OBJECTIVETo assess the implementation of five key tobacco control policies in China: protection from second-hand smoke (SHS); offering help to quit; health warnings regarding tobacco use; the enforcement of bans on tobacco advertising, promotion, and sponsorship; and increasing tobacco taxes and prices.

METHODSUsing 2010 Global Adults Tobacco Survey in China (GATS-China), 10 indicators are used to assess the implementation of five key tobacco control policies of MPOWER in China.

RESULTSOverall, 63.3% and 72.7% of adults noticed people smoking indoor workplaces and public places, respectively. Approximately 60% of smokers were not asked about their smoking habits and approximately 67% were not advised to quit on their visit to a health worker. Sixty percent of adults noticed health warning messages on cigarette packaging and in the media in the last 30 days, 63.6% stated that they would not consider quitting. Twenty percent of respondents noticed tobacco advertising, promotion, and/or sponsorship activities in the 30 days prior to the survey. Among them, 76.3% noticed the direct advertising and 50% noticed from TV programs. Although purchasing price of one pack of cigarettes ranged from 1 to 200 RMB, 50% of current smokers (about 150 million) spent 5 RMB or less on one pack of cigarette. The expenditure on 100 packets of cigarettes represents 2% of 2009 GDP per capita.

CONCLUSIONThe average score for the implementation of the 5 policies of MPOWER in China is 37.3 points, indicating tobacco control policies in China is poor and there is a large gaps from the FCTC requirements.

Adult ; China ; epidemiology ; Female ; Health Surveys ; Humans ; Male ; Population Surveillance ; Smoking ; Tobacco Use Cessation ; methods ; Tobacco Use Disorder ; epidemiology

Objective: To analyze the changes in tobacco use and exposure in primary school students in Shandong province in 2012 and 2019. Methods: A multi-stage stratified cluster random sampling method was used in the survey. In 2012 and 2019, 5 861 and 4 021 students from 3 different cities of Shandong province were selected as the study population. The questionnaire was filled anonymously by the subjects. χ² test was conducted to compare the difference of groups. Results: In 2012 and 2019, the rate of attempting smoking among pupils under this study in Shandong province were 6.0％and 6.3%, respectively, while the current smoking rate were 1.2％and 2.3%, respectively. The sex ratio of male and female students attempting to smoke was 2.56∶1 in 2012 and 1.31∶1 in 2019. The sex ratio of current smoking rate was 2.43∶1 and 2.00∶1, respectively in 2012 and in 2019. The rate of tobacco exposure in the public places was 50.5％and 41.4%, respectively. The rate of tobacco exposure in family was 49.7% and 46.4%, respectively. Two rates of tobacco exposure decreased, but the reduction in family (3.3%) was far less than that in public places (9.1%). In 2019, the rate of tobacco exposure in family was higher than that in public places. Conclusions: The tobacco exposure rate declined in senior pupils in Shandong province. However, the situation is still grim for the current smoking rate, growth trend of girls tobacco use, and tobacco exposure in family.
Cities ; Environment ; Female ; Humans ; Male ; Prevalence ; Students ; Surveys and Questionnaires ; Tobacco Smoke Pollution ; Tobacco Use/epidemiology*

Objective: To understand the prevalence and influencing factors of tobacco dependence among the population aged 15-69 in Tianjin to provide the basis for formulating targeted smoking control intervention policies and carrying out scientific smoking cessation intervention services. Methods: The data of this study comes from the 2018 Tianjin residents' health literacy monitoring survey. Probability-proportional-to-size sampling is adopted for sampling. SPSS 26.0 software was used for data cleaning and statistical analysis, and χ² test and binary logistic regression were used to analyze the influencing factors. Results: A total of 14 641 subjects aged 15-69 were included in this study. After standardized, with a smoking rate of 25.5%, including 45.5% for men and 5.2% for women. Among the population aged 15-69, the prevalence of tobacco dependence was 10.7%; among current smokers, the prevalence rate of tobacco dependence is 40.1%, of which the prevalence rate of male tobacco dependence is 40.0%, and the prevalence rate of female tobacco dependence is 40.6%. According to multivariate logistic regression analysis, people who live in rural areas, have an education level of primary school or below, smoke every day, smoke the first cigarette ≤15 years old, smoke ≥21 cigarettes per day, and smoke for more than 20 packet years, people who report poor physical health are more likely to suffer from tobacco dependence (all P<0.05); age and smoking age did not affect the possibility of tobacco dependence (all P>0.05). Among current smokers, there was no significant difference in their willingness to quit smoking whether they had tobacco dependence (P>0.05). The proportion of people with tobacco dependence who have tried to quit smoking and failed is higher (P<0.001). Conclusions: The prevalence of tobacco dependence among smokers aged 15-69 in Tianjin is high, and the demand for quitting smoking is great. Therefore, smoking cessation publicity should be carried out for key groups, and smoking cessation intervention work in Tianjin should be continuously promoted.
Adolescent ; Female ; Humans ; Male ; Smokers ; Smoking/epidemiology* ; Tobacco Smoking ; Tobacco Use Disorder/epidemiology* ; Young Adult ; Adult ; Middle Aged ; Aged

