Abstract

BackgroundNear vision (NV) is essential to visual quality of individuals, and could be affected by different factors and changed gradually with the development of society. An update estimates is needed. Our study aims to investigate the age-trends in and sociodemographic characteristics associated with uncorrected near vision acuity (UNVA) in people ≥50 years in southern China.MethodsA population-based, cross-sectional survey on the eye health status of residents in both inland and coastal areas of Fujian Province, southern China was performed by Eye Institute and Affiliated Xiamen Eye Center of Xiamen University. People aged ≥50 years (10,044 subjects) in Fujian province were recruited according to the cluster sampling design by Fujian eye cross sectional study (FJES) group. The contents of the questionnaire survey included age, gender, education, occupation and other socioeconomic status. UNVA and slit lamp examination were performed for the participants in the field survey. Analysis of variance (ANOVA) was applied to compare the mean among groups of normally distributed parameters of UNVA and the chi-square (χ2) test was used to compare the proportion.ResultsAmong the baseline participants, 8,211 (81.8%) attended follow-up examinations. The sample had a mean age of 64.4 years [standard deviation (SD) =8.9], and 4,836 of the participants were female (58.9%). The average UNVA values for males and females were 0.29±0.18 and 0.28±0.17, respectively (P=0.000). UNVA gradually decreased with age and plateaued between 65 and 80 years old. There were significant differences in the mean values of UNVA associated with different occupations (P=0.000). UNVA was significantly different among people with different education levels (P=0.000). The average UNVA in people in coastal areas was 0.28, while that in people in inland areas was 0.29 (P=0.006). People in urban areas appeared to have better UNVA on average (0.29) than those in rural areas (0.27; P=0.000).ConclusionsAfter age 50, NV was reduced gradually. Age, gender, education, occupation, income and geographical factors may affect the NV performance of adults, which should be taken into account to achieve a good management of vision quality.

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