EXPLORING DRUG CONSUMPTION TRENDS: A DATA DRIVEN ANALYSIS

This study identifies key demographic and personality-based predictors of drug consumption by analyzing behavioural patterns associated with drug use. Leveraging a multidisciplinary approach, it integrates epidemiological data, social science research, and advanced machine learning techniques, with SAS programming playing a pivotal role in data analysis. A review of over 300 articles published between 2000 and 2022 provides a comprehensive understanding of trends in drug initiation, frequency, and cessation among diverse demographic groups. Significant factors influencing drug-related behaviours include age,gender, socioeconomic status, and geographic location.The study also uncovers risk factors, protective factors, and patterns of polydrug use through large-scale dataset analyses. Additionally, it explores the role of digital platforms and social networks,highlighting how social media,online communities,and peer influences contribute to drug initiation, sharing of experiences, and the normalization of substance use. By combining behavioural science with data-driven methodologies,this research offers actionable insights for developing evidencebased public health policies and intervention strategies. Future investigations should focus on emerging drug trends, novel substances,and the rapidly evolving digital landscape influencing drug-related behaviours.