{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,14]],"date-time":"2025-10-14T11:17:39Z","timestamp":1760440659697,"version":"build-2065373602"},"reference-count":45,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2025,10,14]],"date-time":"2025-10-14T00:00:00Z","timestamp":1760400000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Japan Society for the Promotion of Science (JSPS) and SECOM Science and Technology Foundation","award":["20H01546","21H00739","23K20622"],"award-info":[{"award-number":["20H01546","21H00739","23K20622"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Nutrients"],"abstract":"<jats:p>Background: Occupational accidents, injuries, and illnesses are serious problems for organizations. Workplace sleepiness is a major issue that affects occupational safety and productivity. Workplace sleepiness is influenced by sleep, diet, and blood glucose levels, but the causal relationship is unclear. This scoping review aimed to investigate the factors affecting work productivity, with a particular focus on the impact of sleepiness caused by food intake and blood glucose level on productivity. Methods: PubMed, and Web of Science were used to search terms, such as \u201cworkplace,\u201d \u201csleepiness or postprandial hypoglycemia,\u201d \u201cproductivity,\u201d and \u201cmeasurement.\u201d The following studies were included: (1) those with working hours evaluations; (2) that excluded patients with diabetes, heart diseases, or other diseases; (3) that excluded patients with mental illness; (4) that did not limit the evaluation of sleepiness at work to sleep only; (5) with publications after 2014; and (6) that were research articles. Results: The search yielded 521 articles. Nine papers met the inclusion criteria. Six studies assessed blood glucose levels, six assessed sleepiness, and one simultaneously assessed blood glucose and sleepiness. The Karolinska Sleepiness Scale (KSS) is the most frequently used sleep measure. Most studies have assessed the effects of controlled diets. Although some studies have used continuous glucometers, their evaluation of blood glucose levels has been limited. The extracted literature also included mild exercise and control of environmental illumination as a countermeasure against sleepiness. Conclusions: Although few studies have analyzed the causes and countermeasures of sleepiness in the workplace, sleepiness affects work productivity, diet affects sleepiness, and several methods for suppressing sleepiness have been researched. However, a few studies have directly evaluated the effects of blood glucose fluctuations and sleepiness on work productivity. These results suggest that further research into the relationship between sleepiness at work and related biological signals and blood glucose fluctuations will be important in understanding the causes, as it will form the basis for measures to improve work productivity.<\/jats:p>","DOI":"10.3390\/nu17203217","type":"journal-article","created":{"date-parts":[[2025,10,14]],"date-time":"2025-10-14T10:37:14Z","timestamp":1760438234000},"page":"3217","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["The Influence of Food Intake and Blood Glucose on Postprandial Sleepiness and Work Productivity: A Scoping Review"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-7648-8764","authenticated-orcid":false,"given":"Hisashi","family":"Kaneda","sequence":"first","affiliation":[{"name":"Medical Data Science Lab, Hoshi University, Tokyo 142-0063, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Itsuki","family":"Kageyama","sequence":"additional","affiliation":[{"name":"Medical Data Science Lab, Hoshi University, Tokyo 142-0063, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1753-2970","authenticated-orcid":false,"given":"Yoshiyuki","family":"Kobayashi","sequence":"additional","affiliation":[{"name":"Medical Data Science Lab, Hoshi University, Tokyo 142-0063, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2360-2034","authenticated-orcid":false,"given":"Kota","family":"Kodama","sequence":"additional","affiliation":[{"name":"Medical Data Science Lab, Hoshi University, Tokyo 142-0063, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,10,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e24640","DOI":"10.1016\/j.heliyon.2024.e24640","article-title":"Enhancing labor productivity as a key strategy for fostering green economic growth and resource efficiency","volume":"10","author":"Yu","year":"2024","journal-title":"Heliyon"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1788","DOI":"10.1016\/j.matpr.2020.05.195","article-title":"Productivity improvement in manufacturing industry by lean tool","volume":"28","author":"Banga","year":"2020","journal-title":"Mater. 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