Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
PLoS One. 2012;7(2):e32363. doi: 10.1371/journal.pone.0032363. Epub 2012 Feb 23.
There are several types of tobacco control interventions/policies which can change future smoking exposure. The most basic intervention types are 1) smoking cessation interventions 2) preventing smoking initiation and 3) implementation of a nationwide policy affecting quitters and starters simultaneously. The possibility for dynamic quantification of such different interventions is key for comparing the timing and size of their effects.
We developed a software tool, DYNAMO-HIA, which allows for a quantitative comparison of the health impact of different policy scenarios. We illustrate the outcomes of the tool for the three typical types of tobacco control interventions if these were applied in the Netherlands. The tool was used to model the effects of different types of smoking interventions on future smoking prevalence and on health outcomes, comparing these three scenarios with the business-as-usual scenario. The necessary data input was obtained from the DYNAMO-HIA database which was assembled as part of this project. All smoking interventions will be effective in the long run. The population-wide strategy will be most effective in both the short and long term. The smoking cessation scenario will be second-most effective in the short run, though in the long run the smoking initiation scenario will become almost as effective. Interventions aimed at preventing the initiation of smoking need a long time horizon to become manifest in terms of health effects. The outcomes strongly depend on the groups targeted by the intervention.
We calculated how much more effective the population-wide strategy is, in both the short and long term, compared to quit smoking interventions and measures aimed at preventing the initiation of smoking. By allowing a great variety of user-specified choices, the DYNAMO-HIA tool is a powerful instrument by which the consequences of different tobacco control policies and interventions can be assessed.
有几种类型的烟草控制干预措施/政策可以改变未来的吸烟暴露。最基本的干预类型是 1)戒烟干预 2)预防吸烟开始,3)实施同时影响戒烟者和开始吸烟者的全国性政策。对这种不同干预措施进行动态量化的可能性是比较其作用的时间和大小的关键。
我们开发了一种软件工具 DYNAMO-HIA,该工具允许对不同政策情景的健康影响进行定量比较。我们以荷兰为例说明了该工具在三种典型的烟草控制干预措施下的结果。该工具用于模拟不同类型的吸烟干预措施对未来吸烟流行率和健康结果的影响,将这三种情景与常规情景进行比较。所需的数据输入是从 DYNAMO-HIA 数据库中获得的,该数据库是作为该项目的一部分组装的。所有吸烟干预措施在长期内都是有效的。在短期和长期内,全民策略都是最有效的。在短期内,戒烟情景的效果将仅次于全民策略,尽管在长期内,预防吸烟开始的情景将变得几乎同样有效。预防吸烟开始的干预措施需要很长时间才能在健康效果上显现出来。结果强烈取决于干预措施针对的群体。
我们计算了与戒烟干预措施和预防吸烟开始的措施相比,在短期和长期内,全民策略的有效性提高了多少。通过允许用户指定多种选择,DYNAMO-HIA 工具是一种强大的工具,可以评估不同烟草控制政策和干预措施的后果。