Int J Public Health (2018) 63 (Suppl 1):S199–S210 https://doi.org/10.1007/s00038-017-1000-7 ORIGINAL ARTICLE Burden of vision loss in the Eastern Mediterranean region, 1990–2015: ﬁndings from the Global Burden of Disease 2015 study GBD 2015 Eastern Mediterranean Region Vision Loss Collaborators Received: 2 May 2017 / Revised: 22 June 2017 / Accepted: 23 June 2017 / Published online: 3 August 2017 The Author(s) 2017. This article is an open access publication Abstract Conclusions The burden of VL is high in the EMR; Objectives To report the estimated trend in prevalence and however, it shows a descending trend over the past years lived with disability (YLDs) due to vision loss (VL) in 25 years. EMR countries need to establish comprehensive the Eastern Mediterranean region (EMR) from 1990 to 2015. eye care programs in their health care systems. Methods The estimated trends in age-standardized preva- lence and the YLDs rate due to VL in 22 EMR countries Keywords Eastern Mediterranean region Global burden were extracted from the Global Burden of Disease (GBD) of disease Vision impairment Vision disorder 2015 study. The association of Socio-demographic Index (SDI) with changes in prevalence and YLDs of VL was evaluated using a multilevel mixed model. Introduction Results The age-standardized prevalence of VL in the EMR was 18.2% in 1990 and 15.5% in 2015. The total age- Vision loss is an important public health issue worldwide. standardized YLDs rate attributed to all-cause VL in EMR About 90% of people with visual impairment live in was 536.9 per 100,000 population in 1990 and 482.3 per developing countries (Congdon et al. 2003;Tabbara 2001; 100,000 population in 2015. For each 0.1 unit increase in WHO 2004, 2013). According to the Global Burden of SDI, the age-standardized prevalence and YLDs rate of VL Disease (GBD) 2015 study, 34.3 million people are blind showed a reduction of 1.5% (p \ 0.001) and 23.9 per globally. In addition, 214 million and 24.3 million people 100,000 population (p\ 0.001), respectively. suffer from moderate and severe vision impairment (VI), respectively. Vision loss was the third-ranked impairment after anemia and hearing loss in the GBD 2015 study This article is part of the supplement ‘‘The state of health in the (GBD 2015). Vision loss affects the quality of life of the Eastern Mediterranean Region, 1990–2015.’’ affected individuals and their families, increases the risk of death by raising the risk of accidents, and increases the The members of GBD (Global Burden of Disease) 2015 Eastern Mediterranean Region Vision Loss Collaborators are listed at the end ﬁnancial burden (McCarty et al. 2001; Taylor et al. of the article. Ali H. Mokdad, on behalf of GBD 2015 Eastern 1991, 2006). The World Health Organization (WHO) Mediterranean Region Vision Loss Collaborators, is the Global Action Plan 2014–2019 emphasized the impor- corresponding author. tance of collecting data on the burden and causes of VI. Electronic supplementary material The online version of this Periodic studies were recommended to identify the burden article (doi:10.1007/s00038-017-1000-7) contains supplementary of vision loss and the avoidable causes of VI and blind- material, which is available to authorized users. ness to achieve a Global Action Plan target and plan & GBD 2015 Eastern Mediterranean Region Vision Loss health policies (WHO 2013). Collaborators Uncorrected refractive errors (RE), cataract, glaucoma, email@example.com age-related macular degeneration (AMD), diabetic retinopathy (DR), trachoma, and corneal opacities were the Institute for Health Metrics and Evaluation, University of main causes of global VI reported by WHO in 2010 Washington, Seattle, WA, USA 123 S200 GBD 2015 Eastern Mediterranean Region Vision Loss Collaborators (Pascolini and Mariotti 2012). Uncorrected RE, cataract, Global Ageing and Adult Health (SAGE) and the United and glaucoma accounted for 43, 33, and 2% of VI, States National Health and Examination Surveys respectively (Pascolini and Mariotti 2012). Hence, almost (NHANES) as the nationally representative reviews that 80% of VI is preventable or treatable, and cost-effective measured VA. In addition to SAGE and NHANES, the interventions can decrease the burden of VI (WHO 2013). Surveys of Health, Ageing, and Retirement in Europe The Eastern Mediterranean region (EMR) has a popu- (SHARE); the Multi-Country Survey Study on Health and lation of about 583 million and consists of 22 countries Responsiveness (MCSS); and the World Health Surveys (WHO 2017). These countries are not uniform in terms of (WHS) studies were assessed to extract the data with self- lifestyle, gross domestic product, and socioeconomic status reported near VA (GBD 2015). (Mandil et al. 2013; Mokdad et al. 2014). A previous study The prevalence of vision loss was modeled in three reported a descending trend in age-standardized prevalence stages. At ﬁrst, the prevalence of moderate and severe VI, of blindness (from 2.1 to 1.1%) and moderate and severe blindness, and presbyopia was evaluated to calculate the VI (from 7.1 to 4.5%) in this region in 2010 (Khairallah total presenting vision loss estimation. Secondly, the pro- et al. 2014). Despite that, the EMR is one of four regions portion of presenting vision loss attributed to uncorrected with a greater than 4% prevalence of blindness among RE was estimated. Thirdly, the prevalence of vision loss older adults (C50 years), compared to B0.4% in high-in- due to cataract, glaucoma, macular degeneration, DR, come regions (Stevens et al. 2013). The current