Changing adolescent activity patterns and the correlation of self-esteem and externalizing mental health symptoms across time: results from the USA from 1991 through 2020.

BACKGROUND: Common adolescent psychiatric symptoms cluster into two dominant domains: internalizing and externalizing. Both domains are linked to self-esteem, which serves as a protective factor against a wide range of internalizing and externalizing problems. This study examined trends in US adolescents' self-esteem and externalizing symptoms, and their correlation, by sex and patterns of time use. METHODS: Using Monitoring the Future data (N = 338 896 adolescents, grades:8/10/12, years:1991-2020), we generated six patterns of time use using latent profile analysis with 17 behavior items (e.g. sports participation, parties, paid work). Groups were differentiated by high/low engagement in sports and either paid work or high/low peer socialization. Within each group, we mapped annual, sex-stratified means of (and correlation between) self-esteem and externalizing factors. We also examined past-decade rates of change for factor means using linear regression and mapped proportions with top-quartile levels of poor self-esteem, externalizing symptoms, or both. RESULTS: We found consistent increases in poor self-esteem, decreases in externalizing symptoms, and a positive correlation between the two across nearly all activity groups. We also identified a relatively constant proportion of those with high levels of both in every group. Increases in poor self-esteem were most pronounced for female adolescents with low levels of socializing, among whom externalizing symptoms also increased. CONCLUSIONS: Rising trends in poor self-esteem are consistent across time use groups, as is the existence of a group facing poor self-esteem and externalizing symptoms. Effective interventions for adolescents' poor self-esteem/co-occurring symptoms are needed broadly, but especially among female adolescents with low peer socialization.

Age differences in patterns of cannabis use among an online US sample of adults who consume cannabis frequently.

Background: Cannabis use is increasing among middle-aged and older US adults, populations that are particularly vulnerable to the adverse effects of cannabis. Risks for adverse effects differ by cannabis use patterns, which have become increasingly heterogeneous. Nevertheless, little is known about age differences in such patterns.Objective: To investigate age differences in cannabis use patterns, comparing younger (age 18-49), middle-aged (age 50-64), and older adults (age ≥65).Methods: A total of 4,151 US adults with past 7-day cannabis consumption completed an online survey (35.1% male; 60.1% female; 4.8% identified as "other"). Regression models examined age differences in cannabis use patterns.Results: Compared to younger adults, middle-aged and older adults were more likely to consume cannabis during evening hours (50-64: adjusted odds ratio [aOR] = 2.98, 95% CI 2.24-3.96; ≥65: aOR = 4.23, 95 CI 2.82-6.35); by only one method (50-64: aOR = 1.67, 95% CI 1.34-2.09; ≥65: aOR = 3.38, 95 CI 2.24-5.09); primarily by smoking as the only method (50-64: aOR = 1.52, 95% CI 1.29-1.78; ≥65: aOR = 2.12, 95 CI 1.64-2.74); but less likely to consume concentrated cannabis products (concentrates) with extremely high %THC (50-64: aOR = 0.71, 95% CI 0.54-0.93; ≥65: aOR = 0.30, 95 CI 0.16-0.55). Age differences in cannabis use patterns were also observed between middle-aged and older adults.Conclusion: Findings suggest that middle-aged and older adults may engage in less risky cannabis use patterns compared to younger groups (e.g. lower likelihood of consuming highly potent concentrates). However, findings also underscore the importance of recognizing risks unique to these older demographics, such as smoking-related health events. Consequently, prevention strategies targeting such use patterns are needed.

Cannabis Recreational Legalization and Prevalence of Simultaneous Cannabis and Alcohol Use in the United States.

