{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T17:28:17Z","timestamp":1777915697747,"version":"3.51.4"},"reference-count":49,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2023,1,17]],"date-time":"2023-01-17T00:00:00Z","timestamp":1673913600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"University of North Florida Faculty Development Grant"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Nutr Health"],"published-print":{"date-parts":[[2026,3]]},"abstract":"<jats:p>\n                    <jats:bold>Background:<\/jats:bold>\n                    Important changes in lifestyle habits, especially diet, typically occur during the transitional period between high school and college and some of these changes may increase the risk of inflammation.\n                    <jats:bold>Aim:<\/jats:bold>\n                    The purpose of this study was to investigate the relationship between lifestyle factors and inflammation in college students.\n                    <jats:bold>Methods:<\/jats:bold>\n                    Students enrolled in a southeastern university participated in this cross-sectional study. Participants completed online questionnaires for assessment of demographics, supplement and dietary intake, sleep quality, and perceived stress. Body composition was measured during a clinic visit via air displacement plethysmography and blood and urine were collected for measurement of C-reactive protein (CRP) and cortisol, respectively. Analysis of variance was used to examine associations between tertiles of CRP levels and lifestyle variables and a linear regression model was fit to investigate whether there were any significant predictors of CRP levels.\n                    <jats:bold>Results:<\/jats:bold>\n                    Analysis included data for 83 participants for whom serum CRP levels and diet intake were available. Approximately 68% of the participants were female; mean age and body mass index (BMI) were 24 years and 23.4\u2005kg\/m\n                    <jats:sup>2<\/jats:sup>\n                    , respectively. Alcohol intake was significantly associated with increasing CRP levels (\n                    <jats:italic toggle=\"yes\">P<\/jats:italic>\n                    = 0.017). No other dietary variables or lifestyle characteristics such as sleep quality, perceived stress, or BMI were associated with tertiles of CRP. The best model to predict CRP levels included urinary cortisol, aerobic exercise duration, alcohol, and vitamin E intake (\n                    <jats:italic toggle=\"yes\">\n                      adjusted R\n                      <jats:sup>2<\/jats:sup>\n                    <\/jats:italic>\n                    =0.27).\n                    <jats:bold>Conclusion:<\/jats:bold>\n                    Alcohol and vitamin E intake were found to be associated with increased CRP levels.\n                  <\/jats:p>","DOI":"10.1177\/02601060231151263","type":"journal-article","created":{"date-parts":[[2023,1,18]],"date-time":"2023-01-18T01:55:25Z","timestamp":1674006925000},"page":"515-523","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["The relationship between diet, exercise, and inflammation in college students: A cross-sectional study"],"prefix":"10.1177","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9017-8624","authenticated-orcid":false,"given":"Andrea Y.","family":"Arikawa","sequence":"first","affiliation":[{"name":"University of North Florida"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Diane","family":"Kraft","sequence":"additional","affiliation":[{"name":"University of North Florida"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michel","family":"Harris","sequence":"additional","affiliation":[{"name":"University of North Florida"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Doreen","family":"Perez","sequence":"additional","affiliation":[{"name":"University of North Florida"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michele","family":"Bednarzyk","sequence":"additional","affiliation":[{"name":"University of North Florida"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jenifer M.","family":"Ross","sequence":"additional","affiliation":[{"name":"University of North Florida"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2023,1,17]]},"reference":[{"key":"e_1_3_3_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.chb.2017.12.010"},{"key":"e_1_3_3_3_1","doi-asserted-by":"publisher","DOI":"10.12816\/0035081"},{"key":"e_1_3_3_4_1","doi-asserted-by":"publisher","DOI":"10.3390\/nu12082389"},{"key":"e_1_3_3_5_1","doi-asserted-by":"publisher","DOI":"10.1177\/1099800420958068"},{"key":"e_1_3_3_6_1","doi-asserted-by":"publisher","DOI":"10.1177\/20587392211000884"},{"key":"e_1_3_3_7_1","doi-asserted-by":"publisher","DOI":"10.1080\/19390211.2022.2134532"},{"key":"e_1_3_3_8_1","doi-asserted-by":"publisher","DOI":"10.1002\/jcp.26791"},{"key":"e_1_3_3_9_1","doi-asserted-by":"publisher","DOI":"10.1080\/07448481.2018.1431910"},{"key":"e_1_3_3_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/0165-1781(89)90047-4"},{"key":"e_1_3_3_11_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1600-0447.2012.01892.x"},{"key":"e_1_3_3_12_1","doi-asserted-by":"publisher","DOI":"10.1111\/obr.12003"},{"key":"e_1_3_3_13_1","unstructured":"Cirelli C (2021) Insufficient sleep: Definition epidemiology and adverse outcomes. 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