China ; Female ; Humans ; Male ; Population Surveillance ; Tobacco Use Cessation ; methods ; Tobacco Use Disorder ; epidemiology ; prevention & control ; World Health Organization

BACKGROUND: Tobacco consumption causes almost 638,000 premature deaths per year in India. This study sought to examine the prevalence and determinants of tobacco use among men in India. METHODS: We analyzed data from the fourth round of the National Family Health Survey in India. These nationally representative cross-sectional sample data were collected from January 20, 2015, to December 4, 2016. A total of 112,122 men aged 15-54 years were included in this study. Primary outcomes were tobacco use categorized into smoking, smokeless, any tobacco, and both smoked and smokeless tobacco use. Complex survey design and sampling weights were applied in both the descriptive analyses and logistic regression models. We present the findings using odds ratios. RESULTS: The prevalence of tobacco use among men in India for the studied period was 45.5% (95% CI 44.9-46.1), smoking was 24.6% (95% CI 24.1-25.1), smokeless tobacco use was 29.1% (95% CI 28.6-29.6), and both smoked and smokeless tobacco use was 8.4% (95% CI 8.1-8.7). The prevalence of tobacco use among men was higher among the elderly, separated/divorced/widowed individuals, those with lower education and wealth status, alcohol consumers, manual workers, and residents of the northeast region. Multivariate analysis showed that age, lower education, occupation, region, alcohol consumption, separated/divorced/widowed status, and economic status were substantially associated with tobacco use among Indian men. CONCLUSIONS Innovative and cost-effective strategies targeting high-risk groups are crucial to curbing the tobacco epidemic in India. Anti-smoking campaigns should also focus on mitigating alcohol abuse. Reducing tobacco marketing and implementing formal education about the dangers of tobacco use, progressive taxing, packaging, and labeling of tobacco products and price strategies should be harmonized in legal provisions.
Adolescent ; Adult ; Humans ; India/epidemiology* ; Male ; Middle Aged ; Prevalence ; Socioeconomic Factors ; Tobacco Use/epidemiology* ; Young Adult

Objective: To understand the rate on tobacco use and associated factors in junior middle school students in Shaanxi province. Methods: We used a multi-stage stratified random sampling method to select students from 30 junior middle schools in 10 areas of Shaanxi province in 2013. All the participants completed a self-administered questionnaire. Results: A total of 4 633 questionnaires were dispatched and 4 298 were qualified for further analysis. The current smoking rate of junior middle school students in Shaanxi was 6.5%, with rate in male (11.1%) higher than that of female students (1.7%). The current smoking rate of students in grade three (9.3%) was higher than those of students in grade one (3.5%) or in grade two (7.0%). The smoking rate of students with pocket money more than 31 Yuan per week was (10.0%) higher than those of students with pocket money less than 10 Yuan (4.6%) or 10-30 Yuan (6.3%) per week. Results from the logistic regression analysis showed that factors as: male, school located in the city, older age, with more pocket money, having smokers in the family and exposure to second hand smoking were high risk factors for current smoking. Conclusion: Rate on current smoking was high in junior middle schools students in Shaanxi, suggesting that comprehensive intervention programs be developed to reduce the rate of tobacco use in junior middle school students.
China/epidemiology* ; Cities ; Cross-Sectional Studies ; Female ; Humans ; Male ; Prevalence ; Schools ; Smoking/epidemiology* ; Students/statistics & numerical data* ; Surveys and Questionnaires ; Tobacco Smoke Pollution/adverse effects* ; Tobacco Use/epidemiology*

BACKGROUND: This study evaluated the association between nicotine dependence and depressive mood in patients who visited a secondary hospital for smoking cessation treatment.METHODS: From March 2016 to February 2017, a total of 48 patients who visited the smoking cessation clinic of a secondary hospital in Seoul were surveyed through questionnaires. Nicotine dependence was assessed by the Fagerström Test for Nicotine Dependence. The Beck Depression Inventory (BDI) was used to assess depressive mood.RESULTS: The mean BDI score was positively associated with nicotine dependence (P=0.01). In multivariable logistic regression analysis, increasing BDI was associated with higher odds (1.21, 95% confidence interval; 1.02–1.44) of high nicotine dependence after adjusting for all confounding variables.CONCLUSION: Depressive mood was positively associated with nicotine dependence among patients who visited a smoking cessation clinic. Consideration of depressive mood in smoking cessation treatment may be helpful for smoking cessation among patients with a willingness to quit smoking.
Confounding Factors (Epidemiology) ; Depression ; Humans ; Logistic Models ; Nicotine ; Seoul ; Smoke ; Smoking Cessation ; Smoking ; Tobacco Use Disorder

OBJECTIVETo describe the prevalence of smoking, quitting smoke, and passive smoking in different populations by education status, occupation and geographic distribution.

