Age patterns of suicide: identification and characterization of European clusters and trends.
Relatively few studies have addressed age patterns of suicide using specifically designed and systematized approaches. Our main objective was to identify and characterize age patterns of suicide in Europe, both on cross-sectional and longitudinal perspectives, based on data comprising the two last decades of the 20th century. A second objective was to determine whether some analytical methods could be useful as complementary approaches to the traditional examination of age-specific rate curves. We identified and characterized four patterns: upward-sloping, convex, downward-sloping, and uniform. The first three reproduce patterns previously described, though we propose some modifications to the respective classification criteria. Longitudinally, pattern stability was found for most countries, but some notable exceptions were detected. From the computation of multiple-decrement life tables by European country, period, and gender, we derived cumulative distributions of age at death for suicide. The results indicate that this methodology is a useful tool, not only for describing and summarizing information, but, more importantly, for providing a better understanding of intrinsic features and complexities of the patterns. Finally, we discuss practical implications of the study in the context of previous theories linking age patterns of suicide to sociological and economic dimensions, and we raise a few questions and hypotheses to be addressed in future research.
da Veiga
Francisco Alte
FA
Suicide Research and Prevention Unit, Psychiatric Clinic, Coimbra University Hospitals, Portugal. fmaveiga@ci.uc.pt
Saraiva
Carlos Braz
CB
D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D016000:Cluster Analysis; D003431:Cross-Cultural Comparison; D003430:Cross-Sectional Studies; D005060:Europe; D005260:Female; D006801:Humans; D015993:Life Tables; D008297:Male; D008875:Middle Aged; D012737:Sex Factors; D013405:Suicide / Q000706:statistics & numerical data* / Q000639:trends