{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T04:11:00Z","timestamp":1770696660849,"version":"3.49.0"},"reference-count":22,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T00:00:00Z","timestamp":1770595200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Cross-ministerial Strategic Innovation Promotion Program","award":["JPJ012425"],"award-info":[{"award-number":["JPJ012425"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Bioengineering"],"abstract":"<jats:p>Background: Specific health checkups in Japan aim to prevent and detect non-communicable diseases (NCDs). Lifestyle information and non-invasive measurements obtained during these checkups are valuable for population health monitoring. This study aimed to develop a predictive model for type 2 diabetes mellitus (T2DM) using only non-invasive measurements and to identify key predictors. Methods: A retrospective observational study was conducted using linked health checkup records and medical claims from a city in Japan. Logistic regression was performed to predict a T2DM diagnosis. Results: A total of 409 of the 1363 participants were diagnosed with T2DM, including 285 of the 950 participants aged 40\u201374 years and 124 of the 413 participants aged \u226575 years. The model achieved an area under the receiver operating characteristic curve of 0.680 for those aged 40\u201374 years and 0.665 for those aged \u226575 years, indicating moderate discrimination. Key predictors included male sex, use of antihypertensive drugs, walking speed, and eating habits within 2 h before bedtime. In particular, male sex, having a slower walking speed, and not eating within 2 h before bedtime were positively associated with T2DM diagnosis. Conversely, the absence of antihypertensive or lipid-lowering medications was negatively associated with T2DM diagnosis. Conclusion: A model based solely on non-invasive measurements moderately identified individuals at risk for T2DM in this community-based Japanese population. Routinely collected health checkup data may support early identification and targeted preventive strategies.<\/jats:p>","DOI":"10.3390\/bioengineering13020194","type":"journal-article","created":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T09:41:02Z","timestamp":1770630062000},"page":"194","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Development of a Type 2 Diabetes Prediction Model Using Specific Health Checkup Data and Extraction of Predictive Factors"],"prefix":"10.3390","volume":"13","author":[{"given":"Kenichiro","family":"Shimai","sequence":"first","affiliation":[{"name":"Faculty of Health Care Sciences, Department of Clinical Engineering, Jikei University of Health Care Sciences, Yodogawa-ku, Osaka 532-0003, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3779-3628","authenticated-orcid":false,"given":"Kazuki","family":"Ohashi","sequence":"additional","affiliation":[{"name":"Faculty of Health Sciences, Hokkaido University, N12-W5, Kita-ku, Sapporo 060-0812, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1030-2788","authenticated-orcid":false,"given":"Teppei","family":"Suzuki","sequence":"additional","affiliation":[{"name":"Faculty of Health Sciences, Hokkaido University, N12-W5, Kita-ku, Sapporo 060-0812, Japan"},{"name":"Faculty of Education, Hokkaido University of Education, Iwamizawa Campus, Midorigaoka, Iwamizawa 068-0835, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ryota","family":"Konno","sequence":"additional","affiliation":[{"name":"Graduate School of Health Sciences, Hokkaido University, N12-W5, Kita-ku, Sapporo 060-0812, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-9577-5352","authenticated-orcid":false,"given":"Ryuichiro","family":"Ueda","sequence":"additional","affiliation":[{"name":"Faculty of Health Sciences, Hokkaido University, N12-W5, Kita-ku, Sapporo 060-0812, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6315-6078","authenticated-orcid":false,"given":"Masami","family":"Mukai","sequence":"additional","affiliation":[{"name":"Division of Medical Informatics, National Cancer Center Hospital, 5-1-1, Tsukiji, Chuo-ku, Tokyo 104-0045, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5474-7861","authenticated-orcid":false,"given":"Katsuhiko","family":"Ogasawara","sequence":"additional","affiliation":[{"name":"Faculty of Health Sciences, Hokkaido University, N12-W5, Kita-ku, Sapporo 060-0812, Japan"},{"name":"Faculty of Engineering, Muroran Institute of Technology, Mizumoto-cho, Muroran 050-8585, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,2,9]]},"reference":[{"key":"ref_1","unstructured":"International Diabetes Federation (2024). 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Big Data"}],"container-title":["Bioengineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2306-5354\/13\/2\/194\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T10:22:29Z","timestamp":1770632549000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2306-5354\/13\/2\/194"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2,9]]},"references-count":22,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2026,2]]}},"alternative-id":["bioengineering13020194"],"URL":"https:\/\/doi.org\/10.3390\/bioengineering13020194","relation":{},"ISSN":["2306-5354"],"issn-type":[{"value":"2306-5354","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2,9]]}}}