BMC Public Health (Aug 2019)
Socioeconomic disparities in prevalence and behaviors of smoking in rural Southwest China
Abstract
Abstract Background This study examines how prevalence and behaviors of smoking differ by socioeconomic status among rural southwest Chinese adults. Methods A cross-sectional survey was conducted including 7743 adults aged ≥35 years in rural regions of Yunnan Province, China from 2016 to 2018. Information on individual socioeconomic status (SES), ethnicity, and self-reported smoking behaviors was collected utilizing a standardized questionnaire. The individual socioeconomic position (SEP) index was constructed using principal component analysis. Multivariate logistic regression models were used to analyze the association between individual SES variables and the prevalence and behaviors of smoking. Results In the study population, the overall prevalence rate of current smokers was 33.5%. Males had a markedly higher prevalence of current smokers than females (62.6% vs. 4.8%, P < 0.01). Of these smokers, 74.5% began smoking during adolescence, 88.8% had never attempted to quit smoking, and 81.1% reported smoking in public places. Ethnic minority participants and those with low levels of education and/or low SEP were more likely to use tobacco as well as more likely to start smoking, and regularly smoke, during adolescence (P < 0.01). Participants with poor access to medical services had a higher prevalence of current smoking than their counterparts (P < 0.01). Among current smokers, Han ethnicity, good access to medical services, and high SEP were positively associated with the probability of having attempted to quit smoking at least once, while a high level of education and high SEP were negatively associated with the probability of smoking in public places. Conclusions Disparities in prevalence and behaviors of smoking exist across a diversity of indicators of individual SES in rural southwest China. Future tobacco cessation interventions should focus on men, ethnic minorities, and those with low education levels, poor access to medical services, and low SEP.
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