7
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Design, methodology, and baseline of whole city-million scale children and adolescents myopia survey (CAMS) in Wenzhou, China

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Myopia is the most common visual impairment in children and adolescents worldwide. This study described an economical and effective population-based screening pipeline and performed the project of a million scale children and adolescents myopia survey (CAMS), which will shed light on the further study of myopia from the level of epidemiology and precision medicine.

          Methods

          We developed a novel population-based screening pattern, an intelligent screening process and internet-based information transmission and analysis system to carry out the survey consisting of school children in Wenzhou, China. The examination items include unaided distance visual acuity, presenting distance visual acuity, and non-cycloplegic autorefraction. Myopia and high myopia were defined as spherical equivalent (SE) ≤ − 1.00 diopters (D) and SE ≤ − 6.00 D, respectively. Next, the reports of the vision checking were automatically sent to parents and the related departments. The CAMS project will be done two to four times annually with the support of the government. An online eyesight status information management system (OESIMS) was developed to construct comprehensive and efficient electronic vision health records (EVHRs) for myopia information inquiry, risk pre-warning, and further study.

          Results

          The CAMS completed the first-round of screening within 30 days for 99.41% of Wenzhou students from districts and counties, in June 2019. A total of 1,060,925 participants were eligible for CAMS and 1,054,251 (99.37% participation rate) were selected through data quality control, which comprised 1305 schools, and 580,609, 251,050 and 170,967 elementary, middle, and high school students. The mean age of participants was 12.21 ± 3.32 years (6–20 years), the female-to-male ratio was 0.82. The prevalence of myopia in elementary, middle, and high school students was 38.16%, 77.52%, and 84.00%, respectively, and the high myopia incidence was 0.95%, 6.90%, and 12.98%.

          Conclusions

          The CAMS standardized myopia screening model involves automating large-scale information collection, data transmission, data analysis and early warning, thereby supporting myopia prevention and control. The entire survey reduced 90% of staff, cost, and time consumption compared with previous surveys. This will provide new insights for decision support for public health intervention.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s40662-021-00255-1.

          Related collections

          Most cited references84

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

          Summary Background As mortality rates decline, life expectancy increases, and populations age, non-fatal outcomes of diseases and injuries are becoming a larger component of the global burden of disease. The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of prevalence, incidence, and years lived with disability (YLDs) for 328 causes in 195 countries and territories from 1990 to 2016. Methods We estimated prevalence and incidence for 328 diseases and injuries and 2982 sequelae, their non-fatal consequences. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring consistency between incidence, prevalence, remission, and cause of death rates for each condition. For some causes, we used alternative modelling strategies if incidence or prevalence needed to be derived from other data. YLDs were estimated as the product of prevalence and a disability weight for all mutually exclusive sequelae, corrected for comorbidity and aggregated to cause level. We updated the Socio-demographic Index (SDI), a summary indicator of income per capita, years of schooling, and total fertility rate. GBD 2016 complies with the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, low back pain, migraine, age-related and other hearing loss, iron-deficiency anaemia, and major depressive disorder were the five leading causes of YLDs in 2016, contributing 57·6 million (95% uncertainty interval [UI] 40·8–75·9 million [7·2%, 6·0–8·3]), 45·1 million (29·0–62·8 million [5·6%, 4·0–7·2]), 36·3 million (25·3–50·9 million [4·5%, 3·8–5·3]), 34·7 million (23·0–49·6 million [4·3%, 3·5–5·2]), and 34·1 million (23·5–46·0 million [4·2%, 3·2–5·3]) of total YLDs, respectively. Age-standardised rates of YLDs for all causes combined decreased between 1990 and 2016 by 2·7% (95% UI 2·3–3·1). Despite mostly stagnant age-standardised rates, the absolute number of YLDs from non-communicable diseases has been growing rapidly across all SDI quintiles, partly because of population growth, but also the ageing of populations. The largest absolute increases in total numbers of YLDs globally were between the ages of 40 and 69 years. Age-standardised YLD rates for all conditions combined were 10·4% (95% UI 9·0–11·8) higher in women than in men. Iron-deficiency anaemia, migraine, Alzheimer’s disease and other dementias, major depressive disorder, anxiety, and all musculoskeletal disorders apart from gout were the main conditions contributing to higher YLD rates in women. Men had higher age-standardised rates of substance use disorders, diabetes, cardiovascular diseases, cancers, and all injuries apart from sexual violence. Globally, we noted much less geographical variation in disability than has been documented for premature mortality. In 2016, there was a less than two times difference in age-standardised YLD rates for all causes between the location with the lowest rate (China, 9201 YLDs per 100 000, 95% UI 6862–11943) and highest rate (Yemen, 14 774 YLDs per 100 000, 11 018–19 228). Interpretation The decrease in death rates since 1990 for most causes has not been matched by a similar decline in age-standardised YLD rates. For many large causes, YLD rates have either been stagnant or have increased for some causes, such as diabetes. As populations are ageing, and the prevalence of disabling disease generally increases steeply with age, health systems will face increasing demand for services that are generally costlier than the interventions that have led to declines in mortality in childhood or for the major causes of mortality in adults. Up-to-date information about the trends of disease and how this varies between countries is essential to plan for an adequate health-system response.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            IMI – Defining and Classifying Myopia: A Proposed Set of Standards for Clinical and Epidemiologic Studies

