Global and Regional Risk Factors for Vision Impairment in 2020 and Multi-decadal Trends 1990-2020: A Meta-Analysis and Visual Display Based on Prevalence Data From the Global Burden of Disease study and Vision Loss Expert Group.
22 affiliations
- 1Imperial College, London, UK.
- 2Rothschild Foundation Hospital, Paris, France.
- 3Institute for Health Metrics and Evaluation, Seattle, Washington, USA.
- 4Centre for Translational Medicine, King's Health Partners, London, UK.
- 5University of Adelaide, Adelaide, South Australia, Australia.
- 6University of Michigan, Ann Arbor, Michigan, USA.
- 7University of Melbourne, Melbourne, Victoria, Australia.
- 8Massachusetts Eye and Ear Infirmary, Boston, Massachusetts, USA.
- 9Queen's University Belfast, Belfast, UK.
- 10Nova Southeastern University, Davie, Florida, USA.
- 11Beijing Tongren Hospital, Beijing, China.
- 12L V Prasad Eye Institute, Hyderabad, India.
- 13Universidade de Sao Paulo, Sao Paulo, Brazil.
- 14Tsinghua University, Beijing, China.
- 15Stanford University, Stanford, California, USA.
- 16Vita-Salute San Raffaele University, Milan, Italy.
- 17University of New South Wales, Sydney, New South Wales, Australia.
- 18University of Miami, Miami, Florida, USA.
- 19Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
- 20University of Arizona, Tucson, Arizona, USA.
- 21University of Oxford, Oxford, UK.
- 22Anglia Ruskin University, Cambridge, UK. [email protected].
Abstract
Purpose
To investigate global and regional risk factors for blindness and vision impairment pertaining to all geographical locations between 1990 and 2020.Methods
(1) Twenty-four covariates were selected with a potential link to vision impairment from the Global Burden of Disease Study (GBD) Covariates database as predictive factors. (2) From these, the linear association was investigated, with crude and age-standardised prevalence estimates of blindness and distance and near vision impairment in 2020 by using data for the whole population, sex and 5-year age groups, and by stratifying severity through mild, moderate, severe and total impairment. (3) Analysis investigated whether percentage rates of change in risk factors were associated with rates of change in prevalence in 1990-2020.Results
For adults (50+ years), for crude and age-standardised vision loss prevalence estimates for the year 2020, a significant negative association of smoking prevalence was found initially for all persons and for each sex, which appears to be due to ecological confounding and became a positive association using more granular regional and age group data. Maternal care and immunisation, sanitation proportion, Health Access and Quality Index and Socio-demographic Index were other significant age-standardised negative associations. Ophthalmologists/million population had a weak but significant protective effect, and positive associations were found for pollution (outdoor and indoor), stronger for greater vision impairment severities. Years in education per capita were weakly, negatively associated with vision loss prevalence, yet zero education proportion had a stronger but positive association for both sexes.Conclusions
This study confirmed associations at population level globally, which appear to be stable over decades. In addition, the study quantified the contribution of epidemiologically-based risk factors to vision loss at a GBD super-regional level, which is novel. This opens useful avenues for targeted intervention by policymakers. For example, reduction in sex inequity in blindness rates over 30 years has been positively associated with reducing overall prevalence of blindness.
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BibTeX
@article{bottone2026global,
title = {{Global and Regional Risk Factors for Vision Impairment in 2020 and Multi-decadal Trends 1990-2020: A Meta-Analysis and Visual Display Based on Prevalence Data From the Global Burden of Disease study and Vision Loss Expert Group.}},
author = {Michele Bottone and Jost Jonas and Jaimie Steinmetz and Tasanee Braithwaite and Robert Casson and Joshua Ehrlich and Hugh R Taylor and David Friedman and Nathan Congdon and John Kempen and Janet Leasher and Ningli Wang and Rohit Khanna and Tunde Peto and Joao M Furtado and Tien Y Wong and Mary E Hartnett and Maria V Cicinelli and Nina Tahhan and Van C Lansingh and Sophia Y Wang and Ian Tapply and Paul Briant and Theo Vos and Serge Resnikoff and Seth R Flaxman and Rupert R A Bourne and Vision Loss Expert Group of the Global Burden of Disease Study},
journal = {Ophthalmic \& physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists)},
year = {2026},
month = oct,
doi = {10.1007/s44402-026-00208-y},
url = {https://europepmc.org/article/MED/42888377},
note = {CC BY},
}
RIS
TY - JOUR
TI - Global and Regional Risk Factors for Vision Impairment in 2020 and Multi-decadal Trends 1990-2020: A Meta-Analysis and Visual Display Based on Prevalence Data From the Global Burden of Disease study and Vision Loss Expert Group.
AU - Michele Bottone
AU - Jost Jonas
AU - Jaimie Steinmetz
AU - Tasanee Braithwaite
AU - Robert Casson
AU - Joshua Ehrlich
AU - Hugh R Taylor
AU - David Friedman
AU - Nathan Congdon
AU - John Kempen
AU - Janet Leasher
AU - Ningli Wang
AU - Rohit Khanna
AU - Tunde Peto
AU - Joao M Furtado
AU - Tien Y Wong
AU - Mary E Hartnett
AU - Maria V Cicinelli
AU - Nina Tahhan
AU - Van C Lansingh
AU - Sophia Y Wang
AU - Ian Tapply
AU - Paul Briant
AU - Theo Vos
AU - Serge Resnikoff
AU - Seth R Flaxman
AU - Rupert R A Bourne
AU - Vision Loss Expert Group of the Global Burden of Disease Study
PY - 2026
DA - 2026/10/16
JO - Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists)
DO - 10.1007/s44402-026-00208-y
UR - https://europepmc.org/article/MED/42888377
AB - Purpose To investigate global and regional risk factors for blindness and vision impairment pertaining to all geographical locations between 1990 and 2020.Methods (1) Twenty-four covariates were selected with a potential link to vision impairment from the Global Burden of Disease Study (GBD) Covariates database as predictive factors. (2) From these, the linear association was investigated, with crude and age-standardised prevalence estimates of blindness and distance and near vision impairment in 2020 by using data for the whole population, sex and 5-year age groups, and by stratifying severity through mild, moderate, severe and total impairment. (3) Analysis investigated whether percentage rates of change in risk factors were associated with rates of change in prevalence in 1990-2020.Results For adults (50+ years), for crude and age-standardised vision loss prevalence estimates for the year 2020, a significant negative association of smoking prevalence was found initially for all persons and for each sex, which appears to be due to ecological confounding and became a positive association using more granular regional and age group data. Maternal care and immunisation, sanitation proportion, Health Access and Quality Index and Socio-demographic Index were other significant age-standardised negative associations. Ophthalmologists/million population had a weak but significant protective effect, and positive associations were found for pollution (outdoor and indoor), stronger for greater vision impairment severities. Years in education per capita were weakly, negatively associated with vision loss prevalence, yet zero education proportion had a stronger but positive association for both sexes.Conclusions This study confirmed associations at population level globally, which appear to be stable over decades. In addition, the study quantified the contribution of epidemiologically-based risk factors to vision loss at a GBD super-regional level, which is novel. This opens useful avenues for targeted intervention by policymakers. For example, reduction in sex inequity in blindness rates over 30 years has been positively associated with reducing overall prevalence of blindness.
SN - 0275-5408
SN - 1475-1313
ER -