[Prevalence of tobacco smoking and related factors in people aged 15 years and above in Beijing, 2014-2021]

Zhonghua Liu Xing Bing Xue Za Zhi. 2024 Jul 10;45(7):955-962. doi: 10.3760/cma.j.cn112338-20240205-00061.
[Article in 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.

目的: 评价2015年《北京市控制吸烟条例》出台后对2014-2021年≥15岁吸烟人群的作用,探索北京市居民烟草使用行为的影响因素。 方法: 使用混合横断面研究设计,汇总2014、2016、2019和2021年4轮北京市成人烟草监测数据(4轮监测);4轮监测均采用分层多阶段整群概率抽样方法;统计分析过程均经过复杂抽样加权,利用多因素logistic回归探索人群吸烟状况的影响因素。 结果: 2014、2016、2019和2021年分别纳入8 484、9 372、8 534和10 551人,北京市≥15岁人群现在吸烟率分别为23.4%、22.3%、20.3%和19.9%,随年份呈线性下降趋势(P=0.010)。年龄为25~44岁(OR=2.22,95%CI:1.68~2.95)、45~64岁(OR=2.64,95%CI:2.06~3.39)、文化程度为高中(OR=0.69,95%CI:0.49~0.95)、大专及以上(OR=0.46,95%CI:0.33~0.63)、知道吸烟会导致脑卒中(OR=0.71,95%CI:0.61~0.81)、知道吸烟会导致肺癌(OR=0.53,95%CI:0.42~0.66)与男性现在吸烟相关,差异有统计学意义(均P<0.05)。在控制混杂因素后,2019年(OR=0.73,95%CI:0.63~0.87,P<0.001)和2021年(OR=0.72,95%CI:0.61~0.88,P<0.001),男性现在吸烟率显著低于立法前的2014年。独居(OR=1.80,95%CI:1.33~2.44)、大专及以上文化程度(OR=0.43,95%CI:0.27~0.69)、从事医生/教师外的其他职业(OR=8.54,95%CI:2.80~26.02)、退休/无职业(OR=9.39,95%CI:3.19~27.65)、知道吸烟会导致心肌梗死(OR=0.58,95%CI:0.39~0.84)、知道吸烟会导致肺癌(OR=0.54,95%CI:0.35~0.83)与女性现在吸烟相关,差异有统计学意义(均P<0.05)。女性吸烟状况在4轮监测中无显著变化。 结论: 北京市控烟立法5年后,男性现在吸烟率显著降低,立法卓有成效。社会人口学因素和烟草危害知识共同影响吸烟状况,应将低文化程度人群、青年男性、女性独居者、从事医生/教师外的其他职业者和退休/无职业者作为下一步控烟工作的重点人群,开展更有针对性的烟草危害知识教育。.

Publication types

  • English Abstract

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Beijing / epidemiology
  • Cross-Sectional Studies
  • Female
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Prevalence
  • Smoking / epidemiology
  • Tobacco Smoking* / epidemiology
  • Young Adult