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

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

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

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

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

Racial/ethnic differences in use of alcohol, tobacco, and marijuana: Is there a cross-over from adolescence to adulthood?

Black adolescents in the US are less likely to use alcohol, marijuana, and tobacco compared with non-Hispanic Whites, but little is known about the consistency of these racial/ethnic differences in substance use across the lifecourse. Understanding lifecourse patterning of substance use is critical to inform prevention and intervention efforts. Data were drawn from four waves of the National Longitudinal Study of Adolescent Health (Add Health; Wave 1 (mean age = 16): N = 14,101; Wave 4 (mean age = 29): N = 11,365). Outcomes included alcohol (including at-risk drinking, defined as 5+/4+ drinks per drinking occasion or 14+/7+ drinks per week on average for men and women, respectively), cigarette, and marijuana use in 30-day/past-year. Random effects models stratified by gender tested differences-in-differences for wave by race interactions, controlling for age, parents' highest education/income, public assistance, and urbanicity. Results indicate that for alcohol, Whites were more likely to use alcohol and engage in at-risk alcohol use at all waves. By mean age 29.9, for example, White men were 2.1 times as likely to engage in at-risk alcohol use (95% C.I. 1.48–2.94). For cigarettes, Whites were more likely to use cigarettes and smoked more at Waves 1 through 3; there were no differences by Wave 4 for men and a diminished difference for women, and difference-in-difference models indicated evidence of convergence. For marijuana, there were no racial/ethnic differences in use for men at any wave. For women, by Wave 4 there was convergence in marijuana use and a cross-over in frequency of use among users, with Black women using more than White women. In summary, no convergence or cross-over for racial/ethnic differences through early adulthood in alcohol use; convergence for cigarette as well as marijuana use. Lifecourse patterns of health disparities secondary to heavy substance use by race and ethnicity may be, at least in part, due to age-related variation in cigarette and marijuana use

US Traffic Fatalities, 1985–2014, and Their Relationship to Medical Marijuana Laws

Objectives. To determine the association of medical marijuana laws (MMLs) with traffic fatality rates. Methods. Using data from the 1985–2014 Fatality Analysis Reporting System, we examined the association between MMLs and traffic fatalities in multilevel regression models while controlling for contemporaneous secular trends. We examined this association separately for each state enacting MMLs. We also evaluated the association between marijuana dispensaries and traffic fatalities. Results. On average, MML states had lower traffic fatality rates than non-MML states. Medical marijuana laws were associated with immediate reductions in traffic fatalities in those aged 15 to 24 and 25 to 44 years, and with additional yearly gradual reductions in those aged 25 to 44 years. However, state-specific results showed that only 7 states experienced post-MML reductions. Dispensaries were also associated with traffic fatality reductions in those aged 25 to 44 years. Conclusions. Both MMLs and dispensaries were associated with reductions in traffic fatalities, especially among those aged 25 to 44 years. State-specific analysis showed heterogeneity of the MML–traffic fatalities association, suggesting moderation by other local factors. These findings could influence policy decisions on the enactment or repealing of MMLs and how they are implemented

Prescription opioid use disorder and heroin use among 12-34 year-olds in the United States from 2002 to 2014

Trend analyses of prescription opioids in the U.S. indicate use, especially use of prescription opioids stronger than morphine, has more than doubled among adults since the early 1990's (Frenk, Porter, & Paulozzi, 2015). Prescription opioids, like Oxycontin®, are effective pharmacological treatments for acute and chronic pain (Fitzcharles and Shir, 2009 ; Gallagher and Rosenthal, 2008). When used as indicated, these medications can be an important component of pain management. However, their high abuse potential presents concerns regarding their nonmedical use, which can be defined as ‘use of a prescription opioid that was not prescribed, or taken for the experience or feeling it caused’ (SAMHSA, 2014). In the United States, nonmedical use of prescription opioids (NMPO) is increasingly recognized as a serious public health problem among adults (Blanco et al., 2007; Han et al., 2015 ; Huang et al., 2006). Nonmedical prescription drug use, specifically nonmedical use of prescription opioids, is also a growing problem in other countries such as Canada (Fischer et al., 2014 ; Fischer et al., 2013) and Australia (Degenhardt et al., 2006 ; Rintoul et al., 2011)

Alcohol consumption mediates the relationship between ADH1B and DSM-IV alcohol use disorder and criteria

OBJECTIVE: A single nucleotide variation in the alcohol dehydrogenase 1B (ADH1B) gene, rs1229984, produces an ADH1B enzyme with faster acetaldehyde production. This protective variant is associated with lower alcohol consumption and lower risk for alcohol use disorders (AUDs). Based on the premise that faster ADH1B kinetics decreases alcohol consumption, we formally tested if the association between ADH1B variant rs1229984 and AUDs occurs through consumption. We also tested whether the association between rs1229984 and each of the 11 Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), AUD criteria occurs through consumption. METHOD: A total of 1,130 lifetime drinkers from an Israeli household sample were assessed with a structured interview and genotyped for rs1229984 (protective allele frequency = 0.28). Logistic regression evaluated the association between rs1229984 and each phenotype (AUDs, 11 individual DSM-IV criteria). For phenotypes significantly related to rs1229984, the effect through consumption was tested with logistic regression and bootstrapping. RESULTS: ADH1B rs1229984 was significantly associated with AUDs and six criteria, with odds ratios ranging from 1.32 to 1.96. The effect through consumption was significant for these relationships, explaining 23%-74% of the total ADH1B effect. CONCLUSIONS: This is the first study to show that ADH1B rs1229984 is related to 6 of the 11 DSM-IV AUD criteria and that alcohol consumption explained a significant proportion of these associations and the association of ADH1B with AUDs. Better understanding of the relationship between ADH1B and the DSM-IV AUD criteria, including effects through consumption, will enhance our understanding of the etiologic model through which AUDs can occur