2024
DOI: 10.1002/pcn5.188
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Suicide mortality rates in Japan before and beyond the COVID‐19 pandemic era

Motohiro Okada,
Ryusuke Matsumoto,
Eishi Motomura

Abstract: Statistical analyses from Japan reported increasing suicides in 2020, first in the world, proving the severity of the public health crisis during the COVID‐19 pandemic; however, so far, international suicides have not been shown to be objectively increasing at population level. Followed studies reported the existence of a substantial heterogeneity of suicides among subgroups and time‐lag impacts. Against public health crisis in Japan, policymakers, psychiatrists and public health personnel should prioritize im… Show more

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Cited by 3 publications
(9 citation statements)
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“…Contrary to our expectations, we did not detect any decreasing SMRs with the end of the pandemic. Therefore, the temporal fluctuation patterns of the SMRs of males younger than 30 and all females were similar to the results of previous reports that analyzed fluctuations from 2009 to 2022 using joinpoint regression analysis [14,15,39]; however, the non-significantly but sharply (transiently) increasing SMRs of working-age males in early 2022 possibly contributed to the tendency of previous reports to underestimate the decrease in SMRs in late 2022 [14,15,39].…”
Section: Discussionsupporting
confidence: 88%
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“…Contrary to our expectations, we did not detect any decreasing SMRs with the end of the pandemic. Therefore, the temporal fluctuation patterns of the SMRs of males younger than 30 and all females were similar to the results of previous reports that analyzed fluctuations from 2009 to 2022 using joinpoint regression analysis [14,15,39]; however, the non-significantly but sharply (transiently) increasing SMRs of working-age males in early 2022 possibly contributed to the tendency of previous reports to underestimate the decrease in SMRs in late 2022 [14,15,39].…”
Section: Discussionsupporting
confidence: 88%
“…Interrupted time series analysis can incorporate various options, including parametric/non-parametric regressions, seasonal variation and panel data analyses [15,[54][55][56], but it cannot detect unknown joinpoints (changing trends periods) during observation periods. Indeed, previous reports have suggested, when the intervention is set at the COVID-19 pandemic outbreak alone, interrupted time series analysis tends to overestimate the positive impacts of the pandemic outbreak on SMRs due to the attenuation of decreasing trends of male SMRs before the pandemic (in the late 2010s) [15,23,39,41]. In contrast, joinpoint regression analysis has been evaluated to be an appropriate statistical method, which can detect unknown joinpoints, where trends change via fitting the simplest joinpoint model that the trend data allow [57,58].…”
Section: Statistical Analysesmentioning
confidence: 99%
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