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Table 4 Effect of age, gender, occupation and literacy on visual impairment after best correction in better eye using Logistic regression model

From: Prevalence and causes of low vision and blindness in an elderly population in Nepal: the Bhaktapur retina study

Variable No visual impairment (%) (N = 1404) Visual impairment (%) (N = 456) Univariate analysis Multivariable analysis
    OR(95% CI) P value OR(95% CI) P value
Age(years)
 60–69 856(60.97) 94 (20.61) 1   1  
 70–79 466(33.19) 231(50.66) 4.51(3.46–5.88) < 0.001 4.27(3.26–5.58) < 0.001
  ≥ 80 82(5.84) 131 (28.73) 14.72(10.38–20.88) < 0.001 13.85(9.72–19.73) < 0.001
Gender:
 Men 629(44.80) 192 (42.11) 1   1  
 Women 775(55.19) 264 (57.89) 1.11(0.90–1.38) 0.308 1.04(0.80–1.35) 0.733
Occupation:
 Agricultural 992(70.65) 359 (78.73) 1   1  
 Others 412(29.34) 97 (21.27) 0.65(0.50–0.83) 0.001 0.77(0.58–1.03) 0.083
Literacy:
 Illiteracy 1033(73.57) 400 (87.72) 1   1  
 Literacy 371(26.42) 56 (12.28) 0.38(0.28–0.52) < 0.001 0.52(0.36–0.75) < 0.001
  1. Best corrected visual acuity (BCVA) in better eye measured in LogMAR. No Visual impairment (< 0.3 logMAR), visual impairment (both low vision (< 0.3 LogMAR≥1.3 LogMAR), and blindness (> 1.3 LogMAR)
  2. All the independent variables for visual impairment after best correction considered in the univariate analysis were included for analysis in multivariable logistic regression model
  3. Abbreviation: N Number, OR Odds Ratio, CI Confidence Interval