Gender differences in antidepressant use-related seasonality change in suicide mortality in Hungary, 1998–2006

Sebestyen, Beata; Rihmer, Zoltán; Bálint, Lajos; Szokontor, Nora; Gonda, Xénia; Gyarmati, Béla; Bödecs, Tamás; Sándor, János

doi:10.3109/15622970903397722

Cited by 24 publications

(32 citation statements)

References 39 publications

(68 reference statements)

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“…Internet search volume for the term “suicide” is lowest during the summer, the time where most studies report a peak in suicide deaths (Bjorksten et al, 2009; Reutfors et al, 2009; Sebestyen et al, 2009). The interpretation above explains this discrepancy between internet search activity and the seasonality of suicide.…”

Section: Discussionmentioning

confidence: 99%

Internet monitoring of suicide risk in the population

McCarthy

2010

Journal of Affective Disorders

142

102

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Background-Public health statistics are often released too late to affect reversible societal factors affecting suicide. Increasingly, internet search volume is used in epidemiology, but this method has not yet been applied to suicide. Results-Google search volumes correlated to CDC statistics for both suicide and self-injury, but in patterns that differed by age. Whereas internet search activity was negatively correlated to the suicide rate in the general population, it was positively correlated to both intentional self-injury and completed suicides among youth. Methods-GoogleConclusions-Monitoring changes in search volumes on the internet may provide an early indicator of suicide risk within the population. Furthermore, youth may utilize the internet in ways that differ from the general population with respect to suicide.

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Section: Discussionmentioning

confidence: 99%

Internet monitoring of suicide risk in the population

McCarthy

2010

Journal of Affective Disorders

142

102

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“…Though speculative, it may be that a sudden reduction in the duration of direct contact with a dependent represents a type of suicide risk in these women. Gender effect on seasonality of suicide was also noted in Hungary where a steadily increasing prescription rate for antidepressants was associated with a decrease in national suicide rate but significantly decreased seasonality of suicide only in males [70]. The suicide peak in spring has been considered to be a consequence of seasonal occurrence of depression-related suicides and the decreased seasonality of suicide in this Hungarian study was suggested to be a marker of lowering depression-related suicides (especially among men) as a result of increased antidepressant utilization in the population [70].…”

Section: Demographic Variablesmentioning

confidence: 98%

Seasonality of Suicidal Behavior

Woo

Okusaga

Postolache

2012

IJERPH

126

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A seasonal suicide peak in spring is highly replicated, but its specific cause is unknown. We reviewed the literature on suicide risk factors which can be associated with seasonal variation of suicide rates, assessing published articles from 1979 to 2011. Such risk factors include environmental determinants, including physical, chemical, and biological factors. We also summarized the influence of potential demographic and clinical characteristics such as age, gender, month of birth, socioeconomic status, methods of prior suicide attempt, and comorbid psychiatric and medical diseases. Comprehensive evaluation of risk factors which could be linked to the seasonal variation in suicide is important, not only to identify the major driving force for the seasonality of suicide, but also could lead to better suicide prevention in general.

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“…Winter months (from November till January) can be characterised by relatively more frequent negatively loaded tweets (November is especially outstanding). In the months of transition (February, September, October) negative tweets are relatively fewer (but their number 13 Some researchers investigating the relationship between suicides and antidepressants argue that taking medication could weaken or might even eliminate seasonality from suicide time series (Sebestyen et al, 2010). American data provide no support for this hypothesis, what is more, between 2012 and 2014 findings suggest even stronger seasonality effects.…”

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confidence: 99%