BACKGROUND: Simultaneous cannabis/alcohol use, using both substances within a short time interval so that their effects overlap, has a greater risk of potential negative consequences than single-substance use and is more common in younger age. Relationships between recreational cannabis laws (RCLs) and changes in simultaneous cannabis/alcohol use prevalence remain untested. OBJECTIVE: To examine trends in simultaneous cannabis/alcohol use from 2008 to 2019, and investigate associations between implementation of RCLs (i.e., presence of active legal dispensaries or legal home cultivation) and simultaneous cannabis/alcohol use in the United States (U.S.). DESIGN: Repeated cross-sectional samples from the 2008-2019 U.S. National Survey on Drug Use and Health (NSDUH). PARTICIPANTS: Respondents (51% female) aged 12 and older. INTERVENTIONS: Changes in simultaneous cannabis/alcohol use before and after RCL implementation (controlling for medical cannabis law implementation) were compared in different age groups (12-20, 21-30, 31-40, 41-50, 51+), using adjusted multi-level logistic regression with state random intercepts and an RCL/age group interaction. MEASUREMENTS: Self-reported simultaneous cannabis/alcohol use. RESULTS: From 2008 to 2019, the overall prevalence of simultaneous cannabis/alcohol use declined among those aged 12-20 but increased in adults aged 21+. Model-based simultaneous cannabis/alcohol use prevalence increased after RCL implementation among respondents aged 21-30 years (+1.2%; aOR= 1.15 [95%CI = 1.04-1.27]), 31-40 years (+1.0; 1.15 [1.04-1.27]), and 41-50 years (+1.75; 1.63 [1.34-1.98]), but not in individuals aged <21 or 51+ years. CONCLUSIONS: Implementation of recreational cannabis policies resulted in increased simultaneous use of cannabis and alcohol, supporting the complementarity hypothesis, but only among adults aged 21+. Efforts to minimize harms related to simultaneous cannabis/alcohol use are critical, especially in states with RCLs. Future studies should investigate cultural norms, perceived harm, and motives related to simultaneous use.

Risks of opioid overdose among New York State Medicaid recipients with chronic pain before and during the COVID-19 pandemic.

OBJECTIVE: The COVID-19 pandemic contributed to healthcare disruptions for patients with chronic pain. Following initial disruptions, national policies were enacted to expand access to long-term opioid therapy (LTOT) for chronic pain and opioid use disorder (OUD) treatment services, which may have modified risk of opioid overdose. We examined associations between LTOT and/or OUD with fatal and non-fatal opioid overdoses, and whether the pandemic moderated overdose risk in these groups. METHODS: We analyzed New York State Medicaid claims data (3/1/2019-12/31/20) of patients with chronic pain (N = 236,391). We used generalized estimating equations models to assess associations between LTOT and/or OUD (neither LTOT or OUD [ref], LTOT only, OUD only, and LTOT and OUD) and the pandemic (03/2020-12/2020) with opioid overdose. RESULTS: The pandemic did not significantly (ns) affect opioid overdose among patients with LTOT and/or OUD. While patients with LTOT (vs. no LTOT) had a slight increase in opioid overdose during the pandemic (pre-pandemic: aOR:1.65, 95% CI:1.05, 2.57; pandemic: aOR:2.43, CI:1.75,3.37, ns), patients with OUD had a slightly attenuated odds of overdose during the pandemic (pre-pandemic: aOR:5.65, CI:4.73, 6.75; pandemic: aOR:5.16, CI:4.33, 6.14, ns). Patients with both LTOT and OUD also experienced a slightly reduced odds of opioid overdose during the pandemic (pre-pandemic: aOR:5.82, CI:3.58, 9.44; pandemic: aOR:3.70, CI:2.11, 6.50, ns). CONCLUSIONS: Findings demonstrated no significant effect of the pandemic on opioid overdose among people with chronic pain and LTOT and/or OUD, suggesting pandemic policies expanding access to chronic pain and OUD treatment services may have mitigated the risk of opioid overdose.

Evaluating chronic pain as a risk factor for COVID-19 complications among New York State Medicaid beneficiaries: a retrospective claims analysis.

OBJECTIVE: To assess whether chronic pain increases the risk of COVID-19 complications and whether opioid use disorder (OUD) differentiates this risk among New York State Medicaid beneficiaries. DESIGN, SETTING, AND SUBJECTS: This was a retrospective cohort study of New York State Medicaid claims data. We evaluated Medicaid claims from March 2019 through December 2020 to determine whether chronic pain increased the risk of COVID-19 emergency department (ED) visits, hospitalizations, and complications and whether this relationship differed by OUD status. We included beneficiaries 18-64 years of age with 10 months of prior enrollment. Patients with chronic pain were propensity score-matched to those without chronic pain on demographics, utilization, and comorbidities to control for confounders and were stratified by OUD. Complementary log-log regressions estimated hazard ratios (HRs) of COVID-19 ED visits and hospitalizations; logistic regressions estimated odds ratios (ORs) of hospital complications and readmissions within 0-30, 31-60, and 61-90 days. RESULTS: Among 773 880 adults, chronic pain was associated with greater hazards of COVID-related ED visits (HR = 1.22 [95% CI: 1.16-1.29]) and hospitalizations (HR = 1.19 [95% CI: 1.12-1.27]). Patients with chronic pain and OUD had even greater hazards of hospitalization (HR = 1.25 [95% CI: 1.07-1.47]) and increased odds of hepatic- and cardiac-related events (OR = 1.74 [95% CI: 1.10-2.74]). CONCLUSIONS: Chronic pain increased the risk of COVID-19 ED visits and hospitalizations. Presence of OUD further increased the risk of COVID-19 hospitalizations and the odds of hepatic- and cardiac-related events. Results highlight intersecting risks among a vulnerable population and can inform tailored COVID-19 management.

