The influencing factors of the smoking behavior of online ride-hailing drivers in China: A cross-sectional analysis

Abstract Background：Online ride-hailing is a fast-developing new travel mode, and tobacco control policies on it have not yet been improved. This study aims to reveal the smoking status and influencing factors of ride-hailing drivers, so as to provide a basis for the formulation of tobacco control policies.Methods：The cross-sectional data used in this study were derived from an online survey of full-time ride-hailing drivers in China. Questionnaires were employed to collect variables including sociodemographic and work-related characteristics, health status, health behavior, health literacy, and smoking status. Chi-Square test and multivariate logistic regression were used to analyze the influencing factors of current smoking.Results：A total of 8990 ride-hailing drivers were investigated, in which 5024 were current smokers, accounted to 55.9%. Current smokers (53.7% (2696/5024) v 44.2% (1752/3966); P<0.001) and drivers who smoked on the car (85.8% (1389/1618) v 38.4 (1307/3406); P<0.001) were more likely to allow passengers to smoke. Logistic regression analysis showed that men (OR=0.519, 95%CI (0.416, 0.647)), central regions (OR=1.172, 95%CI (1.049, 1.309)), eastern regions (OR=1.330, 95%CI (1.194, 1.480)), working at both daytime and night (OR=1.287, 95%CI (1.164, 1.424)), and working at non-fixed time (OR=0.847, 95%CI (0.718, 0.999)), 35-54 years old (OR=0.585, 95%CI (0.408, 0.829)), current drinker (OR=1.663, 95%CI (1.526, 1.813)), eating very irregularly (OR=1.370, 95%CI (1.233, 1.523)), the number of days a week of engaging in at least 10 minutes of moderate or vigorous exercise ≥ 3 (OR=0.752, 95%CI (0.646, 0.875)), taking the initiative to acquire health knowledge occasionally (OR=0.882, 95%CI (0.783, 0.992)) or frequently (OR=0.675, 95%CI (0.591, 0.770)) , underweight (OR=1.249, 95%CI (1.001, 1.559)) and overweight (OR=0.846, 95%CI (0.775, 0.924)) were associated with the prevalence of current smoking among online ride-hailing drivers (P<0.05). Conclusions：The smoking rate of ride-hailing drivers was high, and the social demographic and work-related characteristics, and health-related factors all affected their smoking behavior. Tobacco control measures targeted at online-hailing drivers should correct their cultural beliefs about smoking, increase their health literacy, guide them to exercise more and keep a regular schedule, as well as combine with drinking intervention and weight intervention.