September 2016
Volume 57, Issue 12
Open Access
ARVO Annual Meeting Abstract  |   September 2016
Distribution of mean refractive error for London 2012 competitors and support teams
Author Affiliations & Notes
  • Manbir Nagra
    Division of Optometry and Visual Science, City University London, London, United Kingdom
  • Clare Wilson
    Chelsea and Westminster Hospital NHS Foundation Trust, London, United Kingdom
  • Stefano Ceccon
    Division of Optometry and Visual Science, City University London, London, United Kingdom
  • W David Thomson
    Division of Optometry and Visual Science, City University London, London, United Kingdom
  • Penny J D’Ath
    Division of Optometry and Visual Science, City University London, London, United Kingdom
  • Footnotes
    Commercial Relationships   Manbir Nagra, None; Clare Wilson, None; Stefano Ceccon , None; W Thomson, None; Penny D’Ath, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science September 2016, Vol.57, 3983. doi:
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      Manbir Nagra, Clare Wilson, Stefano Ceccon, W David Thomson, Penny J D’Ath; Distribution of mean refractive error for London 2012 competitors and support teams. Invest. Ophthalmol. Vis. Sci. 2016;57(12):3983.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : It is widely acknowledged that there are significant global differences in prevalence and distribution of refractive error. Of particular interest is how population means of refractive error vary within sub-continents, but few studies have collected worldwide refraction data using matched experimental protocols. We conducted a single cross-sectional survey of mean refractive error distribution, which included data for individuals from all continents and sub-continents.

Methods : One thousand nine-hundred and eight-five competitors and support teams attended a purpose-built eye clinic during the London 2012 Olympic and Paralympic Games. All individuals underwent full optometric and ophthalmological examination by a team of experienced optometrists and ophthalmologists. Refractive error data were also collected using a Topcon TRK-1P autorefractor and expressed as Mean Spherical Error (MSE). The United Nations Geographical sub-regions classification was used to categorise data by continent (Africa; Americas; Asia; Europe; Oceania) and further categorised into one of twenty-two sub-continents. ANOVA analyses and post-hoc testing were used to investigate differences between both continents and sub-continents.

Results : Mean OD MSE±standard deviation (D) by continent was, in ranked ascending order: Asia -0.75±2.57, Africa -0.59±2.82, Europe -0.29±2.84, Oceania -0.27±1.86, and the Americas -0.20±1.92. There were no significant inter-eye MSE differences (p>0.05).
Analysis of sub-continents showed mean MSE (D) for Eastern Asia (-1.83±2.41) was significantly more myopic than both Southern Asia (+0.03±1.84) and Western Asia (+0.08±2.15) (p<0.05 for both). Mean MSE for Northern Africa (-1.45±4.43) was significantly more myopic compared to Middle Africa (+0.05±1.11) and Western Africa (-0.08±1.69) (p<0.05 for both). Large differences between mean MSE were also noted between other sub-continents; North America and Caribbean (mean difference 1.07D), Northern and Western Europe (mean difference 0.91D), and between Australia & New Zealand and Micronesia (mean difference 0.80D), but such differences failed to reach statistical significance (p>0.05).

Conclusions : Significant variation in population means of refractive error within continents highlights the importance of undertaking data analysis by sub-continent. Further work is required to understand the factors underlying such variations in global refractive error distribution.

This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.

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