{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T15:26:06Z","timestamp":1789140366394,"version":"build-2803163510"},"reference-count":45,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T00:00:00Z","timestamp":1783641600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Musculoskeletal pain (MSP) is a leading cause of disability worldwide, yet evidence among young adults remains limited. University students face unique lifestyle risks, including prolonged sedentary study, poor sleep, and excessive screen use. This study aimed to estimate MSP prevalence and burden, compare lifestyle behaviors between students with and without pain, and identify independent predictors of pain occurrence and severity.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A cross-sectional web-based survey was conducted among students at Sichuan University, China. A structured lifestyle questionnaire assessed physical activity, diet, sedentary behavior, sleep, screen use, and pain burden across major body sites. Univariate and multivariate logistic regression were used to identified risk factors of MSP prevalence and pain burden.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      A total of 9,122 students participated (mean age 21.1 \u00b1 1.7 years; 44.5% female). MSP prevalence was 58.7%, with the neck (43.6%), back (37.1%), and shoulders (36.2%) most affected. Pain burden was considerable, with 22.6% reporting moderate and 18.5% severe pain. Multivariable analysis showed that female gender (\n                      <jats:italic>OR<\/jats:italic>\n                      = 1.99, 95% CI: 1.80\u20132.19), poor sleep (\n                      <jats:italic>OR<\/jats:italic>\n                      = 2.81, 95% CI: 2.26\u20133.49), poor diet (\n                      <jats:italic>OR<\/jats:italic>\n                      = 1.83, 95% CI: 1.59\u20132.10), high sedentary risk (\n                      <jats:italic>OR<\/jats:italic>\n                      = 1.33, 95% CI: 1.10\u20131.60), long screen duration (\n                      <jats:italic>OR<\/jats:italic>\n                      = 1.49, 95% CI: 1.31\u20131.69), and low physical activity (\n                      <jats:italic>OR<\/jats:italic>\n                      = 1.14, 95% CI: 1.02\u20131.27) were independent predictors of MSP prevalence. For pain burden, poor sleep (\n                      <jats:italic>OR<\/jats:italic>\n                      = 3.72, 95% CI: 2.86\u20134.83), poor diet (\n                      <jats:italic>OR<\/jats:italic>\n                      = 1.90, 95% CI: 1.66\u20132.18), high sedentary risk (\n                      <jats:italic>OR<\/jats:italic>\n                      = 1.68, 95% CI: 1.42\u20131.99), long screen duration (\n                      <jats:italic>OR<\/jats:italic>\n                      = 1.37, 95% CI: 1.20\u20131.55), low physical activity (\n                      <jats:italic>OR<\/jats:italic>\n                      = 1.04, 95% CI: 1.02\u20131.15), and female gender (\n                      <jats:italic>OR<\/jats:italic>\n                      = 1.90, 95% CI: 1.73\u20132.08) were the strongest predictors.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>MSP is highly prevalent among university students, with a substantial proportion experiencing moderate to severe burden. Lifestyle factors influence both pain occurrence and severity. Poor sleep, poor diet, sedentary behavior, long screen use and insufficient physical activity were consistently associated with higher risk. These findings highlight the need for multidomain but tailored interventions to reduce both prevalence and burden, supporting healthier long-term habits and effective campus health strategies.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpubh.2026.1831482","type":"journal-article","created":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T05:37:33Z","timestamp":1783661853000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Musculoskeletal pain in university students: lifestyle determinants of prevalence and burden"],"prefix":"10.3389","volume":"14","author":[{"given":"Yan","family":"Li","sequence":"first","affiliation":[{"name":"Sichuan University Hospital, Sichuan University","place":["Chengdu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juan","family":"Liang","sequence":"additional","affiliation":[{"name":"Sichuan University Hospital, Sichuan 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