The relationship between working hours and the intention to quit smoking in male office workers: data from the 7th Korean National Health and Nutrition Examination Survey (2016–2017)

BACKGROUND: The intention to quit smoking is one of the most important factors in smoking cessation. Long working hours is also a constant issue, and many studies have shown an association between the working hours and diseases, including cardiovascular and gastrointestinal diseases. This study evaluated the relationship between working hours and the intention to quit smoking among Korean male office workers, and blue collar workers for comparison. METHODS: This study was based on the Seventh Korea National Health and Nutrition Examination Survey (2016–2017). A total of 1,389 male workers were smokers, and then office workers and blue collar workers were selected. Logistic regression was used to calculate the odds ratio (OR) for the intention to quit smoking according to smoking-related characteristics and working hours after adjusting for age group, body mass index (kg/m(2)), marital status, household income (quartile), educational level, drinking, exercise, smoking-related characteristics (smoking initiation age, smoking amount, and attempt to quit smoking more than 1day in the past year) and working hours. RESULTS: The percentage of workers who had the intention to quit smoking in 6 months was higher in office workers (38.9% for office workers and 29.4% for blue collars, p = 0.017). Blue collar workers had higher percentages of workers who worked more than 52 hours per week (19.8% for office workers and 38.9% for blue collar workers, p < 0.001). Logistic regression analysis showed that working > 52 hours per week was significantly associated with a lower intention to quit smoking within 6 months among male office workers (OR = 0.30, 95% confidence interval = 0.14–0.66). CONCLUSIONS: Working more than 52 hours per week was positively related with a lower intention to quit smoking among currently smoking male office workers. Further studies are needed considering more work-related variables such as job stress and physical load.