{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T13:46:21Z","timestamp":1777556781932,"version":"3.51.4"},"reference-count":25,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T00:00:00Z","timestamp":1772409600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T00:00:00Z","timestamp":1772409600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["J Diabetes Sci Technol"],"abstract":"<jats:sec>\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>As type 2 diabetes mellitus (T2DM) becomes an increasingly urgent global health concern, interest has grown in how screen-based behaviors contribute to its risk. Excessive screen exposure is often associated with sedentary lifestyles, poor sleep quality, and circadian disruption\u2014all potential contributors to T2DM. Yet, how screen time interacts with specific sleep characteristics in shaping diabetes risk remains underexplored.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective:<\/jats:title>\n                    <jats:p>This study investigates the relationship between screen exposure and T2DM risk, with particular focus on sleep duration and diagnosed sleep disorders as potential effect modifiers. We also explored variation by age, sex, and racial\/ethnic groups.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>We analyzed data from 23\u2009023 US adults in the 2007 to 2016 National Health and Nutrition Examination Survey. Screen exposure was dichotomized using age-specific thresholds (\u22652 vs &lt;2 hours\/day for ages 3 to 18; \u22653 vs &lt;3 hours\/day for adults). Type 2 diabetes mellitus was defined by self-reported physician diagnosis. Sleep duration and diagnosed sleep disorders were examined as modifiers. Missing data were handled using multiple imputation by chained equations, and survey-weighted multinomial logistic regression was applied.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>High screen exposure was associated with increased odds of T2DM in fully adjusted models (odds ratio [OR] = 3.47, 95% confidence interval [CI]: 2.74, 4.36). Sleep duration was not independently associated with T2DM, whereas sleep disorders were linked to approximately twofold higher odds (OR = 2.21, 95% CI: 1.17, 4.18). The screen-T2DM association was stronger among females than males, with variation observed across sleep and racial\/ethnic subgroups.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>Excessive screen time is linked to elevated T2DM risk, particularly among females and individuals with sleep disorders. Longitudinal research is needed to assess causality and inform targeted interventions.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/19322968261426022","type":"journal-article","created":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T10:49:29Z","timestamp":1772448569000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Associations Between Screen Exposure, Multidimensional Sleep Indicators, and Type 2 Diabetes: A Cross-sectional Study Using US National Survey Data"],"prefix":"10.1177","author":[{"given":"Feng","family":"Zhai","sequence":"first","affiliation":[{"name":"Department of Otolaryngology, Shanghai Children\u2019s Medical Center, Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7324-7712","authenticated-orcid":false,"given":"Yanbo","family":"Li","sequence":"additional","affiliation":[{"name":"School of Population and Public Health, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2026,3,2]]},"reference":[{"key":"e_1_3_2_2_2","volume-title":"IDF Diabetes Atlas","author":"International Diabetes Federation","year":"2021","unstructured":"International Diabetes Federation. 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Accessed February 10 2026."},{"key":"e_1_3_2_10_2","unstructured":"CSEP Youth (Children and Youth 5\u201317 years); Canadian Society for Exercise Physiology. Canadian 24-hour movement guidelines for children and youth (ages 5\u201317): an integration of physical activity sedentary behaviour and sleep 2020. https:\/\/csepguidelines.ca\/guidelines\/children-youth\/. Accessed February 10 2026."},{"key":"e_1_3_2_11_2","unstructured":"CSEP Adults (18\u201364 years); Canadian Society for Exercise Physiology. Canadian 24-hour movement guidelines for adults aged 18\u201364 years: an integration of physical activity sedentary behaviour and sleep 2020. https:\/\/csepguidelines.ca\/guidelines\/adults-18-64\/. Accessed February 10 2026."},{"key":"e_1_3_2_12_2","unstructured":"CSEP Older Adults (65+ years); Canadian Society for Exercise Physiology. Canadian 24-hour movement guidelines for adults aged 65 years or older: an integration of physical activity sedentary behaviour and sleep 2020. https:\/\/csepguidelines.ca\/guidelines\/adults-65\/. Accessed February 10 2026."},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.b2393"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1002\/sim.4067"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1136\/archdischild-2016-312016"},{"key":"e_1_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.dsx.2020.07.014"},{"key":"e_1_3_2_17_2","doi-asserted-by":"publisher","DOI":"10.1089\/dia.2021.0090"},{"key":"e_1_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.1002\/dmrr.3395"},{"key":"e_1_3_2_19_2","doi-asserted-by":"publisher","DOI":"10.1001\/archpediatrics.2010.88"},{"key":"e_1_3_2_20_2","unstructured":"National Health Nutrition Examination Survey (NHANES). National Health and Nutrition Examination Survey (NHANES) 2024. https:\/\/www.cdc.gov\/nchs\/nhanes\/index.htm. 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