Socioeconomic Status and Glaucoma: Associations in High Levels of Income and Education.

ABSTRACT

PURPOSE: Glaucoma affects millions of people globally, and socioeconomic status is known to be associated with glaucoma. This study expands the understanding of the relationship between socioeconomic factors and glaucoma. METHODS: This study used Korean National Health and Nutrition Examination Survey (KNHANES) from 2008 to 2012, with 24,664 persons who did not have missing records on the key variables. The combined relationship between levels of income and education and the prevalence of glaucoma was examined, as well as the occupational difference in the prevalence of glaucoma. Logistic regression models were constructed to generate odds ratios with 95% confidence intervals for predictors of glaucoma. All analyses were adjusted for strata, cluster, and weight. RESULTS: The prevalence of glaucoma generally decreased with increasing levels of education and income, but this trend did not hold at the top two levels of education and income, wherein the prevalence was either the same or somewhat higher. Occupation types were shown to be significantly associated with glaucoma (p < 0.0001), and among all the occupations in the survey, farming/forestry/fishing showed the highest percentage of those with glaucoma (4.9%), and service/retail showed the lowest percentage (1.3%). In the multivariable adjusted model, the odds of glaucoma decreased with increasing income level, and increased at the highest income quartile, though the odds were significant only for the top two quartiles. The odds of glaucoma showed neither a nonlinear relationship nor statistical significance with education level when adjusted for other factors. In contrast, age and gender remained significant even after adjusting for other factors. CONCLUSIONS: There exists a nonlinear relationship between key socioeconomic factors and the prevalence of glaucoma, though the exact nature of the relationship requires further investigation. These findings merit attention in studies that relate disease prevalence to education and income.