{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T07:56:01Z","timestamp":1791186961619,"version":"4.1.0"},"reference-count":33,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T00:00:00Z","timestamp":1787702400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T00:00:00Z","timestamp":1787702400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Health Science Reports"],"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background and Aims<\/jats:title>\n                    <jats:p>Parkinson's (PD) diagnosis is frequently delayed, particularly when patients present with non\u2010motor symptoms (NMS). This study evaluates the association between NMS, socio\u2010demographic factors, and diagnostic timing in PD using PPMI data. We aimed to determine how clinical and demographic profiles influence the interval between NMS onset and clinical diagnosis, acknowledging that this interval reflects both biological disease progression and healthcare\u2010related factors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      A cross\u2010sectional analysis was conducted on de\u2010identified data from 1024 PD patients in the PPMI cohort (2012\u20132018). Multivariable logistic regression was utilized to identify independent factors associated with diagnostic timing (early vs. late). Predictive performance was assessed using the Area Under the ROC Curve (AUC) and calibration analysis. Statistical significance was defined as\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.05, and an Odds Ratio (OR)\u2009&gt;\u20091 was considered indicative of later diagnostic timing.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Among the 1024 examined patients, multivariable logistic regression indicated that individual early NMS were not independently associated with diagnostic timing (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&gt;\u20090.05 for all). In contrast, specific socio\u2010demographic factors exhibited significant independent associations: male gender was associated with higher odds of later diagnosis (aOR\u2009=\u20091.48,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.0114), while primary education (aOR\u2009=\u20090.29,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001) and unemployment (aOR\u2009=\u20090.53,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.0025) were significantly associated with earlier diagnosis. The overall model showed fair\u2010to\u2010good discriminative ability with an AUC of 0.692, and no issues with multicollinearity (GVIF\u2009\u2264\u20091.15) were detected.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Socio\u2010demographic variables, rather than individual non\u2010motor symptoms, demonstrate the strongest independent associations with diagnostic timing in this cohort. The results suggest that diagnostic delays may be influenced more by gender\u2010based healthcare\u2010seeking behaviors and socioeconomic factors than by specific clinical NMS profiles. These findings highlight the need for socio\u2010demographically tailored screening strategies in the prodromal phase of PD.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/hsr2.73081","type":"journal-article","created":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T12:07:01Z","timestamp":1787746021000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Evaluating the Relationship Between Early Non\u2010Motor Symptoms and Late Diagnosis of Parkinson's Disease Based on the PPMI Database From 2012 to 2018: A Retrospective Cross\u2010Sectional Study"],"prefix":"10.1002","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-5050-2275","authenticated-orcid":false,"given":"Shakawat","family":"Hossain","sequence":"first","affiliation":[{"name":"Department of Biochemistry and Molecular Biology Shahjalal University of Science and Technology Sylhet 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