Prevalence and correlates of DSM-5 opioid withdrawal syndrome in U.S. adults with non-medical use of prescription opioids: results from a national sample.

Background: In the U.S. non-medical use of prescription opioids (NMOU) is prevalent and often accompanied by opioid withdrawal syndrome (OWS). OWS has not been studied using nationally representative data.Objectives: We examined the prevalence and clinical correlates of OWS among U.S. adults with NMOU.Methods: We used data from 36,309 U.S. adult participants in the 2012-2013 National Epidemiologic Survey on Alcohol and Related Conditions-III, 1,527 of whom reported past 12-month NMOU. Adjusted linear and logistic regression models examined associations between OWS and its clinical correlates, including psychiatric disorders, opioid use disorder (OUD; excluding the withdrawal criterion), medical conditions, and healthcare utilization among people with regular (i.e. ≥3 days/week) NMOU (n = 534).Results: Over half (50.4%) of the sample was male. Approximately 9% of people with NMOU met criteria for DSM-5 OWS, with greater prevalence of OWS (∼20%) among people with regular NMOU. Individuals with bipolar disorder, dysthymia, panic disorder, and borderline personality disorder had greater odds of OWS (aOR range = 2.71-4.63). People with OWS had lower mental health-related quality of life (ß=-8.32, p < .001). Individuals with OUD also had greater odds of OWS (aOR range = 26.02-27.77), an association that increased with more severe OUD. People using substance use-related healthcare services also had greater odds of OWS (aOR range = 6.93-7.69).Conclusion: OWS was prevalent among people with OUD and some psychiatric disorders. These findings support screening for OWS in people with NMOU and suggest that providing medication- assisted treatments and behavioral interventions could help to reduce the burden of withdrawal in this patient population.

Exploring survey methods for measuring consumption quantities of cannabis flower and concentrate products.

Background: Researchers need accurate measurements of cannabis consumption quantities to assess risks and benefits. Survey methods for measuring cannabis flower and concentrate quantities remain underdeveloped.Objective: We examined "grams" and "hits" units for measuring flower and concentrate quantities, and calculating milligrams of THC (mgTHC).Methods: Online survey participants (n = 2,381) reported preferred unit (hits or grams), past-week hits and grams for each product, and product %THC. Quantile regression compared mgTHC between unit-preference subgroups. Hits-based mgTHC calculations assumed a universal grams-per-hit ratio (GPHR). To examine individualized GPHRs, we tested a "two-item approach," which divided total grams by total hits, and "one-item approach," which divided 0.5 grams by responses to the question: "How many total hits would it take you to finish 1/2 g of your [product] by [administration method]?"Results: Participants were primarily daily consumers (77%), 50% female sex, mean age 39.0 (SD 16.4), 85% White, 49% employed full-time. Compared to those who preferred the hits unit, those who preferred the grams unit reported consuming more hits and grams, higher %THC products, and consequently, larger median mgTHC (flower-hits mgTHC: 32 vs. 91 (95%CI: 52-67); flower-grams mgTHC: 27 vs. 113 (95%CI: 73-95); concentrate-hits mgTHC: 29 vs. 59 (95%CI: 15-43); concentrate-grams mgTHC: 61 vs. 129 (95%CI: 43-94)). "Two-item" and "one-item" approach GPHRs were similar and frequently 50% larger or smaller than the universal GPHR.Conclusion: Allowing respondents to choose "hits" or "grams" when reporting cannabis quantities does not compromise mgTHC estimates. A low-burden, one-item approach yields individualized "hit sizes" that may improve mgTHC estimates.

Non-pharmacological Treatment for Chronic Pain in US Veterans Treated Within the Veterans Health Administration: Implications for Expansion in US Healthcare Systems.

