IMI Risk Factors for Myopia

Risk factor analysis provides an important basis for developing interventions for any condition. In the case of myopia, evidence for a large number of risk factors has been presented, but they have not been systematically tested for confounding. To be useful for designing preventive interventions, r...

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Vydané v:Investigative ophthalmology & visual science Ročník 62; číslo 5; s. 3
Hlavní autori: Morgan, Ian G., Wu, Pei-Chang, Ostrin, Lisa A., Tideman, J. Willem L., Yam, Jason C., Lan, Weizhong, Baraas, Rigmor C., He, Xiangui, Sankaridurg, Padmaja, Saw, Seang-Mei, French, Amanda N., Rose, Kathryn A., Guggenheim, Jeremy A.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States The Association for Research in Vision and Ophthalmology 28.04.2021
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Special Issue
ISSN:1552-5783, 0146-0404, 1552-5783
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Abstract Risk factor analysis provides an important basis for developing interventions for any condition. In the case of myopia, evidence for a large number of risk factors has been presented, but they have not been systematically tested for confounding. To be useful for designing preventive interventions, risk factor analysis ideally needs to be carried through to demonstration of a causal connection, with a defined mechanism. Statistical analysis is often complicated by covariation of variables, and demonstration of a causal relationship between a factor and myopia using Mendelian randomization or in a randomized clinical trial should be aimed for. When strict analysis of this kind is applied, associations between various measures of educational pressure and myopia are consistently observed. However, associations between more nearwork and more myopia are generally weak and inconsistent, but have been supported by meta-analysis. Associations between time outdoors and less myopia are stronger and more consistently observed, including by meta-analysis. Measurement of nearwork and time outdoors has traditionally been performed with questionnaires, but is increasingly being pursued with wearable objective devices. A causal link between increased years of education and more myopia has been confirmed by Mendelian randomization, whereas the protective effect of increased time outdoors from the development of myopia has been confirmed in randomized clinical trials. Other proposed risk factors need to be tested to see if they modulate these variables. The evidence linking increased screen time to myopia is weak and inconsistent, although limitations on screen time are increasingly under consideration as interventions to control the epidemic of myopia.
AbstractList Risk factor analysis provides an important basis for developing interventions for any condition. In the case of myopia, evidence for a large number of risk factors has been presented, but they have not been systematically tested for confounding. To be useful for designing preventive interventions, risk factor analysis ideally needs to be carried through to demonstration of a causal connection, with a defined mechanism. Statistical analysis is often complicated by covariation of variables, and demonstration of a causal relationship between a factor and myopia using Mendelian randomization or in a randomized clinical trial should be aimed for. When strict analysis of this kind is applied, associations between various measures of educational pressure and myopia are consistently observed. However, associations between more nearwork and more myopia are generally weak and inconsistent, but have been supported by meta-analysis. Associations between time outdoors and less myopia are stronger and more consistently observed, including by meta-analysis. Measurement of nearwork and time outdoors has traditionally been performed with questionnaires, but is increasingly being pursued with wearable objective devices. A causal link between increased years of education and more myopia has been confirmed by Mendelian randomization, whereas the protective effect of increased time outdoors from the development of myopia has been confirmed in randomized clinical trials. Other proposed risk factors need to be tested to see if they modulate these variables. The evidence linking increased screen time to myopia is weak and inconsistent, although limitations on screen time are increasingly under consideration as interventions to control the epidemic of myopia.
