Effect of Education on Myopia: Evidence from the United Kingdom ROSLA 1972 Reform

Purpose Cross-sectional and longitudinal studies have consistently reported an association between education and myopia. However, conventional observational studies are at risk of bias due to confounding by factors such as socioeconomic position and parental educational attainment. The current study aimed to estimate the causal effect of education on refractive error using regression discontinuity analysis. Methods Regression discontinuity analysis was applied to assess the influence on refractive error of the raising of the school leaving age (ROSLA) from 15 to 16 years introduced in England and Wales in 1972. For comparison, a conventional ordinary least squares (OLS) analysis was performed. The analysis sample comprised 21,548 UK Biobank participants born in a nine-year interval centered on September 1957, the date of birth of those first affected by ROSLA. Results In OLS analysis, the ROSLA 1972 reform was associated with a −0.29 D (95% confidence interval [CI]: −0.36 to −0.21, P < 0.001) more negative refractive error. In other words, the refractive error of the study sample became more negative by −0.29 D during the transition from a minimum school leaving age of 15 to 16 years of age. Regression discontinuity analysis estimated the causal effect of the ROSLA 1972 reform on refractive error as −0.77 D (95% CI: −1.53 to −0.02, P = 0.04). Conclusions Additional compulsory schooling due to the ROSLA 1972 reform was associated with a more negative refractive error, providing additional support for a causal relationship between education and myopia.

[1]  Jeremy A Guggenheim,et al.  Association Between Polygenic Risk Score and Risk of Myopia , 2019, JAMA ophthalmology.

[2]  Jonathan H. Morgan,et al.  Quantile regression analysis reveals widespread evidence for gene-environment or gene-gene interactions in myopia development , 2019, Communications Biology.

[3]  Rachael A. Hughes,et al.  Selection Bias When Estimating Average Treatment Effects Using One-sample Instrumental Variable Analysis , 2019, Epidemiology.

[4]  P. Donnelly,et al.  The UK Biobank resource with deep phenotyping and genomic data , 2018, Nature.

[5]  G. Smith,et al.  Education and myopia: assessing the direction of causality by mendelian randomisation , 2018, British Medical Journal.

[6]  Gerard J. van den Berg,et al.  The Causal Effects of Education on Health Outcomes in the UK Biobank , 2017, Nature Human Behaviour.

[7]  Tanya Wilson Compulsory Education and Teenage Motherhood , 2017 .

[8]  C. Sudlow,et al.  Comparison of Sociodemographic and Health-Related Characteristics of UK Biobank Participants With Those of the General Population , 2017, American journal of epidemiology.

[9]  T. Bärnighausen,et al.  Regression Discontinuity for Causal Effect Estimation in Epidemiology , 2016, Current Epidemiology Reports.

[10]  P. Cumberland,et al.  Accuracy and Utility of Self-report of Refractive Error. , 2016, JAMA ophthalmology.

[11]  K. Naidoo,et al.  Global Prevalence of Myopia and High Myopia and Temporal Trends from 2000 through 2050. , 2016, Ophthalmology.

[12]  B. Barker Secondary education and the raising of the school-leaving age: coming of age? , 2016 .

[13]  P. Mitchell,et al.  Assessing the Genetic Predisposition of Education on Myopia: A Mendelian Randomization Study , 2016, Genetic epidemiology.

[14]  P. Visscher,et al.  Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores , 2015, bioRxiv.

[15]  M. He,et al.  Effect of Time Spent Outdoors at School on the Development of Myopia Among Children in China: A Randomized Clinical Trial. , 2015, JAMA.

[16]  Gabriëlle H S Buitendijk,et al.  Prevalence of refractive error in Europe: the European Eye Epidemiology (E3) Consortium , 2015, European Journal of Epidemiology.

[17]  P. Elliott,et al.  UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age , 2015, PLoS medicine.

[18]  Till Bärnighausen,et al.  Regression discontinuity designs are underutilized in medicine, epidemiology, and public health: a review of current and best practice. , 2015, Journal of clinical epidemiology.

[19]  Sebastian Calonico,et al.  Robust Nonparametric Confidence Intervals for Regression‐Discontinuity Designs , 2014 .

