Howe Samantha, Wilson Tim, Gartner Coral, Blakely Tony, Ait Ouakrim Driss
Melbourne School of Population and Global Health, University of Melbourne, Parkville, Australia.
School of Public Health, Faculty of Medicine, The University of Queensland, Brisbane, Australia.
Int J Epidemiol. 2025 Feb 16;54(2). doi: 10.1093/ije/dyaf038.
Australia is one of several countries aiming to achieve a commercial tobacco endgame, with a current target of ≤5% daily smoking prevalence by 2030. Like other jurisdictions, the Australian target ignores large variations in smoking across sociodemographic groups and risks perpetuating current smoking-related inequities. To help mitigate this risk, we calculated future smoking rates under business-as-usual for multiple sociodemographic categories and compared them to the endgame target.
We used a simulated annealing optimization approach to estimate historic daily smoking rates in Australia by six dimensions of sex, age, remoteness, index of relative socioeconomic advantage and disadvantage, and Indigenous status, using multiple datasets from 2001 to 2022-23. We applied logistic regression to the modelled outputs to forecast cohort smoking rates for 30 years.
At the population level, daily smoking is expected to reach 7.8% by 2030 under business-as-usual. Of the 15 strata combinations of remoteness and socioeconomic status in the model, only two met the ≤5% target by 2030, with smoking prevalence remaining highest (34.6% in 2030) for people living in the most disadvantaged (remote, SES1) areas.
Our modelling suggests that if equity is not at the forefront of Australian tobacco policy, ongoing smoking disparities are likely to continue even if the endgame goal is achieved. Our approach offers a crucial baseline for assessing the impact of tobacco control interventions by different sociodemographic dimensions and presents a methodological framework that could be adapted for analysing smoking-related inequities in other jurisdictions. This framework should also be extended, incorporating uncertainty into modelled estimates.
澳大利亚是几个旨在实现商业烟草终结目标的国家之一,目前的目标是到2030年将每日吸烟率降至5%以下。与其他司法管辖区一样,澳大利亚的目标忽视了社会人口群体中吸烟情况的巨大差异,并有可能使当前与吸烟相关的不平等现象长期存在。为了帮助降低这种风险,我们计算了多个社会人口类别在照常营业情况下的未来吸烟率,并将其与终结目标进行了比较。
我们使用模拟退火优化方法,利用2001年至2022 - 2023年的多个数据集,按性别、年龄、偏远程度、相对社会经济优势和劣势指数以及原住民身份这六个维度估算澳大利亚的历史每日吸烟率。我们对模型输出应用逻辑回归来预测30年的队列吸烟率。
在总体水平上,照常营业情况下预计到2030年每日吸烟率将达到7.8%。在模型中偏远程度和社会经济地位的15个分层组合中,到2030年只有两个达到了≤5%的目标,生活在最不利(偏远,SES1)地区的人群吸烟率仍然最高(2030年为34.6%)。
我们的模型表明,如果公平性不在澳大利亚烟草政策的首要位置,即使实现了终结目标,当前的吸烟差距仍可能持续。我们的方法为评估不同社会人口维度的烟草控制干预措施的影响提供了关键基线,并提出了一个可适用于分析其他司法管辖区与吸烟相关不平等现象的方法框架。这个框架还应扩展,将不确定性纳入模型估计中。