STUDY OBJECTIVE: The drive to tackle health inequalities at the local level has increased interest in mortality data for small populations. There is some concern that nursing homes may affect measures of mortality for small populations, but there has been little in depth analysis of this. DESIGN AND SETTING: Deaths between 1997 and 2001 and population figures from the GP register (Exeter) database and census 2001 were used to produce life expectancy (LE) figures for all electoral wards in West Sussex. The proportion of those dying within each ward that had been residents of nursing homes was calculated and the relation between these variables and deprivation investigated. RESULTS: There was a significant linear relation between nursing home deaths and LE (p<0.0001), which explained 36% of variation in LE between wards. Deprivation accounted for around 35% of the variation in LE (p<0.0001) but was not correlated with nursing home deaths (p> or =0.0982). Multiple linear regression shows that over 60% of the variation in LE at ward level can be explained by both nursing home deaths and deprivation (p<0.0001) and that the two variables explain similar proportions of this variation. The relation between LE and nursing home deaths within wards grouped by deprivation suggests that the impact of nursing homes is strongest in deprived wards. CONCLUSIONS: This finding has important implications for LE calculations in small populations. Further investigation is now needed to examine the impact of nursing homes in other areas, on other mortality measures, and in larger populations.
STUDY OBJECTIVE: The drive to tackle health inequalities at the local level has increased interest in mortality data for small populations. There is some concern that nursing homes may affect measures of mortality for small populations, but there has been little in depth analysis of this. DESIGN AND SETTING: Deaths between 1997 and 2001 and population figures from the GP register (Exeter) database and census 2001 were used to produce life expectancy (LE) figures for all electoral wards in West Sussex. The proportion of those dying within each ward that had been residents of nursing homes was calculated and the relation between these variables and deprivation investigated. RESULTS: There was a significant linear relation between nursing home deaths and LE (p<0.0001), which explained 36% of variation in LE between wards. Deprivation accounted for around 35% of the variation in LE (p<0.0001) but was not correlated with nursing home deaths (p> or =0.0982). Multiple linear regression shows that over 60% of the variation in LE at ward level can be explained by both nursing home deaths and deprivation (p<0.0001) and that the two variables explain similar proportions of this variation. The relation between LE and nursing home deaths within wards grouped by deprivation suggests that the impact of nursing homes is strongest in deprived wards. CONCLUSIONS: This finding has important implications for LE calculations in small populations. Further investigation is now needed to examine the impact of nursing homes in other areas, on other mortality measures, and in larger populations.