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Identifying high-risk population of depression: association between metabolic syndrome and depression using a health checkup and claims database
Depression and metabolic syndrome (MetS) are correlated, leading to an increased healthcare burden and decreased productivity. We aimed to investigate the association between MetS-related factors and depression using a health checkup and claims database. Individuals aged 18–75 years who underwent he...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9633757/ https://www.ncbi.nlm.nih.gov/pubmed/36329095 http://dx.doi.org/10.1038/s41598-022-22048-9 |
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author | Imaizumi, Takahiro Toda, Takuya Maekawa, Michitaka Sakurai, Daisuke Hagiwara, Yuta Yoshida, Yasuko Ando, Masahiko Maruyama, Shoichi |
author_facet | Imaizumi, Takahiro Toda, Takuya Maekawa, Michitaka Sakurai, Daisuke Hagiwara, Yuta Yoshida, Yasuko Ando, Masahiko Maruyama, Shoichi |
author_sort | Imaizumi, Takahiro |
collection | PubMed |
description | Depression and metabolic syndrome (MetS) are correlated, leading to an increased healthcare burden and decreased productivity. We aimed to investigate the association between MetS-related factors and depression using a health checkup and claims database. Individuals aged 18–75 years who underwent health examinations between 2014 and 2019 were enrolled in the study. Among 76,277 participants, “ever” and “incident” antidepressant users exhibited worse metabolic profiles and were more likely to be prescribed hypnotics and anxiolytics than “never” users. In a nested case–control study with a 1:10 ratio of incident users to controls, MetS was associated with incident antidepressant use (odds ratio, 1.53 [95% confidence interval 1.24–1.88]) adjusted for lifestyle information obtained from a self-administered questionnaire, medical history, and medications. Other metabolic traits also showed significant associations: body mass index (1.04 [1.02–1.06]), abdominal circumference per 10 cm (1.17 [1.08–1.27]), high blood pressure (1.17 [1.00–1.37]), glucose intolerance (1.29 [1.05–1.58]), and dyslipidemia (1.27 [1.08–1.51]). A bodyweight increase > 10 kg from age 20 years (1.46 [1.25–1.70]) was also significantly associated with incident antidepressant use. In conclusion, metabolic abnormalities were associated with incident antidepressant use and can be useful in identifying populations at high risk of depression. |
format | Online Article Text |
id | pubmed-9633757 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-96337572022-11-05 Identifying high-risk population of depression: association between metabolic syndrome and depression using a health checkup and claims database Imaizumi, Takahiro Toda, Takuya Maekawa, Michitaka Sakurai, Daisuke Hagiwara, Yuta Yoshida, Yasuko Ando, Masahiko Maruyama, Shoichi Sci Rep Article Depression and metabolic syndrome (MetS) are correlated, leading to an increased healthcare burden and decreased productivity. We aimed to investigate the association between MetS-related factors and depression using a health checkup and claims database. Individuals aged 18–75 years who underwent health examinations between 2014 and 2019 were enrolled in the study. Among 76,277 participants, “ever” and “incident” antidepressant users exhibited worse metabolic profiles and were more likely to be prescribed hypnotics and anxiolytics than “never” users. In a nested case–control study with a 1:10 ratio of incident users to controls, MetS was associated with incident antidepressant use (odds ratio, 1.53 [95% confidence interval 1.24–1.88]) adjusted for lifestyle information obtained from a self-administered questionnaire, medical history, and medications. Other metabolic traits also showed significant associations: body mass index (1.04 [1.02–1.06]), abdominal circumference per 10 cm (1.17 [1.08–1.27]), high blood pressure (1.17 [1.00–1.37]), glucose intolerance (1.29 [1.05–1.58]), and dyslipidemia (1.27 [1.08–1.51]). A bodyweight increase > 10 kg from age 20 years (1.46 [1.25–1.70]) was also significantly associated with incident antidepressant use. In conclusion, metabolic abnormalities were associated with incident antidepressant use and can be useful in identifying populations at high risk of depression. Nature Publishing Group UK 2022-11-03 /pmc/articles/PMC9633757/ /pubmed/36329095 http://dx.doi.org/10.1038/s41598-022-22048-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Imaizumi, Takahiro Toda, Takuya Maekawa, Michitaka Sakurai, Daisuke Hagiwara, Yuta Yoshida, Yasuko Ando, Masahiko Maruyama, Shoichi Identifying high-risk population of depression: association between metabolic syndrome and depression using a health checkup and claims database |
title | Identifying high-risk population of depression: association between metabolic syndrome and depression using a health checkup and claims database |
title_full | Identifying high-risk population of depression: association between metabolic syndrome and depression using a health checkup and claims database |
title_fullStr | Identifying high-risk population of depression: association between metabolic syndrome and depression using a health checkup and claims database |
title_full_unstemmed | Identifying high-risk population of depression: association between metabolic syndrome and depression using a health checkup and claims database |
title_short | Identifying high-risk population of depression: association between metabolic syndrome and depression using a health checkup and claims database |
title_sort | identifying high-risk population of depression: association between metabolic syndrome and depression using a health checkup and claims database |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9633757/ https://www.ncbi.nlm.nih.gov/pubmed/36329095 http://dx.doi.org/10.1038/s41598-022-22048-9 |
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