Objectives. We assessed global inequality in eye health by using data on the global burden of disease measured in disability-adjusted life years (DALYs).

Methods. We estimated the burden of eye disease by calculating the sum of DALYs (from the Global Burden of Disease study, 2004 update) due to trachoma, vitamin A deficiency, glaucoma, cataract, refractive errors, and macular degeneration. We assessed the geographic distribution of eye disease in relation to economic status and etiology by calculating the Gini coefficient, the Theil index, and the Atkinson index.

Results. The global burden of eye disease was estimated at 61.4 million DALYs worldwide (4.0% of total DALYs). Vitamin A deficiency and trachoma were distributed more unevenly than were noncommunicable eye diseases, regardless of economic status. For noncommunicable eye diseases, the major contributor was refractive errors, regardless of economic status. The most uneven distribution was observed for cataract (high-income countries) and refractive errors (middle- and low-income countries).

Conclusions. Creating new eye health service for refractive errors and reducing the unacceptable eye health disparity in refractive errors should be the highest priorities for international public health services in eye care and eye health.

The World Health Organization (WHO) estimates that 314 million people have visual impairment worldwide, of whom 269 million have low vision and 45 million are blind.1 Ninety percent of all blind and visually disabled people live in middle- and low-income countries.2,3 However, blindness is not always prioritized by health and public health practices, especially when mortality indicators are used. It is true that some population-based studies have suggested an indirect relationship between visual impairment and mortality,48 but this is difficult to prove.

The first Global Burden of Disease (GBD) study quantified health effects by employing a new metric known as the disability-adjusted life year (DALY).9 This is a summary measure of population health, integrating mortality with morbidity and disability information in a single unit. One DALY can be thought of as 1 lost year of “healthy” life, and the burden of disease measures the gap between the current health status and an ideal situation in which everyone would live to old age while remaining free of disease and disability.10 Therefore, the GBD study lifts the curtain on the true magnitude of underestimated diseases and conditions, most of which are not direct causes of mortality.

Our goals in this study were as follows: (1) to calculate DALYs due to visual impairment at the global and regional levels, (2) to compare DALYs due to specific causes of visual impairment in relation to economic status, and (3) to measure the global imbalance of eye disease in relation to economic status and specific causes by using recent data from the GBD study.

DALYs are calculated as the sum of years of life lost (YLLs) through premature death and years lived with disability (YLDs). YLDs are computed by multiplying the number of incident cases by a weighting factor of between 0 (perfect health) and 1 (death) and the mean duration of the disease with a 3% time discount.11 To estimate DALYs due to each eye disease, the weighted value for low vision due to any eye diseases and cornea scar due to vitamin A deficiency were fixed at 0.170 and 0.277, respectively, whereas the weighted value for blindness due to trachoma, glaucoma, cataract, refractive errors, and macular degeneration were fixed at 0.581, 0.600, 0.570, 0.430, and 0.600, respectively.12 Thus, the YLD value is higher if a disease or condition leads to more severe disability at a younger age.

The data for our study came from the GBD study (2004 update). A summary of cause-specific death and DALY estimates for WHO member states in 2004 was obtained from the WHO Web site.13 This file included estimates of total deaths, of total DALYs, of deaths per 100 000 population, of DALYs per 100 000 population, of age-standardized death rates per 100 000 population, and of age-standardized DALYs per 100 000 population stratified by cause and member state. For the GBD study, the data set divided the causes of death into 3 groups: Group I (communicable, maternal, perinatal, and nutritional conditions), Group II (noncommunicable diseases), and Group III (injuries). Each group was then divided into subcategories (5 subcategories in group I, 14 in Group II, and 2 in Group III). A third level of categorization was then used to identify additional specific causes within each subcategory. From Group I, trachoma and vitamin A deficiency were used for our analysis but not onchocerciasis, because the sequelae of onchocerciasis consist of visual impairment and the dermatologic complication of itching.12 From Group II, glaucoma, cataract, refractive errors, and macular degeneration were used. We did not use DALYs due to diabetes mellitus because DALYs due to diabetic retinopathy were not available (DALYs due to diabetes mellitus were the sum of case, diabetic retinopathy, diabetic foot, neuropathy, and amputation12). No data on eye injuries were available in Group III.

