Table 3.

Association of seroepidemiology of rubella IgG and related variables via multivariate analysis

The independent variables	Seropositivity of rubella = ya		GMC(IU/ml) of rubella = yb
	OR (95%CI)	P-values	OR (95%CI)	P-values
Gender
Male	1		1
Female	1.035(.881–1.217)	0.675	1.024(.995–1.06)	0.104
District
Urban	1		1
Rural	1.018(.861–1.203)	0.835	1.033(1.005–1.074)	0.024
Age(y)
<1	1		1
1	0.153(.108–.216)	<.001	0.761(.58–.662)	<.001
2	0.055(.034–.09)	<.001	1.058(1.044–1.204)	0.002
3-4	0.072(.049–.106)	<.001	1.105(1.143–1.323)	<.001
5-6	0.179(.131–.245)	<.001	1.031(.989–1.127)	0.103
7-9	0.254(.187–.344)	<.001	0.968(.876–1.005)	0.071
10-14	0.253(.188–.341)	<.001	0.938(.818–.944)	<.001
15-19	0.173(.128–.232)	<.001	0.923(.798–.918)	<.001
20-29	0.163(.117–.228)	<.001	1.037(1.001–1.154)	0.047
30-39	0.175(.122–.25)	<.001	1.01(.947–1.102)	0.581
≥40	0.243(.176–0336)	<.001	0.964(.856–.994)	0.034

Logistic regression was used to analyze the associations between the changes in the rate of rubella IgG seropositivity and the related factors.

Linear regression was used to analyze the associations between the changes in the GMC levels of rubella IgG and the related factors.