study aims ROP, trachoma, vitamin A deﬁciency, onchocerciasis, to present trends in prevalence and years lived with dis- meningitis, and other causes was assessed (GBD 2015). ability (YLDs) rate for the main causes of vision loss in The YLDs rate, a GBD metric, demonstrates years lived EMR countries by sex and age from 1990 to 2015 using the in less than ideal health and is calculated by sequela as results of the GBD 2015 study. Considering the diversity of prevalence multiplied by the disability weight for the the EMR countries in terms of socioeconomic status, the condition associated with that sequela (GBD 2015). relationship between the prevalence of vision loss and We extracted the estimated trends in prevalence and Socio-demographic Index (SDI) was also evaluated. YLDs rates for vision loss and four leading causes, including refraction and accommodation disorders, catar- act, glaucoma, and macular degeneration, in Afghanistan, Methods Bahrain, Djibouti, Egypt, Iran, Iraq, Jordan, Kuwait, Lebanon, Libya, Morocco, Oman, Pakistan, Palestine, We used data from the Global Burden of Disease 2015 study Qatar, Saudi Arabia, Somalia, Sudan, Syria, Tunisia, the (GBD 2015). The methodology of the GBD 2015 study for United Arab Emirates, and Yemen from 1990 to 2015 from estimating the prevalence of vision loss has been compre- the GBD 2015 study using an online interactive tool hensively described in a recent GBD publication (GBD (https://vizhub.healthdata.org/gbd-compare/) developed by 2015). In brief, the GBD group estimated the prevalence of the Institute for Health Metrics and Evaluation. We also vision loss by deﬁning VI and blindness, providing the input determined the relationship between SDI and the reduction model, and deﬁning the modeling strategy. VI was deﬁned as in prevalence of vision loss and YLDs rate. The SDI was visual acuity (VA)\6/18 based on the Snellen chart, while developed for GBD 2015 to provide an interpretable syn- the blindness deﬁnition was VA\3/60 or visual ﬁeld around thesis of overall development, as measured by lag-depen- central ﬁxation\10%. Uncorrected RE, cataract, glaucoma, dent income per capita, average educational attainment in macular degeneration, and other causes including DR, tra- the population over 15 years, and the total fertility rates. In choma, vitamin A deﬁciency, retinopathy of prematurity GBD 2015, SDI was computed by rescaling each compo- (ROP), meningitis, encephalitis, and onchocerciasis were nent to the scale of zero to one, and then taking the geo- used for modeling vision loss (GBD 2015). metric mean of these values for each location-year. Zero The vision loss data were from population-based studies indicates the lowest observed educational attainment, that measured VA. Both peer-reviewed publications and lowest income per capita, and highest fertility rate from gray literature were used. Those which reported the causes of 1980 to 2015, and one indicates the highest observed vision loss were used for estimating the VI and blindness educational attainment, highest income per capita, and prevalence due to cataract, glaucoma, macular degeneration, lowest fertility rate during that time (GBD 2015). DR, and other causes (GBD 2015). Studies missing best- corrected or presenting VA were excluded (GBD 2015). Statistical methods A systematic literature review was performed for the period of January 1, 2013–May 20, 2015, to add new A multilevel linear model was used to assess the relation of evidence to that compiled for GBD 2013. Additionally, the SDI values extracted from the GBD 2015 study for 22 data were extracted from WHO-sponsored Studies on countries in the EMR and the changes in prevalence and 123 Burden of vision loss in the Eastern Mediterranean region, 1990–2015… S201 YLDs during the period 1990–2015. In this way, the The age-standardized prevalence and YLDs rates of probable geographic correlation was also considered. All vision loss in the EMR were higher than the global rate and statistics were presented with 95% uncertainty intervals ranked third following the Southeast Asia and Africa (95% UI). Statistical analysis was performed using lme4 regions in 1990 and 2015. However, this region had the package in R software (version 3.2.3) (Bates et al. 2015). highest reduction from 1990 to 2015 compared to all six world regions (ESM_1). Results Age-standardized prevalence and YLDs for causes of vision loss The age-standardized prevalence of vision loss in the EMR was 18.2% (95% UI 17.5–19%) in 1990 and 15.5% (95% Refraction and accommodation disorders UI 14.8–16.2%) in 2015. The total age-standardized YLDs rate attributed to vision loss in EMR was 536.9 per 100,000 The total age-standardized prevalence of refraction and population (95% UI 378.5–746) in 1990 and 482.3 per accommodation disorders in the EMR was 12.9% (95% UI 100,000 population (95% UI 342.5–667.8) in 2015. Vision 12.4–13.4%) in males and 17.8% (95% UI 17.1–18.6%) in loss was more prevalent in females than males in both 1990 females in 1990. In 2015, these values were 10.8% (95% UI and 2015 (p \ 0.001). There were similar ﬁndings in terms 10.3–11.2%) in males and 14.8% (95% UI 14.1–15.5%) in of the estimated YLDs rate (p \ 0.001) (Fig. 1). females. The prevalence of this disorder in 1990 was highest Table 1 shows decreased prevalence of vision loss and in Yemen and lowest in Lebanon. In 2015, Afghanistan had the attributed YLDs rate in all 22 countries from 1990 to the highest prevalence in terms of refraction and accom- 2015. The highest decrease was observed in Oman modation disorders (ESM_2). The age-standardized YLD (prevalence -26.6, YLDs -16.2), while the lowest was rate from refraction and accommodation disorders in the observed in Somalia (prevalence -1.6, YLDs -2.0). EMR in 1990 amounted to 263.3 (95% UI 174.3–395.6) per A descending trend in the age-standardized prevalence 100,000 males and 337.9 (95% UI 221.9–518.7) per 100,000 and YLDs rates for vision loss was noted among both sexes females. In 2015, YLDs attributed to refraction and accom- from 1990 to 2015 (Fig. 2). modation disorders in the EMR were 231.9 (95% UI Fig. 1 Age-standardized prevalence and years lived with disability (YLDs) rate of vision loss in Eastern Mediterranean Region countries in 1990 and 2015 (Global Burden of Disease Study 2015, Eastern Mediterranean Countries, 1990–2015) 123 S202 GBD 2015 Eastern Mediterranean Region Vision Loss Collaborators Table 1 Age-standardized prevalence and years lived with disability rate per 100,000 population of vision loss in the Eastern Mediterranean Region in 1990 and 2015 (Global Burden of Disease Study 2015, Eastern Mediterranean Countries, 1990–2015) Location Prevalence (%) Percent YLDs per 100,000 population Percent change change 1990 2015 1990 2015 Value 95% UI Value 95% UI Value 95% UI Value 95% UI Lower Upper Lower Upper Lower Upper Lower Upper Eastern 18.2 17.5 19 15.5 14.8 16.2 -15.1 536.9 378.5 746 482.3 342.5 667.8 -10.2 Mediterranean Region Afghanistan 23.8 21.9 25.8 20.7 19.1 22.4 -12.9 547.1 374.5 785.5 499 341.9 711.6 -8.8 Bahrain 15.5 14.3 16.9 13.2 12.2 14.4 -14.7 454.2 318.6 631.1 412.6 290.3 573.3 -9.2 Djibouti 15.6 13.9 17.5 14.1 12.5 15.7 -10.2 450.2 312.3 627.6 421.1 291.2 587.5 -6.5 Egypt 21.1 20.3 21.9 18.1 17.3 18.8 -14.5 642.7 456.6 893.5 586.8 418.2 807.3 -8.7 Iran 15.3 14.7 15.9 12.3 11.8 12.9 -19.5 468.3 331.2 647 413.2 295.4 563.9 -11.8 Iraq 18.9 17.4 20.6 16.1 14.8 17.6 -14.7 495.3 339.9 697 449.2 312.2 636.2 -9.3 Jordan 17.3 15.9 18.7 14.5 13.3 15.8 -16.1 473.9 329.1 667.6 429 299.7 596 -9.5 Kuwait 14.3 13.3 15.5 12.4 11.4 13.4 -13.7 436.2 305.6 604.9 398.8 280.1 552.1 -8.6 Lebanon 13.3 12.8 13.9 11.2 10.7 11.6 -16.1 319.4 220.9 457.4 290.6 202.7 408.5 -9 Libya 16.5 15.3 18 14.2 13.2 15.4 -14 439.8 310.3 613.3 400.3 283.8 556.6 -9 Morocco 22.7 21.9 23.5 19.2 18.5 19.9 -15.3 536.5 373.2 770.7 480.1 335.1 677.7 -10.5 Oman 19.3 17.9 20.8 14.1 13.2 15.3 -26.6 602.4 434.9 824.1 505 364.4 683.1 -16.2 Pakistan 16 15.3 16.8 14.1 13.4 14.8 -12.3 555.3 395.6 760.1 514.7 368.2 699 -7.3 Palestine 17.6 16.3 19 15.3 14.1 16.5 -13.3 392.7 267.6 574.1 360.4 249.3 517.5 -8.2 Qatar 15 14 16.1 12.6 11.8 13.5 -15.7 414.5 290.7 577.6 373.3 261.2 515.5 -9.9 Saudi Arabia 18.2 17.5 18.9 15 14.4 15.7 -17.4 451.8 310.1 644.2 402.3 275.8 569.2 -11 Somalia 18.9 16.8 21.2 18.6 16.6 20.8 -1.6 487.1 335.3 690.9 477.2 329.9 671 -2 Sudan 21.3 19.7 23.1 18.3 16.8 20 -14.1 524.5 360.6 744.2 476.1 327.7 669.7 -9.2 Syria 14.7 13.9 15.6 12.5 11.8 13.4 -14.7 458.8 321.9 637.8 416.7 294.7 574.1 -9.2 Tunisia 16.1 15.5 16.7 13.3 12.8 13.8 -17.6 402.3 280.7 571.8 364 254.4 506 -9.5 United Arab 18.8 17.7 19.9 14.2 13.4 15.2 -24.4 478.5 329 678.5 408.6 284.8 572.7 -14.6 Emirates Yemen 24.8 23 26.8 19.2 17.8 20.7 -22.8 611.7 425.3 870.5 522.5 367.4 726.7 -14.6 UI uncertainty interval, YLDs years lived with disability 154.4–344.7) per 100,000 males and 296.4 (95% UI Age-standardized YLDs attributed to cataract in the 195.4–446.4) per 100,000 females. In 1990 and 2015, Egypt EMR in 1990 were 97.9 (95% UI 70.3–132.7) per 100,000 had the highest age-standardized YLDs per 100,000 person, population in males and 124.4 (95% UI 89.0–168.3) per and Lebanon had the lowest (ESM_2). 100,000 population in females. In 2015, the corresponding values were 84.9 (95% UI 60.6–113.9) per 100,000 popu- Cataract lation in males and 113.6 (95% UI 81.6–152.5) per 100,000 population in females (ESM_3). The highest rate of YLDs The age-standardized prevalence of cataract in the EMR per 100,000 population for cataract were observed in was 1.5% (95% UI 1.3–1.6%) among males and 1.8% Pakistan, and the lowest in Lebanon both in 1990 and 2015. (95% UI 1.6–2.0%) among females in 1990. The corre- sponding values were 1.3% (95% UI 1.2–1.5%) in males Glaucoma and 1.7% (95% UI 1.5–1.9%) in females in 2015 (ESM_3). Cataract was most prevalent in Pakistan and least prevalent In both 1990 and 2015, the highest age-standardized in Libya in both 1990 and 2015. prevalence of glaucoma was observed in Egypt, and the 123 Burden of vision loss in the Eastern Mediterranean region, 1990–2015… S203 Fig. 2 Trends in age-standardized prevalence and years lived with disability (YLDs) rate of vision loss by gender in the Eastern Mediterranean Region from 1990 to 2015 (Global Burden of Disease Study 2015, Eastern Mediterranean Region, 1990–2015) lowest was reported in Afghanistan. Total age-standardized 5.6–11.2) per 100,000 males and 9.0 (95% UI 6.2–12.6) per prevalence of glaucoma in the EMR was 0.1% (95% UI 100,000 females in 2015 (ESM_5). In both 1990 and 2015, 0.1–0.1%) in males and 0.2% (95% UI 0.1–0.2%) in Oman had the highest and Somalia had the lowest YLDs females in 1990, and 0.1% (95% UI 0.1–0.1%) in males attributed to macular degeneration. and 0.2% (95% UI 0.1–0.2%) in females in 2015 (ESM_4). In 1990, glaucoma accounted for 10.7 age-standardized Other causes of vision loss YLDs (95% UI 7.3–14.8) per 100,000 for males and 15.4 age-standardized YLDs (95% UI 10.5–21.1) per 100,000 Saudi Arabia had the highest prevalence of other causes of for females in the EMR. The rate of age-standardized vision loss, and Somalia had the lowest. In 1990, the age- YLDs for glaucoma in 2015 was 11.5 (95% UI 7.9–16.1) standardized prevalence of other causes of vision loss was per 100,000 for males and 16.7 (95% UI 11.6–23.1) per 0.4% (95% UI 0.4–0.4%) in males and 0.5% (95% UI 100,000 females in this region (ESM_4). YLDs attributed 0.4–0.5%) in females. Corresponding values were 0.5% to glaucoma were highest in Oman and lowest in Pakistan (95% UI 0.4–0.5%) in males and 0.5% (95% UI 0.4–0.5%) in 1990, and highest in Egypt and lowest in Lebanon in in females in 2015 (ESM_6). 