Life expectancy and disability-free life expectancy estimates for Middle Super Output Areas; England, 1999-2003

In recent years, there has been increasing demand for health indicators at small area level to support monitoring and planning. This study investigates the use of a small area geography, Middle Layer Super Output Areas (MSOAs) for the estimation and comparison of disability-free life expectancy (DFLE) in England.

Using death registrations from 1999 to 2003 and data on limiting long-term illness from the Census 2001, life expectancy and DFLE are estimated for English MSOAs and Government Office Regions. Figures are presented for quintiles based on MSOA DFLE values, and quintiles of relative deprivation using the Index of Multiple Deprivation 2004. Health inequalities are assessed at regional level and between quintile extremes for both measures.

The distribution of DFLE across MSOAs was characterised by a north-south geographical divide: the highest DFLE at birth for males was in Kensington and Chelsea 016 (73.9 years) and lowest was in Manchester 013 (44.1 years). For females the highest value was in Kensington and Chelsea 012 (74.4 years) and the lowest in Liverpool 039 (48.2 years). Over 40 per cent of MSOAs in the South East, but only about 3 per cent of those in the North East, were in the quintile with the highest DFLE values at birth. Conversely, the equivalent proportions in the quintile with the lowest values were approximately 4 per cent and 50 per cent respectively.At birth, males in the most affluent areas could expect to spend an additional 12.6 years without a disability compared to those in the most deprived areas. For females this inequality was 10.9 years. At age 65 inequalities persisted but the differences were narrower.

This is the first use of MSOAs in estimating DFLE, and the results highlight the substantial inequalities between quintile groupings based on DFLE values as well as between the least and most deprived MSOAs in England. These findings provide useful health outcomes information to planners at the local level, for benchmarking purposes and to assist in resource allocation through the identification of differences in relative need between local populations.