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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...

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Autores principales: Imaizumi, Takahiro, Toda, Takuya, Maekawa, Michitaka, Sakurai, Daisuke, Hagiwara, Yuta, Yoshida, Yasuko, Ando, Masahiko, Maruyama, Shoichi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
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.
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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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