Prevalence and risk factors for epiretinal membranes in a Japanese population: the Hisayama study

Graefes Arch Clin Exp Ophthalmol. 2003 Aug;241(8):642-6. doi: 10.1007/s00417-003-0723-8. Epub 2003 Jul 17.


Purpose: To examine the prevalence and risk factors for epiretinal membranes (ERMs) in a sample Japanese population.

Methods: In 1998 a cross-sectional community survey was conducted among residents of Hisayama. A total of 688 men and 1087 women living in Hisayama, Japan, aged 40 years or older consented to participate in the study. Each participant underwent a comprehensive physical examination that included an ophthalmic examination. The presence of ERMs was judged from grading based on fundus examination using indirect ophthalmoscopy, slit lamp examination, and color fundus photographs. This study used non-stereoscopic 45 degrees fundus photographs to grade ERMs, whereas the other population-based studies used 30 degrees stereoscopic fundus photographs, which might explain some differences in prevalence of ERMs. Multiple logistic regression analysis was performed on the cross-sectional data to determine the risk factors for ERMs. The following ten possible risk factors were used: age; gender; hypertension; diabetes; serum cholesterol; serum HDL cholesterol; serum triglycerides; smoking habits; alcohol intake; and body mass index.

Results: The prevalence of ERMs was 4.0%, and increased with age. The ERMs were more prevalent in women (4.3%) than in men (3.5%). Multiple logistic regression analysis showed that age and serum cholesterol significantly associated with ERMs.

Conclusions: This study suggests that ERMs are less common in the Japanese population than in similar populations in Western countries, and that hypercholesterolemia is a relevant risk factor for ERMs.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Age Distribution
  • Aged
  • Cholesterol / blood
  • Epiretinal Membrane / epidemiology*
  • Female
  • Health Surveys
  • Humans
  • Japan / epidemiology
  • Logistic Models
  • Male
  • Middle Aged
  • Prevalence
  • Risk Factors
  • Sex Distribution


  • Cholesterol