First, we estimated the global burden of eye disease by calculating the sum of total DALYs due to trachoma, vitamin A deficiency, glaucoma, cataract, refractive errors, and macular degeneration, and then compared these figures with estimated total DALYs due to conditions in Groups I, II, and III. Second, to investigate the global imbalance of eye disease, we calculated the burden of eye disease for each World Bank region14 and specific cause. Third, the 192 WHO member states were divided into 2 groups (high-income states and middle- and low-income states), according to the World Bank's classification. To measure the eye health disparity related to economic status, we computed 3 summary measures (the Gini coefficient, the Theil index, and the Atkinson index) of maldistribution of the DALY data from the estimated DALYs per 100 000 population. If estimated DALYs per 100 000 population for a particular eye disease in a specific country was zero, we substituted a value of 0.0000001 when measuring inequality. These measures were initially designed to assess income inequity, but they have also been used to assess the distribution of health resources.1518

The principles of these measures have been reviewed elsewhere19 or summarized on the World Bank Web site.20 In brief, the Gini coefficient (the best-known index) ranges from zero, which reflects perfect evenness, to 1, which indicates perfect unevenness. The Theil index (a generalized entropy index) ranges from zero, which means an equal distribution, to infinity (a higher value is more uneven). The Atkinson index ranges from zero to 1, with zero meaning a state of evenness. For our analysis, the sensitivity parameter (ϵ) was set at 0.5. We performed statistical analysis using Stata SE 10.0 for Windows (StataCorp LP, College Station, TX).

The 6.43 billion people in the 192 WHO member states were included in the GBD study (2004 update). The total burden of all diseases and conditions in the world was estimated to be 1.52 billion DALYs. The global burden of Group I disease (communicable, maternal, perinatal, and nutritional conditions) was 603.4 million DALYs (39.7% of the total), whereas that of Group II (noncommunicable diseases) and of Group III (injuries) was 730.3 million DALYs (48.0%) and 187.2 million DALYs (12.3%), respectively. The global burden of eye disease was estimated to be 61.4 million DALYs, accounting for 4.0% of total DALYs (8th of 21 subcategories; Figure A, available as a supplement to the online version of this article at http://www.ajph.org).

The highest number of DALYs were found in East Asia and the Pacific (including China) and South Asia (including India), followed by sub-Saharan Africa and the high-income economies (Figure 1). As can be seen in Figure 1, the burden of refractive errors predominantly affects East Asia and the Pacific, South Asia, and high-income economies.

Table 1 shows the burden of eye disease in DALYs stratified by specific cause and economic status. Contributors to the burden of eye disease at the global level were refractive errors (27.7 million DALYs), cataract (17.7 million DALYs), macular degeneration (9.3 million DALYs), glaucoma (4.7 million DALYs), trachoma (1.3 million DALYs), and vitamin A deficiency (0.6 million DALYs). Thirty-nine countries with a population of 0.98 billion were classified as high-income countries, and 153 countries with a population of 5.44 billion were classified as middle-income or low-income countries. There was no burden due to trachoma in the high-income countries, except for Australia and Germany, or in 92 middle- or low-income countries. Five high-income countries (Saudi Arabia, Kuwait, Republic of Korea, Brunei, and Singapore) and 108 middle- and low-income countries had a disease burden due to vitamin A deficiency. Every country had a burden due to all of the eye diseases in Group II. Table 1 also shows that in high-income countries, the largest eye disease burden was caused by refractive errors, followed by macular degeneration, cataract, and glaucoma, and that in middle- and low-income countries the largest burden was from cataract, followed by macular degeneration and glaucoma.

Table

TABLE 1 The Global Burden of Eye Disease, Measured in Disability-Adjusted Life Years (DALYs), by Specific Cause and Economic Status: Global Burden of Disease Study, 2004

TABLE 1 The Global Burden of Eye Disease, Measured in Disability-Adjusted Life Years (DALYs), by Specific Cause and Economic Status: Global Burden of Disease Study, 2004

Worldwide, 1000 DALYs (%)High-Income Countries, 1000 DALYs (%)Middle- and Low-Income Countries, 1000 DALYs (%)
Group I causes
    Trachoma1 331.9 (2.2)0.11 (0.0021)1 331.8 (2.4)
    Vitamin A deficiency628.7 (1.0)0.08 (0.0016)628.6 (1.1)
Group ll causes
    Glaucoma4 716.6 (7.7)366.6 (7.3)4 350.0 (7.7)
    Cataract17 719.8 (28.9)394.1 (7.9)17 325.6 (30.7)
    Refractive errors27 715.5 (45.1)2 729.0 (54.7)24 986.5 (44.3)
    Macular degeneration9 279.0 (15.1)1 501.1 (30.1)7 777.9 (13.8)
All eye diseases61 391.4 (100)4 991.0 (100)56 400.4 (100)

