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Aspetti psicosociali delle condotte suicidarie in Italia. Un'analisi trasversale e multivariata su dati aggregati

Published online by Cambridge University Press:  07 August 2014

Paolo Crepet*
Affiliation:
Unità Operativa CNR, Progetto FATMA, Sottoprogetto «Stress», Dipartimento di Psicologia, Università di Trieste, Trieste
Rocco Micciolo
Affiliation:
Istituto di Statistica e Ricerca Operativa, Università di Trento, Trento
*
Indirizzo per la corrispondenza: Dr. P. Crepet, Via della Gensola 38, 00153 Roma. Fax ( + 39) 06-583.6736.

Summary

Objective - To analyse suicide trends in Italy and to correlate suicide rates with psychosocial indicators. Design - Cross-sectional analysis of aggregate data at national level (1960-1990). Setting - Italy. Main outcome measures - Mortality rates (deaths for suicide, mental disorders and homicide), hospital admission rates (for schizophrenia, neurosis and affective psychosis), unemployment rates, alcohol consumption. Principal components of the correlation matrix calculated on the psychosocial indicators. Results - The study indicates that a slight increate in suicide rates has been recorded among males (+10,7%) but not among females. The regions with the highest suicide rate are the Northern ones (up to twice the national average). The age groups with the highest suicide risk are those over 70 years. In females and males over 65 between 1974 and 1989 the suicide rate rose by 70% and 77% respectively. Between 1978 and 1989, the suicide rate among the people in search of a first job rose by 25%, among the employed it rose by 35%, while among the people in search of a new job it rose by 594%. Correlation between admission and suicide rates shows negative figure both for affective psychosis and neurosis, wherelse the correlation with schizophrenia is positive. The correlation with death both by mental disorders and homicide is positive. The correlation with death both by mental disorders and homicide is positive. The correlation between suicide and alcohol consumption is negative, while that with unemployment is positive. Principal components analysis showed a first component, wich explained more then 60% of the general variation, highly correlated with suicide rates.

Type
Articoli
Copyright
Copyright © Cambridge University Press 1993

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References

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