Department of Basic Psychological Research, School of Psychology, University of Vienna, Vienna, Austria.
PLoS One. 2011 Feb 24;6(2):e17413. doi: 10.1371/journal.pone.0017413.
Seasonality of suicides is well-known and nearly ubiquitous, but recent evidence showed inconsistent patterns of decreasing or increasing seasonality in different countries. Furthermore, strength of seasonality was hypothesized to be associated with suicide prevalence. This study aimed at pointing out methodological difficulties in examining changes in suicide seasonality. METHODODOLOGY/PRINCIPAL FINDINGS: The present study examines the hypothesis of decreasing seasonality with a superior method that allows continuous modeling of seasonality. Suicides in Austria (1970-2008, N = 67,741) were analyzed with complex demodulation, a local (point-in-time specific) version of harmonic analysis. This avoids the need to arbitrarily split the time series, as is common practice in the field of suicide seasonality research, and facilitates incorporating the association with suicide prevalence. Regression models were used to assess time trends and association of amplitude and absolute suicide numbers. Results showed that strength of seasonality was associated with absolute suicide numbers, and that strength of seasonality was stable during the study period when this association was taken into account.
CONCLUSION/SIGNIFICANCE: Continuous modeling of suicide seasonality with complex demodulation avoids spurious findings that can result when time series are segmented and analyzed piecewise or when the association with suicide prevalence is disregarded.
自杀的季节性是众所周知且普遍存在的，但最近的证据表明，不同国家的季节性变化模式不一致。此外，季节性的强度被假设与自杀率有关。本研究旨在指出检查自杀季节性变化时存在的方法学困难。
方法/主要发现：本研究通过一种允许连续建模季节性的优越方法来检验季节性减弱的假设。使用复杂解调（局部（特定时间点）谐波分析版本）分析了奥地利 1970-2008 年（N=67741）的自杀数据。这避免了像自杀季节性研究领域中常见的那样，需要任意分割时间序列的需要，并便于将与自杀率的关联纳入其中。使用回归模型评估时间趋势和振幅与绝对自杀人数的关联。结果表明，季节性的强度与绝对自杀人数有关，并且当考虑到这种关联时，季节性的强度在研究期间是稳定的。
结论/意义：使用复杂解调对自杀季节性进行连续建模可以避免分段和分段分析时间序列或忽略与自杀率的关联时可能导致的虚假发现。
