June 2017
Volume 58, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2017
The Potential value of Big-Data for Epidemiological Studies of Refractive Error
Author Affiliations & Notes
  • Michael Moore
    Dublin Institute of Technology, Dublin, Ireland
  • James Loughman
    Dublin Institute of Technology, Dublin, Ireland
  • Siegfried Wahl
    ZEISS Vision Science Lab, University Tuebingen, Tuebingen, Germany
    Carl Zeiss Vision International GmbH, Tuebingen, Germany
  • Arne Ohlendorf
    ZEISS Vision Science Lab, University Tuebingen, Tuebingen, Germany
    Carl Zeiss Vision International GmbH, Tuebingen, Germany
  • Daniel Ian Flitcroft
    Children's University Hospital Temple Street Dublin Ireland , Dublin, Ireland
    Dublin Institute of Technology, Dublin, Ireland
  • Footnotes
    Commercial Relationships   Michael Moore, None; James Loughman, None; Siegfried Wahl, Carl Zeiss Vision International GmbH (E); Arne Ohlendorf, Carl Zeiss Vision International GmbH (E); Daniel Flitcroft, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2017, Vol.58, 2397. doi:
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      Michael Moore, James Loughman, Siegfried Wahl, Arne Ohlendorf, Daniel Ian Flitcroft; The Potential value of Big-Data for Epidemiological Studies of Refractive Error. Invest. Ophthalmol. Vis. Sci. 2017;58(8):2397.

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

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Abstract

Purpose : In Europe, epidemiological data on refractive error is relatively sparse: the European Eye Epidemiology (E3) consortium, a consortium of 29 groups from 12 European countries, has collated data on only 170,000 European study participants. Our study, based on 13.4 million spectacle lens prescriptions between 2001 and 2015, was conducted to examine the epidemiological value of such large industrial databases (“Big-Data”).

Methods : Anonymised patient lens data was provided by a major European manufacturer. The data included the full sphero-cylindrical correction and whether the dispensed lens included a reading add. The total data set with complete refractive data comprised 134,606,097 spectacle lenses, of which 49,741,993 included a reading add and 84,855,096 were single vision lenses. 98% of these lenses were for European delivery, with Germany being the largest single country (>40% of total). The data was collated into histogram data by spherical equivalent power using the AWK scripting language. The resulting data allowed calculation of empirical distribution functions, sub-grouped by lens type. The manufacturing data was compared with existing population-based studies of refractive error distribution using standard descriptive statistics.

Results : Overall, lens power showed a bimodal distribution with a central minimum corresponding to emmetropia. This bimodal distribution was most apparent in single vision (SV) lenses. In contrast, lenses with reading adds (ADD) showed a classic uni-modal, negatively skewed and leptokurtotic distribution typical of adult refractive error distributions. The ADD lens subgroup should predominantly represent older adults. Comparison population survey data of older adults from the Gutenberg Health Study (GHS) has recently been published from Germany (Wolfram et al, 2014). The proportion of myopia estimated from the ADD lens group closely mirrors the GHS data suggesting that this lens type may have value as a valid estimator of adult refractive errors in a population.

Conclusions : Large lens manufacturing databases manufacturing activity can provide useful epidemiological data. Lenses with a reading addition most closely match distributions reported in population based surveys. Such data may allow collection of far more information on global refractive error distribution than is currently available from orthodox epidemiological surveys.

This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.

 

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