2015. Oman had the largest burden of age-standardized YLDs rate for other causes of vision loss and Lebanon had the Macular degeneration smallest in both 1990 and 2015. Age-standardized YLDs were 34.9 (95% UI 24.7–47.6) per 100,000 males and 35.5 The age-standardized prevalence of macular degeneration (95% UI 25.0–47.8) per 100,000 females in 1990, and 37.7 in the EMR was 0.1% (95% UI 0.1–0.1%) among males (95% UI 26.8–51.0) per 100,000 males and 38.6 (95% UI and 0.1% (95% UI 0.1–0.1%) among females in 1990. In 27.2–51.8) per 100,000 females in 2015 (ESM_6). 2015, the corresponding values were 0.1% (0.1–0.1%) in males and 0.1% (95% UI 0.1–0.1%) in females in 2015 Age-speciﬁc prevalence of the leading causes (ESM_5). Among the 22 countries, Kuwait had the highest of vision loss and Afghanistan had the lowest prevalence of macular degeneration in 1990. However, macular degeneration was The main causes of vision loss, including cataract, glau- most prevalent in Oman and least prevalent in Somalia in coma, macular degeneration, and the category ‘‘other 2015. causes of vision loss’’ were most prevalent in the popula- The age-standardized YLDs rate associated with mac- tion aged 80 and older in both 1990 and 2015. The highest ular degeneration in the EMR was 6.0 (95% UI 4.1–8.3) prevalence of refraction and accommodation disorders was per 100,000 for males and 6.5 (95% UI 4.5–9.1) per noted among people aged 70–74 years in 1990 and 2015 100,000 for females in 1990, increasing to 8.1 (95% UI (Fig. 3). 123 S204 GBD 2015 Eastern Mediterranean Region Vision Loss Collaborators Fig. 3 Age-speciﬁc prevalence (a, b) and years lived with disability (YLDs) rate (c, d) for causes of vision loss in Eastern Mediterranean Region at two time points (1990 and 2015) (Global Burden of Disease Study 2015, Eastern Mediterranean Region, 1990, 2015) Leading causes of age-speciﬁc YLDs rate for vision Discussion loss This is the ﬁrst report on the burden of vision loss in the Figure 3 shows the highest YLDs rates for cataract, glau- EMR countries during 1990–2015 (GBD 2015). Our ﬁnd- coma, macular degeneration, and other causes of vision ings indicated a decline in the age-standardized and age- loss in the population aged 80 or older in 1990 and 2015. speciﬁc prevalence and YLDs rate of vision loss from 1990 The highest rate of YLDs for refraction and accommoda- to 2015. However, vision loss still presents a burden in the tion disorders was demonstrated in the age group region and needs to be addressed in health policies. 70–74 years in 1990 and 2015 (Fig. 3). Our ﬁndings on trends were compatible with the results of the Khairallah et al. study, which showed a descending Association of SDI and changes in age-standardized trend in age-standardized prevalence of blindness and prevalence and YLDs rate of vision loss moderate and severe VI in the Middle East and North Africa from 1990 to 2010 (Khairallah et al. 2014). Despite For each 0.1 unit increase in SDI, the age-standardized a declining trend in age-standardized prevalence and YLDs prevalence of vision loss due to all causes showed a 1.5% rate of vision loss over the past 25 years in the EMR, a reduction using a multilevel linear model (p\ 0.001). wide disparity among the 22 countries in this region was Corresponding values for each cause are presented in demonstrated in terms of vision loss prevalence and YLDs Table 2 and Fig. 4. rate. This can be explained by the difference in socio-de- For each 0.1 unit increase in SDI, a 23.9 per 100,000 mographic conditions and capacities of health systems in population reduction in the age-standardized YLDs rate for these countries (Mandil et al. 2013; Mokdad et al. 2014). vision loss due to all causes was noted using a multilevel On the other hand, in recent years, a number of EMR linear model (p \ 0.001). Cause-speciﬁc YLDs are shown countries have been involved in conﬂicts and wars, in Table 2 and Fig. 4. resulting in limited health resources (Mokdad et al. 2016). Unfavorable and unstable socioeconomic conditions can Ratio of observed-to-expected prevalence and YLDs also lead to a lack of strategic plans and operational pro- of vision loss based on SDI grams for the prevention and treatment of VI and blindness. The EMR had a higher age-standardized prevalence and ESM_7 shows that United Arab Emirates had the highest YLDs rate of vision loss compared to the global rate and and Syria had the lowest observed-to-expected ratio (O/E) ranked third following the Southeast Asia and Africa for prevalence of vision loss due to all causes based on regions in 2015. Stevens et al. reported a greater than 4% SDI. The highest O/E YLDs ratio was noted in the Egypt, prevalence of blindness in older adults in Western sub- whereas Lebanon had the lowest ratio (ESM_8). Saharan Africa, Eastern sub-Saharan Africa, the EMR, and 123 Burden of vision loss in the Eastern Mediterranean region, 1990–2015… S205 Table 2 Association of Socio- Metric Cause of vision loss Estimate 95% UI p value demographic Index and