METHODSSurveillance on risk behaviors in 145 disease surveillance points (DSP) was carried out in 2002 by multi-steps random sampling through questionnaires. 16,407 records had been completed with 16 056 used for analysis. Indicators as smoking, current smoking, average cigarettes smoked and the cost per day, etc., were calculated by weight on age proportions from the 2000 census.

RESULTSEver-smoking rates in males and females aged 15 and over were 66.0% and 3.1%, respectively with ever-smoking rate dropped 1.8% in whole population, but increased in people aged 15-24. The number of total smokers was about 350 million, 30 million more than that in 1996. There were no obvious geographic differences seen among male, but big difference was seen in female smokers. Higher smoking rates were seen in the northeast and northern parts of the country. Rate of quitting smoking was increasing, from 9.42% in 1996 to 11.5% in 2002, referring to an increase of 10 million quitters. However, the rate of no intention to quit among smokers was still very high--74%. The average cigarettes consumption per person-day was the same as that in 1996--14.8 cigarettes/day, which cost 2.73 RBM/day. The cost was various in different groups of population with a 15 times difference. The level of exposure for passive smokers was not improved. The prevalence of passive smoking in nonsmokers were 53% in 1996 and 52% in 2002. Knowledge on smoking and health condition in population had been greatly improved, but still poor in the western areas. 60% of the people claimed in supporting banning of smoking in public places, 45% supporting the banning of all cigarettes ads, but big difference was seen in different geographic areas.

CONCLUSIONThe prevalence of smoking in Chinese males had reached its peak, leveling but had not yet obvious dropped. Communication on the knowledge of harm in smoking remained weak since people did not understand or support the strategies on tobacco control, especially in the western areas. Data indicated that the prevalence of tobacco use would not decrease over in short period and the disease burden caused by tobacco use would still be heavy in the next 30-50 years. The government and public health authorities should develop effective tobacco control in no time to decrease disease burden caused by smoking and passive smoking.

Adolescent ; Adult ; Attitude to Health ; China ; epidemiology ; Female ; Humans ; Male ; Prevalence ; Smoking ; epidemiology ; Smoking Cessation ; statistics & numerical data ; Surveys and Questionnaires ; Tobacco Smoke Pollution ; statistics & numerical data ; Tobacco Use Disorder

OBJECTIVETo review the current evidence that links smoking to obstructive sleep apnea (OSA) and to discuss some potential mechanisms proposed for these links.

DATA SOURCESWe searched PubMed and Medline to identify studies investigating the interaction between smoking and OSA.

STUDY SELECTIONArticles regarding the relationship between smoking and OSA were selected. Studies considered smoking as a confounding factor were excluded.

RESULTSThe association of smoking and OSA has been confirmed in several studies. The effects of smoking on the pathophysiology of OSA may include smoking-induced upper airway inflammation, stimulant effects of nicotine on upper airway muscles, and a "rebound effect" due to nightly short-term nicotine withdrawal, or all of the above. In addition, the coexistence of OSA and smoking may have more widespread implications for cardiovascular dysfunction in patients with OSA. Finally, OSA might be responsible for the addiction to nicotine.

CONCLUSIONSSmoking may act as a risk factor for OSA and join with OSA in a common pathway to increase the risk of systematic injury. OSA, in turn, may be a predisposing factor for smoking. Thus, smoking cessation is recommended when considering treatment for OSA, and treating OSA may be a necessary precondition for successful smoking cessation.

Asthma ; epidemiology ; etiology ; Bronchi ; drug effects ; Humans ; Nicotine ; pharmacology ; Risk Factors ; Sleep ; physiology ; Sleep Apnea, Obstructive ; epidemiology ; etiology ; Smoking ; adverse effects ; Tobacco Use Disorder ; epidemiology ; etiology

OBJECTIVETo understand the smoking behaviors and its influencing factors among male smokers in two districts in Chengdu.

METHODSA face to face questionnaire survey was conducted among 320 male smokers in Chengdu. And the data were analyzed with descriptive epidemiological method, t test, χ2 test, one-way analysis of variance, Kruskal-Wails H rank sum test and cumulative odds logistic regression model.

RESULTSMore cigarette smoking (t=2.327, P=0.021) and using cigarette with lower tar level (t=-11.251, P<0.001) after changing the brand of cigarette were found among the males surveyed. The cumulative odds logistic regression analysis showed that males with lower education level (OR=1.968, P=0.040), with higher income level (OR=2.053, P=0.043), leaving shorter butts (OR=2.366, P=0.010) and with high nicotine dependence (OR=7.143, P<0.001) had more cigarette smoking.

CONCLUSIONSmokers who changed the brand of cigarette were more likely to choose low tar cigarette. Smokers with low education level, high income level and high nicotine dependence are the target population for health education and behavior intervention in smoking control.

China ; epidemiology ; Data Collection ; Humans ; Logistic Models ; Male ; Risk Factors ; Smoking ; epidemiology ; psychology ; Socioeconomic Factors ; Surveys and Questionnaires ; Tobacco Use Disorder ; epidemiology