Social integration and mortality in Australia.
OBJECTIVE
To investigate the relationship between social integration and mortality at the aggregate level of analysis.


METHODS
The data were compiled from several Australian Bureau of Statistics documents. The unit of analysis was State (Territory)-year. The multivariate regression analysis included data from all States and the Australian Capital Territory for 1990-96. Five indicators of social integration--percentage of people living alone; divorce rate; unemployment rate; proportion of people who are discouraged job seekers; and unionization rate--were used as predictors of nine measures of mortality.


RESULTS
Higher levels of social integration, as measured by all indicators except unionization, were associated with lower mortality rates. In the case of unionization, higher levels were associated with increased mortality rates.


CONCLUSIONS
Studies concerning the relationship between social integration and health should investigate the 'type' and 'level' of social integration that is conducive to better health.


CONCLUSIONS
To help reduce disparities in health and mortality across communities, public health researchers and policy makers need to closely monitor geographic and temporal trends in social integration measures. Social policies that emphasise investment in social integration or social capital through job creation and training, provision of gainful employment and social services for discouraged and marginalized workers, improved work conditions and social support may lower mortality directly or through their beneficial effects on health-promoting behaviours such as reduced levels of smoking, drinking and physical inactivity.
Siahpush
M
M
Faculty of Humanities and Social Sciences, La Trobe University, Victoria. M.Siahpush@aw.latrobe.edu.au
Singh
G K
GK
D001315:Australia; D002423:Cause of Death; D005163:Factor Analysis, Statistical; D006801:Humans; D008297:Male; D009026:Mortality / Q000639:trends*; D015999:Multivariate Analysis; D012042:Registries; D012044:Regression Analysis; D012307:Risk Factors; D012933:Social Identification; D012959:Socioeconomic Factors