Is lower severity alcohol use disorder qualitatively different than more severe manifestations? An evaluation of multivariate symptom clusters

Implications of the shift to DSM-5 for alcohol use disorder prevalence estimates in the National Survey on Drug Use and Health

BACKGROUND AND AIMS

The Substance Abuse and Mental Health Services Administration's annual National Survey on Drug Use and Health (NSDUH) is a commonly used source for estimating trends in alcohol use disorders (AUD) in the United States. From 2015 to 2019 the annual prevalence of people diagnosed with either Diagnostic and Statistical Manual 4th edition (DSM-IV) alcohol abuse or dependence ranged from 5.3 to 5.9%. More recent estimates, using the DSM 5th edition (DSM-5) AUD diagnostic formulation, have been higher, with AUD base rates ranging from 10.1 to 10.7% from 2020 to 2022. This study aimed to compare the past 12-month base rates of AUD in the United States general population when using the DSM-5 versus DSM-IV AUD (i.e. abuse or dependence) and assess the AUD severity of individuals captured with each diagnostic formulation using DSM-5 AUD symptom counts.

METHODS

We examined descriptive trends in the rate of past-year NSDUH AUD diagnoses from 2015 to 2022. We contrasted them with trends in drinking behavior: the percentage of individuals who had ever reported drinking and the number of drinking days and binge drinking days for those who drink. We also analyzed the concordance between DSM-IV and DSM-5 AUD diagnoses in the 2020 NSDUH, which concurrently assessed AUD with both diagnostic formulations.

RESULTS

The transition to DSM-5 AUD formulation coincided with a drastic increase in AUD prevalence rates that occurred without increases in drinking behavior. In 2020 NSDUH data, the estimated past-year DSM-5 AUD prevalence rate was 10.1% compared with a 5.4% rate of past-year DSM-IV abuse or dependence. The DSM-5 AUD formulation captured more mild-severity individuals than the DSM-IV formulation.

CONCLUSIONS

Higher recent base rates of alcohol use disorders (AUD) in the National Survey on Drug Use and Health are likely, at least partially, explained by measurement changes in AUD; specifically, the shift from DSM-IV abuse or dependence to DSM-5 AUD. The DSM-5 formulation appears substantially more inclusive than the DSM-IV formulation, leading to a larger number of mild severity individuals being captured.

Examination of the mild, moderate, and severe alcohol use disorder severity indicators using a nationally representative sample

OBJECTIVE

The Diagnostic and Statistical Manual of Mental Disorders, fifth edition conceptualizes alcohol use disorder (AUD) as a single continuum with indicators to denote the level of severity along this spectrum with the presence of 2-3, 4-5, or 6 + symptoms indicating mild, moderate, and severe AUD, respectively. However, despite the labels of these indicators, it remains unclear how individuals compare across these indicators, both in terms of AUD severity, but also risk for other related problems (e.g., depression).

METHOD

Confirmatory factor analysis was conducted on past year AUD symptoms to obtain estimates of latent AUD severity using data from the 2020 National Survey on Drug Use and Health (unweighted n = 31,941). The range and distribution of latent trait estimates were then compared across AUD diagnostic statuses (i.e., no AUD, mild, moderate, and severe). Multinomial regressions were then used to compare diagnostic groups based on alcohol use, problems with other substances, treatment utilization, and mental/physical health.

RESULTS

Results indicated very limited overlap in latent severity estimates between individuals with different severity indicators. Multinomial regression results demonstrated that some measures increased in a roughly stepwise fashion across AUD indicators (e.g., alcohol use and drinking behavior), while many did not.

CONCLUSIONS

Results partially support the current AUD indicators as AUD severity and co-occurring problems did broadly increase across the indicators. However, the present study also explores several ways to improve these indicators in future AUD formulations. For example, having indicators that account not only for the quantitative but also the qualitative differences in AUD presentation at different severity levels. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Diagnostic Criteria for Identifying Individuals at High Risk of Progression From Mild or Moderate to Severe Alcohol Use Disorder

Importance

Current Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) (DSM-5) diagnoses of substance use disorders rely on criterion count-based approaches, disregarding severity grading indexed by individual criteria.

Objective

To examine correlates of alcohol use disorder (AUD) across count-based severity groups (ie, mild, moderate, mild-to-moderate, severe), identify specific diagnostic criteria indicative of greater severity, and evaluate whether specific criteria within mild-to-moderate AUD differentiate across relevant correlates and manifest in greater hazards of severe AUD development.

Design, Setting, and Participants

This cohort study involved 2 cohorts from the family-based Collaborative Study on the Genetics of Alcoholism (COGA) with 7 sites across the United States: cross-sectional (assessed 1991-2005) and longitudinal (assessed 2004-2019). Statistical analyses were conducted from December 2022 to June 2023.

Main Outcomes and Measures

Sociodemographic, alcohol-related, psychiatric comorbidity, brain electroencephalography (EEG), and AUD polygenic score measures as correlates of DSM-5 AUD levels (ie, mild, moderate, severe) and criterion severity-defined mild-to-moderate AUD diagnostic groups (ie, low-risk vs high-risk mild-to-moderate).

