Socioeconomic correlates of mortality and hospital morbidity differentials by Local Government Area in Sydney 1985–1988

Abstract

Objective: To determine the magnitude of differentials in mortality and hospital morbidity by Local Government Area (LGA) in Sydney (1985–1988), and to correlate these with LGA indicators of socioeconomic status. Design: Cross-sectional group-based comparative study of mortality and hospital separations, and a group-based correlations analysis in relation to socioeconomic indicators. Outcome measures: Mortality—life expectancy at birth, infant mortality, 0- to 4-year mortality, age-standardised 15- to 64-year mortality (all-cause and various causes), sex-specific (except infant and 0- to 4-year mortality). Hospital morbidity rates—0- to 4-year hospital separations, age-standardised 15- to 64-year hospital separations (all-cause and various causes), sex-specific. Study factors: Census-derived LGA proportions of immigrants, Aborigines, professionals, unskilled workers, unemployed persons, those with a university degree and those having no qualifications, and the composite Ross Indicator. Results: Considerable differences in mortality and hospital morbidity by LGA in Sydney were found. Males had higher mortality and lower rates of hospital separation than females. LGA differentials were most obvious for adults, with little variation noted for infants or children. Most socioeconomic indicators were highly correlated with adult mortality and hospital morbidity in the expected direction, particularly indicators of low socioeconomic status. The unemployment rate, proportion Aboriginal, proportion unskilled, proportion unqualified, and the Ross Indicator were the most highly correlated variables. Conclusions: There are persistent differentials by LGA in mortality and hospital morbidity in Sydney which are strongly associated with socioeconomic status. The Ross Indicator was found to be a useful composite indicator. The high correlations of mortality and hospital morbidity with the unemployment rate raise the question of to what extent this is due to illness and premature mortality in the unemployed. Monitoring of health status differentials needs to continue if progress towards Health For All targets is to be evaluated.