DOI

https://doi.org/10.25772/AJ1B-BX67

Author ORCID Identifier

https://orcid.org/0000-0002-9966-4039

Defense Date

2021

Document Type

Dissertation

Degree Name

Doctor of Philosophy

Department

Epidemiology

First Advisor

Elizabeth Prom-Wormley

Second Advisor

Juan Lu

Third Advisor

Robert Perera

Fourth Advisor

Roxann Roberson-Nay

Fifth Advisor

Michael Neale

Abstract

Introduction. Substance use disorder (SUD) is a common condition that affects millions of Americans. Addressing SUD has been complicated by comorbid mental disorders and co-occurring substance use. Consequently, detailing and addressing SUD and comorbid SUD represent an important goal to improve the health of Americans.

Objective. The research goal of this dissertation was to characterize the comorbidity between substance use, including tobacco use, and mental disorder symptoms measured as negative affect and externalizing symptoms in a population-based sample using latent variable and network approaches.

Methods. Waves 1 – 3 from the Population Assessment of Tobacco and Health Study were used. Various statistical analyses were used to complete each project including multinomial and ordinal regression, latent class analysis, cumulative ROC curve analysis, and network analysis.

Results. The associations between psychopathology (negative affect vs. externalizing severity) varied by different substance use combinations. Both latent class analysis and network analysis results identified relationships between (1) exclusive cigarette, dual cigarette and e-cigarette, marijuana, and PDNP with negative affect symptoms, and (2) alcohol with externalizing symptoms. The comorbidity structure remained stable with transition to lower severity groups but identification of stronger connections across three data points.

Conclusions. This dissertation identified specific combinations of substance use behaviors and mental disorder symptoms, determined which sociodemographic factors play a role in specific comorbidity profiles, and assessed the patterns of comorbidity among three waves of data. The results can inform robust and targeted prevention strategies to effectively mitigate the substantial burden and societal costs of comorbidity in the U.S. population.

Rights

© The Author

Is Part Of

VCU University Archives

Is Part Of

VCU Theses and Dissertations

Date of Submission

5-12-2021

Included in

Epidemiology Commons

Share

COinS