Background The aims of this study were (1) to estimate 10-year trends in disability-free life expectancy (DFLE) by area-level social disadvantage and (2) to examine how incidence, recovery and mortality transitions contributed to these trends.
Methods Data were drawn from the nationally representative Household Income and Labour Dynamics in Australia survey. Two cohorts (baseline age 50+ years) were followed up for 7 years, from 2001 to 2007 and from 2011 to 2017, respectively. Social disadvantage was indicated by the Socio-Economic Indexes for Areas (SEIFA). Two DFLEs based on a Global Activity Limitation Indicator (GALI) and difficulties with activities of daily living (ADLs) measured by the 36-Item Short Form Survey physical function subscale were estimated by cohort, sex and SEIFA tertile using multistate models.
Results Persons residing in the low-advantage tertile had more years lived with GALI and ADL disability than those in high-advantage tertiles. Across the two cohorts, dynamic equilibrium for GALI disability was observed among men in mid-advantage and high-advantage tertiles, but expansion of GALI disability occurred in the low-advantage tertile. There was expansion of GALI disability for all women irrespective of their SEIFA tertile. Compression of ADL disability was observed for all men and for women in the high-advantage tertile. Compared to the 2001 cohort, disability incidence was lower for the 2011 cohort of men within mid-advantage and high-advantage tertiles, whereas recovery and disability-related mortality were lower for the 2011 cohort of women within the mid-advantage tertile.
Conclusion Overall, compression of morbidity was more common in high-advantage areas, whereas expansion of morbidity was characteristic of low-advantage areas. Trends also varied by sex and disability severity.
- health expectancy
- social inequalities
Data availability statement
Data may be obtained from a third party and are not publicly available. Household Income and Labour Dynamics in Australia data are not publicly available but can be requested from the Australian Department of Social Services National Centre for Longitudinal Data (https://dataverse.ada.edu.au/dataverse/hilda). Data coding and analysis scripts are available online (https://osf.io/tkhyn/).
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