The highest number of DALYs per 100 000 was observed in the middle- and low-income countries of East Asia and the Pacific, South Asia, and sub-Saharan Africa. (Figure B, available as a supplement to the online version of this article at http://www.ajph.org, shows a global map of estimated DALYs for eye disease per 100 000 population.) Table 2 shows the median value (25th percentile–75th percentile) of DALYs per 100 000 stratified by each specific cause and by economic status. Median rather than mean values were used for this analysis because of the skewed sample distribution. The median value of country-level DALYs for refractive errors was found to be the highest worldwide and in high-income countries, whereas it was equal to that for cataract across the middle-income and low-income countries. Refractive errors and macular degeneration had a higher median burden in high-income countries than in middle- and low-income countries.

Table

TABLE 2 Median Value of DALYs per 100 000 Population by Specific Cause (Eye Disease) and Economic Status: Global Burden of Disease Study, 2004

TABLE 2 Median Value of DALYs per 100 000 Population by Specific Cause (Eye Disease) and Economic Status: Global Burden of Disease Study, 2004

Worldwide, Median DALYs (Rangea)High-Income Countries, Median DALYs (Rangea)Middle- and Low-Income Countries, Median DALYs (Rangea)
Group l causes
    Trachoma0.00 (0.0–4.1)0.00 (0.0–0.0)0.00 (0.0–15.4)
    Vitamin A deficiency0.14 (0.00–4.21)0.00 (0.0–0.0)0.37 (0.0–12.2)
Group ll causes
    Glaucoma67.2 (40.7–130.0)39.2 (37.1–68.5)73.0 (48.8–136.2)
    Cataract196.8 (103.1–478.9)11.9 (11.4–160.1)248.6 (144.7–507.4)
    Refractive errors253.3 (205.3–282.9)284.9 (259.0–292.5)247.3 (201.0–264.4)
    Macular degeneration122.3 (105.9–145.1)142.7 (135.1–153.0)114.1 (102.3–142.2)
All eye diseases677.7 (508.3–1040.9)486.5 (472.1–624.0)796.4 (575.2–1068.9)

Note. DALY = Disability-Adjusted Life Year.

a 25th percentile to 75th percentile.

The distribution of DALYs by specific cause and economic status was assessed with the 3 inequality measures (Table 3). Inequality was greater for the eye diseases in Group I than for those in Group II, regardless of the index used and economic status. In Group II, the disease with the most uneven distribution at the global level was cataract, followed by refractive errors, glaucoma, and macular degeneration. Across high-income countries, cataract was distributed most unevenly, followed by refractive errors, glaucoma, and macular degeneration. Across middle- and low-income countries, refractive errors were distributed most unevenly, followed by cataract, glaucoma, and macular degeneration, according to all 3 of the indices.

Table

TABLE 3 The Global Distribution of DALYs Due to Eye Disease, by Specific Cause and Economic Status: Global Burden of Disease Study, 2004

TABLE 3 The Global Distribution of DALYs Due to Eye Disease, by Specific Cause and Economic Status: Global Burden of Disease Study, 2004

Worldwide
High-Income Countries
Middle- and Low-Income Countries
Gini CoefficientTheil IndexAtkinson IndexGini CoefficientTheil IndexAtkinson IndexGini CoefficientTheil IndexAtkinson Index
Group l causes
    Trachoma0.7581.2860.5930.8613.5910.9560.7021.1220.522
    Vitamin A deficiency0.8242.0630.7360.8282.5490.9190.7811.9000.691
Group ll causes
    Glaucoma0.2550.1190.0570.1500.0690.0310.2150.0960.046
    Cataract0.3370.2220.1350.5821.2340.4400.2300.1010.053
    Refractive errors0.3120.1260.0640.1660.0820.0400.3040.1180.061
    Macular degeneration0.1150.0210.0100.0610.0060.0030.1240.0230.011
All eye diseases0.1900.0570.0300.1350.0580.0260.1400.0330.017

Note. DALY = Disability-Adjusted Life Year. The Gini coefficient ranges from zero (perfect evenness) to 1 (perfect unevenness). The Theil index (a generalized entropy index) ranges from zero (equal distribution) to infinity (a higher value is more uneven). The Atkinson index ranges from zero to 1, with zero meaning a state of evenness. For our analysis, the sensitivity parameter (ϵ) was set at 0.5.

