The role of alcohol response phenotypes in the risk for alcohol use disorder

Heavy alcohol use is pervasive and one of our most significant global health burdens. Early theories posited that certain alcohol response phenotypes, notably low sensitivity to alcohol (‘low-level response’) imparts risk for alcohol use disorder (AUD). However, other theories, and newer measures of subjective alcohol responses, have challenged that contention and argued that high sensitivity to some alcohol effects are equally important for AUD risk. This study presents results of a unique longitudinal study in 294 young adult non-dependent drinkers examined with alcohol and placebo testing in the laboratory at initial enrolment and repeated 5 years later, with regular follow-up intervals assessing AUD (trial registration: http://clinicaltrials.gov/ct2/show/NCT00961792). Findings showed that alcohol sedation was negatively correlated with stimulation across the breath alcohol curve and at initial and re-examination testing. A higher rather than lower alcohol response phenotype was predictive of future AUD. The findings underscore a new understanding of factors increasing vulnerability to AUD

Trends in Marijuana Use Among Pregnant and Nonpregnant Reproductive-Aged Women, 2002-2014

Between 2001 and 2013, marijuana use among US adults more than doubled, many states legalized marijuana use, and attitudes toward marijuana became more permissive. In aggregated 2007-2012 data, 3.9% of pregnant women and 7.6% of nonpregnant reproductive-aged women reported past-month marijuana use. Although the evidence is mixed, human and animal studies suggest that prenatal marijuana exposure may be associated with poor offspring outcomes (eg, low birth weight, impaired neurodevelopment). The American College of Obstetricians and Gynecologists recommends that pregnant women and women contemplating pregnancy be screened for and discouraged from using marijuana and other substances. Whether marijuana use has changed over time among pregnant and nonpregnant reproductive-aged women is unknown

DSM-5 criteria for substance use disorders: recommendations and rationale.

Since DSM-IV was published in 1994, its approach to substance use disorders has come under scrutiny. Strengths were identified (notably, reliability and validity of dependence), but concerns have also arisen. The DSM-5 Substance-Related Disorders Work Group considered these issues and recommended revisions for DSM-5. General concerns included whether to retain the division into two main disorders (dependence and abuse), whether substance use disorder criteria should be added or removed, and whether an appropriate substance use disorder severity indicator could be identified. Specific issues included possible addition of withdrawal syndromes for several substances, alignment of nicotine criteria with those for other substances, addition of biomarkers, and inclusion of nonsubstance, behavioral addictions.This article presents the major issues and evidence considered by the work group, which included literature reviews and extensive new data analyses. The work group recommendations for DSM-5 revisions included combining abuse and dependence criteria into a single substance use disorder based on consistent findings from over 200,000 study participants, dropping legal problems and adding craving as criteria, adding cannabis and caffeine withdrawal syndromes, aligning tobacco use disorder criteria with other substance use disorders, and moving gambling disorders to the chapter formerly reserved for substance-related disorders. The proposed changes overcome many problems, while further studies will be needed to address issues for which less data were available

Changes in US Lifetime Heroin Use and Heroin Use Disorder: Prevalence From the 2001-2002 to 2012-2013 National Epidemiologic Survey on Alcohol and Related Conditions

Importance: Heroin use is an urgent concern in the United States. Little is know about the course of heroin use, heroin use disorder, and associated factors. Objective: To examine changes in the lifetime prevalence, patterns, and associated demographics of heroin use and use disorder from 2001-2002 to 2012-2013 in 2 nationally representative samples of the US adult general population. Design, Setting, and Participants: This survey study included data from 43 093 respondents of the 2001-2002 National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) and 36 309 respondents of the 2012-2013 NESARC-III. Data were analyzed from February 2 to September 15, 2016. Main Outcomes and Measures: Lifetime heroin use and DSM-IV heroin use disorder. Results: Among the 79 402 respondents (43.3% men; 56.7% women; mean [SD] age, 46.1 [17.9] years), prevalence of heroin use and heroin use disorder significantly increased from 2001-2002 to 2012-2013 (use: 0.33% [SE, 0.03%] vs 1.6% [SE, 0.08%]; disorder: 0.21% [SE, 0.03%] vs 0.69% [SE, 0.06%]; P < .001). The increase in the prevalence of heroin use was significantly pronounced among white (0.34% [SE, 0.04%] in 2001-2002 vs 1.90% [SE, 0.12%] in 2012-2013) compared with nonwhite (0.32% [SE, 0.05%] in 2001-2002 vs 1.05% [SE, 0.10%] in 2012-2013; P < .001) individuals. The increase in the prevalence of heroin use disorder was more pronounced among white individuals (0.19% [SE, 0.03%] in 2001-2002 vs 0.82% [SE, 0.08%] in 2012-2013; P < .001) and those aged 18 to 29 (0.21% [SE, 0.06%] in 2001-2002 vs 1.0% [0.17%] in 2012-2013; P = .01) and 30 to 44 (0.20% [SE, 0.04%] in 2001-2002 vs 0.77% [0.10%] in 2012-2013; P = .03) years than among nonwhite individuals (0.25% [SE, 0.04%] in 2001-2002 vs 0.43% [0.07%] in 2012-2013) and older adults (0.22% [SE, 0.04%] in 2001-2002 vs 0.51% [SE, 0.07%] in 2012-2013). Among users, significant differences were found across time in the proportion of respondents meeting DSM-IV heroin use disorder criteria (63.35% [SE, 4.79%] in 2001-2001 vs 42.69% [SE, 2.87%] in 2012-2013; P < .001). DSM-IV heroin abuse was significantly more prevalent among users in 2001-2002 (37.02% [SE, 4.67%]) than in 2012-2013 (19.19% [SE, 2.34%]; P = .001). DSM-IV heroin dependence among users was similar in 2001-2002 (28.22% [SE, 3.95%]) and in 2012-2013 (25.02% [SE, 2.20%]; P = .48). The proportion of those reporting initiation of nonmedical use of prescription opioids before initiating heroin use increased across time among white individuals (35.83% [SE, 6.03%] in 2001-2002 to 52.83% [SE, 2.88%] in 2012-2013; P = .01). Conclusions and Relevance: The prevalence of heroin use and heroin use disorder increased significantly, with greater increases among white individuals. The nonmedical use of prescription opioids preceding heroin use increased among white individuals, supporting a link between the prescription opioid epidemic and heroin use in this population. Findings highlight the need for educational campaigns regarding harms related to heroin use and the need to expand access to treatment in populations at increased risk for heroin use and heroin use disorder

