Longitudinal factors associated with living well outcomes in people with mild‐to‐moderate dementia: Initial findings from the IDEAL cohort

Abstract

AbstractBackgroundUnderstanding the factors associated with quality of life (QoL), satisfaction with life (SwL) and wellbeing can help us become more effective in optimizing the potential for people with mild‐to‐moderate dementia to ‘live well’ with the condition. Identifying individuals at risk of declining well‐being could help to target support more appropriately, but there is little evidence available about factors that may influence ability to ‘live well’ longitudinally.MethodsWe used longitudinal data from 1547 individuals with mild‐to‐moderate dementia participating in the IDEAL cohort, who have been assessed on entry and followed up 12 months and 24 months later. We examined how factors found to be important at baseline were associated with change over time using growth curve modelling. Factors were grouped into four domains: psychological characteristics and health; physical health; social capitals, assets and resources; and functional ability.ResultsPsychologically, individuals who were less depressed and lonely, and had positive attitudes to ageing, had better QoL, SwL and wellbeing over three waves. Decreasing loneliness was associated with increasing QoL and Wellbeing, increasing depression with decreasing SwL, and a decrease in their attitude to ageing less wellbeing over time. Physically, better self‐rated health, sleep quality, eyesight, hearing, appetite and olfaction predict better QoL and wellbeing, and all but olfaction predict better SwL, over the 3 waves. Socially, less isolation, greater cultural capital and greater reciprocity and trust in the local neighbourhood predict better QoL, SwL and wellbeing over the 3 waves. Good functional ability was associated with better QoL, SwL and wellbeing over the 3 waves.ConclusionsUsing longitudinal data showed remarkable consistency with different methods of measuring how people with dementia “live well”. Understanding these longitudinal changes is vital to identify potential factors for intervention.