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Adaptation in life satisfaction and self-assessed health to disability - Evidence from the UK
Jannis Stöckel1, Job van Exel2, Werner B F Brouwer2
1Erasmus School of Health Policy & Management (ESHPM), Erasmus University Rotterdam, Rotterdam, the Netherlands; Erasmus Centre for Health Economics Rotterdam (EsCHER), Erasmus University Rotterdam, Rotterdam, The Netherlands; London School of Economics and Political Science, Department of Health Policy, LSE Health, London, United Kingdom.
Abstract:
Experiencing deteriorating health has implications for your quality of life. The theory of adaptation suggests that with time spend living in a health state individuals can adapt, resulting in observed quality of life levels to revert or stagnate despite persistently decreased health. Adaptation has implications for the use of subjective quality of life indicators when quantifying the impact of health changes or the benefits from new medical technologies. As both the impact from ill health and the benefit from new interventions might be disease- or subgroup-specific adaptation further raises ethical concerns but empirical evidence on its existence, magnitude, and heterogeneity remains inconclusive. This paper uses a general population sample of 9,543 individuals that participate in the UK Understanding Society survey and experience the onset of a long-standing illness or disability to provide evidence on these questions. Using ordered-response fixed effects models we explore longitudinal changes in self-assessed health and life satisfaction around the onset of disability. Our results indicate that disability onset is associated with large decreases in subjective health and well-being. Over time this initial decrease in subjective quality of life indicators attenuates, especially in life satisfaction and to a lesser extent for self-assessed health. While the relative difference in adaptation across these two measures remains persistent, we find that across demographic and severity groups the initial impact of disability onset and adaptation differs considerably in its magnitude. These results have important implications for studies aiming to quantify the impact of health conditions on quality of life outcomes, especially when using observational datasets.
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