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Kanagawa Investigation of the Total Check-up Data from the National database (KITCHEN): protocol for data-driven population-based repeated cross-sectional and 6-year cohort studies
INTRODUCTION: The unmitigated incidence of cardiometabolic diseases, such as type 2 diabetes and metabolic syndrome, has gained attention in Japan. ‘Big data’ can be useful to clarify conflicting observations obtained from studies with small samples and about rare conditions that are often neglected...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6398776/ https://www.ncbi.nlm.nih.gov/pubmed/30796118 http://dx.doi.org/10.1136/bmjopen-2018-023323 |
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author | Nakajima, Kei Iwane, Taizo Higuchi, Ryoko Shibata, Michi Takada, Kento Uda, Jun Anan, Mami Sugiyama, Michiko Nakamura, Teiji |
author_facet | Nakajima, Kei Iwane, Taizo Higuchi, Ryoko Shibata, Michi Takada, Kento Uda, Jun Anan, Mami Sugiyama, Michiko Nakamura, Teiji |
author_sort | Nakajima, Kei |
collection | PubMed |
description | INTRODUCTION: The unmitigated incidence of cardiometabolic diseases, such as type 2 diabetes and metabolic syndrome, has gained attention in Japan. ‘Big data’ can be useful to clarify conflicting observations obtained from studies with small samples and about rare conditions that are often neglected. We epidemiologically address these issues using data from health check-ups conducted in Kanagawa Prefecture, the prefecture with the second largest population in Japan, in the Kanagawa Investigation of the Total Check-up Data from the National Database (KITCHEN). METHODS AND ANALYSIS: This research consists of a series of population-based cross-sectional studies repeated from 2008–2014 and 6-year cohort studies. Since 2017, we have reviewed the data of people living in Kanagawa Prefecture who underwent a health check-up mainly for general health and the prevention of metabolic syndrome. The sample size ranges from 1.2 million to 1.8 million people in the cross-sectional studies and from 370 000 to 590 000 people in the cohort studies. These are people aged 40–74 years, whose clinical parameters were measured and who responded individually to a questionnaire. We investigate potential associations and causalities of various aetiologies, including diabetes and metabolic syndrome, using clinical data and lifestyle information. With multidisciplinary analysis, including data-driven analysis, we expect to obtain a wide range of novel findings, to confirm indeterminate previous findings, especially in terms of cardiometabolic disease, and to provide new perspectives for human health promotion and disease prevention. ETHICS AND DISSEMINATION: Ethical approval was received from the Ethics Committee of Kanagawa University of Human Services (10-43). The protocol was approved in December 2016 by the Japanese Ministry of Health, Labour and Welfare (No. 121). The study results will be disseminated through open platforms including journal articles, relevant conferences and seminar presentations. |
format | Online Article Text |
id | pubmed-6398776 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-63987762019-03-20 Kanagawa Investigation of the Total Check-up Data from the National database (KITCHEN): protocol for data-driven population-based repeated cross-sectional and 6-year cohort studies Nakajima, Kei Iwane, Taizo Higuchi, Ryoko Shibata, Michi Takada, Kento Uda, Jun Anan, Mami Sugiyama, Michiko Nakamura, Teiji BMJ Open Epidemiology INTRODUCTION: The unmitigated incidence of cardiometabolic diseases, such as type 2 diabetes and metabolic syndrome, has gained attention in Japan. ‘Big data’ can be useful to clarify conflicting observations obtained from studies with small samples and about rare conditions that are often neglected. We epidemiologically address these issues using data from health check-ups conducted in Kanagawa Prefecture, the prefecture with the second largest population in Japan, in the Kanagawa Investigation of the Total Check-up Data from the National Database (KITCHEN). METHODS AND ANALYSIS: This research consists of a series of population-based cross-sectional studies repeated from 2008–2014 and 6-year cohort studies. Since 2017, we have reviewed the data of people living in Kanagawa Prefecture who underwent a health check-up mainly for general health and the prevention of metabolic syndrome. The sample size ranges from 1.2 million to 1.8 million people in the cross-sectional studies and from 370 000 to 590 000 people in the cohort studies. These are people aged 40–74 years, whose clinical parameters were measured and who responded individually to a questionnaire. We investigate potential associations and causalities of various aetiologies, including diabetes and metabolic syndrome, using clinical data and lifestyle information. With multidisciplinary analysis, including data-driven analysis, we expect to obtain a wide range of novel findings, to confirm indeterminate previous findings, especially in terms of cardiometabolic disease, and to provide new perspectives for human health promotion and disease prevention. ETHICS AND DISSEMINATION: Ethical approval was received from the Ethics Committee of Kanagawa University of Human Services (10-43). The protocol was approved in December 2016 by the Japanese Ministry of Health, Labour and Welfare (No. 121). The study results will be disseminated through open platforms including journal articles, relevant conferences and seminar presentations. BMJ Publishing Group 2019-02-21 /pmc/articles/PMC6398776/ /pubmed/30796118 http://dx.doi.org/10.1136/bmjopen-2018-023323 Text en © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/. |
spellingShingle | Epidemiology Nakajima, Kei Iwane, Taizo Higuchi, Ryoko Shibata, Michi Takada, Kento Uda, Jun Anan, Mami Sugiyama, Michiko Nakamura, Teiji Kanagawa Investigation of the Total Check-up Data from the National database (KITCHEN): protocol for data-driven population-based repeated cross-sectional and 6-year cohort studies |
title | Kanagawa Investigation of the Total Check-up Data from the National database (KITCHEN): protocol for data-driven population-based repeated cross-sectional and 6-year cohort studies |
title_full | Kanagawa Investigation of the Total Check-up Data from the National database (KITCHEN): protocol for data-driven population-based repeated cross-sectional and 6-year cohort studies |
title_fullStr | Kanagawa Investigation of the Total Check-up Data from the National database (KITCHEN): protocol for data-driven population-based repeated cross-sectional and 6-year cohort studies |
title_full_unstemmed | Kanagawa Investigation of the Total Check-up Data from the National database (KITCHEN): protocol for data-driven population-based repeated cross-sectional and 6-year cohort studies |
title_short | Kanagawa Investigation of the Total Check-up Data from the National database (KITCHEN): protocol for data-driven population-based repeated cross-sectional and 6-year cohort studies |
title_sort | kanagawa investigation of the total check-up data from the national database (kitchen): protocol for data-driven population-based repeated cross-sectional and 6-year cohort studies |
topic | Epidemiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6398776/ https://www.ncbi.nlm.nih.gov/pubmed/30796118 http://dx.doi.org/10.1136/bmjopen-2018-023323 |
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