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Exploring the Covariation between Anxiety and Depression Symptoms: A Genetic Analysis of the Effects of Age and Sex

Eley, Thalia C., Stevenson, Jim·1999·Journal of Child Psychology and Psychiatry

Abstract

Self-reported anxiety and depression symptoms in children and adolescents have been shown to be heritable, and are also highly correlated. Furthermore, there have been indications in the literature of sex and age differences in the aetiologies of these two types of symptoms. This study set out to ascertain to what extent the genetic and environmental factors that influence anxiety symptoms also influence depression symptoms, and whether these are the same in children and adolescents, and males and females. Four hundred and ninety pairs of twins aged 8 to 16 years completed the Children's Depression Inventory and the Trait scale of the State-Trait Anxiety Inventory for Children. There were significant effects of age and sex on the variance in and covariance between these two types of symptom. Bivariate genetic analyses of the measures indicated that the genetic influences on anxiety and depression were shared for all four groups, a finding that has been consistently demonstrated for adults.

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Metadata

Authors
Eley, T. C., & Stevenson, J.
Venue
Journal of Child Psychology and Psychiatry
Publisher
Wiley
Published
1999-11
Volume
40
Issue
8
Pages
1273-1282
ISSN
0021-9630 (ISSN-L)
OpenAlex
W2166102513
Cited by
184
References
0
FWCI
7.46
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Exploring the Covariation between Anxiety and Depression Symptoms: A Genetic Analysis of the Effects of Age and Sex. https://app.cochat.ai/papers/10.1017/s0021963099004734
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Eley, T. C., & Stevenson, J. (1999). Exploring the Covariation between Anxiety and Depression Symptoms: A Genetic Analysis of the Effects of Age and Sex. Journal of Child Psychology and Psychiatry. https://doi.org/10.1017/s0021963099004734

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.