Possible unintended consequences for pregnant women of legalizing cannabis use

Cannabis use, cannabis use disorder and mental health disorders among pregnant and postpartum women in the US: A nationally representative study

BACKGROUND

Cannabis use and cannabis use disorder (CUD) are associated with mental health disorders, however the extent of this matter among pregnant and recently postpartum (e.g., new moms) women in the US is unknown. Associations between cannabis use, DSM-5 CUD and DSM-5 mental health disorders (mood, anxiety, personality and post-traumatic stress disorders) were examined among a nationally representative sample of pregnant and postpartum women.

METHODS

The 2012-2013 National Epidemiologic Survey on Alcohol and Related Conditions-III was used to examine associations between past-year cannabis use, CUD and mental health disorders. Weighted logistic regression models were used to estimate unadjusted and adjusted odds ratios (aORs). The sample (N=1316) included 414 pregnant and 902 postpartum women (pregnant in the past year), aged 18-44 years old.

RESULTS

The prevalence of past-year cannabis use and CUD was 9.8% and 3.2%, respectively. The odds of cannabis use (aORs range 2.10-3.87, p-values<0.01) and CUD (aORs range 2.55-10.44, p-values< 0.01) were higher among women with versus without any past-year mood, anxiety or posttraumatic stress disorders or any lifetime personality disorder. aORs for the association of cannabis use with specific mood, anxiety or personality disorders ranged from 1.95 to 6.00 (p-values<0.05). aORs for the association of CUD with specific mood, anxiety or personality disorders ranged from 2.36 to 11.60 (p-values<0.05).

CONCLUSIONS

From pregnancy up to one year postpartum is a critical period where women may be particularly vulnerable to mental health disorders, cannabis use and CUD. Treatment and prevention are essential.

Trends in Use of Conventional Cigarettes, E-cigarettes, and Marijuana in Pregnancy and Impact of Health Policy

The substance use policy context continues to evolve. As tobacco control policies have become more restrictive, marijuana legalization has increased access to marijuana. Data suggest that prenatal conventional cigarette use is declining, while e-cigarette and marijuana use are increasing among persons preconception, prenatally, and postpartum. Policy evaluations have found that increasing cigarette taxes reduces prenatal smoking and improves birth outcomes; however, there have been few studies of e-cigarette policies or marijuana legalization on prenatal use or birth outcomes. It is important for clinicians to screen for prenatal substance use, as recommended by American College of Obstetricians and Gynecologists (ACOG), and understand how policies influence use among their patients.

A preliminary risk prediction model for cannabis use disorder

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Substance use disorders are currently a major public health crisis in the US.

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The prevalence of cannabis use disorder is rising due to legalization of cannabis.

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This study built models to predict the risk of cannabis use disorder for a user.

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Risk factors include personality traits, impulsivity and initial smoking enjoyment.

The ongoing trend toward legalization of cannabis for medicinal/recreational purposes is expected to increase the prevalence of cannabis use disorder (CUD). Thus, it is imperative to be able to predict the quantitative risk of developing CUD for a cannabis user based on their personal risk factors. Yet no such model currently exists. In this study, we perform preliminary analysis toward building such a model. The data come from n = 94 regular cannabis users recruited from Albuquerque, New Mexico during 2007–2010. As the data are cross-sectional, we only consider risk factors that remain relatively stable over time. We apply statistical and machine learning classification techniques that allow n to be small relative to the number of predictors. We use predictive accuracy estimated using leave-one-out-cross-validation to evaluate model performance. The final model is a LASSO logistic regression model consisting of the following seven risk factors: age; level of enjoyment from initial cigarette smoking; total score on Impulsive Sensation-Seeking Scale questionnaire; score on cognitive instability factor of Barratt Impulsivity Scale questionnaire; and scores on neuroticism, openness, and conscientiousness personality traits of Neuroticism, Extraversion, and Openness inventory. This model has an overall accuracy of 0.66 and the area under its receiver operating characteristic curve is 0.65. In summary, a preliminary relative risk model for predicting the quantitative risk of CUD is developed. It can be employed to identify users at high risk of CUD who may be provided with early intervention.