{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T05:04:50Z","timestamp":1783919090605,"version":"3.55.0"},"reference-count":42,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T00:00:00Z","timestamp":1783900800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100008387","name":"Xi'an Municipal Bureau of Science and Technology","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100008387","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Ophthalmol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Investigation of the global profile of myopia prevalence in children and adolescents and analysis of the impact of social factors, including economic development level, social welfare, education, demographic structure, and geographical environment, on the progression of myopia.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A retrospective study analyzed data from 31 global datasets (2004-2023) to assess social determinants of myopia prevalence. Using univariate and multiple linear regression, we evaluated the associations between myopia prevalence in children and adolescents and macroeconomic, educational, demographic, and environmental factors sourced from public databases. To further assess the robustness of the results, sensitivity analyses were conducted.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Univariate linear regression analysis revealed that GDP (\u03b2 = 0.369,\n                      <jats:italic>P<\/jats:italic>\n                      \u00a0=\u00a00.027, R\n                      <jats:sup>2<\/jats:sup>\n                      \u00a0=\u00a00.128) and longitude (\u03b2 = 0.551,\n                      <jats:italic>P<\/jats:italic>\n                      =\u00a00.001, R\n                      <jats:sup>2<\/jats:sup>\n                      \u00a0=\u00a00.280) are significantly positively correlated with myopia prevalence. The multiple linear regression model demonstrated a good overall fit (R\u00a0=\u00a00.834, R\n                      <jats:sup>2<\/jats:sup>\n                      \u00a0=\u00a00.695, adjusted R\n                      <jats:sup>2<\/jats:sup>\n                      \u00a0=\u00a00.565), and in this model, GDP per capita was negatively associated with myopia prevalence (\u03b2 = \u20130.863,\n                      <jats:italic>P<\/jats:italic>\n                      =\u00a00.001), whereas population distribution in the Northern and Southern Hemispheres (\u03b2 = 0.572, P\u00a0=\u00a00.011), urban population (% of total population) (\u03b2 = 0.737,\n                      <jats:italic>P<\/jats:italic>\n                      =\u00a00.008), and longitude (\u03b2 = 0.508,\n                      <jats:italic>P<\/jats:italic>\n                      =\u00a00.006) were significantly positively correlated with myopia prevalence (\n                      <jats:italic>P<\/jats:italic>\n                      &amp;lt;\u00a00.05).The negative associations of GDP per capita and average sunshine duration with myopia prevalence remained directionally consistent across most sensitivity analyses.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>East Asia exhibits the highest global prevalence of myopia in children and adolescents, while Europe and the Americas demonstrate comparatively lower, though variable, rates. Key influencing factors include economic development (GDP), social welfare (GDP per capita), demographic structure (population distribution and urbanization), and geographical setting (longitude).<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fopht.2026.1793615","type":"journal-article","created":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T04:23:28Z","timestamp":1783916608000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["The global landscape of myopia prevalence and its social determinants in children and adolescents: a cross-regional analysis"],"prefix":"10.3389","volume":"6","author":[{"given":"Chengfei","family":"Liu","sequence":"first","affiliation":[{"name":"Department of Ophthalmology, Xi\u2019an Central Hospital","place":["Xi\u2019an, China"]},{"name":"Department of Clinical Medicine, Yan\u2019an University","place":["Yan\u2019an, Shaanxi, 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China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Boyang","family":"Song","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology, Xi\u2019an Central Hospital","place":["Xi\u2019an, China"]},{"name":"Department of Clinical Medicine, Yan\u2019an University","place":["Yan\u2019an, Shaanxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yukang","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology, Xi\u2019an Central Hospital","place":["Xi\u2019an, China"]},{"name":"Department of Clinical Medicine, Yan\u2019an University","place":["Yan\u2019an, Shaanxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ye","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology, Xi\u2019an Central Hospital","place":["Xi\u2019an, China"]},{"name":"Department of Ophthalmology, The Second Affiliated Hospital of Xi\u2019an Jiaotong 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