BACKGROUND: Consensus guidelines recommend multimodal chronic pain treatment with increased use of non-pharmacological treatment modalities (NPM), including as first-line therapies. However, with many barriers to NPM uptake in US healthcare systems, NPM use may vary across medical care settings. Military veterans are disproportionately affected by chronic pain. Many veterans receive treatment through the Veterans Health Administration (VHA), an integrated healthcare system in which specific policies promote NPM use. OBJECTIVE: To examine whether veterans with chronic pain who utilize VHA healthcare were more likely to use NPM than veterans who do not utilize VHA healthcare. DESIGN: Cross-sectional nationally representative study. PARTICIPANTS: US military veterans (N = 2,836). MAIN MEASURES: In the 2019 National Health Interview Survey, veterans were assessed for VHA treatment, chronic pain (i.e., past 3-month daily or almost daily pain), symptoms of depression and anxiety, substance use, and NPM (i.e., physical therapy, chiropractic/spinal manipulation, massage, psychotherapy, educational class/workshop, peer support groups, or yoga/tai chi). KEY RESULTS: Chronic pain (45.2% vs. 26.8%) and NPM use (49.8% vs. 39.4%) were more prevalent among VHA patients than non-VHA veterans. After adjusting for sociodemographic characteristics, psychiatric symptoms, physical health indicators, and use of cigarettes or prescription opioids, VHA patients were more likely than non-VHA veterans to use any NPM (adjusted odds ratio [aOR] = 1.52, 95% CI: 1.07-2.16) and multimodal NPM (aOR = 1.80, 95% CI: 1.12-2.87) than no NPM. Among veterans with chronic pain, VHA patients were more likely to use chiropractic care (aOR = 1.90, 95% CI = 1.12-3.22), educational class/workshop (aOR = 3.02, 95% CI = 1.35-6.73), or psychotherapy (aOR = 4.28, 95% CI = 1.69-10.87). CONCLUSIONS: Among veterans with chronic pain, past-year VHA use was associated with greater likelihood of receiving NPM. These findings may suggest that the VHA is an important resource and possible facilitator of NPM. VHA policies may offer guidance for expanding use of NPM in other integrated US healthcare systems.

The Heart and Cannabis (THC) Cohort: Differences in Baseline Health and Behaviors by Cannabis Use.

BACKGROUND: Evidence on the cardiovascular health effects of cannabis use is limited. We designed a prospective cohort study of older Veterans (66 to 68 years) with coronary artery disease (CAD) to understand the cardiovascular consequences of cannabis use. We describe the cohort construction, baseline characteristics, and health behaviors that were associated with smoking cannabis. OBJECTIVE: To understand the cardiovascular consequences of cannabis use. DESIGN: We designed a prospective cohort study of older Veterans (66 to 68 years) with CAD. PARTICIPANTS: A total of 1,015 current cannabis smokers and 3,270 non-cannabis smokers with CAD. MAIN MEASURES: Using logistic regression, we examined the association of baseline variables with smoking cannabis in the past 30 days. RESULTS: The current cannabis smokers and non-current smokers were predominantly male (97.2% vs 97.1%, p=0.96). Characteristics associated with recent cannabis use in multivariable analyses included lack of a high school education (odds ratio [OR] 2.15, 95% confidence interval [CI]: 1.10 to 4.19), financial difficulty (OR 1.47, 95% CI: 1.02 to 2.11), tobacco use (OR 3.02, 95% CI: 1.66 to 5.48), current drug use (OR 2.82, 95% CI: 1.06 to 7.46), and prior drug use (OR 2.84, 95% CI: 2.11 to 3.82). In contrast, compared to individuals with 0 to 1 comorbid conditions, those with 5 chronic conditions or more (OR 0.43, 95% CI: 0.27 to 0.70) were less likely to smoke cannabis. CONCLUSIONS: In this older high-risk cohort, smoking cannabis was associated with higher social and behavioral risk, but with fewer chronic health conditions.

Alcohol withdrawal in past-year drinkers with unhealthy alcohol use: Prevalence, characteristics, and correlates in a national epidemiologic survey.

