Care Need Index, Social Deprivation and Health. Epidemiological Studies in Swedish Health Care

Detta är en avhandling från Dept. of Community Medicine, Malmö University Hospital, S-205 02 Malmö, Sweden

Sammanfattning: Aims: To analyse the associations between health and neighbourhood social position, measured by a composite index (Care Need Index, CNI). Furthermore evaluate CNI in preparation for future analysis of its usefulness for allocating primary health care resources to deprived neighbourhoods. Methods: One fourth of the Swedish general practitioners ranked the impact of eight different variables: elderly, living alone, children under five, manual workers, unemployed people, single parents, overcrowding, foreign-born people from non-Western countries and highly mobile people, had on their workload. CNI, a composite index of these eight variables, was calculated on small area level for the whole of Sweden (n=8,519). The relation between CNI and different aspects of health was analysed. Statistical methods used were Poisson regression, Cox regression and hierarchical logistic regression. Results: Individuals living in deprived neighbourhoods had higher frequencies of death, both total and from coronary heart disease, and admissions to psychiatric and alcoholic clinics. There were also associations between socially disadvantaged neighbourhoods and self-reported poor health, self-reported long-term illness and mortality. With hierarchical logistic regression it was possible to demonstrate an influence of the neighbourhood on the residents' health by adjusting for variables such as age, gender, marital status, education/occupation, social network and lifestyle factors. Conclusions: CNI was able to identify socially deprived neighbourhoods with an increased need for health care and may therefore be a useful instrument for allocating resources to primary health care and psychiatric care to such neighbourhoods. The finding that neighbourhood social positions influence the residents' health is interesting, but further analyses are needed to better understand the association.

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