May 2005
Volume 46, Issue 13
Free
ARVO Annual Meeting Abstract  |   May 2005
Major Risk Factors for Myopia Compared in English and Singaporean Cohorts of 7–Year Old Children
Author Affiliations & Notes
  • C. Williams
    Department of Community–Based Medicine, University of Bristol, Bristol, United Kingdom
  • S. Saw
    Department of Community, Occupational and Family Medicine, National University of Singapore, Singapore, Singapore
  • L. Miller
    Department of Community–Based Medicine, University of Bristol, Bristol, United Kingdom
  • G. Gazzard
    Department of Ophthalmology, St Thomas's Hospital, London, United Kingdom
  • ALSPAC Study Group
    Department of Community–Based Medicine, University of Bristol, Bristol, United Kingdom
  • Footnotes
    Commercial Relationships  C. Williams, None; S. Saw, None; L. Miller, None; G. Gazzard, None.
  • Footnotes
    Support  Southwest Regional Health Authority, UK and Medical Research Council, Singapore
Investigative Ophthalmology & Visual Science May 2005, Vol.46, 4622. doi:
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      C. Williams, S. Saw, L. Miller, G. Gazzard, ALSPAC Study Group; Major Risk Factors for Myopia Compared in English and Singaporean Cohorts of 7–Year Old Children . Invest. Ophthalmol. Vis. Sci. 2005;46(13):4622.

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

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Abstract

Abstract: : Purpose: To compare and contrast risk factors for myopia at 7 years in children from England and from Singapore Methods: Data on refractive error at the age of 7 years were obtained from two population birth cohorts, the Avon Longitudinal Study of Parents and Children, UK (ALSPAC, n = 6758) and the Singapore Cohort Study of the Risk Factors for Myopia (SCORM; n = 840 ). Measurements had been taken without cycloplegia in ALSPAC and after cycloplegia in SCORM. Results: The prevalence (%, 95% CI) of readings of –0.5D or greater was 13.6% (12.8 to 14.4) in the ALSPAC data and 25.7% (22.7 to 28.7) in the SCORM data. In both datasets the main predictor of myopic status was the number of myopic parents. The adjusted Odds Ratios (95% CI) were 1.32 (1.14, 1.52; p < 0.001) for 1 parent and (1.50 (1.14, 1.97; p = 0.004) for 2 parents in the ALSPAC data and the corresponding SCORM results were 1.59 (1.06, 2.36; p = 0.024) and 3.22 (2.05, 5.08; p < 0.001). The child's sex was not a significant predictor in either dataset; p = 0.14 in ALSPAC and p = 0.82 in SCORM. There was a non–significant trend for Asian children to have a higher risk for myopia than white children in the ALSPAC data. The adjusted ORs were 1.81 (0.86, 3.80; p = 0.118) for Indian Asians and 1.75 (0.57,5.39; p = 0.33). In the SCORM data there was no difference in risk between Indian vs. non–Indian Asians (p = 0.855). Parental education was not a significant predictor of myopic status in the ALSPAC data (p = 0.89). In the SCORM data the univariate risk associated with tertiary vs. secondary paternal education was 1.60 (1.16, 2.20; p = 0.004), but this reduced in adjusted analyses to 1.08 (0.76, 1.55; p = 0.66). A preliminary pooled analysis of the SCORM data combined with that for the ALSPAC Asians suggetsed that country of residence was not a significant risk factor for myopia. The adjusted OR was 1.08 (0.50, 2.29; p = 0.84). Conclusions: The number of myopic parents was the main predictor of a child's myopic status at 7 in both datasets. Similarly, sex, ethnicity and parental education had either comparatively little or no influence in both datasets. Further exploration of the similarities and differences between the development of myopia in these two cohorts may help to determine the mechanisms involved, particularly if gene–environment interactions are present.

Keywords: myopia • clinical (human) or epidemiologic studies: prevalence/incidence • clinical (human) or epidemiologic studies: risk factor assessment 
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