@article{marois_projecting_2021,
	title = {Projecting health-ageing trajectories in {Europe} using a dynamic microsimulation model},
	volume = {11},
	issn = {2045-2322},
	url = {http://www.nature.com/articles/s41598-021-81092-z},
	doi = {10.1038/s41598-021-81092-z},
	abstract = {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.},
	language = {en},
	number = {1},
	urldate = {2021-01-26},
	journal = {Scientific Reports},
	author = {Marois, Guillaume and Aktas, Arda},
	month = jan,
	year = {2021},
	pmcid = {PMC7815779},
	pmid = {33469046},
	keywords = {ATHLOS, Ageing Trajectories of Health – Longitudinal Opportunities and Synergies},
	pages = {1785},
}

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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.","language":"en","number":"1","urldate":"2021-01-26","journal":"Scientific Reports","author":[{"propositions":[],"lastnames":["Marois"],"firstnames":["Guillaume"],"suffixes":[]},{"propositions":[],"lastnames":["Aktas"],"firstnames":["Arda"],"suffixes":[]}],"month":"January","year":"2021","pmcid":"PMC7815779","pmid":"33469046","keywords":"ATHLOS, Ageing Trajectories of Health – Longitudinal Opportunities and Synergies","pages":"1785","bibtex":"@article{marois_projecting_2021,\n\ttitle = {Projecting health-ageing trajectories in {Europe} using a dynamic microsimulation model},\n\tvolume = {11},\n\tissn = {2045-2322},\n\turl = {http://www.nature.com/articles/s41598-021-81092-z},\n\tdoi = {10.1038/s41598-021-81092-z},\n\tabstract = {Abstract\n 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. 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