Visual impairment and blindness in Spanish adults: Geographic inequalities are not explained by age or education

Objectives The objectives of this study were to examine for the first time the prevalence of visual impairment and blindness among adults in Spain, to explore regional differences, and to assess whether they may vary as a function of sex or be explained by age and individual or regional socioeconomic position. Design Data were obtained from the 2008 Spanish Survey on Disability, Personal Autonomy, and Dependency Situations, a cross-sectional survey based on a representative sample of the noninstitutionalized population of Spain. Participants The sample was composed of 213 626 participants aged ≥15 years (103 093 men and 110 533 women); 360 were blind (160 men and 200 women), 4048 had near visual impairment (1397 men and 2651 women), and 4034 had distance visual impairment (1445 men and 2589 women). Methods The prevalence of near and distance visual impairment was calculated for each region. Multiple logistic regression models were fitted to calculate odds ratios and 95% confidence intervals. All analyses were stratified by sex. Main Outcome Measures Visual impairment was based on 3 questions aimed at identifying blindness and near and distance visual impairment. Results The prevalence (percentage) of blindness was 0.17 (men, 0.16; women, 0.18): 1.89 for near visual impairment (men, 1.36; women, 2.40), 1.89 for distance visual impairment (men, 1.40; women, 2.34), and 2.43 for any visual impairment (men, 1.81; women, 3.02). Regional inequalities in the prevalence of visual impairment were observed, correlated with regional income, and the prevalence was consistently higher among women than men. The magnitude of the inequalities remained after adjusting for age and educational level, and a north-to-south pattern of increasing prevalence was observed. Conclusions Regional and sex inequalities in the prevalence of visual impairment and blindness were observed in Spain, with a north-to-south gradient of increasing prevalence that was not explained by age or individual educational level but was correlated with regional level of economic development. Factors that could be prioritized for future policies and research include differential regional economic development, rural environment, quality of eye care services, diabetes, ultraviolet light exposure, or gender inequalities in diagnostic and therapeutic health care.