Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan.
Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, Maryland.
Am J Prev Med. 2023 Apr;64(4 Suppl 1):S53-S62. doi: 10.1016/j.amepre.2022.12.006. Epub 2023 Feb 11.
The impact of cigarette smoking on mortality is well studied, with estimates of the relative mortality risks for the overall population widely available. However, age-specific mortality estimates for different sociodemographic groups in the U.S. are lacking.
Using the 1987-2018 National Health Interview Survey Linked Mortality Files through 2019, all-cause mortality relative risks (RRs) were estimated for current smokers or recent quitters and long-term quitters compared with those for never smokers. Stratified Cox proportional hazards regression models were used to estimate RRs by age, gender, race/ethnicity, and educational attainment. RRs were also assessed for current smokers or recent quitters by smoking intensity and for long-term quitters by years since quitting. The analysis was conducted in 2021-2022.
All-cause mortality RRs among current smokers or recent quitters were generally highest for non-Hispanic White individuals than for never smokers, followed by non-Hispanic Black individuals, and were lowest for Hispanic individuals. RRs varied greatly by educational attainment; generally, higher-education groups had greater RRs associated with smoking than lower-education groups. Conversely, the RRs by years since quitting among long-term quitters did not show clear differences across race/ethnicity and education groups. Age-specific RR patterns varied greatly across racial/ethnic and education groups as well as by gender.
Age-specific all-cause mortality rates associated with smoking vary considerably by sociodemographic factors. Among high-education groups, lower underlying mortality rates for never smokers result in correspondingly high RR estimates for current smoking. These estimates can be incorporated in modeling analyses to assess tobacco control interventions' impact on smoking-related health disparities between different sociodemographic groups.
吸烟对死亡率的影响已有大量研究,总体人群的相对死亡率估计值广泛可用。然而,美国不同社会人口群体的特定年龄死亡率估计值尚缺乏。
利用 1987-2018 年全国健康访谈调查与 2019 年的死亡档案,通过 2019 年的分层 Cox 比例风险回归模型,估计当前吸烟者或近期戒烟者与从不吸烟者相比的全因死亡率相对风险(RR)。使用分层 Cox 比例风险回归模型,按年龄、性别、种族/民族和受教育程度对 RR 进行估计。还根据吸烟强度评估当前吸烟者或近期戒烟者的 RR,以及根据戒烟年限评估长期戒烟者的 RR。分析于 2021-2022 年进行。
当前吸烟者或近期戒烟者的全因死亡率 RR 普遍高于从不吸烟者的非西班牙裔白人,其次是非西班牙裔黑人,最低的是西班牙裔。RR 因受教育程度而异;通常,与吸烟相关的 RR 随着教育程度的提高而增加。相反,长期戒烟者的 RR 随着戒烟年限的增加而逐渐降低,在种族/民族和教育群体中没有明显差异。特定年龄的 RR 模式在种族/民族和教育群体以及性别方面差异很大。
与吸烟相关的特定年龄的全因死亡率因社会人口因素而有很大差异。在高教育群体中,从不吸烟者的基础死亡率较低,导致当前吸烟的 RR 估计值相应较高。这些估计值可以纳入建模分析中,以评估烟草控制干预措施对不同社会人口群体之间与吸烟相关的健康差异的影响。