{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T11:08:19Z","timestamp":1791889699045,"version":"4.3.4"},"reference-count":37,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,6,4]],"date-time":"2021-06-04T00:00:00Z","timestamp":1622764800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2021,6,4]],"date-time":"2021-06-04T00:00:00Z","timestamp":1622764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Public Health"],"published-print":{"date-parts":[[2021,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Population-based screening was essential for glaucoma management. Although various studies have investigated the cost-effectiveness of glaucoma screening, policymakers facing with uncontrollably growing total health expenses were deeply concerned about the potential financial consequences of glaucoma screening. This present study was aimed to explore the impact of glaucoma screening with artificial intelligence (AI) automated diagnosis from a budgetary standpoint in Changjiang county, China.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A Markov model based on health care system\u2019s perspective was adapted from previously published studies to predict disease progression and healthcare costs. A cohort of 19,395 individuals aged 65 and above were simulated over a 15-year timeframe. Fur illustrative purpose, we only considered primary angle-closure glaucoma (PACG) in this study. Prevalence, disease progression risks between stages, compliance rates were obtained from publish studies. We did a meta-analysis to estimate diagnostic performance of AI automated diagnosis system from fundus image. Screening costs were provided by the Changjiang screening programme, whereas treatment costs were derived from electronic medical records from two county hospitals. Main outcomes included the number of PACG patients and health care costs. Cost-offset analysis was employed to compare projected health outcomes and medical care costs under the screening with what they would have been without screening. One-way sensitivity analysis was conducted to quantify uncertainties around model results.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Among people aged 65 and above in Changjiang county, it was predicted that there were 1940 PACG patients under the AI-assisted screening scenario, compared with 2104 patients without screening in 15\u2009years\u2019 time. Specifically, the screening would reduce patients with primary angle closure suspect by 7.7%, primary angle closure by 8.8%, PACG by 16.7%, and visual blindness by 33.3%. Due to early diagnosis and treatment under the screening, healthcare costs surged dramatically to $107,761.4 dollar in the first year and then were constantly declining over time, while without screening costs grew from $14,759.8 in the second year until peaking at $17,900.9 in the 9th year. However, cost-offset analysis revealed that additional healthcare costs resulted from the screening could not be offset by decreased disease progression. The 5-, 10-, and 15-year accumulated incremental costs of screening versus no screening were estimated to be $396,362.8, $424,907.9, and $434,903.2, respectively. As a result, the incremental cost per PACG of any stages prevented was $1464.3.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This study represented the first attempt to address decision-maker\u2019s budgetary concerns when adopting glaucoma screening by developing a Markov prediction model to project health outcomes and costs. Population screening combined with AI automated diagnosis for PACG in China were able to reduce disease progression risks. However, the excess costs of screening could never be offset by reduction in disease progression. Further studies examining the cost-effectiveness or cost-utility of AI-assisted glaucoma screening were needed.