@techreport{marois_projecting_2020,
	address = {Laxenburg, Austria},
	type = {{IIASA} {Working} {Paper}},
	title = {Projecting health trajectories in {Europe} using microsimulation},
	url = {https://pure.iiasa.ac.at/id/eprint/16323/},
	abstract = {This working paper presents an innovative methodological framework for projecting the health of individuals with a set of risk factors using a microsimulation model. The model developed, called ATHLOS-Mic, projects the health of cohorts born before 1960 and a set of risk factors for the horizon 2060 for some European countries. It simulates the lives of individuals using statistical models that explicitly take into account interactions between the different dimensions, either biological and behavioral risk factors (smoking, obesity, depression, arterial hypertension and physical activity), socioeconomic characteristics (education), a health metric, and mortality. Using data from SHARE-HD, we used parameters from statistical models to project dynamically changes in risk factors with a set of covariates and their impact on a health metric. The health metric is then used to modulate the probability of survival. A set of analytical scenarios are built showing the effect of each risk factors 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. In average, an individual of our base population will live about 18 more years, but only 5 in good health. The scenario removing the effect of having a low level of education on the health metric is the one having the largest effect on both the projected average health metric, the average number of years lived per person, and the average number of years lived in good health. Summing up, removing all risk factors would add 2 years of life, but 6 years in good health.},
	number = {WP-20-004},
	institution = {IIASA},
	author = {Marois, G. and Aktas, A.},
	month = feb,
	year = {2020},
}

{"_id":"nhrJdmJCrW4RcmvbW","bibbaseid":"marois-aktas-projectinghealthtrajectoriesineuropeusingmicrosimulation-2020","author_short":["Marois, G.","Aktas, A."],"bibdata":{"bibtype":"techreport","type":"IIASA Working Paper","address":"Laxenburg, Austria","title":"Projecting health trajectories in Europe using microsimulation","url":"https://pure.iiasa.ac.at/id/eprint/16323/","abstract":"This working paper presents an innovative methodological framework for projecting the health of individuals with a set of risk factors using a microsimulation model. The model developed, called ATHLOS-Mic, projects the health of cohorts born before 1960 and a set of risk factors for the horizon 2060 for some European countries. It simulates the lives of individuals using statistical models that explicitly take into account interactions between the different dimensions, either biological and behavioral risk factors (smoking, obesity, depression, arterial hypertension and physical activity), socioeconomic characteristics (education), a health metric, and mortality. Using data from SHARE-HD, we used parameters from statistical models to project dynamically changes in risk factors with a set of covariates and their impact on a health metric. The health metric is then used to modulate the probability of survival. A set of analytical scenarios are built showing the effect of each risk factors 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. In average, an individual of our base population will live about 18 more years, but only 5 in good health. The scenario removing the effect of having a low level of education on the health metric is the one having the largest effect on both the projected average health metric, the average number of years lived per person, and the average number of years lived in good health. Summing up, removing all risk factors would add 2 years of life, but 6 years in good health.","number":"WP-20-004","institution":"IIASA","author":[{"propositions":[],"lastnames":["Marois"],"firstnames":["G."],"suffixes":[]},{"propositions":[],"lastnames":["Aktas"],"firstnames":["A."],"suffixes":[]}],"month":"February","year":"2020","bibtex":"@techreport{marois_projecting_2020,\n\taddress = {Laxenburg, Austria},\n\ttype = {{IIASA} {Working} {Paper}},\n\ttitle = {Projecting health trajectories in {Europe} using microsimulation},\n\turl = {https://pure.iiasa.ac.at/id/eprint/16323/},\n\tabstract = {This working paper presents an innovative methodological framework for projecting the health of individuals with a set of risk factors using a microsimulation model. The model developed, called ATHLOS-Mic, projects the health of cohorts born before 1960 and a set of risk factors for the horizon 2060 for some European countries. It simulates the lives of individuals using statistical models that explicitly take into account interactions between the different dimensions, either biological and behavioral risk factors (smoking, obesity, depression, arterial hypertension and physical activity), socioeconomic characteristics (education), a health metric, and mortality. Using data from SHARE-HD, we used parameters from statistical models to project dynamically changes in risk factors with a set of covariates and their impact on a health metric. The health metric is then used to modulate the probability of survival. A set of analytical scenarios are built showing the effect of each risk factors 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. In average, an individual of our base population will live about 18 more years, but only 5 in good health. The scenario removing the effect of having a low level of education on the health metric is the one having the largest effect on both the projected average health metric, the average number of years lived per person, and the average number of years lived in good health. Summing up, removing all risk factors would add 2 years of life, but 6 years in good health.},\n\tnumber = {WP-20-004},\n\tinstitution = {IIASA},\n\tauthor = {Marois, G. and Aktas, A.},\n\tmonth = feb,\n\tyear = {2020},\n}\n\n\n\n","author_short":["Marois, G.","Aktas, A."],"key":"marois_projecting_2020","id":"marois_projecting_2020","bibbaseid":"marois-aktas-projectinghealthtrajectoriesineuropeusingmicrosimulation-2020","role":"author","urls":{"Paper":"https://pure.iiasa.ac.at/id/eprint/16323/"},"metadata":{"authorlinks":{}},"downloads":4,"html":""},"bibtype":"techreport","biburl":"https://bibbase.org/zotero-group/iagogv/4865242","dataSources":["GdZFePjpwY9sghZoY","ovn29uG6Mbp3JWCRR","hjeq3HDahJ7qoS8sT","3ixEQFKYYWDDWTnwK"],"keywords":[],"search_terms":["projecting","health","trajectories","europe","using","microsimulation","marois","aktas"],"title":"Projecting health trajectories in Europe using microsimulation","year":2020,"downloads":4}