Table 3. Displays the results of five multiple imputations performed to address the missing data in regression analysis of CKD and testosterone.

			Exposure
			Non-adjusted	Adjust I	Adjust II
Model 1
	CKD
		Yes	Reference	Reference	Reference
		No	19.819 (7.762, 31.876)	59.020 (50.451, 67.589)	27.839 (19.469, 36.209)
		p-value	0.00128	<0.00001	<0.00001
Mode 2
	CKD
		Yes	Reference	Reference	Reference
		No	19.819 (7.762, 31.876)	59.020 (50.451, 67.589)	27.602 (19.233, 35.972)
		p-value	0.00128	<0.00001	<0.00001
Mode 3
	CKD
		Yes	Reference	Reference	Reference
		No	19.819 (7.762, 31.876)	59.020 (50.451, 67.589)	27.889 (19.519, 36.260)
		p-value	0.00128	<0.00001	<0.00001
Mode 4
	CKD
		Yes	Reference	Reference	Reference
		No	19.819 (7.762, 31.876)	59.020 (50.451, 67.589)	27.466 (19.101, 35.832)
		p-value	0.00128	<0.00001	<0.00001
Mode 5
	CKD
		Yes	Reference	Reference	Reference
		No	19.819 (7.762, 31.876)	59.020 (50.451, 67.589)	27.707 (19.334, 36.080)
		p-value	0.00128	<0.00001	<0.00001
Summary			Pool estimates from multiple imputed data=27.700 (23.427, 31.974)

Values are presented as β (95% confidence interval).

Non-adjusted model adjust for: none; Adjust I model to adjust for: sex, age, BMI; Adjust II model adjust for: sex, age, BMI, total cholesterol, HDL, LDL, DM, waist, hemoglobin, race/ethnicity, education status, marital status, smoking status, HBP status, anemia, alcohol status.

CKD: chronic kidney disease, BMI: body mass index, HDL: high-density lipoprotein cholesterol, LDL: low-density lipoprotein cholesterol, DM: diabetes mellitus, HBP: high blood pressure.