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Anxiety-specific associations with substance use: Evidence of a protective factor in adolescence and a risk factor in adulthood

Published online by Cambridge University Press:  02 May 2022

Maya M. Rieselbach*
Affiliation:
Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, Colorado, USA Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
Robin P. Corley
Affiliation:
Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
John K. Hewitt
Affiliation:
Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, Colorado, USA Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
Soo Hyun Rhee
Affiliation:
Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, Colorado, USA Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
*
Corresponding author: Maya M. Rieselbach, email: maya.rieselbach@colorado.edu
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Abstract

Externalizing psychopathology is a strong risk factor for substance use, whereas the role of internalizing manifestations of distress, and anxiety in particular, in predicting substance use remains unclear. Studies have suggested that anxiety may be either a protective or risk factor for substance use. The present study aimed to clarify evidence for anxiety-specific associations with substance use, examining sex and developmental period (adolescence vs. adulthood) as potential moderators that may help explain conflicting results in the literature. In a longitudinal twin sample, cross-sectional associations of anxiety with substance use differed in adolescents and adults and in girls/women and boys/men. Controlling for externalizing psychopathology and depression, anxiety was associated with reduced substance use in adolescent girls and increased substance use in adult women. In contrast, anxiety-specific associations with substance use were not significant in boys and men. Possible explanations for these contrasting results across development and sex are discussed.

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Type
Regular Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2022. Published by Cambridge University Press
Figure 0

Figure 1. Multivariate Regressions in Adolescents and Adults. Adolescents (girls/boys). Model fit: χ2(37) = 71.28, RMSEA = 0.03, CFI = .98. Adults (women/men). Model fit: χ2(28) = 85.08, RMSEA = 0.05, CFI = .92. Note. Standardized parameters are shown. Although factor loadings and thresholds were invariant across sex in adolescents, the standardized parameters are different for girls and boys because the variance of the latent substance use variable was allowed to differ by sex. Parameter estimates are displayed separately by sex (girls/boys and women/men). * p < 0.05.

Figure 1

Figure 2. Quadrivariate Phenotypic Cholesky Decompositions in Adolescents and Adults. Adolescents (girls/boys). Model fit: χ2(40) = 144.42, RMSEA = 0.05, CFI = .97. Adults (women/men). Model fit: χ2(40) = 99.86, RMSEA = 0.04, CFI = .96. Note. Factor 1 (F1) represents common influences on externalizing, depression, and anxiety that also influence substance use. Factor 2 (F2) represents influences on internalizing symptoms that also influence substance use, controlling for externalizing symptoms. Factor 3 (F3) represents influences on anxiety symptoms that also influence substance use, controlling for externalizing and depression. Factor 4 (F4) represents influences unique to substance use. Standardized parameters are shown. Paths are displayed separately by sex. For the sake of clarity, the measurement model for the latent substance use variable is not displayed here. ^Variance explained by F1 is fixed to 1.00 in adults, because F1 is the only predictor of ASPD in adults, whereas age predicts CD in the adolescent model. *p < .05.

Figure 2

Figure 3. Quintivariate Phenotypic Cholesky Decomposition with Adolescent Variables and Adult Substance Use. Model fit: χ2(103) = 538.14, RMSEA = 0.05, CFI = .96. Note. Standardized parameterizations are shown, presented separately by sex (girls/boys and women/men). For the sake of clarity, measurement models for the adolescent and adult latent substance use variables are not displayed here. *p < .05.

Figure 3

Table 1. Phenotypic correlations in adolescents and adults

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