Economic Inequality in Presenting Vision in Shahroud, Iran: Two Decomposition Methods

Document Type: Original Article

Authors

1 Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran

2 Ophthalmic Epidemiology Research Center, Shahroud University of Medical Sciences, Shahroud, Iran

3 Noor Ophthalmology Research Center, Noor Eye Hospital, Tehran, Iran

Abstract

Background
Visual acuity, like many other health-related problems, does not have an equal distribution in terms of socio-economic factors. We conducted this study to estimate and decompose economic inequality in presenting visual acuity using two methods and to compare their results in a population aged 40-64 years in Shahroud, Iran.
 
Methods: The data of 5188 participants in the first phase of the Shahroud Cohort Eye Study, performed in 2009, were used for this study. Our outcome variable was presenting vision acuity (PVA) that was measured using LogMAR (logarithm of the minimum angle of resolution). The living standard variable used for estimation of inequality was the economic status and was constructed by principal component analysis on home assets. Inequality indices were concentration index and the gap between low and high economic groups. We decomposed these indices by the concentration index and BlinderOaxaca decomposition approaches respectively and compared the results.
 
Results
The concentration index of PVA was -0.245 (95% CI: -0.278, -0.212). The PVA gap between groups with a high and low economic status was 0.0705 and was in favor of the high economic group. Education, economic status, and age were the most important contributors of inequality in both concentration index and Blinder-Oaxaca decomposition. Percent contribution of these three factors in the concentration index and Blinder-Oaxaca decomposition was 41.1% vs. 43.4%, 25.4% vs. 19.1% and 15.2% vs. 16.2%, respectively. Other factors including gender, marital status, employment status and diabetes had minor contributions.
 
Conclusion
This study showed that individuals with poorer visual acuity were more concentrated among people with a lower economic status. The main contributors of this inequality were similar in concentration index and Blinder-Oaxaca decomposition. So, it can be concluded that setting appropriate interventions to promote the literacy and income level in people with low economic status, formulating policies to address economic problems in the elderly, and paying more attention to their vision problems can help to alleviate economic inequality in visual acuity.

