Projecting health trajectories in Europe using microsimulation

16323 8 89639 2 257774 document 89639 WP-20-004.pdf application/pdf 09b3d360e097fef4d389945e193e3099 MD5 505200 2020-02-28 06:46:33 https://pure.iiasa.ac.at/id/eprint/16323/1/WP-20-004.pdf 16323 1 1 application/pdf text en public cc_by_nc_4

WP-20-004.pdf

published 89640 2 257780 document 89640 lightbox.jpg image/png c2ee88da3aca369c912beb449900b446 MD5 16190 2020-02-28 06:56:46 https://pure.iiasa.ac.at/id/eprint/16323/2/lightbox.jpg 16323 2 2 image/png other Thumbnails conversion from text to thumbnail_lightbox en public

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/89639 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/89639 http://eprints.org/relation/isIndexCodesVersionOf https://pure.iiasa.ac.at/id/document/89639 archive 353 disk0/00/01/63/23 2020-02-28 06:51:37 2021-08-27 17:32:41 2020-02-28 06:51:37 monograph show 1 Marois G. 2145 0000-0002-2701-6286 Aktas A. 8876 Wolfgang Lutz, Program Director World Population Program Projecting health trajectories in Europe using microsimulation pub prog_pop 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. 2020-02-28 published WP-20-004 2905 2978 public working_paper Laxenburg, Austria Ageing Trajectories of Health: Longitudinal Opportunities and Synergies (ATHLOS, H2020 635316) FALSE yes info:eu-repo/grantAgreement/EC/H2020/635316/EU//ATHLOS info:eu-repo/semantics/book info:eu-repo/semantics/openAccess