Full length articleShared and specific associations of substance use disorders on adverse outcomes: A national prospective study
Introduction
The shifting landscape of cannabis legalization (Pacula and Smart, 2017) and increases in the prevalence of use of alcohol (Grant et al., 2017), cannabis (Hasin et al., 2015), and other drug use disorders (SUD) (Grant et al., 2016) have brought to the fore the question of whether certain SUDs are more strongly associated with adverse outcomes and could therefore be considered more dangerous. The answer to this important question has been hampered by two important methodological limitations. First, most published studies examining the adverse outcomes related to SUDs have focused on a single substance (e.g., alcohol or nicotine dependence) rather than comparing SUDs with one another (Hall and Degenhardt, 2009; Sommers et al., 2006). Second, SUDs often co-occur in the same individual (Blanco et al., 2015, 2013a; Grant et al., 2016; Hoertel et al., 2018; Pascal et al., 2018), making it difficult to differentiate whether adverse outcomes are associated with a specific SUD or are shared across different disorders.
Multiple lines of evidence suggest the existence of drug-specific and shared mechanisms that may contribute to the development of SUDs and consequently their adverse outcomes. Shared mechanisms include shared genetic and epigenetic vulnerabilities (Cerda et al., 2010; Nestler, 2014; Tsuang et al., 1998), gene-environment interactions (Agrawal and Lynskey, 2008; Koob and Volkow, 2016), deficits in the brain reward systems (Fontenelle et al., 2011; Ross and Peselow, 2012) or HPA axis activity (Sinha, 2008), and environmental influences such as deficits in social support and early exposure to stress or trauma (Kelly and Daley, 2013). Drug-specific mechanisms also play a role in the development of individual SUD. For example, convergent results using genome-wide association support that a nicotinic receptor subunit gene cluster (CHRNA5/CHRNA3/CHRNB4) influences heavy smoking behavior (Berrettini et al., 2008). Genetic variation in nicotine metabolism and variations in the CYP2a6 region of chromosome 19 also play an important role in the development of nicotine use disorder (Audrain-McGovern et al., 2007). Polymorphisms in alcohol metabolizing enzymes strongly influence alcohol consumption and alcohol dependence (Bierut, 2011), with aldehyde dehydrogenase 2 deficiency exerting a protective role in the risk of alcohol use disorder (Harada et al., 1982). Variants in the alcohol metabolizing genes contribute to differences in alcohol use patterns but not to other drug use patterns. Similarly, variations of nicotine metabolizing genes increase smoking behavior but not other drug behavior (Bierut, 2011). Like their mechanisms, some adverse outcomes may be specific or more associated with certain SUDs, which would help stratify different SUDs risks; however, given their frequent co-occurrence, this can be an arduous task.
In this report, we sought to address whether adverse outcomes are associated with specific SUDs or are shared across different disorders by using a latent variable approach in which each SUD is conceptualized as a manifestation of a general latent predisposition for SUDs. The approach of representing this predisposition or liability as a latent factor is uniquely equipped to disentangle which associations are shared by all SUDs and which (if any) are unique to specific SUDs without making a priori assumptions about the reasons for these associations. We drew on data from a large, prospective general population study, the National Epidemiological Survey on Alcohol and Related Conditions (NESARC), to maximize the generalizability of our results. Prior studies (Blanco et al., 2015, 2013a; Blanco et al., 2013b; Eaton et al., 2012, 2015; Hoertel et al., 2015b; Pascal et al., 2018) have found that a single factor represents an underlying predisposition to psychiatric disorders. Based on this prior literature, we sought to examine whether the associations of SUDs with adverse outcomes occurred through a shared liability or were disorder-specific even after taking comorbidity into account. We hypothesized that: 1) the latent structure of SUD would be well-described by a single liability factor for SUDs, and 2) this factor would explain the association of SUDs with adverse consequences.
Prior research has documented that SUDs are strongly associated with a variety of adverse outcomes that may co-occur, including financial (Robbins and Nugent, 1975), social (Robbins and Nugent, 1975), marital (Lander et al., 2013), employment (Platt, 1995), violence (Goldstein, 1985), and legal (Robbins and Nugent, 1975) problems. Furthermore, individuals with SUDs have an increased risk of general medical conditions (Lieber, 1998; Stein, 1999) and psychiatric disorders (Kessler et al., 1996; Regier et al., 1990), which can affect health-related quality of life (Schaar and Ojehagen, 2003). Because of the lack of prior prospective national studies comparing the adverse consequences of different SUDs, we did not make any assumption regarding the specific contribution of each disorder to each adverse consequence. One application of factor analysis is the potential to better understand SUDs mechanisms leading to adverse outcomes and to develop management strategies targeted at multiple SUDs (Kim et al., 2012).