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12889-021-11097-w","type":"journal-article","created":{"date-parts":[[2021,6,4]],"date-time":"2021-06-04T18:03:28Z","timestamp":1622829808000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":45,"title":["Health care cost and benefits of artificial intelligence-assisted population-based glaucoma screening for the elderly in remote areas of China: a cost-offset analysis"],"prefix":"10.1186","volume":"21","author":[{"given":"Xuan","family":"Xiao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Long","family":"Xue","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lin","family":"Ye","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongzheng","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yunzhen","family":"He","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,6,4]]},"reference":[{"issue":"5","key":"11097_CR1","doi-asserted-by":"publisher","first-page":"614","DOI":"10.1136\/bjophthalmol-2011-300539","volume":"96","author":"D Pascolini","year":"2012","unstructured":"Pascolini D, Mariotti SP. Global estimates of visual impairment: 2010. Br J Ophthalmol. 2012 May 1;96(5):614\u20138. https:\/\/doi.org\/10.1136\/bjophthalmol-2011-300539.","journal-title":"Br J Ophthalmol"},{"issue":"2","key":"11097_CR2","first-page":"1","volume":"7","author":"P Song","year":"2017","unstructured":"Song P, Wang J, Bucan K, Theodoratou E, Rudan I, Chan KY, et al. National and subnational prevalence and burden of glaucoma in China: a systematic analysis. J Glob Health. 2017;7(2):1\u201318.","journal-title":"J Glob Health"},{"issue":"3","key":"11097_CR3","doi-asserted-by":"publisher","first-page":"262","DOI":"10.1136\/bjo.2005.081224","volume":"90","author":"HA Quigley","year":"2006","unstructured":"Quigley HA, Broman AT. The number of people with glaucoma worldwide in 2010 and 2020. Br J Ophthalmol. 2006 Mar 1;90(3):262\u20137. https:\/\/doi.org\/10.1136\/bjo.2005.081224.","journal-title":"Br J Ophthalmol"},{"issue":"2","key":"11097_CR4","doi-asserted-by":"publisher","first-page":"200","DOI":"10.1016\/j.ophtha.2008.08.051","volume":"116","author":"DC Musch","year":"2009","unstructured":"Musch DC, Gillespie BW, Lichter PR, Niziol LM, Janz NK, Investigators CS. Visual field progression in the collaborative initial Glaucoma treatment study: the impact of treatment and other baseline factors. Ophthalmology. 2009;116(2):200\u20137. https:\/\/doi.org\/10.1016\/j.ophtha.2008.08.051.","journal-title":"Ophthalmology"},{"issue":"12","key":"11097_CR5","doi-asserted-by":"publisher","first-page":"2329","DOI":"10.1016\/j.ophtha.2010.08.049","volume":"117","author":"M Sehi","year":"2010","unstructured":"Sehi M, Grewal DS, Goodkin ML, Greenfield DS. Reversal of retinal ganglion cell dysfunction after surgical reduction of intraocular pressure. Ophthalmology. 2010 Dec 1;117(12):2329\u201336. https:\/\/doi.org\/10.1016\/j.ophtha.2010.08.049.","journal-title":"Ophthalmology."},{"issue":"18","key":"11097_CR6","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1186\/1749-8546-5-12","volume":"25","author":"Y Cheng","year":"2010","unstructured":"Cheng Y. Expert advocates: improve prevention of glaucoma to achieve early detection and treatment, the undiagnostic rate of glaucoma in China reaches 90% (in Chinese). China Medical News. 2010;25(18):12.","journal-title":"China Medical News"},{"issue":"4","key":"11097_CR7","first-page":"372","volume":"35","author":"Z Yunlong","year":"2017","unstructured":"Yunlong Z. Research progress of awareness of glaucoma. Chin J Exp Ophthalmol. 2017 Jan 1;35(4):372\u20136.","journal-title":"Chin J Exp Ophthalmol"},{"issue":"12","key":"11097_CR8","doi-asserted-by":"publisher","first-page":"1353","DOI":"10.1001\/jamaophthalmol.2019.3501","volume":"137","author":"H Liu","year":"2019","unstructured":"Liu H, Li L, Wormstone IM, Qiao C, Zhang C, Liu P, et al. Development and validation of a deep learning system to detect glaucomatous optic neuropathy using fundus photographs. Jama Ophthalmol. 2019;137(12):1353\u201360. https:\/\/doi.org\/10.1001\/jamaophthalmol.2019.3501.","journal-title":"Jama Ophthalmol"},{"issue":"4","key":"11097_CR9","first-page":"245","volume":"36","author":"X Zhang","year":"2018","unstructured":"Zhang X, Fei LI. Artificial intelligence and glaucoma: opportunities and challenges. Chin J Exp Ophthalmol. 2018;36(4):245\u20137.","journal-title":"Chin J Exp Ophthalmol"},{"key":"11097_CR10","doi-asserted-by":"crossref","unstructured":"Li Z, Guo C, Lin D, Nie D, Zhu Y, Chen C, et al. Deep learning for automated glaucomatous optic neuropathy detection from ultra-widefield fundus images. Br J Ophthalmol. 2020; [10] Li F, Yan L, Wang Y, Shi J, Chen H, Zhang X, Jiang M, Wu Z, Zhou K. Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs. Graefes Arch Clin Exp Ophthalmol 2020 27:1\u20137.","DOI":"10.1136\/bjophthalmol-2020-317327"},{"issue":"8","key":"11097_CR11","doi-asserted-by":"publisher","first-page":"1207","DOI":"10.1016\/j.ophtha.2018.04.020","volume":"125","author":"DC Hood","year":"2018","unstructured":"Hood DC, De Moraes CG. Efficacy of a deep learning system for detecting glaucomatous optic neuropathy based on color fundus photographs. Ophthalmology. 2018 Aug 1;125(8):1207\u20138. https:\/\/doi.org\/10.1016\/j.ophtha.2018.04.020.","journal-title":"Ophthalmology."},{"issue":"1","key":"11097_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41598-018-35044-9","volume":"8","author":"M Christopher","year":"2018","unstructured":"Christopher M, Belghith A, Bowd C, Proudfoot JA, Goldbaum MH, Weinreb RN, et al. Performance of deep learning architectures and transfer learning for detecting glaucomatous optic neuropathy in fundus photographs. Sci Rep. 2018 Nov 12;8(1):1\u20133.","journal-title":"Sci Rep"},{"issue":"1","key":"11097_CR13","doi-asserted-by":"publisher","first-page":"149","DOI":"10.18240\/ijo.2020.01.22","volume":"13","author":"P Murtagh","year":"2020","unstructured":"Murtagh P, Greene G, O'Brien C. Current applications of machine learning in the screening and diagnosis of glaucoma: a systematic review and meta-analysis. Int J Ophthalmol. 2020;13(1):149\u201362. https:\/\/doi.org\/10.18240\/ijo.2020.01.22.","journal-title":"Int J Ophthalmol"},{"key":"11097_CR14","doi-asserted-by":"publisher","first-page":"153","DOI":"10.3233\/SHTI200141","volume":"270","author":"M Islam","year":"2020","unstructured":"Islam M, Poly TN, Yang HC, Atique S, Li YC. Deep learning for accurate diagnosis of glaucomatous optic neuropathy using digital fundus image: a meta-analysis. Stud Health Technol Informatics. 2020 Jun 16;270:153\u20137. https:\/\/doi.org\/10.3233\/SHTI200141.","journal-title":"Stud Health Technol Informatics"},{"issue":"6","key":"11097_CR15","doi-asserted-by":"publisher","first-page":"436","DOI":"10.22608\/APO.2018438","volume":"7","author":"Z Li","year":"2018","unstructured":"Li Z, Keel S, He M. Can artificial intelligence make screening faster, more accurate, and more accessible? Asia Pac J Ophthalmol. 2018;7(6):436\u201341. https:\/\/doi.org\/10.22608\/APO.2018438.","journal-title":"Asia Pac J Ophthalmol"},{"issue":"7","key":"11097_CR16","doi-asserted-by":"publisher","first-page":"124","DOI":"10.1007\/s10916-020-01590-x","volume":"44","author":"Y Zhang","year":"2020","unstructured":"Zhang Y, Wang N, Liu H. Applications of artificial intelligence in the screening of Glaucoma in China. J Med Syst. 2020 May 27;44(7):124. https:\/\/doi.org\/10.1007\/s10916-020-01590-x.","journal-title":"J Med Syst"},{"key":"11097_CR17","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1016\/j.puhe.2017.02.016","volume":"148","author":"D John","year":"2017","unstructured":"John D, Parikh R. Cost-effectiveness and cost utility of community screening for glaucoma in urban India. Public Health. 2017 Jul 1;148:37\u201348. https:\/\/doi.org\/10.1016\/j.puhe.2017.02.016.","journal-title":"Public Health"},{"key":"11097_CR18","volume-title":"Hainan Statistical Yearbook","author":"The People\u2019s Government of Hainan Province","year":"2019","unstructured":"The People\u2019s Government of Hainan Province. Hainan Statistical Yearbook 2019. http:\/\/www.hainan.gov.cn\/hainan\/tjnj\/201901\/465cf410dbf54c52ab2cc202ab0d22d0.shtml. Accessed 6 December 2020."},{"issue":"7","key":"11097_CR19","doi-asserted-by":"publisher","first-page":"e968","DOI":"10.1016\/S2214-109X(19)30201-3","volume":"7","author":"J Tang","year":"2019","unstructured":"Tang J, Liang Y, O'Neill C, Kee F, Jiang J, Congdon N. Cost-effectiveness and cost-utility of population-based glaucoma screening in China: a decision-analytic Markov model. Lancet Glob Health. 2019 Jul 1;7(7):e968\u201378. https:\/\/doi.org\/10.1016\/S2214-109X(19)30201-3.","journal-title":"Lancet Glob Health"},{"key":"11097_CR20","doi-asserted-by":"crossref","unstructured":"Hern\u00e1ndez RA, Burr JM, Vale LD; OAG Screening Project Group. Economic evaluation of screening for open-angle glaucoma. Int J Technol Assess Health Care. 2008;24(2):203-11.","DOI":"10.1017\/S0266462308080288"},{"issue":"2","key":"11097_CR21","doi-asserted-by":"publisher","first-page":"238","DOI":"10.1136\/bjo.86.2.238","volume":"86","author":"PJ Foster","year":"2002","unstructured":"Foster PJ, Buhrmann R, Quigley HA, Johnson GJ. The definition and classification of glaucoma in prevalence surveys. Br J Ophthalmol. 