A search algorithm for identifying likely users and non-users of marijuana from the free text of the electronic medical record

Background The harmful effects of marijuana on health and in particular cardiovascular health are understudied. To develop such knowledge, an efficient method of developing an informative cohort of marijuana users and non-users is needed. Methods We identified patients with a diagnosis of coronary artery disease using ICD-9 codes who were seen in the San Francisco VA in 2015. We imported these patients’ medical record notes into an informatics platform that facilitated text searches. We categorized patients into those with evidence of marijuana use in the past 12 months and patients with no such evidence, using the following text strings: “marijuana”, “mjx”, and “cannabis”. We randomly selected 51 users and 51 non-users based on this preliminary classification, and sent a recruitment letter to 97 of these patients who had contact information available. Patients were interviewed on marijuana use and domains related to cardiovascular health. Data on marijuana use collected from the medical record was compared to data collected as part of the interview. Results The interview completion rate was 71%. Among the 35 patients identified by text strings as having used marijuana in the previous year, 15 had used marijuana in the past 30 days (positive predictive value = 42.9%). The probability of use in the past month increased from 8.8% to 42.9% in people who have these keywords in their medical record compared to those who did not have these terms in their medical record. Conclusion Methods that combine text search strategies for participant recruitment with health interviews provide an efficient approach to developing prospective cohorts that can be used to study the health effects of marijuana

How does state marijuana policy affect US youth? Medical marijuana laws, marijuana use and perceived harmfulness: 1991–2014

AimsTo test, among US students: (1) whether perceived harmfulness of marijuana has changed over time, (2) whether perceived harmfulness of marijuana changed post‐passage of state medical marijuana laws (MML) compared with pre‐passage; and (3) whether perceived harmfulness of marijuana statistically mediates and/or modifies the relation between MML and marijuana use as a function of grade level.DesignCross‐sectional nationally representative surveys of US students, conducted annually, 1991–2014, in the Monitoring the Future study.SettingSurveys conducted in schools in all coterminous states; 21 states passed MML between 1996 and 2014.ParticipantsThe sample included 1 134 734 adolescents in 8th, 10th and 12th grades.MeasurementsState passage of MML; perceived harmfulness of marijuana use (perceiving great or moderate risk to health from smoking marijuana occasionally versus slight or no risk); and marijuana use (prior 30 days). Data were analyzed using time‐varying multi‐level regression modeling.FindingsThe perceived harmfulness of marijuana has decreased significantly since 1991 (from an estimated 84.0% in 1991 to 53.8% in 2014, P < 0.01) and, across time, perceived harmfulness was lower in states that passed MML [odds ratio (OR) = 0.86, 95% confidence interval (CI) = 0.75–0.97]. In states with MML, perceived harmfulness of marijuana increased among 8th graders after MML passage (OR = 1.21, 95% CI = 1.08–1.36), while marijuana use decreased (OR = 0.81, 95% CI = 0.72–0.92). Results were null for other grades, and for all grades combined. Increases in perceived harmfulness among 8th graders after MML passage was associated with ~33% of the decrease in use. When adolescents were stratified by perceived harmfulness, use in 8th graders decreased to a greater extent among those who perceived marijuana as harmful.ConclusionsWhile perceived harmfulness of marijuana use appears to be decreasing nationally among adolescents in the United States, the passage of medical marijuana laws (MML) is associated with increases in perceived harmfulness among young adolescents and marijuana use has decreased among those who perceive marijuana to be harmful after passage of MML.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134418/1/add13523_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/134418/2/add13523.pd