BACKGROUND: Despite its potential to produce serious adverse outcomes, DSM-5 alcohol withdrawal syndrome (AWS) has not been widely studied in the general population. METHODS: We used cross-sectional data from 36,309 U.S. adults from the 2012-2013 National Epidemiologic Survey on Alcohol and Related Conditions-III to examine the past-year prevalence of AWS and its correlates. We focused on an important clinical population-past-year drinkers with unhealthy alcohol use-i.e., those with a positive score on the Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) questionnaire. We also examined the association of AWS with sociodemographic measures, psychiatric disorders, alcohol-related measures, and healthcare utilization. RESULTS: Approximately one-third (n = 12,634) of respondents reported unhealthy alcohol use (AUDIT-C+). Of these, 14.3% met criteria for a DSM-5 AWS diagnosis. The mean (SE) number of withdrawal symptoms among individuals with AWS was 2.83 (1.88), with the most common being nausea/vomiting and insomnia (19.8% and 11.6%, respectively). Among AUDIT-C+ respondents, the odds of AWS were significantly higher among males (adjusted odds ratio [aOR] = 1.17 [95% CI, 1.02-1.33]), unmarried participants (aOR = 1.55 [95% CI, 1.25-1.92]), and those at the lowest (vs. highest) income levels (aOR = 1.62 [95% CI, 1.37-1.92]). Among AUDIT-C+ respondents, AWS was also associated with psychiatric disorders (with aORs that ranged from 2.08 [95% CI, 1.79-2.41]) for major depressive disorder to 3.14 (95% CI, 1.79-2.41) for borderline personality disorder. AUDIT-C+ respondents with AWS also had higher odds of past-year alcohol use disorder (aOR = 11.2 [95% CI, 9.66-13.07]), other alcohol-related features (e.g., binge drinking), and healthcare utilization. CONCLUSIONS: Among individuals with unhealthy alcohol use, AWS is prevalent, highly comorbid, and disabling. Given the risk of AWS among unhealthy drinkers, a comparatively large segment of the general population, clinicians should seek to identify individuals with AWS and intervene with them to prevent serious adverse outcomes.

Comparing mental and physical health of U.S. veterans by VA healthcare use: implications for generalizability of research in the VA electronic health records.

OBJECTIVE: The Department of Veterans Affairs' (VA) electronic health records (EHR) offer a rich source of big data to study medical and health care questions, but patient eligibility and preferences may limit generalizability of findings. We therefore examined the representativeness of VA veterans by comparing veterans using VA healthcare services to those who do not. METHODS: We analyzed data on 3051 veteran participants age ≥ 18 years in the 2019 National Health Interview Survey. Weighted logistic regression was used to model participant characteristics, health conditions, pain, and self-reported health by past year VA healthcare use and generate predicted marginal prevalences, which were used to calculate Cohen's d of group differences in absolute risk by past-year VA healthcare use. RESULTS: Among veterans, 30.4% had past-year VA healthcare use. Veterans with lower income and members of racial/ethnic minority groups were more likely to report past-year VA healthcare use. Health conditions overrepresented in past-year VA healthcare users included chronic medical conditions (80.6% vs. 69.4%, d = 0.36), pain (78.9% vs. 65.9%; d = 0.35), mental distress (11.6% vs. 5.9%; d = 0.47), anxiety (10.8% vs. 4.1%; d = 0.67), and fair/poor self-reported health (27.9% vs. 18.0%; d = 0.40). CONCLUSIONS: Heterogeneity in veteran sociodemographic and health characteristics was observed by past-year VA healthcare use. Researchers working with VA EHR data should consider how the patient selection process may relate to the exposures and outcomes under study. Statistical reweighting may be needed to generalize risk estimates from the VA EHR data to the overall veteran population.

Co-Use of Opioids and Sedatives Among Retired National Football League Athletes.

OBJECTIVE: Among the general population, co-use of opioids and sedatives is associated with greater risk of overdose compared with opioid use alone. National Football League (NFL) retirees experience higher rates of opioid use than the general population, although little is known about their co-use with sedatives. The aim of this study was to examine the prevalence and risk factors of opioid and sedative co-use among NFL retirees. DESIGN: Retrospective cohort study. SETTING: Professional American football. PARTICIPANTS: NFL retirees (N = 644). INDEPENDENT VARIABLES: Self-reported concussions, pain intensity, heavy alcohol use, physical and mental health impairment, disability status. MAIN OUTCOME MEASURE: Any past 30-day co-use of opioids and sedatives. RESULTS: Approximately 4.9% of the sample reported past 30-day co-use of opioids and sedatives, although nearly 30% of retirees using opioids also used sedatives. Greater pain was associated with co-use of opioids and sedatives (adjusted odds ratios [aOR] = 1.58; 95% confidence interval [CI] = 1.23-1.98), although retirees with moderate/severe mental health impairment (vs none/mild; aOR = 2.47; 95% CI = 1.04-5.91) and disability (vs no disability; aOR = 1.35; 95% CI = 1.05-1.73) demonstrated greater odds of co-use compared with retirees not using either substance. CONCLUSIONS: Given the high rate of sedative use among participants also using opioids, NFL retirees may be susceptible to the negative health consequences associated with co-use. Interventions focused on improving pain and mental health may be especially effective for reducing co-use of these substances among NFL retirees.

