Table 4. Binary Logistic Regression Model for Associated Factors (Focus on Current Smoking Status and Different types of Tea Drinking Habits) of Metabolic Syndrome in Elderly Males Living in a Rural Community (N = 361).

					Odds ratio	95%CI		P
Age					1.02	0.97,	1.08	0.45
Body mass index (kg/m2)					1.38	1.21,	1.60	<0.001
Uric acid (mg/dl)					1.44	1.16,	1.80	0.001
HOMA index#					4.52	2.54,	8.05	<0.001
hsCRP (mg/L)#					1.22	0.94,	1.59	0.13
Occupational status			(No = 0, Yes = 1)		0.74	0.37,	1.47	0.39
Lived with partner			(No = 0, Yes = 1)		1.49	0.67,	3.33	0.33
Literate			(No = 0, Yes = 1)		0.87	0.39,	1.96	0.74
Alcohol drinking			(No = 0, Yes = 1)		1.23	0.65,	2.32	0.52
Coffee drinking			(No = 0, Yes = 1)		0.92	0.27,	3.14	0.90
Current tea drinking
			(No = 0)		1
			(Fermented = 1)		0.64	0.29	1.42	0.27
			*(Unfermented = 2)		0.42	0.22	0.84	0.01
Current smoking habit
		(Non-smoker = 0)			1
		(Ex-smoker = 1)			1.68	0.84,	3.33	0.14
	(Current smoker = 2)				2.72	1.03,	7.19	0.04
Physical activity (IPAQ-short form)
				(Low = 0)	1
				(Middle = 1)	0.73	0.35,	1.53	0.40
				(High = 2)	0.77	0.34,	1.74	0.53

HOMA: Homeostatic model assessment; hsCPR: high sensitivity C-reactive protein;

IPAQ: International Physical Activity Questionnaire.

Dependent variable: without vs with metabolic syndrome.

^#:Log transformation.

^*Unfermented tea including green tea (unfermented) and oolong tea (partial fermented).

Nagelkerke R square = 0.526; Cox & Snell R square : 0.384.