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How Sleep Quality Relates to Bodily and Oral Symptoms: An Analysis from Japanese National Statistics

Background: Sleep is one of the most important health-related factors. This cross-sectional study focused on sleep quality relates to systemic symptoms, including dental symptoms. Methods: Resource data were compiled from 7995 men and women aged 30 to 69 years, which is the core of the Japanese work...

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Detalles Bibliográficos
Autores principales: Yokoi, Yasuno, Komatsuzaki, Akira
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9690173/
https://www.ncbi.nlm.nih.gov/pubmed/36421622
http://dx.doi.org/10.3390/healthcare10112298
Descripción
Sumario:Background: Sleep is one of the most important health-related factors. This cross-sectional study focused on sleep quality relates to systemic symptoms, including dental symptoms. Methods: Resource data were compiled from 7995 men and women aged 30 to 69 years, which is the core of the Japanese working population. The subjects were divided into four groups based on their answers to two questions, one on sleep time and one on sleep sufficiency, and groups were compared with other items in the questionnaire by means of a contingency table analysis (χ(2) test). Results: Relationships were found between the sleep groups and basic attributes, the presence of subjective symptoms, and the presence of hospital visits. The items with significant relationships included 14 symptoms, such as lower back pain (p < 0.01) and four diseases, including high blood pressure (p < 0.01). A multinomial logistic regression was conducted with the sleep groups as objective variables. In the poor sleep group, significant odds ratios were found for four items, including hours of work (odds ratio: 2.53) and feeling listless (2.01). Conclusions: The results allowed multiple symptoms and diseases related to sleep quality to be identified, and different trends in the response rates of the groups were found. These results suggest that the useful classification of sleep quality groups according to health problems contributes to understanding the effects of different symptoms.