Risk factor analysis provides an important basis for developing interventions for any condition. In the case of myopia, evidence for a large number of risk factors has been presented, but they have not been systematically tested for confounding. To be useful for designing preventive interventions, risk factor analysis ideally needs to be carried through to demonstration of a causal connection, with a defined mechanism. Statistical analysis is often complicated by covariation of variables, and demonstration of a causal relationship between a factor and myopia using Mendelian randomization or in a randomized clinical trial should be aimed for. When strict analysis of this kind is applied, associations between various measures of educational pressure and myopia are consistently observed. However, associations between more nearwork and more myopia are generally weak and inconsistent, but have been supported by meta-analysis. Associations between time outdoors and less myopia are stronger and more consistently observed, including by meta-analysis. Measurement of nearwork and time outdoors has traditionally been performed with questionnaires, but is increasingly being pursued with wearable objective devices. A causal link between increased years of education and more myopia has been confirmed by Mendelian randomization, whereas the protective effect of increased time outdoors from the development of myopia has been confirmed in randomized clinical trials. Other proposed risk factors need to be tested to see if they modulate these variables. The evidence linking increased screen time to myopia is weak and inconsistent, although limitations on screen time are increasingly under consideration as interventions to control the epidemic of myopia.Risk factor analysis provides an important basis for developing interventions for any condition. In the case of myopia, evidence for a large number of risk factors has been presented, but they have not been systematically tested for confounding. To be useful for designing preventive interventions, risk factor analysis ideally needs to be carried through to demonstration of a causal connection, with a defined mechanism. Statistical analysis is often complicated by covariation of variables, and demonstration of a causal relationship between a factor and myopia using Mendelian randomization or in a randomized clinical trial should be aimed for. When strict analysis of this kind is applied, associations between various measures of educational pressure and myopia are consistently observed. However, associations between more nearwork and more myopia are generally weak and inconsistent, but have been supported by meta-analysis. Associations between time outdoors and less myopia are stronger and more consistently observed, including by meta-analysis. Measurement of nearwork and time outdoors has traditionally been performed with questionnaires, but is increasingly being pursued with wearable objective devices. A causal link between increased years of education and more myopia has been confirmed by Mendelian randomization, whereas the protective effect of increased time outdoors from the development of myopia has been confirmed in randomized clinical trials. Other proposed risk factors need to be tested to see if they modulate these variables. The evidence linking increased screen time to myopia is weak and inconsistent, although limitations on screen time are increasingly under consideration as interventions to control the epidemic of myopia.
Author Yam, Jason C.
French, Amanda N.
Rose, Kathryn A.
Guggenheim, Jeremy A.
Wu, Pei-Chang
Baraas, Rigmor C.
Lan, Weizhong
Sankaridurg, Padmaja
Saw, Seang-Mei
Ostrin, Lisa A.
Tideman, J. Willem L.
He, Xiangui
Morgan, Ian G.
AuthorAffiliation 5 College of Optometry, University of Houston, Houston, Texas, United States
9 Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China
2 State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, China
20 Brien Holden Vision Institute Limited, Sydney, Australia
13 Aier School of Optometry, Hubei University of Science and Technology, Xianning, China
6 Department of Ophthalmology, Erasmus MC, University Medical Centre, Rotterdam, The Netherlands
17 Department of Preventative Ophthalmology, Shanghai Eye Disease Prevention and Treatment Center, Shanghai Eye Hospital, Shanghai, China
10 Hong Kong Eye Hospital, Hong Kong, China
18 Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai, China
19 Shanghai Key Laboratory of Ocular Fundus Diseases, National Clinical Research Center for Eye Diseases, Shanghai, China
11 Department of Ophthalmology and Visual Sciences, Prince of
AuthorAffiliation_xml – name: 13 Aier School of Optometry, Hubei University of Science and Technology, Xianning, China
– name: 5 College of Optometry, University of Houston, Houston, Texas, United States
– name: 24 Duke-NUS Medical School, Singapore
– name: 17 Department of Preventative Ophthalmology, Shanghai Eye Disease Prevention and Treatment Center, Shanghai Eye Hospital, Shanghai, China
– name: 22 Saw Swee Hock School of Public Health, National University of Singapore (NUS), Singapore
– name: 15 Guangzhou Aier Eye Hospital, Jinan University, Guangzhou, China
– name: 2 State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, China
– name: 16 National Centre for Optics, Vision and Eye Care, Faculty of Health and Social Sciences, University of South-Eastern Norway, Kongsberg, Norway
– name: 19 Shanghai Key Laboratory of Ocular Fundus Diseases, National Clinical Research Center for Eye Diseases, Shanghai, China
– name: 20 Brien Holden Vision Institute Limited, Sydney, Australia
– name: 10 Hong Kong Eye Hospital, Hong Kong, China
– name: 6 Department of Ophthalmology, Erasmus MC, University Medical Centre, Rotterdam, The Netherlands
– name: 18 Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai, China
– name: 21 School of Optometry and Vision Science, University of New South Wales, Sydney, Australia
– name: 7 Department of Epidemiology, Erasmus MC, University Medical Centre, Rotterdam, The Netherlands
– name: 14 Aier Institute of Optometry and Vision Science, Aier Eye Hospital Group, Changsha, China
– name: 9 Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China
– name: 25 Discipline of Orthoptics, Graduate School of Health, University of Technology Sydney, Sydney, Australia
– name: 3 Department of Ophthalmology, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
– name: 1 Research School of Biology, Australian National University, Canberra, ACT, Australia
– name: 26 School of Optometry & Vision Sciences, Cardiff University, Cardiff, United Kingdom
– name: 23 Singapore Eye Research Institute, Singapore
– name: 11 Department of Ophthalmology and Visual Sciences, Prince of Wales Hospital, Hong Kong, China
– name: 4 Chang Gung University College of Medicine, Kaohsiung, Taiwan
– name: 12 Aier School of Ophthalmology, Central South University, Changsha, China
– name: 8 The Generation R Study Group, Erasmus MC, University Medical Centre, Rotterdam, The Netherlands
Author_xml – sequence: 1
  givenname: Ian G.