Chiang et al., using data from the GBD study in 2001, reported that the global burden of visual impairment due to onchocerciasis, trachoma, vitamin A deficiency, glaucoma, cataract, and age-related visual disorders was 53.7 million DALYs (3.5% of the total).21 Our study, however, represents the first attempt to measure eye health disparity by using DALY data from the GBD study. According to our findings, major contributors to the worldwide burden of eye disease were refractive errors, cataract, macular degeneration, and glaucoma in descending order of DALYs. This ranking was different from the recent estimate of the major causes of blindness by the WHO, which was cataract (39.1%), refractive errors (18.2%), glaucoma (10.1%), and age-related macular degeneration (7.1%).1 Possible reasons for the differences are (1) the GBD study not only included blindness but also low vision and (2) DALYs have a 3% time discount and are age-weighted. In other words, a specific leading cause of blindness at a younger age will attract a higher number of DALYs. It is therefore reasonable for refractive errors to have higher DALYs than cataract because refractive errors generally occur at a younger age than cataract. Some epidemiological studies have indicated a higher prevalence of blindness due to macular degeneration than glaucoma at a younger age.2224 This would contribute to the burden of macular degeneration and higher DALYs, although the prevalence of blindness due to glaucoma is higher than that due to macular degeneration.

Regional differences were also obvious, with a higher eye disease burden in East Asia and the Pacific (including China), South Asia (including India), and sub-Saharan Africa. Overall, more than 90% of the eye disease burden occurred in middle- and low-income countries. A greater proportion of the eye disease burden in middle- and low-income countries was due to refractive errors and cataract, whereas that in high-income countries was due to refractive errors and macular degeneration.

In our study, the ranking of eye health disparity was not influenced by the index selected, as Kawachi and Kennedy reported.25 Eye diseases from Group I showed a more uneven distribution, because trachoma and vitamin A deficiency have been controlled or eliminated in many countries. In Group II, cataract was most unevenly distributed around the world, which has motivated various international organizations to perform cataract surgeries in developing countries. Our results, however, suggested that the eye health disparity in cataract was greater among high-income countries than middle- and low-income countries. One reason is that necessary cataract surgery is not being performed in some high-income countries, whereas unnecessary cataract surgery (when the lens is relatively clear) is being performed in others to fulfill the demands of customers. In the year 2000, the WHO recommended a cataract surgical rate (defined as the number of cataract surgery procedures per million population per year) of 3000 as the minimum to eliminate blindness from cataract and a rate of 3500 in the established market economies.26 Among high-income countries, however, the cataract surgical rate varies dramatically (e.g., 1200 in the United Arab Emirates, 1308 in Kuwait, 2175 in Bahrain, 6500 in the United States, and 8000 in Australia27).

The other reason is that several factors related to eye health disparity were not considered in this study. All high-income countries were not always equipped with sufficient universal insurance coverage, sufficient health care financing, and regular health care provision. If such confounding factors were adjusted, inequality in cataract across higher-income countries could be smaller.

Blinding eye diseases and conditions are strongly associated with poverty, and preventable or curable eye diseases and conditions are therefore believed to exist mainly in developing countries. However, our results indicated that we could not ignore the burden of refractive errors in high-income countries. Refractive errors have not received much attention because many definitions of blindness have been based on best-corrected visual distance acuity,28 so that eye health planners probably have not comprehended the true magnitude of the problem due to refractive errors. The GBD study in 2004 used the presenting visual acuity to estimate the global burden of refractive errors. However, the burden of refractive errors was probably underestimated because it was based on epidemiological data from the presenting distance visual acuity. If the presenting near visual acuity was taken into consideration, the imbalance of refractive errors as well as its burden would be greater for females because females are less likely to be able to afford spectacles for presbyopia. Even high-income countries need to strengthen their refractive services, and also transfer knowledge, cost-effective techniques, and experience to the developing countries.

There are some limitations to this study. First, certain leading causes of blindness, such as diabetic retinopathy and onchocerciasis, were not included. It is true that the 2004 estimates of the GBD study included data on diabetes mellitus and onchocerciasis; however, the disease burden due to diabetic retinopathy and ocular onchocerciasis was not specified, and these data could lead to an underestimation of the global burden of eye disease. Assuming that 80% of the burden for onchocerciasis and one third of that for diabetes mellitus was due to visual impairment, the global burden of eye disease would increase to 4.5%. However, the distribution of DALYs for these diseases could not be derived from the data of the GBD study.