Prevalence of marijuana use does not differentially increase among youth after states pass medical marijuana laws: Commentary on Stolzenberg et al. (2015) and reanalysis of US National Survey on Drug Use in Households data 2002–2011

There is considerable interest in the effects of medical marijuana laws (MML) on marijuana use in the USA, particularly among youth. The article by Stolzenberg et al. (2015) “The effect of medical cannabis laws on juvenile cannabis use” concludes that “implementation of medical cannabis laws increase juvenile cannabis use”. This result is opposite to the findings of other studies that analysed the same US National Survey on Drug Use in Households data as well as opposite to studies analysing other national data which show no increase or even a decrease in youth marijuana use after the passage of MML. We provide a replication of the Stolzenberg et al. results and demonstrate how the comparison they are making is actually driven by differences between states with and without MML rather than being driven by pre and post-MML changes within states. We show that Stolzenberg et al. do not properly control for the fact that states that pass MML during 2002–2011 tend to already have higher past-month marijuana use before passing the MML in the first place. We further show that when within-state changes are properly considered and pre-MML prevalence is properly controlled, there is no evidence of a differential increase in past-month marijuana use in youth that can be attributed to state MML

The social norms of birth cohorts and adolescent marijuana use in the United States, 1976–2007

Aims  Studies of the relationship between social norms and marijuana use have generally focused on individual attitudes, leaving the influence of larger societal‐level attitudes unknown. The present study investigated societal‐level disapproval of marijuana use defined by birth cohort or by time‐period. Design  Combined analysis of nationally representative annual surveys of secondary school students in the United States conducted from 1976 to 2007 as part of the Monitoring the Future study. Setting  In‐school surveys completed by adolescents in the United States. Participants  A total of 986 003 adolescents in grades 8, 10 and 12. Measurements  Main predictors included the percentage of students who disapproved of marijuana in each birth cohort and time‐period. Multi‐level models with individuals clustered in time‐periods of observation and birth cohorts were modeled, with past‐year marijuana use as the outcome. Findings  Results indicated a significant and strong effect of birth cohort disapproval of marijuana use in predicting individual risk of marijuana use, after controlling for individual‐level disapproval, perceived norms towards marijuana and other characteristics. Compared to birth cohorts in which most (87–90.9%) adolescents disapproved of marijuana use, odds of marijuana use were 3.53 times higher in cohorts where fewer than half (42–46.9%) disapproved (99% confidence interval: 2.75, 4.53). Conclusions  Individuals in birth cohorts that are more disapproving of marijuana use are less likely to use, independent of their personal attitudes towards marijuana use. Social norms and attitudes regarding marijuana use cluster in birth cohorts, and this clustering has a direct effect on marijuana use even after controlling for individual attitudes and perceptions of norms.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86928/1/j.1360-0443.2011.03485.x.pd

Alcohol metabolizing genes and alcohol phenotypes in an Israeli household sample

BACKGROUND: Alcohol dehydrogenase 1B and 1C (ADH1B and ADH1C) variants have been robustly associated with alcohol phenotypes in East Asian populations, but less so in non-Asian populations where prevalence of the most protective ADH1B allele is low (generally <5%). Further, the joint effects of ADH1B and ADH1C on alcohol phenotypes have been unclear. Therefore, we tested the independent and joint effects of ADH1B and ADH1C on alcohol phenotypes in an Israeli sample, with higher prevalence of the most protective ADH1B allele than other non-Asian populations. METHODS: A structured interview assessed lifetime drinking and alcohol use disorders (AUDs) in adult Israeli household residents. Four single nucleotide polymorphisms (SNPs) were genotyped: ADH1B (rs1229984, rs1229982, and rs1159918) and ADH1C (rs698). Regression analysis examined the association between alcohol phenotypes and each SNP (absence vs. presence of the protective allele) as well as rs698/rs1229984 diplotypes (also indicating absence or presence of protective alleles) in lifetime drinkers (n = 1,129). RESULTS: Lack of the ADH1B rs1229984 protective allele was significantly associated with consumption- and AUD-related phenotypes (OR = 1.77 for AUD; OR = 1.83 for risk drinking), while lack of the ADH1C rs698 protective allele was significantly associated with AUD-related phenotypes (OR = 2.32 for AUD). Diplotype analysis indicated that jointly ADH1B and ADH1C significantly influenced AUD-related phenotypes. For example, among those without protective alleles for ADH1B or ADH1C, OR for AUD was 1.87 as compared to those without the protective allele for ADH1B only and was 3.16 as compared to those with protective alleles for both ADH1B and ADH1C. CONCLUSIONS: This study adds support for the relationship of ADH1B and ADH1C and alcohol phenotypes in non-Asians. Further, these findings help clarify the mixed results from previous studies by showing that ADH1B and ADH1C jointly effect AUDs, but not consumption. Studies of the association between alcohol phenotypes and either ADH1B or ADH1C alone may employ an oversimplified model, masking relevant information