INTRODUCTION: China has a higher household secondhand smoke exposure rate than other countries. This study aims to estimate the prevalence rate of households implementing smoking bans in Guangdong and to identify factors correlated with household smoking bans. METHODS: A cross-sectional, stratified random cluster sampling survey was conducted in Guangdong in 2010. A total of 2,114 adults aged 15 and older completed the face-to-face interviews with a response rate of 70%. The survey employed an adapted and validated questionnaire from the China Global Adult Tobacco Survey. Household smoking policy was divided into 3 groups: full ban, partial ban, and no ban. A multiple logistic regression model was employed to explore factors related to a full household smoking ban. RESULTS: The survey found 14.2% of respondents reported a full ban, 23.6% reported a partial ban, and 62.2% reported no ban of smoking at home. Current smoking status was the strongest predictor for less restrictive household smoking policies (odds ratio [OR] = 4.9, 95% CI = 2.634-8.999). Our study suggested that people with a high level of education were more likely to implement a full household smoking ban (OR = 4.4, 95% CI = 2.388-8.178). Additionally, urban residents were significantly more likely to report a full household smoking ban than rural residents (OR = 1.67, 95% CI = 1.202-2.322). CONCLUSIONS: Household smoking bans were not sufficiently established in Guangdong, China. Intensified efforts were called to promote home smoking bans, especially for those with a lower education level, with lower income, and living in rural areas.
INTRODUCTION: China has a higher household secondhand smoke exposure rate than other countries. This study aims to estimate the prevalence rate of households implementing smoking bans in Guangdong and to identify factors correlated with household smoking bans. METHODS: A cross-sectional, stratified random cluster sampling survey was conducted in Guangdong in 2010. A total of 2,114 adults aged 15 and older completed the face-to-face interviews with a response rate of 70%. The survey employed an adapted and validated questionnaire from the China Global Adult Tobacco Survey. Household smoking policy was divided into 3 groups: full ban, partial ban, and no ban. A multiple logistic regression model was employed to explore factors related to a full household smoking ban. RESULTS: The survey found 14.2% of respondents reported a full ban, 23.6% reported a partial ban, and 62.2% reported no ban of smoking at home. Current smoking status was the strongest predictor for less restrictive household smoking policies (odds ratio [OR] = 4.9, 95% CI = 2.634-8.999). Our study suggested that people with a high level of education were more likely to implement a full household smoking ban (OR = 4.4, 95% CI = 2.388-8.178). Additionally, urban residents were significantly more likely to report a full household smoking ban than rural residents (OR = 1.67, 95% CI = 1.202-2.322). CONCLUSIONS: Household smoking bans were not sufficiently established in Guangdong, China. Intensified efforts were called to promote home smoking bans, especially for those with a lower education level, with lower income, and living in rural areas.
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