The effect of macroeconomic variables on suicide.
BACKGROUND
There are a large number of factors mediating suicide. Many studies have searched for a direct causal relationship between economic hardship and suicide, however, findings have been varied.


METHODS
Suicide data was obtained from the Australian Bureau of Statistics for the period between January 1968 and August 2002. These were correlated with a suite of macroeconomic data including housing loan interest rates, unemployment rates, days lost to industrial disputes, Consumer Price Index, gross domestic product, and the Consumer Sentiment Index.


RESULTS
A total of 51845 males and 16327 females committed suicide between these dates. There were significant associations between suicide rates and eleven macroeconomic indicators for both genders in at least one age range. Data was divided into male and female and five age ranges and pooled ages. Analyses were conducted on these 132 datasets resulting in 80 significant findings. The data was generally stronger for indices measuring economic performance than indices measuring consumers' perceptions of the state of the economy. A striking difference between male and female trends was seen. Generally, male suicide rates increased with markers of economic adversity, while the opposite pattern was seen in females. There were significantly different patterns in age-stratified data, with for example higher housing loan interest rates having a positive association with suicide in younger people and a negative association in older age groups.


CONCLUSIONS
Macroeconomic trends are significantly associated with suicide. The patterns in males and females are very different, and there are further substantial age-related differences.
Berk
Michael
M
Department of Clinical and Biomedical Sciences - Barwon Health, University of Melbourne, Geelong, Victoria, Australia.
Dodd
Seetal
S
Henry
Margaret
M
D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D001315:Australia / Q000453:epidemiology; D002648:Child; D016000:Cluster Analysis; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D012737:Sex Factors; D012959:Socioeconomic Factors; D013405:Suicide / Q000191:economics* / Q000706:statistics & numerical data*; D013997:Time Factors; D014478:Unemployment / Q000706:statistics & numerical data*