{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T07:00:32Z","timestamp":1784962832451,"version":"3.55.0"},"reference-count":36,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2026,7,24]],"date-time":"2026-07-24T00:00:00Z","timestamp":1784851200000},"content-version":"vor","delay-in-days":204,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100002383","name":"King Saud University","doi-asserted-by":"publisher","award":["ORF-2026-1094"],"award-info":[{"award-number":["ORF-2026-1094"]}],"id":[{"id":"10.13039\/501100002383","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Aging Research"],"published-print":{"date-parts":[[2026,1]]},"abstract":"<jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>To examine associations of demographic, behavioral, and clinical factors with physiological dysregulation across cardiometabolic, renal, and hepatic functions among United States (US) adults aged 45\u2009years and older using nationally representative data.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      This cross\u2010sectional study analyzed data from the National Health and Nutrition Examination Survey (NHANES) 2017\u2013March 2020 prepandemic cycle (weighted\n                      <jats:italic>N<\/jats:italic>\n                      \u2009\u2248\u200917,219,945; analytic\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u2009496). Eight biomarkers representing cardiometabolic (glucose, total cholesterol, and triglycerides), renal (serum creatinine and blood urea nitrogen), and hepatic (alanine aminotransferase, aspartate aminotransferase, and total bilirubin) functions were standardized using survey\u2010weighted\n                      <jats:italic>z<\/jats:italic>\n                      \u2010scores. They averaged with equal weighting to construct a physiological dysregulation index (PDI). Higher PDI scores indicate greater physiological dysregulation. Survey\u2010weighted multivariable linear regression models were used to examine associations between PDI and sociodemographic, behavioral, and clinical factors.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Female sex was associated with significantly lower physiological dysregulation compared with male sex (\n                      <jats:italic>\u03b2<\/jats:italic>\n                      \u2009=\u2009\u22120.302, SE\u2009=\u20090.066,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001). Physically active individuals also had lower dysregulation scores than inactive individuals (\n                      <jats:italic>\u03b2<\/jats:italic>\n                      \u2009=\u2009\u22120.186, SE\u2009=\u20090.069,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.007). Overweight (\n                      <jats:italic>\u03b2<\/jats:italic>\n                      \u2009=\u20090.108, SE\u2009=\u20090.043,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.012) and obesity (\n                      <jats:italic>\u03b2<\/jats:italic>\n                      \u2009=\u20090.191, SE\u2009=\u20090.087,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.028) were associated with greater dysregulation than normal body mass index (BMI).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Female sex and physical activity were associated with lower physiological dysregulation, whereas higher BMI was associated with greater dysregulation. These findings underscore the importance of sex differences and modifiable lifestyle factors, particularly physical activity and adiposity in multisystem physiological burden among older US adults.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1155\/jare\/3289222","type":"journal-article","created":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T06:02:16Z","timestamp":1784959336000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Factors Associated With Physiological Dysregulation Among US Adults Aged 45 Years and Older: A Nationally Representative Study"],"prefix":"10.1155","volume":"2026","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7616-3955","authenticated-orcid":false,"given":"Vishal","family":"Vennu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,7,24]]},"reference":[{"key":"e_1_2_14_1_2","doi-asserted-by":"publisher","DOI":"10.1113\/jphysiol.2014.282665"},{"key":"e_1_2_14_2_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11912-021-01097-9"},{"key":"e_1_2_14_3_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41569-018-0064-2"},{"key":"e_1_2_14_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2013.05.039"},{"key":"e_1_2_14_5_2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1506264112"},{"key":"e_1_2_14_6_2","doi-asserted-by":"publisher","DOI":"10.1177\/2752535X241273820"},{"key":"e_1_2_14_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ebiom.2017.03.046"},{"key":"e_1_2_14_8_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pmed.1002718"},{"key":"e_1_2_14_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(15)00516-4"},{"key":"e_1_2_14_10_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-025-67622-7"},{"key":"e_1_2_14_11_2","doi-asserted-by":"publisher","DOI":"10.1249\/MSS.0000000000003041"},{"key":"e_1_2_14_12_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.psyneuen.2025.107661"},{"key":"e_1_2_14_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.arr.2021.101536"},{"key":"e_1_2_14_14_2","doi-asserted-by":"publisher","DOI":"10.1002\/agm2.12331"},{"key":"e_1_2_14_15_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.socscimed.2017.09.025"},{"key":"e_1_2_14_16_2","doi-asserted-by":"publisher","DOI":"10.1093\/gerona\/glaa021"},{"key":"e_1_2_14_17_2","doi-asserted-by":"publisher","DOI":"10.1177\/23337214211046419"},{"key":"e_1_2_14_18_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.amepre.2022.02.003"},{"key":"e_1_2_14_19_2","first-page":"1","article-title":"National Health and Nutrition Examination Survey, 2017-March 2020 Prepandemic File: Sample Design, Estimation, and Analytic Guidelines","volume":"1","author":"Akinbami L. 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