changes in age-standardized prevalence Lower Upper and years lived with disability rate of vision loss from 1990 to Prevalence All causes -1.51 -1.59 -1.43 \0.001 2015 in the Eastern Refraction and accommodation disorders -1.46 -1.53 -1.39 \0.001 Mediterranean Region (Global Cataract -0.04 -0.05 -0.03 \0.001 Burden of Disease Study 2015, Glaucoma 0.00 0.00 0.01 \0.001 Eastern Mediterranean Region, 1990–2015) Macular degeneration 0.01 0.01 0.01 \0.001 Other vision loss 0.02 0.01 0.02 \0.001 YLDs All causes -23.94 -26.68 -21.20 \0.001 Refraction and accommodation disorders -17.89 -19.11 -16.67 \0.001 Cataract -4.41 -5.42 -3.40 \0.001 Glaucoma 0.25 0.07 0.42 0.007 Macular degeneration 0.90 0.81 0.98 \0.001 Other vision loss 0.88 0.50 1.27 \0.001 SDI socio-demographic index, UI uncertainty interval, YLDs years lived with disability Fig. 4 Association of Socio-demographic Index (SDI) and changes disorders (b), cataract (c), glaucoma (d), macular degeneration (e), in age-standardized prevalence and years lived with disability (YLDs) and other causes of vision loss (f) (Global Burden of Disease Study rate of all-cause vision loss (a), refraction and accommodation 2015, Eastern Mediterranean Region, 2015) South Asia in 2010 (Stevens et al. 2013). However, the reporting on the EMR (Abou-Gareeb et al. 2001; GBD highest reduction was observed in this region from 1990 to 2015; Hashemi et al. 2012; Jadoon et al. 2006; Khairallah 2015 compared to all six world regions. et al. 2014; Rajavi et al. 2016; Stevens et al. 2013; WHO With regard to gender disparity, females were more 2007). The gender disparity might be due to allocation of affected by vision loss in the EMR, consistent with the less family ﬁnancial resources, resulting in limited access global ﬁndings of the GBD 2015 study and other studies to eye care services for females (Hashemi et al. 2012; 123 S206 GBD 2015 Eastern Mediterranean Region Vision Loss Collaborators Stevens et al. 2013). This inequality may be attributed to acceptability of these resources in low socioeconomic areas cultural backgrounds which could be overcome by pro- (Mundy et al. 2016). moting awareness and education in affected societies. Glaucoma was the third-leading cause of vision loss in the Our results follow previous global and regional studies EMR. A slightly ascending trend of age-standardized that reported refraction and accommodation disorders, prevalence and the rate of YLDs from glaucoma were cataract, glaucoma, and macular degeneration as the main observed over our study period. This ﬁnding follows the causes of vision loss (GBD 2015; Khairallah et al. 2014; global results in the GBD 2015 study (GBD 2015). A meta- Katibeh et al. 2017a, b;Ko¨berlein et al. 2013; Naidoo et al. analysis by Bourne et al. showed an increased percentage of 2014; Keeffe et al. 2014). Among these, refraction and blindness due to glaucoma from 1990 to 2010 globally, with accommodation disorders remained the most prevalent in no signiﬁcant difference between regions (Bourne et al. the EMR from 1990 to 2015. A similar global-scale ﬁnding 2016). We also found that the slightly increasing age-stan- was reported in the GBD 2015 study and WHO global data dardized YLDs rate of glaucoma (0.25 per 100,000 person) 2010 (GBD 2015; Pascolini and Mariotti 2012; Bourne was associated with the improved SDI score (by 0.1 unit). et al. 2013; Resnikoff et al. 2008; Naidoo et al. 2016). Given the increasing trend of vision loss due to glaucoma, a However, a decreasing trend in age-standardized preva- number of issues should be considered for public health lence and YLDs rate due to refraction and accommodation planning. First, glaucoma and macular degeneration are disorders was observed in this region. There was a 1.46% responsible for the majority of irreversible blindness in the reduction in age-standardized prevalence and 17.89 per world. One out of 15 cases of blindness and one out of 45 100,000 population reduction in YLDs from refraction and cases of VI were due to glaucoma by 2010 (Bourne et al. accommodation disorders per 0.1 unit improvement in SDI 2016). Early diagnosis and proper medical and surgical score in the current study. Refraction and accommodation management can prevent blindness due to glaucoma. Sec- disorders had a considerable impact on the socioeconomic ondly, the Bourne et al. study also revealed that regions with condition of the affected persons and their families via younger populations had lower percentages of blindness due limiting educational and employment opportunities, to glaucoma compared to high-income regions with older resulting in productivity loss (Naidoo and Jaggernath 2012; populations (Bourne et al. 2016). Tham et al. demonstrated Smith et al. 2009). A large amount of vision loss can be the highest prevalence of glaucoma in Africa (primary open- potentially prevented and cured through developing and angle glaucoma 4.20%) and Asia (primary angle-closure implementing national screening programs and cost-effec- glaucoma 1.20%) in 2013 (Tham et al. 2014). Therefore, tive interventions (WHO 2013). considering increasing life expectancy, the prevalence of VI Cataract was the second-ranked cause of vision loss in due to glaucoma is expected to increase in the EMR in the the EMR in both 1990 and 2015, with female predomi- future. Clinical and targeted screening would be appropriate nance that was compatible with global ﬁndings from the approaches for preventing vision loss due to glaucoma GBD 2015 study (GBD 2015). The global WHO report (Mohammadi et al. 2014). also indicated