Health and quality of life in aging populations: A structural equation modeling approach

Higher life expectancy and lower fertility rates are changing the global population structure, leading to a fast-growing aging society. To face this societal challenge, governments worldwide are increasing public expenditures focusing on healthy aging. The objective of these investments is to increase quality of life among older people. However, there is a lack of studies focused on understanding the extent to which a wide range of demographic, socioeconomic, and health characteristics are associated with quality of life in advanced ages. Therefore, the objective of this presentation is to explore the role of a variety of factors toward quality of life, with a particular focus on health. Structural equation modeling (SEM) is employed using Stata 16 to explore these associations, using data drawn from the Survey of Health, Ageing and Retirement in Europe (SHARE). Contrary to many studies that use self-assessed single-item questions or additive indices to measure unobserved concepts, such as health and quality of life, this presentation models such constructs as latent variables. Moreover, a minor contribution of this presentation is to employ standard statistical techniques using additive indices along with the main SEM estimation. As the theory predicts, estimates found with additive indices are downward biased compared with latent variables, but so far, there are no studies showing this empirical exercise. The overall findings suggest that nonpecuniary factors, especially physical health status and participating in social activities, play a larger role in enhancing quality of life in advanced age compared with pecuniary factors such as income and financial assets. Therefore, greater attention should be paid on non-economic factors to enrich quality of life among an increasingly aging population.