Assessment of Computer Vision Syndrome and Personal Risk Factors among Employees of Commercial Bank of Ethiopia in Addis Ababa, Ethiopia

Table 4

Bivariate analysis for computer vision syndrome among bank workers in Addis Ababa, Ethiopia, 2018, n = 359.

Variables	Categories	Computer vision syndrome		COR (95% CI)	value
		Yes (%)	No (%)
Age	≤29	171 (65.3)	79 (88.8)	1
	30–39	72 (27.5)	8 (9.0)	4.16 (1.9–9.04)	0.000 (<0.001)
	≥40	19 (7.3)	2 (2.2)	4.39 (0.99–19.38)	0.05
Sex	Female	92 (35.1)	43 (48.3)	1
	Male	170 (64.9)	46 (51.7)	1.73 (1.06–2.8)	0.028
Work experience	<5 years	138 (52.7)	86 (96.6)	1
	≥5 years	124 (47.3)	3 (3.4)	25.7 (8–84)	0.000 (<0.001)
Job title	Managerial	54 (20.6)	9 (10.1)	1
	Others	208 (79.4)	80 (89.9)	2.31 (1.1–4.89)	0.029
Awareness	No	122 (46.6)	42 (47.2)	1
	Yes	140 (53.4)	47 (52.8)	1.025 (0.63–1.67)	0.919
Use of electronics out of work	No	15 (5.7)	11 (12.4)	1
	Yes	247 (94.3)	78 (87.6)	2.322 (1.024–5.265)	0.044
Habit of taking break	No	183 (69.8)	50 (56.2)	1
	Yes	79 (30.2)	39 (43.8)	0.55 (0.337–0.908)	0.019
Using eye glass	No	223 (85.1)	88 (98.9)	1
	Yes	39 (14.9)	1 (1.1)	15.4 (2–114)	0.007
Preexisting disease	No	244 (93.5)	78 (87.6)	1
	Yes	17 (6.5)	11 (12.4)	0.494 (0.222–1.1)	0.084
Habit of brightness and contrast adjustment	No	120 (45.8)	42 (47.2)	1
	Yes	142 (54.2)	47 (52.8)	1.057 (0.653–1.712)	0.820

Variables which were significant in the first model, 1: reference, COR: crude odds ratio, CI: confidence interval.