Who Seeks Help? A Sociodemographic Analysis of Cannabis Use Disorder Treatment in New York

Introduction: Cannabis use disorder (CUD) is being increasingly diagnosed in the United States, but access to treatment remains unequal, particularly in New York. Identifying the factors that contribute to disparities in receiving treatment for CUD among different population groups is essential for ensuring effective and targeted interventions. This study explores the sociodemographic factors influencing treatment utilization for CUD in New York. Methods: Data for this study were retrieved from the 2018 Treatment Episode Data Set—Discharges (TEDS-D) of the U.S. Substance Abuse and Mental Health Services Administration (SAMHSA). Sample size for the study is 422,319 people with CUD. Logistic regression analysis was performed to examine the odds of receiving treatment for CUD based on demographic and socioeconomic factors, as well as the type of treatment setting. Results: The results revealed significant disparities in treatment utilization. Asians/Pacific Islanders and Hawaiian Natives had lower odds of receiving treatment compared to African Americans (OR = 0.367, 95% CI 0.341–0.394). Similarly, Caucasians had the lowest odds of receiving treatment (OR = 0.270, 95% CI 0.266–0.275). Females were less likely to receive treatment compared to males (OR = 0.756, 95% CI 0.744–0.768). Those with higher educational attainment (over four years of college) had the lowest odds of receiving treatment, while individuals with 9–11th grade education had the highest odds. Employment status also influenced treatment access, with the unemployed having the highest odds, and full-time employees having the lowest. Additionally, individuals with no source of income had significantly lower odds of receiving treatment. Conclusions: This study highlights significant disparities in the provision of treatment for CUD in New York, influenced by sociodemographic factors such as race, gender, age, education, and employment status. These findings emphasize the need for targeted interventions to reduce these disparities and improve treatment access for underserved populations.