Bi-variable and multivariable binary logistic regression model on factors associated with maternal near-miss women visited at HUCSH, Hawassa, Ethiopia, 2020 (N = 316).

Table 4: Bi-variable and multivariable binary logistic regression model on factors associated with maternal near-miss women visited at HUCSH, Hawassa, Ethiopia, 2020 (N = 316).

Variables	Category	Near-miss		COR (95% CI)	AOR (95% CI)
Variables	Category	Yes	No	COR (95% CI)	AOR (95% CI)
Place of residency	Rural	32	64	5.3 (2.8, 9.9)	4.2 (1.3, 13.9)^*
Place of residency	Urban	19	201	1	1
Estimated monthly income	< 2000	19	63	2.4 (1.1, 5.2)	0.72 (0.14, 3.7)
	2000-4000	19	98	1.6 (0.73, 3.3)	1.2 (0.35, 4.7)
	> 4000	13	104	1	1
Educational status	No formal education	10	16	3.8 (1.6, 8.9)	2.6 (0.49, 13.7)
Educational status	Have formal education	41	249	1	1
Parity	Para 1	10	81	1	1
	Para 2-4	13	51	2.1 (0.84, 5.1)	1.2 (0.32, 4.6)
	Para > 4	5	8	5.1 (1.4, 18.5)	0.22 (0.02, 3.1)
Gravidity	Prim-gravid	22	112	0.7 (0.35, 1.3)	0.52 (0.1, 2.9)
Gravidity	Multi-gravid	29	152	1	1
Referral case	Yes	36	36	15 (7.6, 30.7)	5.5 (1.8, 17.4)^*
Referral case	No	15	229	1	1
History of stillbirth	Yes	5	5	5.6 (1.6, 20)	10.2 (1.4, 71.8)^*
History of stillbirth	No	46	259	1	1
History of abortion	Yes	2	24	0.41 (0.1, 1.8)	0.2 (0.01, 3.9)
History of abortion	No	49	241	1	1
Delay to make a decision	Yes	8	4	12.5 (3.5, 42)	1.2 (0.12, 7.7)
Delay to make a decision	No	43	261	1	1
Time to reachthe hospital	Within 60 minute	28	243	1	1
Time to reachthe hospital	> 60 minute	23	22	9.1 (4.5, 18.3)	4.8 (1.34,16.9)^*

^*: Association.