Keywords

Main Subjects


  1. World Health Organization (WHO). Handbook on health inequality monitoring: with a special focus on low-and middle-income countries. WHO Press; 2013.
  2. O'Donnell O, Van Doorslaer E, Wagstaff A, Lindelow M. Analyzing Health Equity Using Household Survey Data: A Guide to Techniques and Their Implementation. Washington: The World Bank; 2009.
  3. Fotouhi A, Hashemi H, Mohammad K, Jalali K. The prevalence and causes of visual impairment in Tehran: the Tehran Eye Study. Br J Ophthalmol. 2004;88(6):740-745. doi:10.1136/bjo.2003.031153.
  4. Hashemi H, Mehravaran S, Emamian MH, Fotouhi A. Five-Year Incidence of Visual Impairment in Middle-Aged Iranians: The Shahroud Eye Cohort Study. Ophthalmic Epidemiol. 2016;24(1):11-16. doi:10.1080/09286586.2016.1255342
  5. Pascolini D, Mariotti SP. Global estimates of visual impairment: 2010. Br J Ophthalmol. 2012;96(5):614-618. doi:10.1136/bjophthalmol-2011-300539
  6. Singh N, Eeda SS, Gudapati BK, et al. Prevalence and causes of blindness and visual impairment and their associated risk factors, in three tribal areas of Andhra Pradesh, India. PloS One. 2014,9(7):e100644. doi:10.1371/journal.pone.0100644 
  7. Shahriari HA, Izadi S, Rouhani MR, Ghasemzadeh F, Maleki AR. Prevalence and causes of visual impairment and blindness in Sistan-va-Baluchestan Province, Iran: Zahedan Eye Study. Br J Ophthalmol. 2007;91(5):579-584. doi:10.1136/bjo.2006.105734
  8. Song W, Sun X, Shao Z, et al. Prevalence and causes of visual impairment in a rural North‐east China adult population: a population based survey in Bin County, Harbin. Acta Ophthalmol. 2010;88(6):669-674. doi:10.1111/j.1755-3768.2009.01768.x
  9. Emamian MH, Zeraati H, Majdzadeh R, Shariati M, Hashemi H, Fotouhi A. The gap of visual impairment between economic groups in Shahroud, Iran: a Blinder-Oaxaca decomposition. Am J Epidemiol. 2011;173(12):1463-1467. doi:10.1093/aje/kwr050
  10. Gilbert CE, Shah SP, Jadoon MZ, et al. Poverty and blindness in Pakistan: results from the Pakistan national blindness and visual impairment survey. BMJ. 2008;336(7634):29. doi:10.1136/bmj.39395.500046.AE
  11. Kirtland KA, Saaddine JB, Geiss LS, Thompson TJ, Cotch MF, Lee PP. Geographic Disparity of Severe Vision Loss-United States, 2009–2013. MMWR Morb Mortal Wkly Rep. 2015;64(19):513-517.
  12. Zheng Y, Lamoureux EL, Chiang PP, et al. Literacy is an independent risk factor for vision impairment and poor visual functioning. Invest Ophthalmol Vis Sci. 2011;52(10):7634-7639. doi:10.1167/iovs.11-7725
  13. Zhang X, Cotch MF, Ryskulova A, et al. Vision health disparities in the United States by race/ethnicity, education, and economic status: findings from two nationally representative surveys. Am J Ophthalmol. 2012;154(6):53-62. doi:10.1016/j.ajo.2011.08.045
  14. Combes JB, Gerdtham UG, Jarl J. Equalisation of alcohol participation among socio-economic groups over time: an analysis based on the total differential approach and longitudinal data from Sweden. Int J Equity Health. 2011;10(10):10-24. doi:10.1186/1475-9276-10-10
  15. Fotouhi A, Hashemi H, Shariati M, et al. Cohort Profile: Shahroud eye cohort study. Int J Epidemiol. 2013;42(5):1300-1308. doi:10.1093/ije/dys161
  16. Wagstaff A, Van Doorslaer E, Watanabe N. On decomposing the causes of health sector inequalities with an application to malnutrition inequalities in Vietnam. Journal of Econometrics. 2003;112(1):207-223. doi:10.1016/S0304-4076(02)00161-6
  17. McKenzie DJ. Measuring inequality with asset indicators. J Popul Econ. 2005;18(2):229-260. doi: 10.1007/s00148-005-0224-7
  18. Williams B, Onsman A, Brown T. Exploratory factor analysis: a five-step guide for novices. Journal of Emergency Primary Health Care. 2010;8(3):990399.
  19. Vyas S, Kumaranayake L. Constructing socio-economic status indices: how to use principal components analysis. Health Policy Plan. 2006;21(6):459-468.doi:10.1093/heapol/czl029
  20. Kakwani N, Wagstaff A, Van Doorslaer E. Socio-economic inequalities in health: measurement, computation, and statistical inference. Journal of Econometrics. 1997;77(1):87-103. doi:10.1016/S0304-4076(96)01807-6
