The Athens Insomnia Scale (AIS) can be regarded as a highly useful instrument in both clinical and research settings, except for when assessing the severity level. This study aims to determine the severity criteria for AIS by using the Insomnia Severity Index (ISI). A total of 1666 government employees aged 20 years or older were evaluated using the AIS and ISI, the Patient Health Questionnaire for depressive symptoms, the Epworth Sleepiness Scale for daytime sleepiness, and the Short Form Health Survey of the Medical Outcomes Study for health-related quality of life (QoL). A significant positive correlation (r) was found between the AIS and the ISI (r = 0.80, p < 0.001). As a result of describing receiver–operator curves, the severity criteria of the AIS are capable of categorizing insomnia severity as follows: absence of insomnia (0–5), mild insomnia (6–9), moderate insomnia (10–15), and severe insomnia (16–24). In addition, compared to all scales across groups categorized by AIS or ISI, it was revealed that similar results could be obtained (all p < 0.05). Therefore, the identification of the severity of AIS in this study is important in linking the findings of epidemiological studies with those of clinical studies.
Background: Examining the relationship between sleep and depression may be important for understanding the aetiology of affective disorders. Most studies that use electroencephalography (EEG) to objectively assess sleep have been conducted using polysomnography in the laboratory. Impaired sleep continuity, including prolonged sleep latency and changes in rapid eye movement (REM) sleep, have been reported to be associated with depression in clinical settings. Here, we aimed to use home EEG to analyse the association between sleep and depressive symptoms. Methods: We performed a cross-sectional epidemiological study in a large Japanese working population to identify the EEG parameters associated with depressive symptoms based on the results of a questionnaire survey and home EEG measurements using 1-channel (1-Ch) EEG. Results: The study included 650 Japanese patients (41.2% male, 44.7 ± 11.5 years) who underwent home EEG monitoring along with the Patient Health Questionnaire-9 (PHQ-9) to assess depressive symptoms. Logistic regression analysis revealed that depressive symptoms (PHQ-9 ≥ 10) were associated with sleep latency (odds ratio (OR) 1.02; 95% confidence interval (CI): 1.00–1.04) and REM latency (OR, 0.99; 95% CI: 0.99–1.00). Conclusions: Our results suggest that depressive symptoms are associated with prolonged sleep latency and reduced REM latency in a Japanese working population. The 1-Ch EEG may be a useful tool to monitor sleep and screen depression/depressive symptoms in non-clinical settings.
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