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使用动态微观模拟模型预测欧洲的健康老龄化轨迹。

Projecting health-ageing trajectories in Europe using a dynamic microsimulation model.

机构信息

Asian Demographic Research Institute, School of Sociology and Political Sciences, Shanghai University, 99 Shangda Rd., Shanghai, 200444, China.

Wittgenstein Centre for Demography and Global Human Capital (IIASA, OeAW, University of Vienna), International Institute for Applied Systems Analysis, Schlossplatz 1, 2361, Laxenburg, Austria.

出版信息

Sci Rep. 2021 Jan 19;11(1):1785. doi: 10.1038/s41598-021-81092-z.

Abstract

The extent of the challenges and opportunities that population ageing presents depends heavily on the population's health. Hence, for the development of appropriate strategies that enable countries to adopt the emerging demographic and epidemiological realities, information on future health trajectories of elderly population is a natural requirement. This study presents an innovative methodological framework for projecting the health of individuals using a dynamic microsimulation model that considers interactions between sociodemographic characteristics, health, mortality, bio-medical and behavioral risk factors. The model developed, called ATHLOS-Mic, is used to project the health of cohorts born before 1960 for the period 2015-2060 for selected European Countries using SHARE data to illustrate the possible effects of some selected risk factors and education on future health trajectories. Results show that, driven by a better educational attainment, each generation will be healthier than the previous one at same age. Also, we see that, on average, an individual of our base population will live about 18 more years since the start of the projection period, but only 5 years in good health. Finally, we find that a scenario that removes the effect of having a low level of education on individual health has the largest impact on the projected average health, the average number of years lived per person, and the average number of years lived in good health.

摘要

人口老龄化带来的挑战和机遇的程度在很大程度上取决于人口的健康状况。因此,为了制定使各国能够适应新出现的人口和流行病学现实的适当战略,了解老年人口未来的健康轨迹信息是一个自然的要求。本研究提出了一种创新的方法框架,使用考虑社会人口特征、健康、死亡率、生物医学和行为风险因素之间相互作用的动态微观模拟模型来预测个人的健康状况。该模型名为 ATHLOS-Mic,用于使用 SHARE 数据为选定的欧洲国家预测 1960 年前出生的队列在 2015-2060 年期间的健康状况,以说明一些选定的风险因素和教育对未来健康轨迹的可能影响。结果表明,由于教育程度的提高,每一代人在相同年龄时都将比前一代人更健康。此外,我们发现,在预测期开始后,我们的基础人口中的一个人将平均多活约 18 年,但只有 5 年处于健康状态。最后,我们发现,一个消除低教育水平对个人健康影响的情景对预测的平均健康状况、人均预期寿命和人均健康预期寿命的影响最大。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0769/7815779/29bb0514c7b6/41598_2021_81092_Fig1_HTML.jpg

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