that cataracts accounted for 33% of VI and Macular degeneration was the fourth-leading cause of 51% of blindness in 2010 (Pascolini and Mariotti 2012). vision loss in terms of prevalence and YLDs rate in the Considering the geographic location of EMR countries, EMR. An increasing trend was observed in age-standard- ultraviolet radiation may play a role in the high prevalence ized prevalence and rate of YLDs due to macular degen- of cataract in this region (McCarty and Taylor 2002). eration in both sexes. Our ﬁnding is consistent with the Cataract can be treated simply with a timely and cost- global results from GBD 2015 and the meta-analysis from effective intervention which would result in favorable 1990 to 2010 (GBD 2015; Jonas et al. 2014). This meta- visual outcomes; therefore it is categorized as a pre- analysis demonstrated a lower prevalence of macular ventable cause of blindness (Pascolini and Mariotti 2012; degeneration in regions with younger populations in com- WHO 2013). We found a signiﬁcant correlation between parison with high-income regions (Jonas et al. 2014). Our the improvement of SDI score (by 0.1 unit) and the 0.04% study also showed that the increase in age-standardized reduction in age-standardized prevalence and 4.41 per prevalence (0.01%) and YLDs rate (0.9 per 100,000 per- 100,000 population reduction in the rate of YLDs from son) of macular degeneration from 1990 to 2015 was vision loss due to cataract in the EMR, which was in line associated with the improvement of SDI score (by 0.1 with the Mundy et al. study. They reviewed the literature to unit). With regard to the aging population and availability report the association of cataract care with socioeconomic of effective interventions, especially intravitreal anti-vas- parameters in both developed and developing countries. cular endothelial growth factor drugs, macular degenera- These parameters can lead to limited access to primary eye tion may be recognized as an important public eye health care services. Promotion of education can improve the issue for future planning (Jonas et al. 2014). 123 Burden of vision loss in the Eastern Mediterranean region, 1990–2015… S207 Institute for Health Metrics and Evaluation, University of Washing- Our study has a few limitations. Vision loss due to ton, Seattle, Washington, United States. Nicholas J. Kassebaum, MD, diabetes mellitus is considered part of the diabetes burden Institute for Health Metrics and Evaluation, University of Washing- and is not included in our study (Moradi-Lakeh et al. ton, Seattle, Washington, United States; Department of Anesthesiol- 2017). Considering the high prevalence of diabetes in ogy and Pain Medicine, Seattle Children’s Hospital, United States. Helen E. Olsen, MA, Institute for Health Metrics and Evaluation, EMR, the burden of VI may be higher than what is esti- University of Washington, Seattle, Washington, United States. Jeffrey mated in this study (Katibeh et al. 2017a, b; Khandekar D. Stanaway, PhD, Institute for Health Metrics and Evaluation, 2012; WHO 2016). Some of the countries in the region do University of Washington, Seattle, Washington, United States. Hai- not have appropriate data on the epidemiology of low dong Wang, PhD, Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States. Katie vision or have used nonstandard methods for measuring Wilson, MLIS, Institute for Health Metrics and Evaluation, Univer- and reporting vision loss. We used the GBD general sity of Washington, Seattle, Washington, United States. Gebre methodology to produce more accurate estimates using Yitayih, MS, Mekelle University, Mekelle, Ethiopia. Ayman Al- different study-level or country-level covariates. Eyadhy, MD, King Saud University, Riyadh, Saudi Arabia. Khurshid Alam, PhD, Murdoch Childrens Research Institute, The University of Melbourne, Parkville, Victoria, Australia; The University of Mel- Conclusions bourne, Melbourne, VIC, Australia. Deena Alasfoor, MSc, Ministry of Health, Al Khuwair, Muscat, Oman. Reza Alizadeh-Navaei, PhD, The current study provides an up-to-date estimation based Gastrointestinal Cancer Research Center, Mazandaran University of Medical Sciences, Sari, Iran. Rajaa Al-Raddadi, PhD, Joint Program on the GBD 2015 study, demonstrating a high prevalence of Family and Community Medicine, Jeddah, Saudi Arabia. Ubai and high rate of YLDs due to vision loss with a decreasing Alsharif, MPH, Charite Universita¨tsmedizin, Berlin, Germany. Khalid trend in the EMR. Our ﬁndings call for developing and A. Altirkawi, MD, King Saud University, Riyadh, Saudi Arabia. implementing programs to manage refraction and accom- Nahla Anber, PhD, Mansoura University, Mansoura, Egypt. Hossein Ansari, PhD, Health Promotion Research Center, Department of modation disorders and cataract due to their large burden. Epidemiology and Biostatistics, Zahedan University of Medical Sci- There is a need for balance between prevention and treat- ences, Zahedan, Iran. Palwasha Anwari, MD, Self-employed, Kabul, ment programs to reduce the burden of vision loss in the Afghanistan. Hamid Asayesh, PhD, Department of Medical Emer- region. This can be achieved by developing and imple- gency, School of Paramedic, Qom, Iran; University of Medical Sci- ences, Qom, Iran; Solomon Weldegebreal Asgedom, PhD, Mekelle menting a national operational program and involving all University, Mekelle, Ethiopia. Tesfay Mehari Atey, MS, Mekelle related stakeholders. Education campaigns might be useful University, Mekelle, Ethiopia. Umar Bacha, PhD, School of Health to promote public