Aims (1) Compare post-treatment alcohol use between those who use cannabis and those who abstain during treatment for alcohol use disorders (AUD). (2) Examine potential cannabis use thresholds by comparing post-treatment alcohol use between four frequency groups of cannabis users relative to abstainers. Design Secondary analyses of the COMBINE Study, a randomized control trial of AUD treatments. The current study compares longitudinal drinking data between those who used cannabis vs. those who abstained during COMBINE treatment. Setting The COMBINE Study treatments were delivered on an outpatient basis over 16 weeks. The current analyses include 206 cannabis users and 999 cannabis abstainers. Participants All participants met diagnosis of primary alcohol dependence (N = 1,383). Measurements Primary exposures were any cannabis use and quartiles of cannabis use (Q1: 1–4 use days during treatment, Q2: 5–9 days, Q3: 10–44 days, Q4: 45–112 days). Outcomes were percent days abstinent from alcohol (PDA), drinks per drinking day (DPDD), and percent heavy drinking days (PHD), all measured at treatment end and one year post-treatment. Findings Compared with no cannabis use, any cannabis use during treatment was associated with 4.35% (95% CI: −8.68, −0.02), or approximately four fewer alcohol abstinent days at the end of treatment. This association weakened by one-year post-treatment (95% CI: −9.78, 0.54). Compared with no cannabis use, only those in the second quartile of cannabis use (those who used once or twice per month during treatment) had 8.81% (95% CI: −17.00, −0.63), or approximately ten fewer days alcohol abstinent at end of treatment, and 11.82% (95% CI: −21.56, −2.07), or approximately 13 fewer alcohol abstinent days one-year post-treatment. Neither any cannabis use nor quartiles were associated with DPDD or PHD at either time-point. Conclusions Among individuals in alcohol treatment, any cannabis use (compared with none) is related to significantly lower percent days abstinent from alcohol post-treatment, though only among those who used cannabis once or twice per month.

Aims-To measure and describe drink alcohol content differences between Hispanic, non-Hispanic white and non-Hispanic black men and women in the US.Design-A telephone survey re-interview of 397 respondents who originally participated in the 2005 National Alcohol Survey of whom 306 provided complete information on home drinks. Setting-United StatesParticipants-Adults 18 and older from across the US. Measurements-Direct measurement by respondents of simulated drink pours in respondents'own glassware using a provided beaker and reported beverage brands were used to calculate drink alcohol content.Findings-Black men were found to have the largest overall mean drink alcohol content at 0.79oz (23ml) of alcohol. This was significantly larger than the mean for white men or for black women and added 30% to black men's monthly alcohol intake when applied to their reported number of drinks. Spirits drinks were found to be particularly large for men. Multivariate models indicated that drink alcohol content differences are attributable more to income and family structure differences than to unmeasured cultural factors tied to race or ethnicity per se. Models predicting alcohol-related consequences and dependence indicate that adjusting drink alcohol content improves model fit and reduces differences between race/ethnicity defined groups.Conclusions-Differences in drink alcohol content by gender, race/ethnicity and beverage type choice should be considered in comparisons of drinking patterns and alcohol-related outcomes. Observed differences can be partially explained by measured characteristics regarding family structure and income.

The data came from 8,750 adult men and women in two parallel 2015 U.S. national surveys conducted in English and Spanish. Both surveys used computer-assisted telephone interviews and two-stage, stratified, list-assisted, random samples of adults ages 18 and older. Results: One in five adults experienced at least one of ten 12-month harms because of someone else's drinking. The prevalence of specific harm types and characteristics differed by gender. Women were more likely to report harm due to drinking by a spouse/partner or family member, whereas men were more likely to report harm due to a stranger's drinking. Being female also predicted family/financial harms. Yo unger age increased risk for all AHTO types, except physical aggression. Being of Black/ other ethnicity, being separated/widowed/divorced, and having a college education without a degree each predicted physical aggression harm. The harmed individual's own heavy drinking and having a heavy drinker in the household increased risk for all AHTO types. The risk for physical aggression due to someone else's drinking was particularly elevated for heavy drinking women. Conclusions: Secondhand effects of alcohol in the United States are substantial and affected by sociodemographics, the harmed individual's own drinking, and the presence of a heavy drinker in the household. Broad-based and targeted public health measures that consider AHTO risk factors are needed to reduce alcohol's secondhand harms.