The utility of estimating population-level trajectories of terminal wellbeing decline within a growth mixture modelling framework
Byles, J; Magliano, DJ; Anstey, KJ; Burns, RA; Mitchell, P
Abstract
PURPOSE:
Mortality-related decline has been identified across multiple domains of human functioning, including mental health and wellbeing. The current study utilised a growth mixture modelling framework to establish whether a single population-level trajectory best describes mortality-related changes in both wellbeing and mental health, or whether subpopulations report quite different mortality-related changes.
METHODS:
Participants were older-aged (M = 69.59 years; SD = 8.08 years) deceased females (N = 1,862) from the dynamic analyses to optimise ageing (DYNOPTA) project. Growth mixture models analysed participants' responses on measures of mental health and wellbeing for up to 16 years from death.
RESULTS:
Multi-level models confirmed overall terminal decline and terminal drop in both mental health and wellbeing. However, modelling data from the same participants within a latent class growth mixture framework indicated that most participants reported stability in mental health (90.3 %) and wellbeing (89.0 %) in the years preceding death.
CONCLUSIONS:
Whilst confirming other population-level analyses which support terminal decline and drop hypotheses in both mental health and wellbeing, we subsequently identified that most of this effect is driven by a small, but significant minority of the population. Instead, most individuals report stable levels of mental health and wellbeing in the years preceding death.
| Journal | SOC PSYCHIATRY PSYCHIATR EPIDEMIOL |
| ISSN | 0933-7954 |
| Published | 01 Mar 2015 |
| Volume | 50 |
| Issue | 3 |
| Pages | 479-87 |
| DOI | 10.1007/s00127-014-0948-3 |
| Type | Journal Article |
| Sponsorship |