Effect of the age of visual impairment onset on employment outcomes in South Korea: analysis of the national survey on persons with disabilities data

Jeon, Boyoung; Koo, Heejo; Lee, Hye-Jae; Han, Euna

doi:10.1186/s12889-022-13747-z

Table 3 Impact of the onset age of visual impairment on employment and job security: Subgroup analysis by sex (reference = unemployment)

From: Effect of the age of visual impairment onset on employment outcomes in South Korea: analysis of the national survey on persons with disabilities data

		Men^a						Women^a
		Logistic regression^b		Multinomial logistic regression^c				Logistic regression^b		Multinomial logistic regression^c
		Employment		Permanent employees		Temporary employees		Employment		Permanent employees		Temporary employees
		aOR(95%CI)	p-value	aOR(95%CI)	p-value	aOR(95%CI)	p-value	aOR(95%CI)	p-value	aOR(95%CI)	p-value	aOR(95%CI)	p-value
Prime-aged adults, 20–49
Onset age of visual impairment
Model 1.1	Continuous	0.94(0.89, 1.00)	0.044	0.94(0.89,1.00)	0.047	0.96(0.90,1.01)	0.133	0.95(0.90,1.00)	0.073	0.96(0.90,1.02)	0.192	0.92(0.84,1.00)	0.046
Model 1.2 (ref. = Age 0–5)	Age 6–17	0.42(0.10,1.85)	0.252	0.35(0.07,1.79)	0.205	0.49(0.09,2.58)	0.396	0.46(0.09,2.39)	0.359	0.38(0.45,3.73)	0.410	0.53(0.44,2.74)	0.445
	Age 18–24	0.69(0.12,3.88)	0.675	0.65(0.11,4.06)	0.649	0.67(0.09,4.88)	0.696	0.83(0.13,5.35)	0.847	0.46(0.61,6.01)	0.557	0.95(1.14,10.09)	0.963
	Age 25 +	0.18(0.03,0.93)	0.041	0.14(0.02,0.77)	0.025	0.30(0.04,2.04)	0.219	0.14(0.02,0.90)	0.038	0.15(0.17,1.39)	0.095	0.05(0.07,0.75)	0.030
Pseudo R2		Model 1: 0.3720 Model 2: 0.3755		Model 1: 0.2766 Model 2: 0.2836				Model 1: 0.1626 Model 2: 0.1802			Model 1: 0.1603 Model 2: 0.1754
Late-middle-aged adults, 50–64
Onset age of visual impairment
Model 1.1	Continuous	1.02(0.99,1.04)	0.144	1.01(0.98,1.04)	0.418	1.02(1.00,1.04)	0.133	0.99(0.97,1.02)	0.556	0.96(0.92,1.00)	0.083	1.00(0.97,1.02)	0.819
Model 1.2 (ref. = Age 0–5)	Age 6–17	1.23(0.24,6.37)	0.804	0.65(0.08,5.25)	0.688	1.60(0.21,12.18)	0.649	1.51(0.22,10.33)	0.675	4.14(0.32,53.37)	0.276	0.93(0.12,7.34)	0.942
	Age 18–24	1.04(0.19, 5.84)	0.965	0.69(0.07,6.31)	0.739	1.28(0.13,12.52)	0.830	0.96(0.14,6.63)	0.964	2.02(0.06,65.04)	0.692	0.80(0.08,8.51)	0.854
	Age 25 +	2.89(0.64,13.05)	0.167	1.16(0.18,7.36)	0.874	4.25(0.66,27.45)	0.128	1.76(0.48,6.41)	0.393	2.15(0.18,25.05)	0.541	1.43(0.39,5.31)	0.591
Pseudo R2		Model 1: 0.1947 Model 2: 0.2078			Model 1: 0.2118 Model 2: 0.2236			Model 1: 0.2270 Model 2: 0.2307			Model 1: 0.2775 Model 2: 0.2741

Note. Robust standard errors were used in the logistic and multinomial regression analyses. aOR means adjusted odds ratio. Model 1.1 and Model 1.2 applied the same covariates in the regression
^aNumber of observations: Prime-aged adults: Men (n = 168), women (n = 77); Late-middle-aged adults: Men (n = 202), women (n = 136)
^bIn the logistic regression, disability severity, reason for disability, sex, age, marriage status, education, chronic diseases, self-rated health, job training, and dummy year variables were adjusted
^cIn the multinomial regression, the same covariates were used as in the logistic regression model except for job training due to the small sample size

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