Table 4.
Logistic regression analyses of antibiotic use.
| Factors | Kept antibiotics in dorm/home N = 3963 |
Bought antibiotics without prescriptions N = 2121 | Asked for antibiotics N = 3963 |
Took antibiotics prophylactically N = 3963 |
|---|---|---|---|---|
| Province | ||||
| Zhejiang (ref) | 1 | 1 | 1 | 1 |
| Guizhou | 1.01(0.86,1.19) | 1.71(1.36,2.15)*** | 1.48(1.22,1.80)*** | 2.28(1.89,2.76)*** |
| Age | 1.00(0.96,1.04) | 0.96(0.91,1.02) | 1.05(1.00,1.11)* | 1.00(0.95,1.05) |
| Gender | ||||
| Female (ref) | 1 | 1 | 1 | 1 |
| Male | 0.70(0.61,0.80)*** | 0.96(0.79,1.16) | 0.87(0.74,1.02) | 0.94(0.81,1.10) |
| Education level | ||||
| Undergraduate (ref) | 1 | 1 | 1 | 1 |
| Graduate | 0.99(0.78,1.27) | 1.94(1.35,2.80)*** | 1.07(0.81,1.43) | 0.83(0.63,1.09) |
| Major | ||||
| Non-medicine (ref) | 1 | 1 | 1 | 1 |
| Medicine | 1.18(0.98,1.42) | 1.15(0.88,1.50) | 0.71(0.56,0.90)** | 0.69(0.55,0.87)** |
| Education level of parents | ||||
| Illiteracy/primary school (ref) | 1 | 1 | 1 | 1 |
| Junior high school | 1.33(1.07,1.66)* | 0.88(0.63,1.22) | 1.10(0.83,1.47) | 1.13(0.87,1.46) |
| Senior high school | 1.70(1.32,2.17)*** | 0.86(0.59,1.24) | 1.39(1.01,1.91)* | 1.31(0.98,1.74) |
| University/above | 2.03(1.53,2.69)*** | 0.82(0.55,1.24) | 1.40(0.98,2.00) | 1.17(0.85,1.63) |
| Parent’s medical background | ||||
| No (ref) | 1 | 1 | 1 | 1 |
| Yes | 1.68(1.24,2.27)** | 0.62(0.43,0.89)* | 1.07(0.78,1.48) | 1.45(1.08,1.95)* |
| Household income per month | ||||
| < 3000 (ref) | 1 | 1 | 1 | 1 |
| 3000 ~ 10,000 | 1.30(1.10,1.53)** | 1.14(0.90,1.44) | 1.17(0.95,1.43) | 0.98(0.81,1.18) |
| > 10,000 | 1.14(0.90,1.43) | 1.05(0.76,1.46) | 1.22(0.92,1.62) | 1.03(0.79,1.34) |
| Hometown | ||||
| Urban area (ref) | 1 | 1 | 1 | 1 |
| Rural area | 0.64(0.54,0.76)*** | 0.85(0.66,1.09) | 1.12(0.90,1.39) | 1.10(0.89,1.34) |
*< 0.05; **< 0.01; ***< 0.001.