Section snippets
Sample
Data were drawn from the Wave 1 and Wave 2 of the NESARC, a nationally representative face-to-face survey of the US adult population conducted in 2001–2002 (Wave 1) and 2004–2005 (Wave 2) by the National Institute on Alcoholism and Alcohol Abuse (NIAAA) (Grant et al., 2009, 2016). The target population included the civilian non-institutionalized population, aged 18 years and older, residing in the United States. Face-to-face personal interviews were conducted with 43,093 respondents at Wave 1.
Associations between SUD at wave 1 and adverse outcomes at wave 2
In Wave 1, 12.66% of individuals had 1 SUD, 1.76%, had 2 SUDs, and 0.67% had 3 or more SUDs. In Wave 2, the most common adverse outcome was financial crisis, ranging from 22.8% (for alcohol dependence) to 42.6% (for amphetamine use disorder), whereas the least common was legal problems, ranging from 3.0% (for nicotine dependence) to 24.4% (for cocaine use disorder). After adjusting for sex, age, race/ethnicity, urbanicity, family history of SUDs and other psychiatric disorders, and Wave 1
Discussion
The use of a latent variable model allowed us to examine the underlying structure of SUDs and to address for the first time in a large, nationally representative sample the question of whether certain SUDs are more often associated with adverse outcomes. We had three main findings. First, we found that a one-factor model provided a good fit to the latent structure of SUD. Second, with the exception of nicotine dependence and tranquilizer use disorder, we found no specific associations of any
Conflict of interest
Dr. Blanco owns stock in Eli Lilly, Sanofi and General Electric.
Role of funding source
This study was supported by NIH grants DA019606 (Dr. Olfson), MH076051 and MH082773 (Drs. Blanco, Olfson and Wall) and the New York State Psychiatric Institute (Drs. Blanco, Olfson and Wall). Dr. Blanco’s work was conducted as part of previous work for New York State Psychiatric Institute/Columbia University. The views and opinions expressed in this report are those of the authors and should not be construed to represent the views of any of the sponsoring organizations, agencies, or the US
Contributors
Dr. Franco conceptualized the study, drafted the initial manuscript, and approved the final manuscript as submitted. Dr. Olfson, critically reviewed and revised the manuscript, and approved the final manuscript as submitted. Dr. Wall helped design the study, reviewed the manuscript and approved the final manuscript as submitted. Dr. Wang carried out the initial analyses and approved the final manuscript as submitted. Dr. Hoertel designed the study, drafted the initial manuscript, and approved
References (71)
- et al.
Hostility predicts alcohol consumption over a 21-year follow-up in the Gazel cohort
Drug Alcohol Depend.
(2017) Genetic vulnerability and susceptibility to substance dependence
Neuron
(2011)- et al.
The latent structure and predictors of non-medical prescription drug use and prescription drug use disorders: a national study
Drug Alcohol Depend.
(2013) - et al.
Should pathological gambling and obesity be considered addictive disorders? A national epidemiological study
Psychol. Med.
(2015) - et al.
Genetic and environmental influences on psychiatric comorbidity: a systematic review
J. Affect. Disord.
(2010) - et al.
Reliability of the alcohol and drug modules of the Alcohol Use Disorder and Associated Disabilities Interview Schedule-- Alcohol/Drug-Revised (AUDADIS-ADR): an international comparison
Drug Alcohol Depend.
(1997) - et al.
The Alcohol Use Disorder and Associated Disabilities Interview schedule (AUDADIS): reliability of alcohol and drug modules in a general population sample
Drug Alcohol Depend.
(1995) - et al.
The Alcohol Use Disorder and Associated Disabilities Interview Schedule-IV (AUDADIS-IV): reliability of alcohol consumption, tobacco use, family history of depression and psychiatric diagnostic modules in a general population sample
Drug Alcohol Depend.
(2003) - et al.
Adverse health effects of non-medical cannabis use
Lancet
(2009) - et al.
Possible protective role against alcoholism for aldehyde dehydrogenase isozyme deficiency in Japan
Lancet
(1982)
The Alcohol Use Disorder and Associated Disabilities Interview schedule (AUDADIS): reliability of alcohol and drug modules in a clinical sample
Drug Alcohol Depend.
A dimensional liability model of age differences in mental disorder prevalence: evidence from a national sample
J. Psychiatr. Res.
A comprehensive model of predictors of persistence and recurrence in adults with major depression: results from a national 3-year prospective study
J. Psych. Res.
A comprehensive model of predictors of suicide attempt in heavy drinkers: results from a national 3-year longitudinal study
Drug Alcohol Depend.
