The utility of estimating population-level trajectories of terminal wellbeing decline within a growth mixture modelling framework
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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.
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.
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.
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.
KeywordsWell-being Mental health Mortality Epidemiology Mixture modelling
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