USING MORTALITY DATA TO DESCRIBE GEOGRAPHIC VARIATIONS IN HEALTH-STATUS AT SUB-DISTRICT LEVEL

Objective: To describe sub-district variations in health status, using mortality data that are processed locally. Design: A descriptive stud y of routinely collected death registration data, using multicause cod ing. Setting: The London Borough of Croydon, with a population of 319, 200 divided into 27 electoral wards. Subjects: Deaths of Croydon resid ents, registered with the Registrar of Births and Deaths, which occurr ed between January 1990 and December 1992 inclusive.Main outcome measu res: Variations in life expectancy, all-cause standardised mortality r atios (SMRs), and disease-specific mortality ratios between selected w ards. Deaths in nursing homes were excluded to avoid bias. Results: Da ta from 8,930 death registrations, of which 852 occurred in nursing ho mes, were analysed by electoral ward. The range for all-cause SMRs, in cluding nursing home deaths, was 153 (139-168) to 66 (58-75). When nur sing home deaths were excluded, the SMRs for two wards that were signi ficantly higher than the Cryodon average fell into the average range. The range, excluding nursing home deaths, was 133 (113-153) to 71 (62- 80). Life expectancy at birth varied from 79.8 years to 74.4 years, an d life expectancy at age 65 by three years between wards at the two en ds of the spectrum. The geographic distribution of ischaemic heart dis ease and diabetes showed significant differences. Conclusions: We cont end that death registration data are a useful tool for describing sub- district variations in health status. Deaths of nursing home residents are a source of bias and should be excluded from the analysis. Multic ause coding allows a more accurate description of geographic variation s in specific diseases, such as ischaemic heart disease and diabetes.