Literature DB >> 26395659

Visual Impairment in White, Chinese, Black, and Hispanic Participants from the Multi-Ethnic Study of Atherosclerosis Cohort.

Diana E Fisher1, Sandi Shrager2, Steven J Shea3, Gregory L Burke4, Ronald Klein5, Tien Y Wong6,7, Barbara E Klein5, Mary Frances Cotch1.   

Abstract

PURPOSE: To describe the prevalence of visual impairment and examine its association with demographic, socioeconomic, and health characteristics in the Multi-Ethnic Study of Atherosclerosis (MESA) cohort.
METHODS: Visual acuity data were obtained from 6134 participants, aged 46-87 years at time of examination between 2002 and 2004 (mean age 64 years, 47.6% male), from six communities in the United States. Visual impairment was defined as presenting visual acuity 20/50 or worse in the better-seeing eye. Risk factors were included in multivariable logistic regression models to determine their impact on visual impairment for men and women in each racial/ethnic group.
RESULTS: Among all participants, 6.6% (n = 421) had visual impairment, including 5.6% of men (n = 178) and 7.5% of women (n = 243). Prevalence of impairment ranged from 4.2% (n = 52) and 6.0% (n = 77) in white men and women, respectively, to 7.6% (n = 37) and 11.6% (n = 44) in Chinese men and women, respectively. Older age was significantly associated with visual impairment in both men and women, particularly in those with lower socioeconomic status, but the effects of increasing age were more pronounced in men. Two-thirds of participants already wore distance correction, and not unexpectedly, a lower prevalence of visual impairment was seen in this group; however, 2.4% of men and 3.5% of women with current distance correction had correctable visual impairment, most notably among seniors.
CONCLUSION: Even in the U.S. where prevalence of refractive correction is high, both visual impairment and uncorrected refractive error represent current public health challenges.

Entities:  

Keywords:  Multi-ethnic; prevalence; risk factors; uncorrected refractive error; visual impairment

Mesh:

Year:  2015        PMID: 26395659      PMCID: PMC4768912          DOI: 10.3109/09286586.2015.1066395

Source DB:  PubMed          Journal:  Ophthalmic Epidemiol        ISSN: 0928-6586            Impact factor:   1.648


  30 in total

1.  Factors associated with undercorrected refractive errors in an older population: the Blue Mountains Eye Study.

Authors:  S Thiagalingam; R G Cumming; P Mitchell
Journal:  Br J Ophthalmol       Date:  2002-09       Impact factor: 4.638

2.  Age-specific prevalence and causes of blindness and visual impairment in an older population: the Rotterdam Study.

Authors:  C C Klaver; R C Wolfs; J R Vingerling; A Hofman; P T de Jong
Journal:  Arch Ophthalmol       Date:  1998-05

3.  Cardiorespiratory fitness and vision loss among young and middle-age U.S. adults.

Authors:  Paul D Loprinzi; Nazlee Zebardast; Pradeep Y Ramulu
Journal:  Am J Health Promot       Date:  2014-04-09

4.  Correctable visual impairment in an older population: the blue mountains eye study.

Authors:  Suriya Foran; Kathryn Rose; Jie Jin Wang; Paul Mitchell
Journal:  Am J Ophthalmol       Date:  2002-11       Impact factor: 5.258

5.  Visual acuity impairment and mortality in US adults.

Authors:  David J Lee; Orlando Gómez-Marín; Byron L Lam; D Diane Zheng
Journal:  Arch Ophthalmol       Date:  2002-11

6.  Causes and prevalence of visual impairment among adults in the United States.

Authors:  Nathan Congdon; Benita O'Colmain; Caroline C W Klaver; Ronald Klein; Beatriz Muñoz; David S Friedman; John Kempen; Hugh R Taylor; Paul Mitchell
Journal:  Arch Ophthalmol       Date:  2004-04

Review 7.  Correctable visual impairment in older people: a major unmet need.

Authors:  Bruce J W Evans; Gillian Rowlands
Journal:  Ophthalmic Physiol Opt       Date:  2004-05       Impact factor: 3.117

8.  Prevalence and risk indicators of visual impairment and blindness in Latinos: the Los Angeles Latino Eye Study.

Authors:  Rohit Varma; Mei Ying-Lai; Ronald Klein; Stanley P Azen
Journal:  Ophthalmology       Date:  2004-06       Impact factor: 12.079

9.  Visual acuity and the causes of visual loss in Australia. The Blue Mountains Eye Study.

Authors:  K Attebo; P Mitchell; W Smith
Journal:  Ophthalmology       Date:  1996-03       Impact factor: 12.079

10.  Multi-Ethnic Study of Atherosclerosis: objectives and design.

Authors:  Diane E Bild; David A Bluemke; Gregory L Burke; Robert Detrano; Ana V Diez Roux; Aaron R Folsom; Philip Greenland; David R Jacob; Richard Kronmal; Kiang Liu; Jennifer Clark Nelson; Daniel O'Leary; Mohammed F Saad; Steven Shea; Moyses Szklo; Russell P Tracy
Journal:  Am J Epidemiol       Date:  2002-11-01       Impact factor: 4.897

View more
  6 in total

1.  Risk Factors for Visual Impairment in an Uninsured Population and the Impact of the Affordable Care Act.

Authors:  Weixia Guo; Maria A Woodward; Michele Heisler; Taylor Blachley; Leah Corneail; Jean Cederna; Ariane D Kaplan; Paula Anne Newman Casey
Journal:  Clin Surg       Date:  2016-12-07

2.  Visual acuity of urban and rural adults in a coastal province of southern China: the Fujian Eye Study.

Authors:  Yang Li; Qin-Rui Hu; Xiao-Xin Li; Yong-Hua Hu; Bin Wang; Xue-Ying Qin; Tao Ren
Journal:  Int J Ophthalmol       Date:  2022-07-18       Impact factor: 1.645

3.  Visual Field Loss Impacts Vision-Specific Quality of Life by Race and Ethnicity: The Multiethnic Ophthalmology Cohorts of California Study.

Authors:  Dominic J Grisafe; Roberta McKean-Cowdin; Bruce S Burkemper; Benjamin Y Xu; Mina Torres; Rohit Varma
Journal:  Ophthalmology       Date:  2022-01-10       Impact factor: 14.277

4.  Retinal Microvascular Caliber and Incident Depressive Symptoms: The Multi-Ethnic Study of Atherosclerosis.

Authors:  April C E van Gennip; Sanaz Sedaghat; Mercedes R Carnethon; Norrina B Allen; Barbara E K Klein; Mary Frances Cotch; Diana A Chirinos; Coen D A Stehouwer; Thomas T van Sloten
Journal:  Am J Epidemiol       Date:  2022-03-24       Impact factor: 5.363

5.  Frequency and source of prescription eyewear insurance coverage in Ontario: a repeated population-based cross-sectional study using survey data.

Authors:  Prem Nichani; Graham E Trope; Yvonne M Buys; Samuel N Markowitz; Sherif El-Defrawy; Gordon Ngo; Michelle Markowitz; Ya-Ping Jin
Journal:  CMAJ Open       Date:  2021-03-17

6.  Low prevalence of spectacle use in the Hungarian Roma population indicates unmet health needs.

Authors:  Gergely Losonczy; Peter Piko; B Jeroen Klevering; Zsigmond Kosa; Janos Sandor; Roza Adany
Journal:  Sci Rep       Date:  2022-03-09       Impact factor: 4.379

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.