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The deep learning\u2013derived retinal age gap (RAG) is a promising measure of retinal aging, but its associations with real-world health determinants remain unclear. We developed a multi-task model to predict retinal age using 29,530 fundus images from 7535 participants in a health screening cohort and evaluated RAG in cohort A for lifestyle, socioeconomic, and systemic factors (\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u20095606) and cohort B for ocular diseases (\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u20091810). The bias-corrected multi-task model trained on mixed data achieved the best performance, with a mean absolute error of 2.656\u00a0years and a Pearson correlation of 0.921 in cohort A and 2.529\u00a0years and 0.938 in cohort B. Higher RAG was significantly associated with smoking (ex-smokers,\n                    <jats:italic>\u03b2<\/jats:italic>\n                    \u2009=\u2009+0.46\u00a0years; current smokers,\n                    <jats:italic>\u03b2<\/jats:italic>\n                    \u2009=\u2009+0.50\u00a0years) and with clinical diabetes (+2.52\u00a0years); both survived false discovery rate (FDR) and Bonferroni correction, and the diabetes association persisted across all sequential covariate-adjustment sets. Married participants had lower RAG (\n                    <jats:italic>\u03b2<\/jats:italic>\n                    \u2009=\u2009\u22120.46\u00a0years), significant after FDR correction only. Hypertension and hyperlipidemia were not associated with RAG. In cohort B, RAG was significantly higher in eyes with age-related macular degeneration (\n                    <jats:italic>\u03b2<\/jats:italic>\n                    \u2009=\u2009+0.60\u00a0years) and cataract (\n                    <jats:italic>\u03b2<\/jats:italic>\n                    \u2009=\u2009+1.86\u00a0years) than in normal controls, both surviving corrections. RAG, an imaging-derived age-prediction residual, is therefore associated with lifestyle, systemic, and ocular health. Whether it reflects biological aging requires longitudinal validation against established aging biomarkers; at present, RAG suits population-level characterization better than individual-level risk stratification.\n                  <\/jats:p>","DOI":"10.1007\/s11357-026-02538-8","type":"journal-article","created":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T06:16:31Z","timestamp":1789625791000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Deep learning\u2013derived retinal age gap and its associations with lifestyle, systemic, and ocular health in a health screening cohort"],"prefix":"10.1007","author":[{"given":"Boa","family":"Jang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Richul","family":"Oh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tae-Hoon","family":"Lee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chang Ki","family":"Yoon","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hyuk Jin","family":"Choi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinwook","family":"Choi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2148-1299","authenticated-orcid":false,"given":"Young-Gon","family":"Kim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7387-1315","authenticated-orcid":false,"given":"Kunho","family":"Bae","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,9,17]]},"reference":[{"key":"2538_CR1","doi-asserted-by":"publisher","DOI":"10.1002\/puh2.213","volume":"3","author":"HT Khan","year":"2024","unstructured":"Khan HT, Addo KM, Findlay H. 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