Second, the data of the GBD study were based on estimates. There have not been enough appropriate epidemiological studies performed around the world. Accordingly, the DALYs due to certain eye disease were estimated from epidemiological surveys focused on other eye diseases. This could also lead to underestimation of the prevalence and burden of some eye diseases, particularly if investigators missed ocular comorbidity.

Third, the use of aggregate data per country rather than provincial or district data might be a source of bias because it is apparent that there are geographic variations in the DALYs of various diseases or conditions. However, use of aggregate provincial or district data are unusual for international comparisons.

Our findings suggest that the major contribution to the global burden of eye disease was not caused by cataract but by refractive errors, regardless of the economic status. It is true that in Group II, the DALYs due to cataract were most unevenly distributed at the global level, but more uneven distribution was observed in high-income countries than in middle- and low-income countries. Most refractive errors are easily and cost-effectively managed with a basic eye examination and spectacles by trained eye care personnel, whereas other eye diseases such as cataract, glaucoma, and macular degeneration require specialized medical knowledge, advanced medical instruments, and expensive medicines. The institutions responsible for eye health should make efforts to reduce the burden of refractive errors, as well as to create cost-effective and universal service for refractive errors. In addition, the appropriate knowledge, skills, and experience should be spread around the world as soon as possible and given the highest priority for international public health services in eye care and eye health.

Acknowledgments

This study was supported by a grant from the WHO Collaborating Centre for Prevention of Blindness (Tokyo).

We extend our deepest gratitude to Kazuichi Konyama, MD, PhD, MPH, of the Department of Ophthalmology, Juntendo University School of Medicine, for useful comments.

Human Participant Protection

In accordance with Japanese law, Juntendo University School of Medicine concluded that this study was officially exempt from review because it employed publicly available data from international organizations.

