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The COVID-19 pandemic profoundly disrupted these determinants. We aimed to assess, using a comparative cross-sectional analysis of nationally representative National Health and Nutrition Examination Survey (NHANES) data, how social, psychosocial, and behavioral determinants of dysglycemia in US adults shifted before and after the COVID-19 pandemic, accounting for differences by sex, age, and disease stage, as well as statistical interactions between these factors and the pandemic period.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We conducted a comparative cross-sectional analysis of nationally representative data from the NHANES, comparing pre-pandemic (2017\u2013March 2020, n\u2009=\u20094,946) and post-pandemic (2021\u20132023, n\u2009=\u20092,820) periods, applying NHANES sampling weights to ensure population representativeness. Multivariable logistic regression examined associations between sociodemographic factors, depressive symptoms, lifestyle behaviors, and glycemic status. To explore potential pandemic-related effect modifications, we performed sex- and age-stratified analyzes and formally tested for interactions by including interaction terms between these determinants and the pandemic period in the models.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The age-adjusted prevalence of type 2 diabetes significantly decreased from 13.9% to 11.3% after the pandemic (P\u2009=\u20090.001), while the prevalence of prediabetes remained stable. Higher education consistently and significantly reduced the risk of type 2 diabetes (Pre-pandemic: OR 0.49,95%CI:0.33\u20130.73, P\u2009=\u20090.002; Pandemic: OR 0.44, 95% CI: 0.29\u20130.65, P\u2009=\u20090.004). Income effects varied by sex\u2014protective for women (OR 0.43, 95% CI: 0.27\u20130.71, P\u2009=\u20090.010) but associated with a higher risk of prediabetes in men (OR 1.54, 95% CI: 1.13\u20132.08, P\u2009=\u20090.024). Depression showed stage-specific moderation: it significantly mitigated the risk-enhancing effects of behavioral factors on prediabetes (smoking, ROR 0.36, 95% CI: 0.16\u20130.83, P\u2009=\u20090.025; alcohol, ROR 0.75, 95% CI: 0.57\u20130.99, P\u2009=\u20090.048), but amplified these risk effects in type 2 diabetes (smoking, ROR 3.17, 95% CI: 1.32\u20137.61, P\u2009=\u20090.017; alcohol, ROR 4.79, 95% CI: 1.96\u201311.71, P\u2009=\u20090.002). The protective effect of high physical activity against prediabetes in young adults (20\u201339\u00a0years) observed pre-pandemic was attenuated post-pandemic. Longer sleep duration significantly protected men from prediabetes before the pandemic (OR 0.54, 95% CI: 0.37\u20130.79, P\u2009=\u20090.005), with no effect observed in women (OR 0.98, 95% CI: 0.68\u20131.40). Dietary inflammatory potential (DII) emerged as a significant risk factor for type 2 diabetes among young adults during the pandemic (OR 2.10, 95% CI: 1.36\u20133.26, P\u2009=\u20090.009).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The COVID-19 pandemic coincided with changes in risk patterns for prediabetes and type 2 diabetes that were highly specific to sex, age, and disease stage. These findings underscore the importance of incorporating psychosocial and behavioral determinants into diabetes surveillance and prevention strategies in the post-pandemic era.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s13098-026-02100-8","type":"journal-article","created":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T05:25:00Z","timestamp":1769837100000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Social, psychosocial, and lifestyle determinants of diabetes and prediabetes in US adults before and after COVID-19: a cross-sectional NHANES analysis"],"prefix":"10.1186","volume":"18","author":[{"given":"Yuan","family":"Zhao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dongyu","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiacheng","family":"Cheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huili","family":"Cao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaojuan","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junhua","family":"He","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yikun","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jin","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,1,31]]},"reference":[{"key":"2100_CR1","doi-asserted-by":"publisher","DOI":"10.3389\/fpubh.2025.1515797","author":"X Huang","year":"2025","unstructured":"Huang X, Wu Y, Ni Y, Xu H, He Y. 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