[20]  D. Mackey,et al.  What is the appropriate age cut‐off for cycloplegia in refraction? , 2014, Acta ophthalmologica.

[21]  N. Jacobsen,et al.  Genetic and environmental effects on myopia development and progression , 2014, Eye.

[22]  Damon Clark,et al.  The Effect of Education on Adult Mortality and Health: Evidence from Britain. , 2013, The American economic review.

[23]  D. Flitcroft The complex interactions of retinal, optical and environmental factors in myopia aetiology , 2012, Progress in Retinal and Eye Research.

[24]  Hirohiko Kakizaki,et al.  Prevalence of myopia and its association with body stature and educational level in 19-year-old male conscripts in seoul, South Korea. , 2012, Investigative ophthalmology & visual science.

[25]  Marie-Andree Somers,et al.  A Practical Guide to Regression Discontinuity , 2012 .

[26]  Joshua M. Korn,et al.  Integrating common and rare genetic variation in diverse human populations , 2010, Nature.

[27]  Olivier Marie,et al.  The Crime Reducing Effect of Education , 2010, SSRN Electronic Journal.

[28]  F. Ferris,et al.  Increased prevalence of myopia in the United States between 1971-1972 and 1999-2004. , 2009, Archives of ophthalmology.

[29]  George Mcmahon,et al.  Season of birth, daylight hours at birth, and high myopia. , 2009, Ophthalmology (Rochester, Minn.).

[30]  David Lee,et al.  Regression Discontinuity Designs in Economics , 2009 .

[31]  U. Polat,et al.  Season of birth, natural light, and myopia. , 2008, Ophthalmology.

[32]  G. Yadegarfar,et al.  Near work, education, family history, and myopia in Greek conscripts , 2008, Eye.

[33]  D. Mutti,et al.  Parental history of myopia, sports and outdoor activities, and future myopia. , 2007, Investigative ophthalmology & visual science.

[34]  Justin McCrary,et al.  Manipulation of the Running Variable in the Regression Discontinuity Design: A Density Test , 2007 .

[35]  S. Johansson,et al.  MONTH OF BIRTH, SOCIOECONOMIC BACKGROUND AND DEVELOPMENT IN SWEDISH MEN , 2004, Journal of Biosocial Science.

[36]  C K Hsiao,et al.  Prevalence of myopia in Taiwanese schoolchildren: 1983 to 2000. , 2004, Annals of the Academy of Medicine, Singapore.

[37]  S. Greenland Quantifying Biases in Causal Models: Classical Confounding vs Collider-Stratification Bias , 2003, Epidemiology.

[38]  Jeffrey M. Wooldridge,et al.  ASYMPTOTIC PROPERTIES OF WEIGHTED M-ESTIMATORS FOR STANDARD STRATIFIED SAMPLES , 2001, Econometric Theory.

[39]  J. Angrist,et al.  Identification and Estimation of Local Average Treatment Effects , 1994 .

[40]  M. K. Lim,et al.  Education and myopia in 110,236 young Singaporean males. , 1993, Singapore medical journal.

[41]  William M. K. Trochim,et al.  Research Design for Program Evaluation: The Regression-Discontinuity Approach , 1984 .

[42]  R D Sperduto,et al.  Prevalence of myopia in the United States. , 1983, Archives of ophthalmology.

[43]  Gabriëlle H S Buitendijk,et al.  Visual consequences of refractive errors in the general population. , 2015, Ophthalmology.

[44]  Till Bärnighausen,et al.  Regression Discontinuity Designs in Epidemiology: Causal Inference Without Randomized Trials , 2014 .

[45]  G. McCulloch,et al.  Secondary Education and the Raising of the School-leaving Age : Coming of Age? (Secondary Education in a Changing World) , 2013 .

[46]  Petra E. Todd,et al.  IDENTIFICATION AND ESTIMATION OF TREATMENT EFFECTS WITH A REGRESSION-DISCONTINUITY DESIGN , 2001 .

[47]  M. Startup,et al.  Month of birth and academic achievement. , 1986 .