title: Path analysis of the chronicity of depression using the comprehensive developmental model framework.
abstract: Background Depressive disorder is recognized as recurrent or chronic in the majority of affected individuals; but literature is not consistent about determinants of the disorder course. Aims To analyse the relationships between familial, personal and environmental characteristics in different life phases and their effects on the chronicity of depression in a population-based sample. Methods It was a longitudinal panel study with three waves (W1-W3) for 651 adult men and women with diagnosis of minor/major depression or dysthymia at W1 of the Swedish PART (mental health, work and relations) study. Risk factors and co-morbidities were assessed with questionnaires. The main outcome was an episode of minor/major depression or dysthymia at 10-12 years of follow-up (W3). Liability for depressive episodes was determined using exploratory structural equation modelling (SEM), following a path approach with step-wise specification searches. Results Most of the risk factors determined, directly or indirectly, depression severity at W3. Somatic trait anxiety, partner loss and other negative life events at W1, depressive symptoms at W2, and life difficulties and other dependent life events at W3 had direct effects on the outcome. Conclusions SEM model revealed complex and intertwined psychopathological pathways leading to chronicity of depression, given previous episodes, which could be assembled in two main mechanisms: a depressive-internalizing path and an adversity path comprised of life events. Pathways are simpler than those of depression occurrence, emphasizing the relevance of personality factors as depression determinants, and excluding disability levels, co-morbidities and social support. These novel findings need to be replicated in future studies.
authors.affiliation: a Andrés Fandiño-Losada, Public Health School and Cisalva Institute, Universidad del Valle, Cali, Colombia , and Department of Public Health Sciences, Karolinska Institutet , Stockholm , Sweden ;
authors.forename: Andrés
authors.initials: A
authors.lastname: Fandiño-Losada
authors.affiliation: b Shrikant I. Bangdiwala, Department of Biostatistics, Gillings School of Global Public Health , University of North Carolina , USA ;
authors.forename: Shrikant I
authors.initials: SI
authors.lastname: Bangdiwala
authors.affiliation: c Catharina Lavebratt, Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden , and Center for Molecular Medicine, Karolinska University Hospital , Stockholm , Sweden ;
authors.forename: Catharina
authors.initials: C
authors.lastname: Lavebratt
authors.affiliation: d Yvonne Forsell, Department of Public Health Sciences , Karolinska Institutet , Stockholm , Sweden.
authors.forename: Yvonne
authors.initials: Y
authors.lastname: Forsell
mesh_terms: D000328:Adult; D002908:Chronic Disease / Q000453:epidemiology; D003863:Depression / Q000453:epidemiology / Q000209:etiology*; D003865:Major Depressive Disorder / Q000453:epidemiology / Q000209:etiology*; D019263:Dysthymic Disorder / Q000453:epidemiology / Q000209:etiology*; D005260:Female; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D013548:Sweden / Q000453:epidemiology; D055815:Young Adult
keywords: Depression; causality; depressive disorder; longitudinal study; path analysis; personality; recurrence; structural equation modelling