Causes of blindness and vision impairment in 2020 and trends over 30 years, and prevalence of avoidable blindness in relation to VISION 2020: the Right to Sight: an analysis for the Global Burden of Disease Study

Authors: GBD 2019 Blindness and Vision Impairment Collaborators

Geographical coverage: Worldwide

Sector: Epidemiolgy

Sub-sector: Trends of causes and prevalence of vision impairment and blindness.

Equity focus: Older populations

Study population: Adults aged 50 years and older

Review type: Other review

Quantitative synthesis method: Narrative synthesis and meta-analysis

Qualitative synthesis method: Not applicable

Background: Many causes of vision impairment can be prevented or treated. With an ageing global population, the demands for eye health services are increasing. The World Health Assembly Global Action Plan (WHA GAP) has set a target of a 25% global reduction from 2010 to 2019 in avoidable vision impairment, defined as cataract and under corrected refractive error.

Objectives: To estimate the prevalence and relative contribution of avoidable causes of blindness and vision impairment globally from 1990 to 2020, to compare the results with the World Health Assembly Global Action Plan (WHA GAP) target of a 25% global reduction from 2010 to 2019 in avoidable vision impairment, defined as cataract and under corrected refractive error.

Main findings:

Authors included 376 data sources reporting cause-specific disaggregated data, including at least one of the following: uncorrected refractive error, cataract, glaucoma, age-related macular degeneration, myopic macular degeneration or diabetic retinopathy. 230 of these were rapid assessment of avoidable blindness (RAABs).

The authors observed that the raw prevalence of moderate or worse avoidable vision impairment remained relatively stable in adults aged 50 and older between 2010 and 2019 (with a percentage change of -0.2% [95% UI -1.5 to 1.0]). However, it rose by 9.1% (7.6 to 10.7) across all age groups. The total number of cases of moderate or worse avoidable vision impairment increased by 29.2% (27.6 to 30.9) in those aged 50 and older, and by 20.8% (19.2 to 22.6) across all ages, resulting in a total of 254 million cases in 2019, up from 211 million in 2010. According to the authors, the prevalence of all moderate/worse avoidable vision impairment and avoidable MSVI saw little change during this period, but there was a decrease in avoidable blindness. While the age-standardized prevalence of avoidable MSVI remained unchanged, blindness decreased by 15.4%.Leading causes of blindness in adults aged 50 years and older were: cataract (15.2 million cases [95% UI 12.7-18.0]), followed by glaucoma (3.6 million cases [2.8-4.4]), under-corrected refractive error (2.3 million cases [1.8-2.8]), age-related macular degeneration (1.8 million cases [1.3-2.4]), and diabetic retinopathy (0.9 million cases [0.6-1.2]).

Leading causes of MSVI in adults aged 50 years and older stated by the review authors were: under-corrected refractive error (86.1 million cases [74.2-101.0]), followed by cataract (78.8 million cases [67.2-91.4]), age-related macular degeneration (6.2 million cases [5.0-7.6]), glaucoma (4.1 million cases [3.2-5.2]), and diabetic retinopathy (2.9 million cases [2.1-3.9]).

When authors assessed age-standardised prevalence of total blindness, cataract caused 45.5% (41.7-49.0) of all global blindness, followed by glaucoma (11.0% [9.3-12.8]), under-corrected refractive error (6.6% [5.6-7.8]), age-related macular degeneration (5.6% [4.3-7.0]) and diabetic retinopathy (2.5% [1.7-3.7]). The leading contributor to global age-standardised prevalence of adult MSVI was under-corrected refractive error (table 4; 41.0% [38.0-44.1]), followed by cataract (38.9% [35.6-42.4]), age-related macular degeneration (3.0% [2.5-3.5]), glaucoma (2.1% [1.7-2.5]), and diabetic retinopathy (1.4% [1·0-1.9]).

Based on the analysis of this review, authors suggest eye care services contributed to the observed reduction of age-standardised rates of avoidable blindness but not of MSVI, and that the target in an ageing global population was not reached. To conclude, authors note that both cataract and under-corrected refractive errors are among the three leading causes of blindness and MSVI in 2020.

Methodology: Preparation of data for this review consisted of a systematic review of published population-based studies of vision impairment and blindness. Eligible studies from this review were then combined with data from the RAAB studies and data from the US National Health and Nutrition Examination survey and the WHO Study on Global Aging and Adult Health.

This review used population-representative studies, primarily national and subnational cross-sectional surveys, to model cause-specific vision impairment. Studies were included if they used a vision chart that could be mapped onto the Snellen scale to measure visual acuity. Self-reported vision impairment studies were excluded. The review considered studies that measured either presenting or best-corrected vision impairment, or both, using WHO criteria for severity. It reported composite terms of Moderate or Severe Visual Impairment (MSVI) and moderate or worse vision impairment. Data inclusion for causes related to vision impairment and blindness had a minimum age of 20 years for cataract and diabetic retinopathy, and 45 years for glaucoma and age-related macular degeneration. Geographic restrictions were applied to impute zero prevalence for non-endemic locations.

A literature search was conducted for studies published between 1980 and 2018 on the following databases: EMBASE, SciELO, Medline, WHOLIS, and Open Grey, and additional grey literature sources.

Authors produced location, year, age and sex-specific estimates of moderate and severe visual impairment using disease modelling meta-regression, which is described elsewhere in more detail. Global estimates were produced with a mixed effects non-linear models using all available data to produce a global model to fit a fixed and random-effects one. Authors generated the final estimates by aggregation and stratified analysis by location and age. Authors applied adjustments if there were potential measurement errors using the meta-regression tool and for studies that used RAAB methodology or non-standard severity definitions. The estimation tool used made quantification of between-study heterogeneity.

Applicability/external validity:

Authors note that data sources for blindness and MSVI caused by myopic macular degeneration were mainly for China, therefore, reported estimates were solely related to China. Furthermore, data from children and young adults was from high income locations. Findings are applicable to people aged 50 years and older. Authors also report that the burden of total blindness due to cataract and uncorrected refractive error has notable regional variability, but it has not been fully addressed in any world region, including high income regions. In terms of LMIC countries, the authors specifically note that, “there remain several regions such as central sub-Saharan Africa, central and eastern Europe, and central Asia, with little or no population-based data where estimates rely on extrapolation from other regions”.

Geographic focus:

When looking at geographical trends, in 2020, authors found cataract the largest contributor to blindness in adults aged 50 years and older in all super-regions except for the high income super-region, where the largest contributor was glaucoma. This was primarily driven by two regions, western Europe (glaucoma: 32.5% [27.3 to 37.3] vs cataract: 11.4% [9.4 to 34.9]) and high income Asia Pacific (glaucoma: 33.7% [29.4 to 37.7] vs cataract: 20.5% [17.7 to 23.9]). For MSVI, cataract was the leading contributor in western and eastern sub-Saharan Africa, southeast Asia, Oceania, and north Africa and the Middle East. Cataract and under-corrected refractive error contributed similarly in central Asia, Andean Latin America, east Asia, and south Asia; under-corrected refractive error was the largest contributor everywhere else.

As noted above, some estimates for LMICs and associated regions will have been primarily generated by population studies undertaken in different settings.

Summary of quality assessment:

This review attempted to pool complex data from population-level surveys, searching a range of databases to identify published and unpublished studies. However, the review has important limitations. The search was not comprehensive enough to ensure that all available studies were identified. Authors did not report the methods used to screen studies for inclusion, extract data and quality assess included studies. Finally, it is not clear how the quality of studies impacts the findings of this review. Therefore, a low confidence was attributed in the conclusions about the effects of this review.