2002 Feb 1;86(2):238\u201342. https:\/\/doi.org\/10.1136\/bjo.86.2.238.","journal-title":"Br J Ophthalmol"},{"issue":"11","key":"11097_CR22","doi-asserted-by":"publisher","first-page":"1472","DOI":"10.1136\/bjo.2009.168682","volume":"94","author":"JL Yip","year":"2010","unstructured":"Yip JL, Foster PJ, Uranchimeg D, Javzandulam B, Javzansuren D, Munhzaya T, et al. Randomised controlled trial of screening and prophylactic treatment to prevent primary angle closure glaucoma. Br J Ophthalmol. 2010;94(11):1472\u20137. https:\/\/doi.org\/10.1136\/bjo.2009.168682.","journal-title":"Br J Ophthalmol"},{"issue":"3","key":"11097_CR23","doi-asserted-by":"publisher","first-page":"355","DOI":"10.1136\/bjophthalmol-2017-311808","volume":"103","author":"L Wang","year":"2019","unstructured":"Wang L, Huang W, Huang S, Zhang J, Guo X, Friedman DS, et al. Ten-year incidence of primary angle closure in elderly Chinese: the Liwan eye study. Br J Ophthalmol. 2019 Mar 1;103(3):355\u201360. https:\/\/doi.org\/10.1136\/bjophthalmol-2017-311808.","journal-title":"Br J Ophthalmol"},{"issue":"4","key":"11097_CR24","doi-asserted-by":"publisher","first-page":"450","DOI":"10.1136\/bjo.87.4.450","volume":"87","author":"R Thomas","year":"2003","unstructured":"Thomas R, George R, Parikh R, Muliyil J, Jacob A. Five year risk of progression of primary angle closure suspects to primary angle closure: a population based study. Br J Ophthalmol. 2003 Apr 1;87(4):450\u20134. https:\/\/doi.org\/10.1136\/bjo.87.4.450.","journal-title":"Br J Ophthalmol"},{"issue":"5","key":"11097_CR25","doi-asserted-by":"publisher","first-page":"480","DOI":"10.1034\/j.1600-0420.2003.00135.x","volume":"81","author":"R Thomas","year":"2003","unstructured":"Thomas R, Parikh R, Muliyil J, Kumar RS. Five-year risk of progression of primary angle closure to primary angle closure glaucoma: a population-based study. Acta Ophthalmol Scand. 2003 Oct;81(5):480\u20135. https:\/\/doi.org\/10.1034\/j.1600-0420.2003.00135.x.","journal-title":"Acta Ophthalmol Scand"},{"issue":"3","key":"11097_CR26","doi-asserted-by":"publisher","first-page":"463","DOI":"10.1016\/j.ajo.2011.02.023","volume":"152","author":"DT Quek","year":"2011","unstructured":"Quek DT, Koh VT, Tan GS, Perera SA, Wong TT, Aung T. Blindness and long-term progression of visual field defects in Chinese patients with primary angle-closure glaucoma. Am J Ophthalmol. 2011;152(3):463\u20139. https:\/\/doi.org\/10.1016\/j.ajo.2011.02.023.","journal-title":"Am J Ophthalmol"},{"issue":"8","key":"11097_CR27","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0136632","volume":"10","author":"L Rossetti","year":"2015","unstructured":"Rossetti L, Digiuni M, Giovanni M, Centofanti M, Fea AM, Iester M, et al. Blindness and glaucoma: a multicenter data review from 7 academic eye clinics. PLoS One. 2015;10(8):e0136632. https:\/\/doi.org\/10.1371\/journal.pone.0136632.","journal-title":"PLoS One"},{"key":"11097_CR28","doi-asserted-by":"crossref","DOI":"10.1093\/oso\/9780198526629.001.0001","volume-title":"Decision modelling for health economic evaluation. Oup Oxford","author":"A Briggs","year":"2006","unstructured":"Briggs A, Sculpher M, Claxton K. Decision modelling for health economic evaluation. Oup Oxford; 2006."},{"issue":"8","key":"11097_CR29","doi-asserted-by":"publisher","first-page":"1000","DOI":"10.1111\/ceo.13564","volume":"47","author":"S Zhang","year":"2019","unstructured":"Zhang S, Sun J, Liu S, Liang Y, Hu Y, Congdon N, et al. Integrating opportunistic glaucoma screening into general health examinations in China: a pilot study. Clin Exp Ophthalmol. 2019 Nov;47(8):1000\u20138. https:\/\/doi.org\/10.1111\/ceo.13564.","journal-title":"Clin Exp Ophthalmol"},{"issue":"12","key":"11097_CR30","doi-asserted-by":"publisher","first-page":"8672","DOI":"10.1167\/iovs.11-7480","volume":"52","author":"Y Liang","year":"2011","unstructured":"Liang Y, Friedman DS, Zhou Q, Yang XH, Sun LP, Guo L, et al. Prevalence and characteristics of primary angle-closure diseases in a rural adult Chinese population: the Handan eye study. Invest Ophthalmol Vis Sci. 2011 Nov 1;52(12):8672\u20139. https:\/\/doi.org\/10.1167\/iovs.11-7480.","journal-title":"Invest Ophthalmol Vis Sci"},{"issue":"5","key":"11097_CR31","first-page":"325","volume":"55","author":"Glaucoma Disease Group of Ophthalmological Society of Chinese Medical Association","year":"2019","unstructured":"Glaucoma Disease Group of Ophthalmological Society of Chinese Medical Association. Expert consensus on the diagnosis and treatment of primary angle-closure glaucoma in China (2019). Chin J Ophthalmol. 