Table 6 Univariate and multivariate logistic regression analysis for practice levels.
From: Nurses knowledge attitude and practice in preventing osteoporosis complications in China
Variables | Univariate analysis | Multivariate analysis | ||
|---|---|---|---|---|
OR (95%CI) | p value | OR (95%CI) | p value | |
Knowledge | 1.19 (1.04, 1.29) | < 0.001 | 1.14 (1.05, 1.26) | 0.007 |
Attitude | 1.05 (1.01, 1.41) | 0.018 | 1.08 (1.03, 1.20) | 0.010 |
Gender | ||||
Male | Ref. | - | - | |
Female | 1.28 (0.91, 1.76) | 0.081 | - | - |
Age | 0.98 (0.88, 1.32) | 0.364 | - | - |
Residence | ||||
Rural | Ref. | - | - | |
Urban | 1.38 (0.76, 2.11) | 0.206 | - | - |
Suburban | 1.47 (0.86, 2.61) | 0.183 | - | - |
Education | ||||
Primary school and below | Ref. | |||
Middle School | 1.26 (0.55, 1.62) | 0.332 | 1.28 (0.64, 2.13) | 0.168 |
High School/Technical secondary school | 1.24 (0.35, 2.76) | 0.812 | 1.12 (0.71, 1.65) | 0.835 |
Junior college/Bachelor’s degree | 1.10 (0.58, 2.11) | 0.692 | 1.36 (0.75, 2.12) | 0.516 |
Master’s degree and above | 3.61 (1.77, 6.23) | 0.024 | 3.51 (1.31, 5.66) | 0.005 |
Work Status | ||||
Employed | Ref. | |||
Unemployed | 0.55 (0.38, 1.46) | 0.366 | 0.78 (0.55, 1.89) | 0.234 |
Monthly per capita income | ||||
< 700 | Ref. | |||
> 700 | 1.33 (0.69, 1.49) | 0.431 | - | - |
Working Years | ||||
< 5 y | Ref. | |||
> 5 y | 1.08 (0.81, 1.36) | 0.294 | ||
Marital status | ||||
Unmarried | Ref. | - | - | |
Married | 0.89 (0.43, 1.42) | 0.189 | - | - |
Divorced/Widowed | 0.92 (0.78, 1.30) | 0.813 | - | - |
Technical titles | ||||
Nurse | Ref. | - | - | |
Associate Professor or Professor of Nursing | 1.08 (0.81, 1.34) | 0.135 | - | - |
Chronic medical history | - | - | ||
Yes | Ref. | - | - | |
No | 1.21 (0.81, 2.15) | 0.284 | - | - |
Sleeping conditions | ||||
Yes | Ref. | |||
No | 1.33 (0.910, 2.07) | 0.311 | ||