  21. Kakwani N. Income Inequality and Poverty: Methods of Estimation and Policy Applications. Oxford University Press; 1980.
  22. Madden D. The relationship between low birth weight and socio-economic status in Ireland. J Biosoc Sc. 2014;46(02):248-265. doi:10.1017/S0021932014000455
  23. Blinder AS. Wage discrimination: reduced form and structural estimatesJ Hum Resour. 1973;8(4):436-455. doi:10.2307/144855
  24. Oaxaca R. Male-female wage differentials in urban labor markets. Int Econ Rev. 1973;14(3):693-709. doi:10.2307/2525981 
  25. Jewell NP. Statistics for Epidemiology. Chapman & Hall/CRC Press; 2003:252-254.
  26. Chong EW, Lamoureux EL, Jenkins MA, Aung T, Saw SM, Wong TY. Sociodemographic, lifestyle, and medical risk factors for visual impairment in an urban Asian population: the Singapore Malay eye study. Arch Ophthalmol. 2009;127(12):1640-1647. doi:10.1001/archophthalmol.2009.298
  27. Cockburn N1, Steven D, Lecuona K, et al. Prevalence, causes and socio-economic determinants of vision loss in Cape Town, South Africa. PloS One. 2012;7(2):e30718. doi:10.1371/journal.pone.0030718
  28. Adigun KOluleye TSLadipo MMOlowookere SA. Quality of life in patients with visual impairment in Ibadan: a clinical study in primary care. J Multidiscip Healthc. 2014;7:173-178. doi:10.2147/JMDH.S51359
  29. Gupta D, Gulati A, Gupta U. Impact of socio-economic status on ear health and behaviour in children: A cross-sectional study in the capital of India. Int J Pediatr Otorhinolaryngol. 2015;79(11):1842-1850. doi:10.1016/j.ijporl.2015.08.022
  30. Rius A, Artazcoz L, Guisasola L, Benach J. Visual impairment and blindness in Spanish adults: geographic inequalities are not explained by age or education. Ophthalmology. 2014;121(1):408-416. doi:10.1016/j.ophtha.2013.07.017
  31. Emamian MH, Zeraati H, Majdzadeh R, Shariati M, Hashemi H, Fotouhi A. Economic inequality in eye care utilization and its determinants: a Blinder–Oaxaca decomposition. Int J Health Policy Manage. 2014;3(6):307-313. doi:10.15171/ijhpm.2014.100
  32. Emamian MH, Zeraati H, Majdzadeh R, et al. Economic inequality in presenting near vision acuity in a middle-aged population: a Blinder–Oaxaca decomposition. Br J Ophthalmol. 2013;97(9):1100-1103. doi:10.1136/bjophthalmol-2013-303249
  33. Rhodes LA, Huisingh CE, McGwin G Jr, et al. Eye Care Quality and Accessibility Improvement in the Community (EQUALITY): impact of an eye health education program on patient knowledge about glaucoma and attitudes about eye care. Patient Relat Outcome Meas. 2016;7:37-48. doi:10.2147/PROM.S98686
  34. Marmamula S, Khanna RC, Rao GN. Unilateral visual impairment in rural south India–Andhra Pradesh Eye Disease Study (APEDS). Int J Ophthalmol. 2016;9(5):763-767. doi:10.18240/ijo.2016.05.23
  35. Zhu RRShi JYang MGuan HJ. Prevalence and causes of vision impairment in elderly chinese: a socio-economic perspective of a comparative report nested in Jiangsu Eye Study. Int J Ophthalmol. 2016;9(7):1051-1056. doi:10.18240/ijo.2016.07.19
  36. Mousa A, Courtright P, Kazanjian A, Bassett K. Prevalence of visual impairment and blindness in Upper Egypt: a gender-based perspective. Ophthalmic Epidemiol. 2014;21(3):190-196. doi:10.3109/09286586.2014.906629
  37. Khedmati Morasae E, Forouzan AS, Majdzadeh R, Asadi-Lari M, Noorbala AA, Hosseinpoor AR. Understanding determinants of socio-economic inequality in mental health in Iran's capital, Tehran: a concentration index decomposition approach. Int J Equity Health. 2012;11(1):1-13. doi:10.1186/1475-9276-11-18
  38. Emamian MH, Zeraati H, Majdzadeh R, Shariati M, Hashemi H, Fotouhi A. Unmet refractive need and its determinants in Shahroud, Iran. Int Ophthalmol. 2012;32(4):329-336. doi:10.1007/s10792-012-9567-8
  39. Firpo S, Fortin NM, Lemieux T. Unconditional quantile regressions. Econometrica. 2009;77(3):953-973. doi:10.3982/ECTA6822
  40. Chernozhukov V, Fernandez‐Val I, Melly B. Inference on counterfactual distributions. Econometrica. 2013;81(6):2205-2268. doi:10.3982/ECTA10582