Correlates of Hookah Smoking among Arab Adults in Israel Identified by a Machine Learning Algorithm

Area of Science:

• Public Health
• Epidemiology
• Behavioral Science

Background:

• Hookah smoking is a global trend, increasingly popular among youth, and linked to chronic diseases.
• A significant rise in hookah use is observed among the Arab population in Israel.
• Previous research has primarily focused on young people, leaving a gap in understanding adult behaviors.

Purpose of the Study:

• To investigate the links between hookah smoking and socioeconomic factors, health status, behaviors, and knowledge in adult Arabs.
• To develop a predictive model for hookah smoking using machine learning techniques.

Main Methods:

• Quantitative study utilizing data from the 2015-2016 Health and Environment Survey.
• Face-to-face interviews conducted with 2046 adults aged 18 and above.
• Machine learning algorithms applied to identify significant predictors of hookah use.

Main Results:

• 13.0% of the adult Arab population reported hookah smoking; 19.5% in the 18-34 age group.
• Risk factors included lower health knowledge, heavy consumption of energy drinks and alcohol, and unemployment.
• Younger age and higher education levels were also associated with increased hookah smoking.

Conclusions:

• Hookah smoking is a widespread behavior within the adult Arab community in Israel.
• The developed machine learning model can aid health organizations in identifying at-risk individuals.
• The model supports the creation of targeted strategies to mitigate hookah smoking prevalence.