{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T16:28:28Z","timestamp":1781108908514,"version":"3.54.1"},"reference-count":40,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,1,26]],"date-time":"2026-01-26T00:00:00Z","timestamp":1769385600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Health literacy plays an important role in disease prevention and control. The aim of this study is to explore the health literacy patterns and associated factors among residents in Zhejiang Province.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This study included 56,863 residents aged 15\u201369 years from the 2024 Zhejiang Province Health Literacy Survey. Latent Profile Analysis (LPA) was used to investigate health literacy patterns, and multinomial logistic regression analysis was employed to identify associated factors. Dominance analysis was performed to compare the relative contribution of the main variables associated with health literacy.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The analysis identified three distinct health literacy profiles: low literacy (15.13%), moderate literacy (32.24%), and relatively high literacy (52.63%). The low literacy group was characterized by an older demographic (with an average age of 58.71 years), lower educational attainment (20.72% had no formal education), a higher proportion of farmers (52.93%), and a significant share of low-income individuals (40.98%). Multinomial logistic regression and dominance analysis revealed that education level, age, and occupation were the most important associated factors of health literacy.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The study findings highlighted the heterogeneity in health literacy among various population groups and emphasized the need for targeted interventions. This study provides empirical evidence to inform precision health promotion strategies in developed regions of China.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpubh.2025.1734757","type":"journal-article","created":{"date-parts":[[2026,1,26]],"date-time":"2026-01-26T10:16:46Z","timestamp":1769422606000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Patterns and associated factors of health literacy among residents aged 15\u201369 in Zhejiang, China: a latent profile analysis"],"prefix":"10.3389","volume":"13","author":[{"given":"Shuiyang","family":"Xu","sequence":"first","affiliation":[{"name":"Zhejiang Provincial Center for Disease Control and Prevention","place":["Hangzhou, Zhejiang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yunfang","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Pharmaceutical Sciences, Wenzhou Medical 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