Prevalence of Visual Acuity Loss or Blindness in the US: A Bayesian Meta-analysis.


Journal

JAMA ophthalmology
ISSN: 2168-6173
Titre abrégé: JAMA Ophthalmol
Pays: United States
ID NLM: 101589539

Informations de publication

Date de publication:
01 Jul 2021
Historique:
pubmed: 14 5 2021
medline: 21 4 2022
entrez: 13 5 2021
Statut: ppublish

Résumé

Globally, more than 250 million people live with visual acuity loss or blindness, and people in the US fear losing vision more than memory, hearing, or speech. But it appears there are no recent empirical estimates of visual acuity loss or blindness for the US. To produce estimates of visual acuity loss and blindness by age, sex, race/ethnicity, and US state. Data from the American Community Survey (2017), National Health and Nutrition Examination Survey (1999-2008), and National Survey of Children's Health (2017), as well as population-based studies (2000-2013), were included. All relevant data from the US Centers for Disease Control and Prevention's Vision and Eye Health Surveillance System were included. The prevalence of visual acuity loss or blindness was estimated, stratified when possible by factors including US state, age group, sex, race/ethnicity, and community-dwelling or group-quarters status. Data analysis occurred from March 2018 to March 2020. The prevalence of visual acuity loss (defined as a best-corrected visual acuity greater than or equal to 0.3 logMAR) and blindness (defined as a logMAR of 1.0 or greater) in the better-seeing eye. For 2017, this meta-analysis generated an estimated US prevalence of 7.08 (95% uncertainty interval, 6.32-7.89) million people living with visual acuity loss, of whom 1.08 (95% uncertainty interval, 0.82-1.30) million people were living with blindness. Of this, 1.62 (95% uncertainty interval, 1.32-1.92) million persons with visual acuity loss are younger than 40 years, and 141 000 (95% uncertainty interval, 95 000-187 000) persons with blindness are younger than 40 years. This analysis of all available data with modern methods produced estimates substantially higher than those previously published.

Identifiants

pubmed: 33983373
pii: 2779910
doi: 10.1001/jamaophthalmol.2021.0527
pmc: PMC8120442
doi:

Types de publication

Journal Article Meta-Analysis Research Support, U.S. Gov't, P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

717-723

Investigateurs

Kira N Baldonado (KN)
Clare Davidson (C)
Michelle C Dougherty (MC)
Michael R Duenas (MR)
David S Friedman (DS)
Kevin M Jackson (KM)
Charlotte E Joslin (CE)
Barbara E K Klein (BEK)
Phoebe A Lamuda (PA)
Yao Liu (Y)
Flora C Lum (FC)
Nnenna L Okeke (NL)
Nita P Sinha (NP)
Bonnielin K Swenor (BK)
Jeff P Todd (JP)
Emily Tolbert (E)

Commentaires et corrections

Type : CommentIn

Auteurs

Abraham D Flaxman (AD)

Institute for Health Metrics and Evaluation, University of Washington, Seattle.

John S Wittenborn (JS)

NORC at the University of Chicago, Chicago, Illinois.

Toshana Robalik (T)

Institute for Health Metrics and Evaluation, University of Washington, Seattle.

Rohit Gulia (R)

Institute for Health Metrics and Evaluation, University of Washington, Seattle.

Robert B Gerzoff (RB)

Applied Statistical Consulting LLC, Atlanta, Georgia.

Elizabeth A Lundeen (EA)

Division of Diabetes Translation, Vision Health Initiative Centers for Disease Control and Prevention, Atlanta, Georgia.

Jinan Saaddine (J)

Division of Diabetes Translation, Vision Health Initiative Centers for Disease Control and Prevention, Atlanta, Georgia.

David B Rein (DB)

NORC at the University of Chicago, Chicago, Illinois.

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