Since 2007, we have been building a resource that facilitates the use of harmonized multi-country data sets, including the 2002 - 2008 waves of the Health and Retirement Study (HRS) as well as the English Longitudinal Study of Ageing (ELSA), the Survey of Health, Ageing, and Retirement in Europe (SHARE), and the Korean Longitudinal Study of Aging (KLoSA). Under this previously funded R01, we have created a digital library of questions equipped with a search engine that enables researchers to identify questions that are comparable across the surveys and waves. In the current application, we propose to expand that R01 by (aim 1) adding three additional harmonized data sets - the Japanese Study on Aging and Retirement (J-STAR), the Indonesia Family Life Surveys (IFLS), and the Irish Longitudinal Study on Aging (TILDA) - that were developed to be comparable to the current HRS family of surveys;
(aim 2) adding waves of HRS collected before 2002;
and (aim 3) adding self-completion data from HRS, ELSA, SHARE, and J-STAR collected using a mail or drop-off survey. The proposed project should generate time savings for individual researchers interested in using the HRS family of surveys by creating a set of identically defined key variables commonly used in studying health and retirement (aim 4). Building on the derived variables created by the RAND HRS, we propose to create a public-use version of the data from the participating studies that is cleaned, easy to use, and ready for cross-country analysis.
Our final aim i s to further disseminate the resulting information system to the scientific community (aim 5). Under the previously funded R01, we have been developing a public website, https://mmic.rand.org/wiki, to share the resulting resources with this community. To further facilitate dissemination, we propose to host a user workshop and make presentations at scientific meetings. By enhancing the usability of large data sets, we will accelerate the tempo of scientific research. In particular, our information system facilitates users'understanding and use of multiple datasets and will generate time savings for all researchers interested in the HRS family of surveys. All expenditures in support of the proposed project will advance the objectives of the Recovery Act by job creation and retention.
Project Narrative Despite the availability of internationally harmonized datasets on health and retirement, cross-national studies are still small in number, leaving scientific opportunities not fully exploited. The goal of our application is to facilitate the use of these data and to encourage the use of multi-country, multi-level, and multi-method data sets by developing an information system. Our proposed information system will help a large number of researchers to jump start cross-country analyses of health, retirement, and aging.
|Liao, Jing; Muniz-Terrera, Graciela; Scholes, Shaun et al. (2018) Lifestyle index for mortality prediction using multiple ageing cohorts in the USA, UK and Europe. Sci Rep 8:6644|
|Suemoto, Claudia Kimie; Ueda, Peter; Beltrán-Sánchez, Hiram et al. (2017) Development and Validation of a 10-Year Mortality Prediction Model: Meta-Analysis of Individual Participant Data From Five Cohorts of Older Adults in Developed and Developing Countries. J Gerontol A Biol Sci Med Sci 72:410-416|