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Impact of Area-Level Socioeconomic and Environmental Measures on Reduced Visual Acuity Among Children and Adolescents

PURPOSE: To assess the impacts of area-level socioeconomic and environmental measures on reduced visual acuity (VA). METHODS: This ecological study used the nationally representative cross-sectional data from the Chinese National Survey on Students’ Constitution and Health in 2014 (CNSSCH 2014), whi...

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Detalles Bibliográficos
Autores principales: Kai, Jia-Yan, Li, Dan-Lin, Hu, Hui-Hui, Zhang, Xiao-Feng, Pan, Chen-Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Association for Research in Vision and Ophthalmology 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10275385/
https://www.ncbi.nlm.nih.gov/pubmed/37314755
http://dx.doi.org/10.1167/iovs.64.7.23
Descripción
Sumario:PURPOSE: To assess the impacts of area-level socioeconomic and environmental measures on reduced visual acuity (VA). METHODS: This ecological study used the nationally representative cross-sectional data from the Chinese National Survey on Students’ Constitution and Health in 2014 (CNSSCH 2014), which included 261,833 participants aged 7 to 22 years randomly selected from 30 mainland provinces in China. Area-level socioeconomic measures assessed included gross domestic product (GDP), population density, density of hospital beds, and nighttime light data measured as the mean digital number (DN) of each region; environmental factors assessed included latitude, annual sunlight duration, and park green space density. The main outcome measure was the prevalence of reduced VA in each province of Mainland China. RESULTS: GDP (coefficient: 0.221; P < 0.001), mean DN (coefficient: 0.461; P < 0.001), latitude (coefficient: 0.093; P < 0.001), and annual sunlight duration (coefficient: 0.112; P < 0.001) were positively associated with the prevalence of reduced VA, while population density (coefficient: −0.256; P < 0.001), park green space per 10,000 people (coefficient: −0.145; P < 0.001), and number of hospital beds per 10,000 people (coefficient: −0.146; P < 0.001) were negatively associated with reduced VA prevalence. Factor analysis indicated a marginally nonsignificant positive correlation between socioeconomic factors and the prevalence of reduced VA (coefficient: 0.034; P = 0.07). CONCLUSIONS: Increased GDP and mean DN, which reflect economic development, were associated with a higher prevalence of reduced VA, while larger park green space and number of hospital beds per 10,000 people seemed to play a protective role, which could be targeted to design preventive strategies for myopia.