4.3 Article

Real-world big data demonstrates prevalence trends and developmental patterns of myopia in China: a retrospective, multicenter study

Journal

ANNALS OF TRANSLATIONAL MEDICINE
Volume 9, Issue 7, Pages -

Publisher

AME PUBL CO
DOI: 10.21037/atm-20-6663

Keywords

Myopia; prevalence; real-world analysis; developmental pattern

Funding

  1. National Key R&D Program of China [2018YFC0116500]
  2. Guangzhou Key Laboratory Project [202002010006]
  3. Guangdong Science and Technology Innovation Leading Talents [2017TX04R031]
  4. National Natural Science Foundation of ChinaGeneral Programs [81770967, 81873675]
  5. National Natural Science Fund for Distinguished Young Scholars [81822010]
  6. National Natural Science FoundationYoung Scientists Fund [81800810]
  7. Science and Technology Planning Projects of Guangdong Province [2018B010109008]

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This study used medical big data to determine the prevalence trends of myopia over the past 60 years and reveal developmental patterns in China. The results showed a significant increase in myopia prevalence among individuals born after the 1960s, reaching a peak of 80% in the 1980s. Additionally, developmental patterns indicated a dramatic increase in myopia prevalence from ages 5 to 11, stabilizing at age 20.
Background: Myopia is a complex disease caused by a combination of multiple pathogenic factors. Prevalence trends and developmental patterns of myopia exhibit substantial variability that cannot be clearly assessed using limited sample sizes. This study aims to determine the myopia prevalence over the past 60 years and trace the myopia development in a school-aged population using medical big data. Methods: The refraction data from electronic medical records in eight hospitals in South China were collected from January 2005 to October 2018; including patients? year of birth, refraction status, and age at the exam. All optometry tests were performed in accordance with standard procedures by qualified senior optometrists. The cross-sectional datasets (individuals with a single examination) and longitudinal datasets (individuals with multiple examinations) were analyzed respectively. SAS statistical software was used to extract and statistically analyse all target data and to identify prevalence trends and developmental patterns related to myopia. Results: In total, 1,112,054 cross-sectional individual refraction records and 774,645 longitudinal records of 273,006 individuals were collected. The myopia prevalence significantly increased among individuals who were born after the 1960s and showed a steep rise until reaching a peak of 80% at the 1980s. Regarding developmental patterns, the cross-sectional data demonstrated that the myopia prevalence increased dramatically from 23.13% to 82.83% aging from 5 to 11, and the prevalence stabilized at the age of 20. The longitudinal data confirmed the results that the age of myopic onset was 7.47?1.67 years, the age of myopia stabilized at 17.14?2.61 years, and the degree of myopia stabilized at ?4.35?3.81 D. Conclusions: The medical big data used in this study demonstrated prevalence trends of myopia over the past 60 years and revealed developmental patterns in the onset, progression and stability of myopia in China.

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