Adolescents' Use of Free Time and Associations with Substance Use from 1991 to 2019.

Background: Understanding time trends in risk factors for substance use may contextualize and explain differing time trends in substance use. Methods: We examined data (N = 536,291; grades 8/10/12) from Monitoring the Future, years 1991-2019. Using Latent Profile Analyses, we identified six time use patterns: one for those working at a paid job and the other five defined by levels of socialization (low/high) and engagement in structured activities like sports (engaged/disengaged), with the high social/engaged group split further by levels of unsupervised social activities. We tested associations between time use profiles and past two-week binge drinking as well as past-month alcohol use, cigarette use, cannabis use, other substance use, and vaping. We examined trends and group differences overall and by decade (or for vaping outcomes, year). Results: Prevalence of most substance use outcomes decreased over time among all groups. Cannabis use increased, with the largest increase in the group engaged in paid employment. Vaping substantially increased, with the highest nicotine vaping increase in the high social/engaged group with less supervision and the highest cannabis vaping increase in the highly social but otherwise disengaged group. Substance use was lowest in the low social groups, highest in the high social and employed groups. Conclusions: While alcohol, cigarette, and other substance use have declined for all groups, use remained elevated given high levels of social time, especially with low engagement in structured activities or low supervision, or paid employment. Cannabis use and vaping are increasing across groups, suggesting the need for enhanced public health measures.

Prescription Opioid Laws and Opioid Dispensing in US Counties: Identifying Salient Law Provisions With Machine Learning.

BACKGROUND: Hundreds of laws aimed at reducing inappropriate prescription opioid dispensing have been implemented in the United States, yet heterogeneity in provisions and their simultaneous implementation have complicated evaluation of impacts. We apply a hypothesis-generating, multistage, machine-learning approach to identify salient law provisions and combinations associated with dispensing rates to test in future research. METHODS: Using 162 prescription opioid law provisions capturing prescription drug monitoring program (PDMP) access, reporting and administration features, pain management clinic provisions, and prescription opioid limits, we used regularization approaches and random forest models to identify laws most predictive of county-level and high-dose dispensing. We stratified analyses by overdose epidemic phases-the prescription opioid phase (2006-2009), heroin phase (2010-2012), and fentanyl phase (2013-2016)-to further explore pattern shifts over time. RESULTS: PDMP patient data access provisions most consistently predicted high-dispensing and high-dose dispensing counties. Pain management clinic-related provisions did not generally predict dispensing measures in the prescription opioid phase but became more discriminant of high dispensing and high-dose dispensing counties over time, especially in the fentanyl period. Predictive performance across models was poor, suggesting prescription opioid laws alone do not strongly predict dispensing. CONCLUSIONS: Our systematic analysis of 162 law provisions identified patient data access and several pain management clinic provisions as predictive of county prescription opioid dispensing patterns. Future research employing other types of study designs is needed to test these provisions' causal relationships with inappropriate dispensing and to examine potential interactions between PDMP access and pain management clinic provisions. See video abstract at, http://links.lww.com/EDE/B861.

Stability of Drinking Reductions and Long-term Functioning Among Patients with Alcohol Use Disorder.

BACKGROUND: The World Health Organization (WHO) categorizes alcohol consumption according to grams consumed into low-, medium-, high-, and very-high-risk drinking levels (RDLs). Although abstinence has been considered the ideal outcome of alcohol treatment, reductions in WHO RDLs have been proposed as primary outcomes for alcohol use disorder (AUD) trials. OBJECTIVE: The current study examines the stability of WHO RDL reductions and the association between RDL reductions and long-term functioning for up to 3 years following treatment. DESIGN AND PARTICIPANTS: Secondary data analysis of patients with AUD enrolled in the COMBINE Study and Project MATCH, two multi-site, randomized AUD clinical trials, who were followed for up to 3 years post-treatment (COMBINE: n = 694; MATCH: n = 806). MEASURES: Alcohol use was measured via calendar-based methods. We estimated all models in the total sample and among participants who did not achieve abstinence during treatment. KEY RESULTS: One-level RDL reductions were achieved by 84% of patients at the end of treatment, with 84.9% of those individuals maintaining that reduction at a 3-year follow-up. Two-level RDL reductions were achieved by 68% of patients at the end of treatment, with 77.7% of those individuals maintaining that reduction at a 3-year follow-up. One- and two-level RDL reductions at the end of treatment were associated with significantly better mental health, quality of life (including physical quality of life), and fewer drinking consequences 3 years after treatment (p < 0.05), as compared to no change or increased drinking. CONCLUSION: AUD patients can maintain WHO RDL reductions for up to 3 years after treatment. Patients who had WHO RDL reductions functioned significantly better than those who did not reduce their drinking. These findings are consistent with prior reports suggesting that drinking reductions, short of abstinence, yield meaningful improvements in patient health, well-being, and functioning.