awareness. Sciences, University of Management and Technology, Lahore, Pak- istan. Aleksandra Barac, PhD, Faculty of Medicine, University of GBD 2015 Eastern Mediterranean Region Vision Loss Collabo- Belgrade, Belgrade, Serbia. Neeraj Bedi, MD, College of Public rators: Ali H. Mokdad, PhD (corresponding author), Institute for Health and Tropical Medicine, Jazan, Saudi Arabia. Zahid A. Butt, Health Metrics and Evaluation, University of Washington, Seattle, PhD, Al Shifa Trust Eye Hospital, Rawalpindi, Pakistan. Abdulaal A. Washington, United States. Sare Saﬁ, MS, Ophthalmic Epidemiology Chitheer, MD, Ministry of Health, Baghdad, Iraq. Shirin Djalalinia, Research Center, Shahid Beheshti University of Medical Sciences, PhD, Undersecretary for Research and Technology, Ministry of Tehran, Iran. Hamid Ahmadieh, MD, Opthalmic Research Center, Health and Medical Education, Tehran, Iran. Huyen Do Phuc, MSc, Shahid Beheshti University of Medical Sciences, Tehran, Iran. Mar- Institute for Global Health Innovations, Duy Tan University, Da zieh Katibeh, MD, Center for Global Health, Aarhus University, Nang, Vietnam. Babak Eshrati, PhD, Ministry of Health and Medical Aarhus, Denmark. Mehdi Yaseri, PhD, Department of Epidemiology Education, Tehran, Iran; Arak University of Medical Sciences, Arak, and Biostatistics, School of Public Health, Tehran University of Iran. Maryam S. Farvid, PhD, Department of Nutrition, Harvard T. H. Medical Sciences, Tehran, Iran. Alireza Ramezani, MD, Ophthalmic Chan School of Public Health, Harvard University, Boston, MA, Epidemiology Research Center, Shahid Beheshti University of United States; Harvard/MGH Center on Genomics, Vulnerable Pop- Medical Sciences, Tehran, Iran. Saeid Shahraz, MD, Tufts Medical ulations, and Health Disparities, Mongan Institute for Health Policy, Center, Boston, MA, United States. Maziar Moradi-Lakeh, MD, Massachusetts General Hospital, Boston, MA, United States. Farshad Department of Community Medicine, Preventive Medicine and Farzadfar, MD, Non-communicable Diseases Research Center, Teh- Public Health Research Center, Gastrointestinal and Liver Disease ran University of Medical Sciences, Tehran, Iran. Seyed-Mohammad, Research Center (GILDRC), Iran University of Medical Sciences, - Fereshtehnejad, PhD, Department of Neurobiology, Care Sciences Tehran, Iran. Ibrahim Khalil, PhMD, Institute for Health Metrics and and Society (NVS), Karolinska Institutet, Stockholm, Sweden. Flo- Evaluation, University of Washington, Seattle, Washington, United rian Fischer, PhD, School of Public Health, Bielefeld University, States. Charbel El Bcheraoui, PhD, Institute for Health Metrics and Bielefeld, Germany. Tsegaye Tewelde Gebrehiwot, MPH, Jimma Evaluation, University of Washington, Seattle, Washington, United University, Jimma, Ethiopia. Randah Ribhi Hamadeh, Arabian Gulf States. Michael Collison, BS, Institute for Health Metrics and Eval- University, Manama, Bahrain. Samer Hamidi, DPhil, Hamdan Bin uation, University of Washington, Seattle, Washington, United States. Mohammed Smart University, Dubai, United Arab Emirates. Tarig B. Adrienne Chew, ND, Institute for Health Metrics and Evaluation, Higazi, PhD, The Ohio University, Zanesville, Ohio, United States. University of Washington, Seattle, Washington, United States. Farah Mohamed Hsairi, MD, Department of Epidemiology, Salah Azaiz Daoud, BA/BS, Institute for Health Metrics and Evaluation, Univer- Institute, Tunis, Tunisia. Aida Jimenez-Corona, PhD, Department of sity of Washington, Seattle, Washington, United States. Kristopher J. Ocular Epidemiology and Visual Health, Institute of Ophthalmology Krohn, BA, Institute for Health Metrics and Evaluation, University of Conde de Valencia, Mexico City, Mexico; General Directorate of Washington, Seattle, Washington, United States. Zane Rankin, BA/ Epidemiology, Ministry of Health, Mexico City, Mexico. Denny BS, Institute for Health Metrics and Evaluation, University of John, MPH, International Center for Research on Women, New Delhi, Washington, Seattle, Washington, United States. Ashkan Afshin, MD, India. Jost B. Jonas, MD, Department of Ophthalmology, Medical 123 S208 GBD 2015 Eastern Mediterranean Region Vision Loss Collaborators Faculty Mannheim, Ruprecht-Karls-University Heidelberg, Man- MD, Sina Trauma and Surgery Research Center, Tehran University of nheim, Germany. Amir Kasaeian, PhD, Hematology-Oncology and Medical Sciences, Tehran University of Medical Sciences, Tehran, Stem Cell Transplantation Research Center, Tehran, Iran; University Iran. Abdallah M. Samy, PhD, Ain Shams University, Cairo, Egypt. of Medical Sciences, Tehran, Iran; Endocrinology and Metabolism Benn Sartorius, PhD, Public Health Medicine, School of Nursing and Population Sciences Institute, Tehran University of Medical Sciences, Public Health, University of KwaZulu-Natal, Durban, South Africa; Tehran, Iran. Yousef Saleh, ScD, Department of Community Medi- UKZN Gastrointestinal Cancer Research Centre, South African cine, Public Health and Family Medicine, Jordan University of Sci- Medical Research Council (SAMRC), Durban, South Africa. Sadaf G. ence and Technology, Irbid, Jordan. Ejaz Ahmad Khan, MD, Health Sepanlou, PhD, Digestive Diseases Research Institute, Tehran Services Academy, Islamabad, Pakistan. Heidi J. Larson, PhD, University of Medical Sciences, Tehran, Iran. Masood Ali Shaikh, Department of Infectious Disease Epidemiology, London School of MD, Independent Consultant, Karachi, Pakistan. Eirini Skiadaresi, Hygiene and Tropical Medicine, London, United Kingdom; Institute MD, Hywel Dda University