            Purpose We provide a standardized set of terminology, definitions, and thresholds of myopia and its main ocular complications. Methods Critical review of current terminology and choice of myopia thresholds was done to ensure that the proposed standards are appropriate for clinical research purposes, relevant to the underlying biology of myopia, acceptable to researchers in the field, and useful for developing health policy. Results We recommend that the many descriptive terms of myopia be consolidated into the following descriptive categories: myopia, secondary myopia, axial myopia, and refractive myopia. To provide a framework for research into myopia prevention, the condition of “pre-myopia” is defined. As a quantitative trait, we recommend that myopia be divided into myopia (i.e., all myopia), low myopia, and high myopia. The current consensus threshold value for myopia is a spherical equivalent refractive error ≤ −0.50 diopters (D), but this carries significant risks of classification bias. The current consensus threshold value for high myopia is a spherical equivalent refractive error ≤ −6.00 D. “Pathologic myopia” is proposed as the categorical term for the adverse, structural complications of myopia. A clinical classification is proposed to encompass the scope of such structural complications. Conclusions Standardized definitions and consistent choice of thresholds are essential elements of evidence-based medicine. It is hoped that these proposals, or derivations from them, will facilitate rigorous, evidence-based approaches to the study and management of myopia.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              The myopia boom.

                Bookmark

                Author and article information

                Contributors
                lufan@mail.eye.ac.cn
                wanghongbio@wmu.edu.cn
                sujz@wmu.edu.cn
                qujia@eye.ac.cn
                Journal
                Eye Vis (Lond)
                Eye Vis (Lond)
                Eye and Vision
                BioMed Central (London )
                2326-0254
                19 August 2021
                19 August 2021
                2021
                : 8
                : 31
                Affiliations
                [1 ]GRID grid.268099.c, ISNI 0000 0001 0348 3990, School of Ophthalmology and Optometry and Eye Hospital, , Wenzhou Medical University, ; Wenzhou, 325027 China
                [2 ]State Key Laboratory of Ophthalmology, Optometry and Visual Science, Wenzhou, 325027 China
                [3 ]GRID grid.268099.c, ISNI 0000 0001 0348 3990, Institute of Biomedical Big Data, , Wenzhou Medical University, ; Wenzhou, 325027 China
                [4 ]National Clinical Research Center for Ocular Disease, Wenzhou, 325027 China
                [5 ]GRID grid.410736.7, ISNI 0000 0001 2204 9268, College of Bioinformatics Science and Technology, , Harbin Medical University, ; Harbin, 150081 People’s Republic of China
                Author information
                http://orcid.org/0000-0003-0965-9955
                Article
                255
                10.1186/s40662-021-00255-1
                8373605
                34407890
                011dd4e3-0a98-4aa5-9b76-9272332e2e16
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 7 February 2021
                : 30 July 2021
                Funding
                Funded by: the Key Research and Development Program of Zhejiang Province
                Award ID: 2021C03102
                Award ID: 2020C03036
                Award Recipient :
                Funded by: National Natural Science Foundation of China
                Award ID: 31801098
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 81830027
                Award Recipient :
                Funded by: National Key Research and Development Program for Active Health and Aging Response
                Award ID: 2020YFC2008200
                Award Recipient :
                Funded by: the Major Scientific and Technological Innovation Projects of Wen Zhou
                Award ID: ZY2020013
                Award Recipient :
                Funded by: the Internal Fund Project of Eye Hospital of Wenzhou Medical University
                Award ID: YJGG20181001 and KYQD20190101
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2021

                baseline,vision screening,myopia prevention and control,population-based

                Comments

                Comment on this article