References

1. Resnikoff S, Pascolini D, Mariotti Pokharel GP. Global magnitude of visual impairment caused by uncorrected refractive errors in 2004. Bull World Health Organ. 2008;86(1):6370. Crossref, MedlineGoogle Scholar
2. Thylefors B. A global initiative for the elimination of avoidable blindness. Am J Ophthalmol. 1998;125(1):9093. Crossref, MedlineGoogle Scholar
3. Cunningham ET. World blindness—no end in sight. Br J Ophthalmol. 2001;85(3):253. Crossref, MedlineGoogle Scholar
4. Cugati S, Cumming RG, Smith W, Burlutsky G, Mitchell P, Wang JJ. Visual impairment, age-related macular degeneration, cataract, and long-term mortality: the Blue Mountains Eye Study. Arch Ophthalmol. 2007;125(7):917924. Crossref, MedlineGoogle Scholar
5. McCarty CA, Nanjan MB, Taylor HR. Visual impairment predict 5 year mortality. Br J Ophthalmol. 2001;85(3):322326. Crossref, MedlineGoogle Scholar
6. Lee DJ, Gomez-Marin O, Lam BL, Zheng DD. Visual acuity impairment and mortality in US adults. Arch Ophthalmol. 2002;120(11):15441550. Crossref, MedlineGoogle Scholar
7. Freeman EE, Egleston BL, West SK, Bandeen-Roche K, Rubin G. Visual acuity change and morality in older adults. Invest Ophthalmol Vis Sci. 2005;46(11):40404045. Crossref, MedlineGoogle Scholar
8. Knudtson MD, Klein BE, Klein R. Age-related eye disease, visual impairment, and survival: the Beaver Dam Eye Study. Arch Ophthalmol. 2006;124(2):243249. Crossref, MedlineGoogle Scholar
9. Murray CJL, Lopez AD, eds. The Global Burden of Disease: A Comprehensive Assessment of Mortality and Disability From Diseases, Injuries and Risk Factors in 1990 and Projected to 2020. Cambridge, MA: Harvard University Press; 1996. Google Scholar
10. World Health Organization. Health statistics and health information systems. Metrics: disability-adjusted life year (DALY). Quantifying the burden of disease from mortality and morbidity. Available at: http://www.who.int/healthinfo/global_burden_disease/metrics_daly/en/index.html. Accessed September 12, 2009. Google Scholar
11. World Health Organization. Health statistics and health information system. Disability weights, discounting and age weighting of DALYs. Available at: http://www.who.int/healthinfo/global_burden_disease/daly_disability_weight/en/index.html. Accessed September 12, 2009. Google Scholar
12. World Health Organization. Global burden of diseases 2004 update: disability weights for diseases and conditions. Available at: http://www.who.int/healthinfo/global_burden_disease/GBD2004_DisabilityWeights.pdf. Accessed August 31, 2009. Google Scholar
13. World Health Organization. Health statistics and health information system. Disease and injury country estimates. Burden of disease. Death and DALY estimates for 2004 by cause for WHO member states. Available at: http://www.who.int/healthinfo/global_burden_disease/estimates_country/en/index.html. Accessed September 5, 2009. Google Scholar
14. World Bank. World Development Report 2004: Making Services Work for Poor People. Washington, DC: Oxford University Press; 2003. Google Scholar
15. Kobayashi Y, Takaki H. Geographic distribution of physicians in Japan. Lancet. 1992;340(8832):13911393. Crossref, MedlineGoogle Scholar
16. Hann M, Gravelle H. The maldistribution of general practitioners in England and Wales 1974–2003. Br J Gen Pract. 2004;54(509):894898. MedlineGoogle Scholar
17. Chang RK, Halfon N. Geographic distribution of pediatricians in the United States: an analysis of the fifty states and Washington DC. Pediatrics. 1997;100(2):172179. Crossref, MedlineGoogle Scholar
18. Ono K, Visonnavong V, Konyama K, Hiratsuka Y, Murakami A. Geographical distribution of eye health professionals and cataract surgery in Lao PDR. Ophthalmic Epidemiol. 2009;16(6):354361. Crossref, MedlineGoogle Scholar
19. De Maio FG. Income inequity measures. J Epidemiol Community Health. 2007;61(10):849852. Crossref, MedlineGoogle Scholar
21. Chiang PP, Keeffe JE, Le Mesurier RT, Taylor HR. Global burden of eye disease and visual impairment. Lancet. 2006;368(9533):365. Crossref, MedlineGoogle Scholar
22. Wang JJ, Foran S, Mitchell P. Age-specific prevalence and causes and unilateral visual impairment in older Australians: the Blue Mountains Eye Study. Clin Experiment Ophthalmol. 2000;28(4):268273. Crossref, MedlineGoogle Scholar
23. Klaver CC, Wolfs RC, Vingerling JR, Hofman A, de Jong PT. Age-specific prevalence and causes of blindness and visual impairment in an older population. Arch Ophthalmol. 1998;116(5):653658. Crossref, MedlineGoogle Scholar
24. Xu L, Wang Y, Li Y, et al.. Causes of blindness and visual impairment in urban and rural areas in Beijing: the Beijing Eye Study. Ophthalmology. 2006;113(7):11341141. Crossref, MedlineGoogle Scholar
25. Kawachi I, Kennedy BP. The relationship of income inequality to mortality: does the choice of indicator matter? Soc Sci Med. 1997;45(7):11211127. Crossref, MedlineGoogle Scholar
26. World Health Organization Global Initiative for the Elimination of Avoidable Blindness. Geneva, Switzerland: World Health Organization; 2000. Publication WHO/PBL/97.61. Google Scholar
27. World Health Organization. Prevention of blindness and visual impairment. Data and maps. Cataract surgical rate. Available at: http://www.who.int/entity/blindness/CSR%202006.pdf. Accessed August 14, 2009. Google Scholar
28. Dandona R, Dandona L. Refractive error blindness. Bull World Health Organ. 2001;79(3):237243. MedlineGoogle Scholar

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Koichi Ono, MD, PhD, MPH, Yoshimune Hiratsuka, MD, PhD, MPH, and Akira Murakami, MD, PhDAt the time of the study, Koichi Ono and Akira Murakami were with the World Health Organization (WHO) Collaborating Centre for Prevention of Blindness, Department of Ophthalmology, Juntendo University School of Medicine, Tokyo, Japan. Yoshimune Hiratsuka was with the Department of Management Sciences, National Institute of Public Health, Wako, Japan. “Global Inequality in Eye Health: Country-Level Analysis From the Global Burden of Disease Study”, American Journal of Public Health 100, no. 9 (September 1, 2010): pp. 1784-1788.

https://doi.org/10.2105/AJPH.2009.187930

PMID: 20634443