Neurobiology of addiction: a neurocircuitry analysis
Lancet Psychiatry
Childhood maltreatment and impulsivity as predictors of interpersonal violence, self-injury and suicide attempts: a national study
Psychiat. Res.
Epigenetic mechanisms of drug addiction
Neuropharmacology
Drug harms in the UK: a multicriteria decision analysis
Lancet
Methamphetamine use among young adults: health and social consequences
Addict. Behav.
Medical consequences of substance abuse
Psychiatr. Clin. North Am.
Comorbidity between DSM-IV alcohol and specific drug use disorders in the United States: results from the National Epidemiologic Survey on Alcohol and Related Conditions
Drug Alcohol Depend.
Are there genetic influences on addiction: evidence from family, adoption and twin studies
Addiction
The role of CYP2A6 in the emergence of nicotine dependence in adolescents
Pediatrics
Decision making, impulse control and loss of willpower to resist drugs: a neurocognitive perspective
Nat. Neurosci.
α-5/α-3 nicotinic receptor subunit alleles increase risk for heavy smoking
Mol. Psychiatry
Mapping common psychiatric disorders: structure and predictive validity in the National Epidemiologic Survey on Alcohol and Related Conditions
JAMA Psychiatry
Testing the drug substitution hypothesis: a national prospective study
JAMA Psychiatry
Towards a comprehensive developmental model of cannabis use disorders
Addiction
Cannabis use and risk of psychiatric disorders: prospective evidence from a US national longitudinal study
JAMA Psychiatry
The Spanish Alcohol Use Disorder and Associated Disabilities Interview Schedule (AUDADIS): reliability and concordance with clinical diagnoses in a Hispanic population
J. Stud. Alcohol
An invariant dimensional liability model of gender differences in mental disorder prevalence: evidence from a national sample
J. Abnorm. Psychol.
Transdiagnostic factors of psychopathology and substance use disorders: a review
Soc. Psychiatry Psychiatr. Epidemiol.
The intricate link between violence and mental disorder: results from the National Epidemiologic Survey on Alcohol and Related Conditions
Arch. Gen. Psychiatry
Obsessive-compulsive disorder, impulse control disorders and drug addiction: common features and potential treatments
Drugs
The drugs/violence nexus: a tripartite conceptual framework
J. Drug Issues
Cited by (19)
Latent class analysis of self-reported substance use during incarceration: Gender differences and associations with emotional distress and aggressiveness
2022, Journal of Substance Abuse TreatmentCitation Excerpt :Further, men and women incarcerated for drug-related offenses were at increased risk of belonging to the high polydrug use class, while men with violent offenses were at increased risk of membership in the high depressant use class. These two pieces of evidence add to the research documenting a link between substance use and adverse personal and community outcomes (Daley, 2013; Franco et al., 2019). Notably, and contrary to their male counterparts, the odds of belonging to the high polydrug use class decreased among women incarcerated for violent offenses.
Evaluating the modified common liability hypothesis of psychiatric comorbidity
2021, Journal of Psychiatric ResearchCitation Excerpt :The predisposition of individuals with SUDs to subsequently develop mood disorders may arise due to direct effects of substance use on brain structures involved in the regulation of mood and anxiety (Koob and Volkow, 2016) or through indirect associations. For example, SUDs are associated with multiple adverse events, such as increased rates of unemployment, and marital instability (Franco et al., 2019) and adverse events have been consistently linked to greater risk of mood disorders (Gilman, 2015; Kendler and Gardner, 2016). The present findings are consistent with observational studies showing that earlier alcohol use predicts later onset of MDD (Brook et al., 2002) and with the failure of clinical trials to consistently show that among patients with both classes of disorders, treating mood disorders leads to improvement in SUD outcomes (Torrens et al., 2005).
Examining the Utility of a General Substance Use Spectrum Using Latent Trait Modeling
2020, Drug and Alcohol DependenceCitation Excerpt :Put another way, the association between severity of use with a given substance and other measures of dysfunction does not appear to be moderated by the type of substance. This is consistent with previous research showing that the associations between alcohol/substance use symptoms and both other mental health disorders (Sunderland et al., 2015) and adverse outcomes (Franco et al., 2019) can almost entirely be explained by a general substance use latent factor. Taken together, there appears to be mounting evidence of the importance of what is common underlying AUD, CUD, and SUDs, perhaps more so than evidence stressing their unique contributions to our understanding of psychopathology.