Table 4 Logistic regression coefficients predicting RH service utilization in three Cities in China

Gender (ref: female)

0.67 (0.59, 0.75)**

1.81 (1.59, 2.05) **

/

City(ref: Wuhan)

   Shenzhen

0.64 (0.55, 0.75)***

1.58 (1.32, 1.91)**

0.15 (0.12, 0.19)***

   Guangzhou

0.53 (0.46, 0.61)***

1.24 (1.06, 1.48)**

0.26 (0.21, 0.32)***

Education (ref: Illiteracy)

   Elementary school

1.36 (1.18, 1.63)***

1.29 (1.23, 1.34)**

1.96(1.68, 2.28)***

   Junior school

2.36 (1.95, 2.94)***

1.47 (1.14, 1.89)**

2.76 (2.37, 3.82)**

   high school

3.48 (2.90, 4.31)**

0.97 (0.87, 1.33)

3.67 (2.88, 4.65)**

   college and above

4.01 (2.63, 6.25)***

0.99 (0.79, 1.24)

3.70 (2.33, 5.88)**

Age (ref:15-19)

   20-24

1.65 (1.50, 1.78)**

1.22 (1.06, 1.42)*

1.84 (1.53, 2.06)**

   25-29

3.74 (2.23, 4.03)***

1.31 (1.14, 1.56)**

2.22 (1.78, 2.57)***

   >30

2.94 (2.27, 3.70)***

1.18 (0.94, 1.47)

3.92 (2.76, 5.11)***

Work experience (ref:<1)

   1~

1.17 (0.92, 1.49)

0.97 (0.85, 1.23)

0.63 (0.46, 0.87) ***

   2~

1.01 (0.83, 1.21)

1.04 (0.86, 1.25)

0.73 (0.57, 0.93)**

   3~

0.90 (0.73, 1.11)

1.28 (1.06, 1.55)**

0.94 (0.72, 1.21)

   5~

1.03 (0.87, 1.23)

1.11 (0.94, 1.32)

0.93 (0.75, 1.16)

   >10

1.12 (0.95, 1.32)

1.14 (0.97, 1.34)

0.84 (0.68, 1.04)

Monthly income (ref: <600)

   600~

1.03 (0.78, 1.34)

1.09 (0.80, 1.65)

0.90 (0.60, 1.41)

   1000~

0.97 (0.79, 1.25)

1.12 (0.90, 1.54)

0.84 (0.62, 1.16)

   1500~

1.08 (0.96, 1.27)

1.07 (0.86, 1.39)

0.85 (0.62, 1.20)

   > = 2000

1.45 (1.02, 1.79)*

0.99 (0.80, 1.28)

0.91 (0.65, 1.22)

Occupation ^b (ref: Blue-collar)

   white-collar

1.33 (1.11,1.61)***

0.67 (0.54, 0.83)**

1.47 (1.14, 1.89)**

   Self-employed laborers

0.99 (0.98,1.03)

0.52 (0.45, 0.57)**

1.29 (1.23, 1.34)**

Constant

1.077**

3.38**

19.36***