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Assessment of health impacts of decreased smoking prevalence in Copenhagen: Application of the DYNAMO-HIA model

机译:评估哥本哈根吸烟率下降对健康的影响:DYNAMO-HIA模型的应用

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Aims: Tobacco smoking is among the leading risk factors for chronic disease and early death in developed countries, including Denmark, where smoking causes 14% of the disease burden. In Denmark, many public health interventions, including smoking prevention, are undertaken by the municipalities, but models to estimate potential health effects of local interventions are lacking. The aim of the current study was to model the effects of decreased smoking prevalence in Copenhagen, Denmark. Methods: The DYNAMO-HIA model was applied to the population of Copenhagen, by using health survey data and data from Danish population registers. We modelled the effects of four intervention scenarios aimed at different target groups, compared to a reference scenario. The potential effects of each scenario were modelled until 2040. Results: A combined scenario affecting both initiation rates among youth, and cessation and re-initiation rates among adults, which reduced the smoking prevalence to 4% by 2025, would have large beneficial effects on incidence and prevalence of smoking-related diseases and mortality. Health benefits could also be obtained through interventions targeting only cessation or re-initiation rates, whereas an intervention targeting only initiation among youth had marginal effects on morbidity and mortality within the modelled time frame. Conclusions: By modifying the DYNAMO-HIA model, we were able to estimate the potential health effects of four interventions to reduce smoking prevalence in the population of Copenhagen. The effect of the interventions on future public health depended on population subgroup(s) targeted, duration of implementation and intervention reach.
机译:目的:在包括丹麦在内的发达国家中,吸烟是导致慢性病和早期死亡的主要危险因素之一,在丹麦,吸烟造成疾病负担的14%。在丹麦,市政当局采取了许多公共卫生干预措施,包括预防吸烟,但缺乏用于估计当地干预措施可能对健康产生影响的模型。当前研究的目的是模拟丹麦哥本哈根减少吸烟率的影响。方法:利用健康调查数据和丹麦人口登记册的数据,将DYNAMO-HIA模型应用于哥本哈根人口。与参考方案相比,我们对针对不同目标人群的四种干预方案的效果进行了建模。对每种情景的潜在影响进行了建模,直到2040年。结果:组合情景既影响了年轻人的启蒙率,又影响了成年人的戒烟和再启始率,到2025年将吸烟率降低到4%,这将对吸烟相关疾病的发病率和流行率以及死亡率。也可以通过仅针对戒烟或重新启动率的干预措施获得健康益处,而仅针对青年人群的干预措施在模拟的时间范围内对发病率和死亡率产生边际影响。结论:通过修改DYNAMO-HIA模型,我们能够估算出四种减少哥本哈根人群吸烟率的干预措施对健康的潜在影响。干预措施对未来公共卫生的影响取决于目标人群,实施时间和干预范围。

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