Visual impairment and mortality in a rural adult population (the Southern Harbin eye study)

Ophthalmic Epidemiol. 2011 Apr;18(2):54-60. doi: 10.3109/09286586.2010.545503.


Purpose: To evaluate the association between visual acuity (VA) and 4-year mortality in an older population-based cohort.

Methods: Five thousand and fifty-seven persons aged 50 to 96 years (91.0% of the eligible population) residents of the Southern Harbin, Heilongjiang Provence, China participated in the study. At baseline (2006), the main ocular diseases were diagnosed from a basic ocular examination including presenting and best-corrected VA. Of the 5,057 participants in the baseline survey, those who died after the study were identified and the death certificate was checked. The physicians in charge of the health of the village population were asked for the presumed cause of death. The rate of death was determined in the follow-up survey in 2010. We evaluated the association of visual impairment (VI) and mortality using multiple logistic regression.

Results: Between the baseline examination and the censoring cutpoint study, a total of 214 subjects (4.2%) were dead. Females with VI were less likely to have died relative to male gender with VI (P<0.05). Compared with participants who reported better presenting VA (VA ≥ 20/60), the risk of mortality was significantly higher for those reporting moderate VI (20/400 ≤ VA < 20/60) (Odds Ratio [OR], 2.1; 95% confidence interval [CI],1-4.1) and those reporting severe VI (VA < 20/400) (OR,3.6; 95% CI, 2.0-6.6). Similar associations were obtained for best-corrected VA in the better eye (OR, 3.1; 95% CI: 1.5-6.4 and 3.9; 95%CI: 2.1-7.2, respectively).

Conclusion: In this Chinese population-based cohort we found that visual impairment predicted a significantly elevated mortality.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Age Distribution
  • Aged
  • Aged, 80 and over
  • Cause of Death
  • China / epidemiology
  • Female
  • Humans
  • Male
  • Middle Aged
  • Risk Factors
  • Rural Population / statistics & numerical data*
  • Sex Distribution
  • Vision Disorders / mortality*
  • Visual Acuity
  • Visually Impaired Persons / statistics & numerical data*