Yao Liu1, Jian Gao2, Juan Shou1, Huiling Xia1, Yao Shen3, Shanzhu Zhu1, Zhigang Pan1. 1. a Department of General Practice, Zhongshan Hospital Fudan University , Shanghai , China. 2. b Department of Nutrition, Zhongshan Hospital Fudan University , Shanghai , China. 3. c Shanghai Pudong Hospital , Shanghai , China.
Abstract
BACKGROUND: The increasing rural-to-urban migrant population in China may be linked to the susceptibility to tobacco use. We aimed to investigate the prevalence of smoking among rural-to-urban migrants in China. METHODS: Major English and Chinese databases were searched for original studies on smoking prevalence among rural-to-urban migrants in China. A validated quality assessment tool was used to evaluate these studies. Subsequently, data were extracted to calculate the overall pooled estimate of prevalence using random effect model, and then stratified by gender, definition, location, and occupation. Meta-regression analysis was used to identify the source of heterogeneity among variables. RESULTS: We identified 17 eligible studies involving 32,694 migrants. The overall pooled prevalence estimate of smoking among rural-to-urban migrants was 27.25% (95% CI: 23.34, 31.34), with significant heterogeneity (I(2) = 98.2, p < .01). In stratified analysis, specific pooled prevalence estimates were 46.71% for male (95% CI: 40.51, 52.97) and 5.34% for female (95% CI: 2.90, 8.45); 26.71% (95% CI: 17.00, 37.71), and 24.96% (95% CI: 18.65, 31.86) in current and daily smoking group, respectively; 21.89% (95% CI: 15.80, 28.66) and 30.59% (95% CI: 20.04, 42.28) for migrants in North and South China, respectively; 48.34% (95% CI: 24.63, 72.46) in construction industry, 31.77% (95% CI: 15.54, 50.67) in manufacturing industry and 18.69% (95% CI: 11.37, 27.32) in service industry, respectively. Meta-regression analysis revealed that gender and occupation differences contributed to high heterogeneity. CONCLUSION: Cigarette smoking is still prevalent among rural-to-urban migrants, which may be influenced by gender and occupations. Policies should be designed and conducted to control smoking prevalence among these populations.
BACKGROUND: The increasing rural-to-urban migrant population in China may be linked to the susceptibility to tobacco use. We aimed to investigate the prevalence of smoking among rural-to-urban migrants in China. METHODS: Major English and Chinese databases were searched for original studies on smoking prevalence among rural-to-urban migrants in China. A validated quality assessment tool was used to evaluate these studies. Subsequently, data were extracted to calculate the overall pooled estimate of prevalence using random effect model, and then stratified by gender, definition, location, and occupation. Meta-regression analysis was used to identify the source of heterogeneity among variables. RESULTS: We identified 17 eligible studies involving 32,694 migrants. The overall pooled prevalence estimate of smoking among rural-to-urban migrants was 27.25% (95% CI: 23.34, 31.34), with significant heterogeneity (I(2) = 98.2, p < .01). In stratified analysis, specific pooled prevalence estimates were 46.71% for male (95% CI: 40.51, 52.97) and 5.34% for female (95% CI: 2.90, 8.45); 26.71% (95% CI: 17.00, 37.71), and 24.96% (95% CI: 18.65, 31.86) in current and daily smoking group, respectively; 21.89% (95% CI: 15.80, 28.66) and 30.59% (95% CI: 20.04, 42.28) for migrants in North and South China, respectively; 48.34% (95% CI: 24.63, 72.46) in construction industry, 31.77% (95% CI: 15.54, 50.67) in manufacturing industry and 18.69% (95% CI: 11.37, 27.32) in service industry, respectively. Meta-regression analysis revealed that gender and occupation differences contributed to high heterogeneity. CONCLUSION: Cigarette smoking is still prevalent among rural-to-urban migrants, which may be influenced by gender and occupations. Policies should be designed and conducted to control smoking prevalence among these populations.
Authors: Y K Yang; Y Zhang; X Meng; K Q Yang; X J Jiang; H Y Wu; H M Zhang; L Song; L P Wang; L G Gao; X L Zhou Journal: Clin Res Cardiol Date: 2016-06-06 Impact factor: 5.460