2019;55(5):325\u20138.","journal-title":"Chin J Ophthalmol"},{"issue":"2","key":"11097_CR32","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1016\/j.ophtha.2011.08.014","volume":"119","author":"Y Jiang","year":"2012","unstructured":"Jiang Y, Chang DS, Foster PJ, He M, Huang S, Aung T, et al. Immediate changes in intraocular pressure after laser peripheral iridotomy in primary angle-closure suspects. Ophthalmology. 2012 Feb 1;119(2):283\u20138. https:\/\/doi.org\/10.1016\/j.ophtha.2011.08.014.","journal-title":"Ophthalmology."},{"issue":"12","key":"11097_CR33","doi-asserted-by":"publisher","first-page":"2227","DOI":"10.1016\/S0161-6420(02)01275-7","volume":"109","author":"M Rosman","year":"2002","unstructured":"Rosman M, Aung T, Ang LP, Chew PT, Liebmann JM, Ritch R. Chronic angle-closure with glaucomatous damage: long-term clinical course in a north American population and comparison with an Asian population. Ophthalmology. 2002;109(12):2227\u201331. https:\/\/doi.org\/10.1016\/S0161-6420(02)01275-7.","journal-title":"Ophthalmology"},{"issue":"3","key":"11097_CR34","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1097\/IJG.0b013e31814b9693","volume":"17","author":"R Hern\u00e1ndez","year":"2008","unstructured":"Hern\u00e1ndez R, Rabindranath K, Fraser C, Vale L, Blanco AA, Burr JM. Screening for open angle glaucoma: systematic review of cost-effectiveness studies. J Glaucoma. 2008;17(3):159\u201368. https:\/\/doi.org\/10.1097\/IJG.0b013e31814b9693.","journal-title":"J Glaucoma"},{"issue":"1","key":"11097_CR35","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1177\/1355819613499748","volume":"19","author":"J Burr","year":"2014","unstructured":"Burr J, Hern\u00e1ndez R, Ramsay C, Prior M, Campbell S, Azuara-Blanco A, et al. Is it worthwhile to conduct a randomized controlled trial of glaucoma screening in the United Kingdom? J Health Serv Res Policy. 2014 Jan;19(1):42\u201351. https:\/\/doi.org\/10.1177\/1355819613499748.","journal-title":"J Health Serv Res Policy"},{"issue":"5","key":"11097_CR36","doi-asserted-by":"publisher","first-page":"823","DOI":"10.1016\/j.ophtha.2008.12.056","volume":"116","author":"DB Rein","year":"2009","unstructured":"Rein DB, Wittenborn JS, Lee PP, Wirth KE, Sorensen SW, Hoerger TJ, et al. The cost-effectiveness of routine office-based identification and subsequent medical treatment of primary open-angle glaucoma in the United States. Ophthalmology. 2009 May 1;116(5):823\u201332. https:\/\/doi.org\/10.1016\/j.ophtha.2008.12.056.","journal-title":"Ophthalmology."},{"key":"11097_CR37","unstructured":"Jiang J, Cong Y, Liang Y. Is glaucoma suitable for community screening? Chin J Exp Ophthalmol. 2018;36(4):294-98."}],"container-title":["BMC Public Health"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12889-021-11097-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12889-021-11097-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12889-021-11097-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,4]],"date-time":"2023-11-04T10:53:00Z","timestamp":1699095180000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcpublichealth.biomedcentral.com\/articles\/10.1186\/s12889-021-11097-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,4]]},"references-count":37,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,12]]}},"alternative-id":["11097"],"URL":"https:\/\/doi.org\/10.1186\/s12889-021-11097-w","relation":{},"ISSN":["1471-2458"],"issn-type":[{"value":"1471-2458","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,6,4]]},"assertion":[{"value":"23 December 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 May 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 June 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that no competing interests existed.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"1065"}}