  surname: Morgan
  fullname: Morgan, Ian G.
  organization: Research School of Biology, Australian National University, Canberra, ACT, Australia, State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, China
– sequence: 2
  givenname: Pei-Chang
  surname: Wu
  fullname: Wu, Pei-Chang
  organization: Department of Ophthalmology, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan, Chang Gung University College of Medicine, Kaohsiung, Taiwan
– sequence: 3
  givenname: Lisa A.
  surname: Ostrin
  fullname: Ostrin, Lisa A.
  organization: College of Optometry, University of Houston, Houston, Texas, United States
– sequence: 4
  givenname: J. Willem L.
  surname: Tideman
  fullname: Tideman, J. Willem L.
  organization: Department of Ophthalmology, Erasmus MC, University Medical Centre, Rotterdam, The Netherlands, Department of Epidemiology, Erasmus MC, University Medical Centre, Rotterdam, The Netherlands, The Generation R Study Group, Erasmus MC, University Medical Centre, Rotterdam, The Netherlands
– sequence: 5
  givenname: Jason C.
  surname: Yam
  fullname: Yam, Jason C.
  organization: Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China, Hong Kong Eye Hospital, Hong Kong, China, Department of Ophthalmology and Visual Sciences, Prince of Wales Hospital, Hong Kong, China
– sequence: 6
  givenname: Weizhong
  surname: Lan
  fullname: Lan, Weizhong
  organization: Aier School of Ophthalmology, Central South University, Changsha, China, Aier School of Optometry, Hubei University of Science and Technology, Xianning, China, Aier Institute of Optometry and Vision Science, Aier Eye Hospital Group, Changsha, China, Guangzhou Aier Eye Hospital, Jinan University, Guangzhou, China
– sequence: 7
  givenname: Rigmor C.
  surname: Baraas
  fullname: Baraas, Rigmor C.
  organization: National Centre for Optics, Vision and Eye Care, Faculty of Health and Social Sciences, University of South-Eastern Norway, Kongsberg, Norway
– sequence: 8
  givenname: Xiangui
  surname: He
  fullname: He, Xiangui
  organization: Department of Preventative Ophthalmology, Shanghai Eye Disease Prevention and Treatment Center, Shanghai Eye Hospital, Shanghai, China, Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai, China, Shanghai Key Laboratory of Ocular Fundus Diseases, National Clinical Research Center for Eye Diseases, Shanghai, China
– sequence: 9
  givenname: Padmaja
  surname: Sankaridurg
  fullname: Sankaridurg, Padmaja
  organization: Brien Holden Vision Institute Limited, Sydney, Australia, School of Optometry and Vision Science, University of New South Wales, Sydney, Australia
– sequence: 10
  givenname: Seang-Mei
  surname: Saw
  fullname: Saw, Seang-Mei
  organization: Saw Swee Hock School of Public Health, National University of Singapore (NUS), Singapore, Singapore Eye Research Institute, Singapore, Duke-NUS Medical School, Singapore
– sequence: 11
  givenname: Amanda N.
  surname: French
  fullname: French, Amanda N.
  organization: Discipline of Orthoptics, Graduate School of Health, University of Technology Sydney, Sydney, Australia
– sequence: 12
  givenname: Kathryn A.
  surname: Rose
  fullname: Rose, Kathryn A.
  organization: Discipline of Orthoptics, Graduate School of Health, University of Technology Sydney, Sydney, Australia
– sequence: 13
  givenname: Jeremy A.
  surname: Guggenheim
  fullname: Guggenheim, Jeremy A.
  organization: School of Optometry & Vision Sciences, Cardiff University, Cardiff, United Kingdom
BackLink https://www.ncbi.nlm.nih.gov/pubmed/33909035$$D View this record in MEDLINE/PubMed
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  publication-title: Ophthalmic Epidemiol
  doi: 10.1080/09286586.2018.1554159
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  year: 2013
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  publication-title: Exp Eye Res
  doi: 10.1016/j.exer.2013.04.018
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Snippet Risk factor analysis provides an important basis for developing interventions for any condition. In the case of myopia, evidence for a large number of risk...
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Title IMI Risk Factors for Myopia
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