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J Epidemiol Community Health. 2015 Nov;69(11):1109-17. doi: 10.1136/jech-2014-205352. Epub 2015 Jun 16.

Childhood and adolescence risk factors and development of depressive symptoms: the 32-year prospective Young Finns follow-up study.

Author information

1
University of Helsinki, Helsinki, Finland National Institute for Health and Welfare, Helsinki, Finland.
2
University of Helsinki, Helsinki, Finland.
3
School of Social and Community Medicine, University of Bristol, Bristol, UK.
4
Department of Epidemiology and Public Health, University College London, London, UK University of Turku, Turku, Finland.

Abstract

BACKGROUND:

Environmental risks in childhood have been shown to predict later depressive symptoms. In this study, we examined whether various environmental risk domains in childhood and adolescence, socioeconomic, psychoemotional, parental lifestyle and life-events, predict depressive symptom trajectories in adulthood individually by domain and as a cumulative risk score across domains.

METHODS:

Participants were a nationally representative sample of 1289 men and 1585 women from the Young Finns study, aged 3-18 years at study entry in 1980. They responded to questions on depressive symptoms (modified version of the Beck Depression Inventory) at four study phases from 1997 to 2012.

RESULTS:

Findings from longitudinal repeated multilevel modelling showed that all clusters of risk within domain and the cumulative risk score were associated with later depressive symptoms (regression coefficient range from 0.07 to 0.34). Socioeconomic risk, psychoemotional risk and the cumulative risk score predicted later depressive symptoms after adjustment for the effects of adulthood risk. No interaction with time was observed.

CONCLUSIONS:

Our findings suggest that environment risks in childhood and adolescence, particularly in the socioeconomic and psychoemotional domains, are associated with a higher risk, but not an increased progression, of depressive symptoms in adulthood.

KEYWORDS:

CHILD HEALTH; Cohort studies; DEPRESSION; Epidemiological methods; MULTILEVEL MODELLING

PMID:
26082517
DOI:
10.1136/jech-2014-205352
[Indexed for MEDLINE]

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