-longitudinal community study of adolescents and young adults

  • E. Asselmann (a1) (a2), H.-U. Wittchen (a1) (a3), R. Lieb (a3) (a4), M. Höfler (a1) and K. Beesdo-Baum (a1) (a2)...

Abstract

Background

There are inconclusive findings regarding whether danger and loss events differentially predict the onset of anxiety and depression.

Method

A community sample of adolescents and young adults (n = 2304, age 14–24 years at baseline) was prospectively followed up in up to four assessments over 10 years. Incident anxiety and depressive disorders were assessed at each wave using the DSM-IV/M-CIDI. Life events (including danger, loss and respectively mixed events) were assessed at baseline using the Munich Event List (MEL). Logistic regressions were used to reveal associations between event types at baseline and incident disorders at follow-up.

Results

Loss events merely predicted incident ‘pure’ depression [odds ratio (OR) 2.4 per standard deviation, 95% confidence interval (CI) 1.5–3.9, p < 0.001] whereas danger events predicted incident ‘pure’ anxiety (OR 2.3, 95% CI 1.1–4.6, p = 0.023) and ‘pure’ depression (OR 2.5, 95% CI 1.7–3.5, p < 0.001). Mixed events predicted incident ‘pure’ anxiety (OR 2.9, 95% CI 1.5–5.7, p = 0.002), ‘pure’ depression (OR 2.4, 95% CI 1.6–3.4, p < 0.001) and their co-morbidity (OR 3.6, 95% CI 1.8–7.0, p < 0.001).

Conclusions

Our results provide further evidence for differential effects of danger, loss and respectively mixed events on incident anxiety, depression and their co-morbidity. Since most loss events referred to death/separation from significant others, particularly interpersonal loss appears to be highly specific in predicting depression.

Copyright

Corresponding author

* Address for correspondence: E. Asselmann, Dipl.-Psych., Institute of Clinical Psychology and Psychotherapy, Behavioral Epidemiology, Technische Universität Dresden, Chemnitzer Str. 45, 01187 Dresden, Germany. (Email: eva.asselmann@tu-dresden.de)

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