Machine learning algorithms to predict khat chewing practice and its predictors among men aged 15 to 59 in Ethiopia: further analysis of the 2011 and 2016 Ethiopian Demographic and Health Survey

Overall, three in 10 men in Ethiopia chew khat. The XGBoost model demonstrated superior predictive performance in identifying the determinants of khat chewing practices. This model identified age, religion, region, wealth index, age at first sexual encounter, media exposure, and the number of sexual partners as key predictors of khat chewing among Ethiopian men. Effective khat prevention strategies should focus on the following: preserving rural norms that discourage khat use and expanding these to urban areas; targeted interventions for young and middle-aged men, including youth programs and economic empowerment initiatives as alternative opportunities; strengthening family values through marriage counseling and spouse involvement to help reduce khat chewing; integrating khat education into reproductive health programs and engaging religious leaders in awareness efforts; and, finally, implementing media campaigns, school-based education, and policy measures-such as restricting sales near schools and enforcing community bylaws-to further curb khat consumption while promoting healthier economic alternatives.