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Understanding ageing in older Australians: the contribution of the Dynamic Analyses to Optimise Ageing (DYNOPTA) project to the evidence base and policy

机译:了解澳大利亚老年人的衰老:优化衰老动态分析(DYNOPTA)项目对证据基础和政策的贡献

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摘要

Aim: To describe the Dynamic Analyses to Optimise Ageing (DYNOPTA) project and illustrate its contributions to understanding ageing through innovative methodology, and investigations on outcomes based on the project themes. DYNOPTA provides a platform and technical expertise that may be used to combine other national and international datasets. Methods: The DYNOPTA project has pooled and harmonised data from nine Australian longitudinal studies to create the largest available longitudinal dataset (n= 50652) on ageing in Australia. Results: A range of findings have resulted from the study to date, including methodological advances, prevalence rates of disease and disability, and mapping trajectories of ageing with and without increasing morbidity. DYNOPTA also forms the basis of a microsimulation model that will provide projections of future costs of disease and disability for the baby boomer cohort. Conclusion: DYNOPTA contributes significantly to the Australian evidence base on ageing to inform key social and health policy domains.
机译:目的:描述优化衰老的动态分析(DYNOPTA)项目,并说明其通过创新的方法对衰老的理解以及基于项目主题的成果调查的贡献。 DYNOPTA提供了一个平台和技术专长,可用于组合其他国家和国际数据集。方法:DYNOPTA项目汇集了来自澳大利亚的九项纵向研究的数据并进行了协调,以创建澳大利亚可用的最大的纵向老龄化纵向数据集(n = 50652)。结果:迄今为止,该研究已得出一系列发现,包括方法学的进步,疾病和残疾的患病率以及绘制发病率与不增加发病率的衰老轨迹。 DYNOPTA还构成了微观模拟模型的基础,该模型将为婴儿潮一代的未来疾病和残疾成本提供预测。结论:DYNOPTA为澳大利亚基于衰老的重要证据做出了重要贡献,从而为关键的社会和卫生政策领域提供了信息。

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