Health Board, Carmarthen, United for Health Metrics and Evaluation, University of Washington, Seattle, Kingdom. Badr H. A. Sobaih, MD, King Saud University, Riyadh, Washington, United States. Asma Abdul Latif, PhD, Department of Saudi Arabia. Rizwan Suliankatchi Abdulkader, MD, Ministry of Zoology, Lahore College for Women University, Lahore, Pakistan. Health, Kingdom of Saudi Arabia, Riyadh, Saudi Arabia. Hugh R. Raimundas Lunevicius, PhD, Aintree University Hospital National Taylor, AC, University of Melbourne, Carlton, Victoria, Australia. Health Service Foundation Trust, Liverpool, United Kingdom; School Arash Tehrani-Banihashemi, PhD, Preventive Medicine and Public of Medicine, University of Liverpool, Liverpool, United Kingdom. Health Research Center, Iran University of Medical Sciences, Tehran, Hassan Magdy Abd El Razek, MBBCH, Mansoura Faculty of Med- Iran. Mohamad-Hani Temsah, MD, King Saud University, Riyadh, icine, Mansoura, Egypt. Mohammed Magdy Abd El Razek, MBBCH, Saudi Arabia. Roman Topor-Madry, PhD, Institute of Public Health, Aswan University Hospital, Aswan Faculty of Medicine, Aswan, Faculty of Health Sciences, Jagiellonian University Medical College, Egypt. 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Uthman, PhD, Warwick Medical School, University of War- Miller, PhD, Paciﬁc Institute for Research and Evaluation, Calverton, wick, Coventry, United Kingdom. Tolassa Wakayo, MS, Jimma MD, United States; Centre for Population Health, Curtin University, University, Jimma, Ethiopia. Naohiro Yonemoto, MPH, Department Perth, WA, Australia. Seyed-Farzad Mohammadi, MD, Translational of Biostatistics, School of Public Health, Kyoto University, Kyoto, Ophthalmology Research Center, Farabi Eye Hospital, Tehran Japan. Mustafa Z. Younis, PH, Jackson State University, Jackson, University of Medical Sciences, Tehran, Iran. Vinay Nangia, MD, MS, United States. Maysaa El Sayed Zaki, PhD, Faculty of Medicine, Suraj Eye Institute, Nagpur, India. Cuong Tat Nguyen, MSc, Institute Mansoura University, Mansoura, Egypt. Aisha O. Jumaan, PhD, for Global Health Innovations, Duy Tan University, Da Nang, Viet- Independent Consultant, Seattle, Washington, United States. Theo nam. Quyen Le Nguyen, MD, Institute for Global Health Innovations, Vos, PhD, Institute for Health Metrics and Evaluation, University of Duy Tan University, Da Nang, Vietnam. Felix Akpojene Ogbo, MPH, Washington, Seattle, Washington, United States. Simon I. Hay, DSc, Centre for Health Research, Western Sydney University, Sydney, Oxford Big Data Institute, Li Ka Shing Centre for Health Information New South Wales, Australia. Farshad Pourmalek, PhD, University of and Discovery, University of Oxford, Oxford, London, United British Columbia, Vancouver, British Columbia, Canada. Mostafa Kingdom; Institute for Health Metrics and Evaluation, University of Qorbani, PhD, Non-communicable Diseases Research Center, Alborz Washington, Seattle, Washington, United States. Mohsen Naghavi, University of Medical Sciences, Karaj, Iran. Anwar Rafay, MS, PhD, Institute for Health Metrics and Evaluation, University of Contech International Health Consultants, Lahore, Pakistan; Contech Washington, Seattle, Washington, United States. Christopher J.L. School of Public Health, Lahore, Pakistan. Vafa Rahimi-Movaghar, Murray, DPhil, Institute for Health Metrics and Evaluation, Univer- MD, Sina Trauma and Surgery Research Center, Tehran University of sity of Washington, Seattle, Washington, United States. Medical Sciences, Tehran, Iran. Rajesh Kumar Rai, MPH, Society for Health and Demographic Surveillance, Suri, India. Saleem M. Rana, Compliance with ethical standards PhD, Contech School of Public Health, Lahore, Pakistan; Contech International Health Consultants, Lahore, Pakistan. David Laith Ethical approval This manuscript reﬂects original work that has not Rawaf, MD, WHO Collaborating Centre, Imperial College London, previously been published in whole or in part and is not under con- London, United Kingdom; North Hampshire Hospitals, Basingstroke, sideration elsewhere. All authors have read the manuscript and have United Kingdom. Salman Rawaf, MD, Imperial College London, agreed that the work is ready for submission and accept responsibility London, United Kingdom. Andre M.N. Renzaho, PhD, Western for its contents. The authors of this paper have complied with all Sydney University, Penrith, NSW, Australia. Satar Rezaei, PhD, ethical standards and do not have any conﬂicts of interest to disclose School of Public Health, Kermanshah University of Medical Sci- at the time of submission. The funding source played no role in the ences, Kermanshah, Iran. Gholamreza Roshandel, PhD, Golestan design of the study, the analysis and interpretation of data, and the Research Center of Gastroenterology and Hepatology, Golestan writing of the paper. The study did not involve human participants University of Medical Sciences, Gorgan, Iran; Digestive Diseases and/or animals; therefore, no informed consent was needed. Research Institute, Tehran University of Medical Sciences, Tehran, Iran. Mahdi Safdarian, MD, Sina Trauma and Surgery Research Conﬂict of interest The authors declare that they have no conﬂicts of Center, Tehran University of Medical Sciences, Tehran, Iran. Saeid interest. Saﬁri, PhD, Managerial Epidemiology Research Center, Department of Public Health, School of Nursing and Midwifery, Maragheh Funding This research was funded by the Bill & Melinda Gates University of Medical Sciences, Maragheh, Iran. 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