Exploring Potential Predictors and Mediators of Marijuana Use Among US Women: A Structural Equation Modeling Approach

Despite concerns about the impact of marijuana on women's health, studies exploring factors influencing use are limited. We examined predictors and mediators of marijuana use among US women.

Structural equation modeling analyzed data on women (n = 16,081) from the 2023 National Survey on Drug Use and Health, with marijuana use as dependent variable. Sociodemographic variables and covariates included age, race and ethnicity, marital status, education, poverty status, county type, criminal history, and binge drinking. Potential mediators were past-year major depressive episode (PY-MDE); past-year use of illicit drugs, tobacco, and alcohol (PY-IDTA); poverty status; and body mass index.

Marijuana use was frequently reported among women aged 26 to 34 years (35.6%), those who were non-Hispanic White (60.8%), never been married (62.5%), with some college-level education (38.1%), living in large metropolitan areas (56.7%), those who did not binge drink (53.8%), without a criminal history (83.7%), with no PY-MDE (74.8%), no PY-IDTA (73.4%), those who were living above the poverty threshold (58.5%), and those with obesity (37.5%). Criminal history (β = 0.188) and binge drinking (β = 0.404) had positive direct effects on marijuana use; age (β =-0.065) and race (β = -0.027) had negative direct effects on use. PY-MDE mediated the relationships between age, race and ethnicity, marital status, county, past criminal history, binge drinking, and marijuana use (indirect βs = -0.008 to 0.080). PY-IDTA mediated the relationships between race and ethnicity, marital status, education, past criminal history, binge drinking, and marijuana use (indirect βs = -0.013 to 0.378), with all P values <.05.

Results suggest potential predictors and mediators of marijuana use, highlighting the need for multi-strategy targeted interventions among US women.