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Year : 2021  |  Volume : 33  |  Issue : 2  |  Page : 165-170

Economic inequality in visual impairment: A study in deprived rural population of Iran

1 School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
2 Department of Epidemiology, Faculty of Health, Ilam University of Medical sciences, Ilam, Iran
3 Refractive Errors Research Center, School of Paramedical Sciences, Mashhad University of Medical Sciences, Mashhad, Iran
4 Noor Research Center for Ophthalmic Epidemiology, Noor Eye Hospital, Tehran, Iran
5 Department of Medical Surgical Nursing, School of Nursing and Midwifery, Shahid Beheshti University of Medical Sciences, Tehran, Iran

Correspondence Address:
Masoomeh Amini
School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/2452-2325.288936

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Purpose: To determine economic inequality in visual impairment (VI) and its determinants in the rural population of Iran. Methods: In this population-based, cross-sectional study, 3850 individuals, aged 3–93 years were selected from the north and southwest regions of Iran using multi-staged stratified cluster random sampling. The outcome was VI, measured in 20 feet. Economic status was constructed using principal component analysis on home assets. The concentration index (C) was used to determine inequality, and the gap between low and high economic groups was decomposed to explained and unexplained portions using the Oaxaca–Blinder decomposition method. Results: Of the 3850 individuals that were invited, 3314 participated in the study. The data of 3095 participants were finally analyzed. The C was −0.248 (95% confidence interval [CI]: −0.347 - −0.148), indicating a pro-poor inequality (concentration of VI in low economic group). The prevalence (95% CI) of VI was 1.72% (0.92–2.52) in the high economic group and 10.66% (8.84–12.48) in the low economic group with a gap of 8.94% (6.95–10.93) between the two groups. The explained and unexplained portions comprised 67.22% and 32.77% of the gap, respectively. Among the study variables, age (13.98%) and economic status (80.70%) were significant determinants of inequality in the explained portion. The variables of education (coefficient: −4.41; P < 0.001), age (coefficient: 14.09; P < 0.001), living place (coefficient: 6.96; P: 0.006), and economic status (coefficient: −7.37; P < 0.001) had significant effects on inequality in the unexplained portion. Conclusions: The result showed that VI had a higher concentration in the low economic group, and the major contributor of this inequality was economic status. Therefore, policymakers should formulate appropriate interventions to improve the economic status and alleviate economic inequality.

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