{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:37:45Z","timestamp":1777455465735,"version":"3.51.4"},"reference-count":36,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T00:00:00Z","timestamp":1748736000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T00:00:00Z","timestamp":1748736000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"Postgraduate Research & Practice Program of Jiangsu Province","award":["KYCX23_3427"],"award-info":[{"award-number":["KYCX23_3427"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Biomed Eng Comput Biol"],"published-print":{"date-parts":[[2025,6]]},"abstract":"<jats:sec>\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>By combining existing Global Burden of Disease (GBD) data with the economic conditions of different regions, we can better understand disease trends and make more accurate estimations, facilitating effective public health interventions. Medical institutions can consequently allocate resources more efficiently. For patients, this helps lower disease risk and reduce the overall disease burden in affected areas.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>We analyzed health patterns in 204 countries using GBD 2021 methodologies and conducted separate analyses of disease burden in China and worldwide. We estimated incidence, prevalence, and years lived with disability (YLDs). We further assessed disease status by incorporating Socio-Demographic Index (SDI) values. In addition, we used Mendelian randomization to identify factors leading from falls to thoracic rib fractures, and we investigated the key protein involved in thoracic rib fractures through detection of 4907 plasma proteins.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>From 1990 to 2021, the age-standardized incidence rate (ASIR) and age-standardized prevalence rate (ASPR) generally showed an upward trend, although male ASIR, and ASPR displayed a slight decline. In China, however, ASIR and ASPR reached a turning point in 2000, dipped in 2005, then trended upward again. Morbidity and prevalence were negatively correlated with SDI. Based on Mendelian randomization analyses, falls leading to thoracic rib fractures were linked to education level and osteoporosis. Moreover, HAMP was identified as the key protein in thoracic rib fractures.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>As global populations age, analyzing the global burden of thoracic rib fractures caused by falls from 1990 to 2021 can help guide the development of effective public health prevention strategies and optimize the allocation of existing medical resources.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/11795972251350223","type":"journal-article","created":{"date-parts":[[2025,6,27]],"date-time":"2025-06-27T07:02:38Z","timestamp":1751007758000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["Rib and Sternum Fractures From Falls: Global Burden of Disease and Predictions"],"prefix":"10.1177","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8537-2214","authenticated-orcid":false,"given":"Zhanghao","family":"Huang","sequence":"first","affiliation":[{"name":"Medical School of Nantong University, Nantong University, Jiangsu, China"},{"name":"Department of Thoracic Surgery, Affiliated Hospital of Nantong University, Jiangsu, China"},{"name":"Nantong Key Laboratory of Translational Medicine in Cardiothoracic Diseases, and Research Institution of Translational Medicine in Cardiothoracic Diseases, Affiliated Hospital of Nantong University, Jiangsu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Thoracic Surgery, Affiliated Hospital of Nantong University, Jiangsu, China"},{"name":"Nantong Key Laboratory of Translational Medicine in Cardiothoracic Diseases, and Research Institution of Translational Medicine in Cardiothoracic Diseases, Affiliated Hospital of Nantong University, Jiangsu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2025,6,27]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1093\/ageing\/afz157"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1111\/jonm.13434"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2023.168189"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jot.2024.03.002"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/S1474-4422(24)00038-3"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(19)32989-7"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(20)30925-9"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/S1474-4422(21)00252-0"},{"issue":"1","key":"e_1_3_2_10_2","article-title":"The health burden of air pollution in the UK: a modelling study using updated exposure-risk associations","volume":"402","author":"Marais EA","year":"2023","unstructured":"Marais EA, Vohra K, Kelly JM, Li Y, Lu G. 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