Evidence map›Paper›PMID 30796118›Full record

ArticleBMJ open2019

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.

Kei Nakajima, Taizo Iwane, Ryoko Higuchi, Michi Shibata, Kento Takada, Jun Uda, Mami Anan, Michiko Sugiyama, Teiji Nakamura

Abstract read
In one paragraph

Article in BMJ open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Kei NakajimaSchool of Nutrition and Dietetics, Faculty of Health and Social Services, Kanagawa University of Human Services, Yokosuka, Japan.
Taizo IwaneSchool of Nutrition and Dietetics, Faculty of Health and Social Services, Kanagawa University of Human Services, Yokosuka, Japan.
Ryoko HiguchiSchool of Nutrition and Dietetics, Faculty of Health and Social Services, Kanagawa University of Human Services, Yokosuka, Japan.
Michi ShibataSchool of Nutrition and Dietetics, Faculty of Health and Social Services, Kanagawa University of Human Services, Yokosuka, Japan.
Kento TakadaSchool of Nutrition and Dietetics, Faculty of Health and Social Services, Kanagawa University of Human Services, Yokosuka, Japan.
Jun UdaGraduate School of Health Care Sciences, Jikei Institute, Osaka-shi, Japan.
Mami AnanSchool of Nutrition and Dietetics, Faculty of Health and Social Services, Kanagawa University of Human Services, Yokosuka, Japan.
Michiko SugiyamaSchool of Nutrition and Dietetics, Faculty of Health and Social Services, Kanagawa University of Human Services, Yokosuka, Japan.
Teiji NakamuraSchool of Nutrition and Dietetics, Faculty of Health and Social Services, Kanagawa University of Human Services, Yokosuka, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe 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.

Indexed as

AgedCohort StudiesCross-Sectional StudiesDatabases, FactualDelivery of Health CareDiabetes Mellitus, Type 2FemaleHumansJapanMaleMass ScreeningMetabolic SyndromeMiddle AgedPhysical ExaminationSurveys and Questionnairesepidemiologygeneral medicine (see internal medicine)geriatric medicinepublic health

Identifiers

PMID30796118
PMCPMC6398776

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.