Results

A total of 13 110 individuals from the cross-sectional COGA cohort (mean [SD] age, 37.8 [14.2] years) and 2818 individuals from the longitudinal COGA cohort (mean baseline [SD] age, 16.1 [3.2] years) were included. Associations with alcohol-related, psychiatric, EEG, and AUD polygenic score measures reinforced the role of increasing criterion counts as indexing severity. Yet within mild-to-moderate AUD (2-5 criteria), the presence of specific high-risk criteria (eg, withdrawal) identified a group reporting heavier drinking and greater psychiatric comorbidity even after accounting for criterion count differences. In longitudinal analyses, prior mild-to-moderate AUD characterized by endorsement of at least 1 high-risk criterion was associated with more accelerated progression to severe AUD (adjusted hazard ratio [aHR], 11.62; 95% CI, 7.54-17.92) compared with prior mild-to-moderate AUD without endorsement of high-risk criteria (aHR, 5.64; 95% CI, 3.28-9.70), independent of criterion count.

Conclusions and Relevance

In this cohort study of a combined 15 928 individuals, findings suggested that simple count-based AUD diagnostic approaches to estimating severe AUD vulnerability, which ignore heterogeneity among criteria, may be improved by emphasizing specific high-risk criteria. Such emphasis may allow better focus on individuals at the greatest risk and improve understanding of the development of AUD.

Polysubstance addiction patterns among 7,989 individuals with cocaine use disorder

To characterize polysubstance addiction (PSA) patterns of cocaine use disorder (CoUD), we performed a latent class analysis (LCA) in 7,989 participants with a lifetime DSM-5 diagnosis of CoUD. This analysis identified three PSA subgroups among CoUD participants (i.e., low, 17%; intermediate, 38%; high, 45%). While these subgroups varied by age, sex, and racial-ethnic distribution (p < 0.001), there was no difference with respect to education or income (p > 0.05). After accounting for sex, age, and race-ethnicity, the CoUD subgroup with high PSA had higher odds of antisocial personality disorder (OR = 21.96 vs. 6.39, difference-p = 8.08✕10-6), agoraphobia (OR = 4.58 vs. 2.05, difference-p = 7.04✕10-4), mixed bipolar episode (OR = 10.36 vs. 2.61, difference-p = 7.04✕10-4), posttraumatic stress disorder (OR = 11.54 vs. 5.86, difference-p = 2.67✕10-4), antidepressant medication use (OR = 13.49 vs. 8.02, difference-p = 1.42✕10-4), and sexually transmitted diseases (OR = 5.92 vs. 3.38, difference-p = 1.81✕10-5) than the low-PSA CoUD subgroup. These findings underscore the importance of modeling PSA severity and comorbidities when examining the clinical, molecular, and neuroimaging correlates of CoUD.

Polysubstance addiction and psychiatric, somatic comorbidities among 7,989 individuals with cocaine use disorder: a latent class analysis

Aims

We performed a latent class analysis (LCA) in a sample ascertained for addiction phenotypes to investigate cocaine use disorder (CoUD) subgroups related to polysubstance addiction (PSA) patterns and characterized their differences with respect to psychiatric and somatic comorbidities.

Design

Cross-sectional study.

Setting

United States.

Participants

Adult participants aged 18-76, 39% female, 47% African American, 36% European American with a lifetime DSM-5 diagnosis of CoUD (N=7,989) enrolled in the Yale-Penn cohort. The control group included 2,952 Yale-Penn participants who did not meet for alcohol, cannabis, cocaine, opioid, or tobacco use disorders.

Measurements

Psychiatric disorders and related traits were assessed via the Semi-structured Assessment for Drug Dependence and Alcoholism. These features included substance use disorders (SUD), family history of substance use, sociodemographic information, traumatic events, suicidal behaviors, psychopathology, and medical history. LCA was conducted using diagnoses and diagnostic criteria of alcohol, cannabis, opioid, and tobacco use disorders.

Findings

Our LCA identified three subgroups of PSA (i.e., low, 17%; intermediate, 38%; high, 45%) among 7,989 CoUD participants. While these subgroups varied by age, sex, and racial-ethnic distribution (p<0.001), there was no difference on education or income (p>0.05). After accounting for sex, age, and race-ethnicity, the CoUD subgroup with high PSA had higher odds of antisocial personality disorder (OR=21.96 vs. 6.39, difference-p=8.08×10 -6 ), agoraphobia (OR=4.58 vs. 2.05, difference-p=7.04×10 -4 ), mixed bipolar episode (OR=10.36 vs. 2.61, difference-p=7.04×10 -4 ), posttraumatic stress disorder (OR=11.54 vs. 5.86, difference-p=2.67×10 -4 ), antidepressant medication use (OR=13.49 vs. 8.02, difference-p=1.42×10 -4 ), and sexually transmitted diseases (OR=5.92 vs. 3.38, difference-p=1.81×10 -5 ) than the low-PSA CoUD subgroup.

Conclusions

We found different patterns of PSA in association with psychiatric and somatic comorbidities among CoUD cases within the Yale-Penn cohort. These findings underscore the importance of modeling PSA severity and comorbidities when examining the clinical, molecular, and neuroimaging correlates of CoUD.