Correlates of mild, moderate, and severe Alcohol Use Disorder among adults with problem substance use: Validity implications for DSM-5.

BACKGROUND: The DSM-5 definition of alcohol use disorder (AUD) has been well validated, but information is lacking on the extent to which alcohol use, comorbidity, and impairment are associated with the 3 DSM-5-defined AUD severity levels: mild, moderate, and severe. This study examined clinical and functional characteristics as predictors (validators) of these severity levels. METHODS: Participants aged ≥18 years reporting current problem substance use (N = 588) were recruited between 2016 and 2019 and assessed for DSM-5 AUD and a set of potential validators: indicators of alcohol use severity (i.e., craving, binge drinking frequency, problematic use, and harmful drinking), psychiatric disorders, and functional impairment. Multinomial logistic regression models examined the association between the predictors and the 3 AUD severity levels (mild, moderate, and severe) vs the reference group, no AUD, controlling for sociodemographic characteristics and other substance use. RESULTS: All alcohol use validators were associated with a greater likelihood of all 3 AUD severity levels compared with the no-AUD group. However, psychiatric disorders were associated only with severe AUD and participants with major depression (aOR = 2.44), posttraumatic stress disorder (aOR = 1.65), borderline personality disorder (aOR = 1.99), and antisocial personality disorder (aOR = 1.78) had a greater likelihood of severe AUD than the no-AUD group. Functioning validators were also associated only with severe AUD and participants with social (aOR = 1.87), physical (aOR = 1.62), or mental (aOR = 1.84) impairment had a greater likelihood of severe AUD than the no-AUD group. Many alcohol-related, psychiatric, and functioning validators were associated with greater odds of severe AUD than mild or moderate AUD. CONCLUSION: This study supports the criterion validity of the DSM-5 tri-categorical measure of AUD. Specifically, results fully supported the validity of severe AUD by its associations with all predictors, whereas the validity of mild and moderate AUD was supported only by alcohol use predictor variables. Findings suggest the value of using severity-specific interventions utilizing the DSM-5 AUD.

Substance use in a sexual context: The association of sex-related substance use motives with substance choice and use behaviors.

BACKGROUND: Substance use before sex is associated with riskier behaviors. Sex-related substance use motives may explain pre-sex substance use. We explored what sex-related motives are associated with alcohol versus drug use, and which motives underlie heavier use. METHODS: A sample of 936 participants (50% male, 80% White) completed an Internet survey about sexuality. Those who drank before sex (n=657) reported on six sex-related drinking motives; those who used drugs before sex (n=271) reported on six (parallel) sex-related drug use motives. The frequency of endorsement of each motive between drinkers and drug users was compared with z-distributions. Logistic regressions assessed whether motives were associated with substance use frequency and intoxication before sex. RESULTS: Substance use to relax and to get a sex partner to use were more commonly endorsed for alcohol than drugs; substance use to improve performance and enhance experience were more commonly endorsed for drugs. Most motives were associated with alcohol frequency and intoxication before sex. None were associated with drug frequency; some were associated with drug intoxication. CONCLUSIONS: Alcohol was generally used to facilitate sex, and drugs to enhance sex. Sex-related drinking motives were associated with drinking before sex; sex-related drug use motives were less predictive.

Reduction in World Health Organization Risk Drinking Levels and Cardiovascular Disease.

