Prevalence of tobacco smoking and related factors in people aged 15 years and above in Beijing, 2014-2021
10.3760/cma.j.cn112338-20240205-00061
- VernacularTitle:北京市2014-2021年15岁及以上人群吸烟状况及影响因素研究
- Author:
Luting XU
1
;
Jianhui SHI
;
Li QI
;
Yuan CAO
;
Xiurong LIU
Author Information
1. 北京市疾病预防控制中心健康教育所，北京 100020
- Keywords:
Smoking;
Tobacco use;
Health risk behavior
- From:
Chinese Journal of Epidemiology
2024;45(7):955-962
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To evaluate the effect of the implementation of Beijing Smoking Control Regulation in 2015 on the smoking prevalence in people aged ≥15 years in Beijing during 2014-2021, and explore factors associated with tobacco use behavior in local population. Methods Using a pooled cross-sectional design, data from Beijing Adult Tobacco Survey in 2014, 2016, 2019 and 2021 (4 surveys) were combined into one dataset. The 4 surveys used same multistage cluster sampling procedure. After complex survey weighting, multiple logistic regression models were constructed to analyze factors influencing smoking status. Results:A total of 8 484, 9 372, 8 534 and 10 551 respondents were included in the surveys in 2014, 2016, 2019 and 2021, respectively. The smoking prevalence rate was 23.4%, 22.3%, 20.3% and 19.9%, respectively, in Beijing residents aged ≥15 years, exhibiting a linear declining trend ( P=0.010). Factors associated with current smoking in men were age 25-44 years ( OR=2.22, 95% CI: 1.68-2.95) and 45-64 years, ( OR=2.64, 95% CI: 2.06-3.39), educational level of high school ( OR=0.69, 95% CI: 0.49-0.95) and undergraduate and above ( OR=0.46, 95% CI: 0.33-0.63), and awareness of smoking causing stroke ( OR=0.71, 95% CI: 0.61-0.81), and awareness of smoking causing lung cancer ( OR=0.53, 95% CI: 0.42-0.66), the differences were significant (all P<0.05). After controlling interfering factors, the current smoking prevalence in men in 2019 ( OR=0.73, 95% CI: 0.63-0.87, P<0.001) and 2021 ( OR=0.72, 95% CI: 0.61-0.88, P<0.001) were significantly lower than that in 2014. Factors associated with current smoking in women were living alone ( OR=1.80, 95% CI: 1.33-2.44), educational level of undergraduate and above ( OR=0.43, 95% CI: 0.27-0.69), other occupations except doctor and teacher ( OR=8.54, 95% CI: 2.80-26.02) or being retired/unemployed ( OR=9.39, 95% CI: 3.19-27.65), and awareness of smoking causing cardiovascular events ( OR=0.58, 95% CI: 0.39-0.84), and awareness of smoking causing lung cancer ( OR=0.54, 95% CI: 0.35-0.83), the differences were significant (all P<0.05). No significant change in smoking status in women was found in 4 surveys. Conclusions:The smoking prevalence rate in men in Beijing has declined since the implementation of Beijing Smoking Control Regulation 5 years, indicating the effectiveness of legislative approach in tobacco control. Socio-demographic factors and the awareness level of tobacco harm could influence smoking status. Future tobacco control programs should target the people with lower education level, young men, women living alone, and those with occupations other than teachers/doctors or the unemployed/retired and include more comprehensive health education.
