A global indicator to track well-being in the silver and golden age Articles uri icon

publication date

  • January 2023

start page

  • 1057

end page

  • 1086

issue

  • 3

volume

  • 169

International Standard Serial Number (ISSN)

  • 0303-8300

Electronic International Standard Serial Number (EISSN)

  • 1573-0921

abstract

  • In this work, we design a protocol to obtain global indicators of health and well-being
    from weighted and longitudinal heterogeneous multivariate data. First, we consider a set
    of thematic sub-indicators of interest observed in several periods. Next, we combine them
    using the Common Principal Component (CPC) model. For this purpose, we put a new
    straightforward CPC model to cope with weighted and longitudinal data and develop a new
    statistic to test the validity of the CPC-longitudinal model, whose distribution is obtained
    by stratified bootstrap. To illustrate this methodology, we use data from the last three
    waves of the Survey of Health, Ageing and Retirement in Europe (SHARE), which is the
    largest cross-European social science panel study data set covering insights into the public
    health and socio-economic living conditions of European individuals. In particular, we first
    design four thematic indicators that focus on general health status, dependency situation,
    self-perceived health, and socio-economic status. We then apply the CPC-longitudinal
    model to obtain a global indicator to track the well-being in the silver and golden age in
    the 18 participating European countries from 2015 to 2020. We found that the latest survey
    wave 8 captures the early reactions of respondents successfully. The pandemic significantly
    worsens people"s physical health conditions; however, the analysis of their self-perceived
    health presents a delay. Tracking the performances of our global indicator, we also found
    that people living in Northern Europe mainly have better health and well-being status than
    in other participating countries.

subjects

  • Statistics

keywords

  • ageing; bootstrap; common principal components; longitudinal data; public health; well-being