BACKGROUND: Reductions in World Health Organization (WHO) risk drinking levels have recently been shown to lower the risk of multiple adverse health outcomes, but prior work has not examined reductions in WHO risk drinking levels in relation to cardiovascular disease (CVD), the leading cause of death for men and women in the United States and of global mortality. This study examined associations between reductions in WHO risk drinking levels and subsequent risk for CVD. METHODS: In a US national survey, 1,058 very-high-risk and high-risk drinkers participated in Wave 1 interviews (2001 to 2002) and Wave 2 follow-ups (2004 to 2005). Self-reported CVD history that was communicated to the participant by a doctor or other healthcare professionals included arteriosclerosis, hypertension, angina, tachycardia, or myocardial infarction. We used logistic regression to estimate adjusted odds ratios (aOR) evaluating relationships between ≥2-level reductions in WHO risk drinking levels from Wave 1 to Wave 2 and the risk of Wave 2 CVD, controlling for baseline characteristics. RESULTS: Reductions of ≥2 WHO risk drinking levels were associated with significantly lower odds of CVD in individuals who at Wave 1 were very-high-risk (aOR = 0.58 [0.41 to 0.80]) or high-risk drinkers (aOR = 0.81 [0.70 to 0.94]). Interaction terms showed that this relationship varied by age. Among individuals >40 years old at Wave 1, reductions of ≥2 WHO risk drinking levels were associated with significantly lower odds of CVD among very-high-risk drinkers (aOR = 0.42 [0.28 to 0.63]) but not high-risk drinkers (p = 0.50). Among individuals ≤40 years old at Wave 1, reductions of ≥2 WHO risk drinking levels were associated with significantly lower odds of CVD among high-risk drinkers (aOR = 0.50 [0.37 to 0.69]) but not very-high-risk drinkers (p = 0.27). CONCLUSIONS: These results show that reductions in WHO risk drinking levels are associated with reduced CVD risk among very-high-risk and high-risk drinkers in the US general population, and provide further evidence that reducing high levels of drinking provides important benefit across multiple clinical domains.

Perceived safety of cannabis intoxication predicts frequency of driving while intoxicated.

Driving under the influence of cannabis (DUIC) is a public health concern, and data are needed to develop screening and prevention tools. Measuring the level of intoxication that cannabis users perceive as safe for driving could help stratify DUIC risk. This study tested whether intoxication levels perceived as safe for driving predicted past-month DUIC frequency. Online survey data were collected in 2017 from a national sample of n = 3010 past-month cannabis users with lifetime DUIC (age 18+). Respondents indicated past-month DUIC frequency, typical cannabis intoxication level (1-10 scale), and cannabis intoxication level perceived as safe for driving (0-10 scale). Approximately 24%, 38%, 13%, and 24% of respondents engaged in DUIC on 0, 1-9, 10-19, and 20-30 days respectively in the past month. Among these four DUIC frequency groups, median typical intoxication varied little (5-6), but median intoxication perceived as safe for driving varied widely (3-8). Higher intoxication levels perceived as safe for driving corresponded to frequent DUIC (Spearman's rho: 0.46). For each unit increase in intoxication level perceived as safe for driving, the odds of past-month DUIC increased 18% to 68% (multinomial logistic regression odds ratio - MOR1-9 days: 1.18, 95% CI: 1.13-1.23; MOR10-19 days: 1.40, 95% CI: 1.30-1.50; MOR20-30 days: 1.68, 95% CI: 1.57-1.80). In this targeted sample of past-month cannabis users, DUIC frequency varied widely, but daily/near-daily DUIC was common (24%). Measuring intoxication levels perceived as safe for driving permits delineation of past-month DUIC frequency. This metric has potential as a component of public health prevention tools.

A data-driven method for identifying shorter symptom criteria sets: the case for DSM-5 alcohol use disorder.

BACKGROUND: Although the DSM is a widely used diagnostic guide, lengthy criteria sets can be problematic and provide the primary motivation to identify short-forms. Using the 11 diagnostic criteria provided by the DSM-5 for alcohol use disorder (AUD), the present study develops a data-driven method to systematically identify subsets and associated cut-offs that yield diagnoses as similar as possible to use all 11 criteria. METHOD: Relying on data from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC-III), our methodology identifies diagnostic short-forms for AUD by: (1) maximizing the association between the sum scores of all 11 criteria with newly constructed subscales from subsets of criteria; (2) optimizing the similarity of AUD prevalence between the current DSM-5 rule and newly constructed diagnostic short-forms; (3) maximizing sensitivity and specificity of the short-forms against the current DSM-5 rule; and (4) minimizing differences in the accuracy of the short-form across chosen covariates. Replication is shown using NESARC-Wave 2. RESULTS: More than 11 000 diagnostic short-forms for DSM-5 AUD can be created and our method narrows down the optimal choices to eight. Results found that 'Neglecting major roles' and 'Activities given up' could be dropped with practically no change in who is diagnosed (specificity = 100%, sensitivity ⩾ 99.6%) or the severity of those diagnosed (κ = 0.97). CONCLUSIONS: With a continuous improvement model adopted by the APA for DSM revisions, we offer a data-driven tool (a SAS Macro) that identifies diagnostic short-forms in a systematic and reproducible way to help advance potential improvements in future DSM revisions.