OBJECTIVES: To identify the effect of worksite smoking prevalence on individual cessation behavior. METHODS: We conducted a cohort study at a Japanese worksite without a total ban on smoking, but with designated smoking areas. Baseline data were obtained in 2005 through a self-administered questionnaire from 15,229 workers in 322 work units as part of annual health checkups, and followed up in 2006. Data on smoking status, time to first cigarette after waking up, desire to quit, number of cigarettes smoked per day, and respiratory symptoms were obtained. Details like workers' demographics, blue/white-collar workers, night shift duties, administrative position, and work unit codes were obtained from the firm's administrative records. Smoking prevalence in work units was calculated as a ratio, standardized by age, and categorized into quartiles. Multiple logistic regression was used to predict cessation by smoking prevalence, adjusting for individual level variables. RESULTS: In the lowest smoking prevalence quartile compared with the highest, odds ratios (95% CI) of cessation among those who smoked their first cigarette more than 30 min after waking up were 2.32 (1.06, 5.09) in white-collar units and 1.86 (0.98, 3.55) in blue-collar units, and that among those with a moderate desire to quit was 2.05 (0.94, 4.49) in white-collar units. CONCLUSION: Worksite smoking prevalence affects the likelihood of successful cessation, especially among those with less nicotine dependence and who are in the early stage of behavioral change. This suggests that serious consideration should be placed not only on individual behavior modification but also on modification of worksite conditions.
OBJECTIVES: To identify the effect of worksite smoking prevalence on individual cessation behavior. METHODS: We conducted a cohort study at a Japanese worksite without a total ban on smoking, but with designated smoking areas. Baseline data were obtained in 2005 through a self-administered questionnaire from 15,229 workers in 322 work units as part of annual health checkups, and followed up in 2006. Data on smoking status, time to first cigarette after waking up, desire to quit, number of cigarettes smoked per day, and respiratory symptoms were obtained. Details like workers' demographics, blue/white-collar workers, night shift duties, administrative position, and work unit codes were obtained from the firm's administrative records. Smoking prevalence in work units was calculated as a ratio, standardized by age, and categorized into quartiles. Multiple logistic regression was used to predict cessation by smoking prevalence, adjusting for individual level variables. RESULTS: In the lowest smoking prevalence quartile compared with the highest, odds ratios (95% CI) of cessation among those who smoked their first cigarette more than 30 min after waking up were 2.32 (1.06, 5.09) in white-collar units and 1.86 (0.98, 3.55) in blue-collar units, and that among those with a moderate desire to quit was 2.05 (0.94, 4.49) in white-collar units. CONCLUSION: Worksite smoking prevalence affects the likelihood of successful cessation, especially among those with less nicotine dependence and who are in the early stage of behavioral change. This suggests that serious consideration should be placed not only on individual behavior modification but also on modification of worksite conditions.