Seasonality in Attempted and Completed Suicide Using Emergency Department Data

The goal of this study was to fill gaps in the literature on the consistent and significant link between seasonality and suicide, specifically with regard to recent suicide attempts and deaths in the United States. To accurately determine current seasonality trends in attempted suicide in the US a large, representative, and up-to-date sample of emergency department cases was analyzed using 2006-2011 data from the Nationwide Emergency Department Sample (NEDS) database. Hypothesis 1 stated that there would be significant seasonal differences in attempted suicide and was supported, with spring and fall peaks. Hypothesis 2 stated that there would be significant seasonal differences in deaths by suicide and was supported, but unexpectedly there was only a summer peak in deaths by suicide, but no spring or fall peaks. Hypothesis 3 stated that there would be significant differences in weekday versus weekend suicide attempt rates, and indeed there were more attempts on weekdays versus weekends. Hypothesis 4 stated that there would be significant differences in weekday versus weekend deaths by suicide, but hypothesis 4 was not supported. Hypothesis 5 stated that the magnitude in seasonal year-to-year trends in attempted suicide would decrease over time, and was supported. Hypothesis 6 stated that the magnitude in seasonal year-to-year trends in deaths by suicide would decrease over time, and was partially supported. Hypothesis 7 stated that seasonality differences for attempted suicide would persist in spite of variance explained by a diagnosis of a bipolar or depressive disorder or by income quartile, and was supported. Hypothesis 8 stated that seasonality differences for deaths by suicide would persist in spite of variance explained by a diagnosis of a bipolar or depressive disorder or by income quartile, and was supported. In general, it can be confidently asserted that seasonal effects exist. Much less confidence is given, however, to the various explanations of the mechanisms behind these effects. Further, the magnitude of seasonal effects is small compared to other factors, such as diagnosis.