Literature DB >> 33386075

Prevalence and associated factors of vision loss in the South African National Health and Nutrition Examination Survey (SANHANES-1).

Emmanuel Kofi Addo1,2,3, Kwadwo Owusu Akuffo4, Ronel Sewpaul5, Natisha Dukhi5, Eldad Agyei-Manu1,6, Akosua Kesewah Asare1, David Ben Kumah1, Moses Awuni1, Priscilla Reddy5,7.   

Abstract

BACKGROUND: Vision loss is a major public health concern that significantly affects developing countries, including South Africa. Although existing literature have reported on the prevalence, causes, and impact of vision loss on the quality of life of affected individuals (children and adults) in parts of South Africa, there is no evidence of the prevalence and associated factors of vision loss in the general population. Hence, this study aimed to determine the prevalence of vision loss and its associated factors in South Africa using a population-based survey.
METHODS: Secondary analyses were conducted using data from the South African National Health and Nutrition Examination Survey (SANHANES-1), a population-based national health survey conducted from 2011 to 2012. Vision loss was defined as presenting visual acuity (PVA) worse than Snellen 6/12 in the better eye. Visual acuity was assessed by clinicians and participants' subjective response to vision-related questions. Univariate and multiple logistic regression models were used to examine the association of the independent variables with vision loss.
RESULTS: The analytic sample comprised 4346 individuals with a mean age of 39.1 years. Female sex accounted for 55.6% of the participants. The prevalence of vision loss among participants was 9.2% (95% CI: 7.7-10.9). Older age (45-54 years, OR = 2.99, p < 0.001; 55-64 years, OR = 5.78, p < 0.001 and ≥ 65 years, OR = 5.12, p < 0.001), female sex (OR = 1.50, p = 0.016), and previous diabetes diagnosis (OR = 2.28, p = 0.001) were significantly associated with increased odds of vision loss. Further, secondary school education (OR = 0.71, p = 0.031), white ethnicity (OR = 0.11, p = 0.007), residing in Mpumalanga province (OR = 0.12, p < 0.001) and having never had an eye examination (OR = 0.56, p = 0.003) were significantly associated with reduced odds of vision loss.
CONCLUSION: Almost one in ten participants had vision loss. Adopting strategies targeted at reducing barriers to the utilization of eye care services will promote early detection and management of blinding conditions, and thereby, decrease the burden of vision loss in South Africa.

Entities:  

Keywords:  Associated factors/determinants; Barriers; Disparities; Eyecare services; Prevalence; SANHANES; South Africa; Vision loss

Mesh:

Year:  2021        PMID: 33386075      PMCID: PMC7775629          DOI: 10.1186/s12886-020-01714-4

Source DB:  PubMed          Journal:  BMC Ophthalmol        ISSN: 1471-2415            Impact factor:   2.209


  65 in total

Review 1.  Perspective on genes and mutations causing retinitis pigmentosa.

Authors:  Stephen P Daiger; Sara J Bowne; Lori S Sullivan
Journal:  Arch Ophthalmol       Date:  2007-02

2.  Population-based survey of prevalence, causes, and risk factors for blindness and visual impairment in an aging Chinese metropolitan population.

Authors:  Jian-Yan Hu; Liang Yan; Yong-Dong Chen; Xin-Hua Du; Ting-Ting Li; De-An Liu; Dong-Hong Xu; Yi-Min Huang; Qiang Wu
Journal:  Int J Ophthalmol       Date:  2017-01-18       Impact factor: 1.779

3.  Access to health care in developing countries: breaking down demand side barriers.

Authors:  Owen O'Donnell
Journal:  Cad Saude Publica       Date:  2007-12       Impact factor: 1.632

4.  Potential lost productivity resulting from the global burden of uncorrected refractive error.

Authors:  T S T Smith; K D Frick; B A Holden; T R Fricke; K S Naidoo
Journal:  Bull World Health Organ       Date:  2009-06       Impact factor: 9.408

5.  A situational analysis of ocular health promotion in the South African primary health-care system.

Authors:  Hlupheka Lawrence Sithole
Journal:  Clin Exp Optom       Date:  2016-09-01       Impact factor: 2.742

6.  A Simple Method for Estimating the Economic Cost of Productivity Loss Due to Blindness and Moderate to Severe Visual Impairment.

Authors:  Kristen A Eckert; Marissa J Carter; Van C Lansingh; David A Wilson; João M Furtado; Kevin D Frick; Serge Resnikoff
Journal:  Ophthalmic Epidemiol       Date:  2015       Impact factor: 1.648

7.  Gender and blindness: a meta-analysis of population-based prevalence surveys.

Authors:  I Abou-Gareeb; S Lewallen; K Bassett; P Courtright
Journal:  Ophthalmic Epidemiol       Date:  2001-02       Impact factor: 1.648

8.  Preventing diabetes blindness: cost effectiveness of a screening programme using digital non-mydriatic fundus photography for diabetic retinopathy in a primary health care setting in South Africa.

Authors:  Taskeen Khan; Melanie Y Bertram; Ruxana Jina; Bob Mash; Naomi Levitt; Karen Hofman
Journal:  Diabetes Res Clin Pract       Date:  2013-06-22       Impact factor: 5.602

9.  Blindness and visual impairment in an urban West African population: the Tema Eye Survey.

Authors:  Donald L Budenz; Jagadeesh R Bandi; Keith Barton; Winifred Nolan; Leon Herndon; Julia Whiteside-de Vos; Graham Hay-Smith; Hanna Kim; James Tielsch
Journal:  Ophthalmology       Date:  2012-06-05       Impact factor: 12.079

10.  Why are we addressing gender issues in vision loss?

Authors:  Paul Courtright; Susan Lewallen
Journal:  Community Eye Health       Date:  2009-06
View more
  2 in total

1.  Vision loss, vision difficulty and psychological distress in South Africa: results from SANHANES-1.

Authors:  Kwadwo Owusu Akuffo; Ronel Sewpaul; Samson Darrah; Natisha Dukhi; David Ben Kumah; Eldad Agyei-Manu; Emmanuel Kofi Addo; Akosua Kesewah Asare; Isaiah Osei Duah; Priscilla Reddy
Journal:  BMC Psychol       Date:  2021-04-29

2.  Visual impairment and associated factors among pregnant women attending antenatal care units at health institutions in Gondar City Administration, Northwest Ethiopia.

Authors:  Mengistie Diress; Yitayeh Belsti; Mihret Getnet; Sofonias Addis Fekadu; Baye Dagnew; Yonas Akalu; Mohammed Abdu Seid; Yibeltal Yismaw Gela
Journal:  BMC Pregnancy Childbirth       Date:  2021-12-13       Impact factor: 3.007

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.