Table 4: Multiple logistics regression output for control of BP (HPT).
Variables |
B |
Wald |
df |
Sig. |
Odds Ratio (OR) |
95% C.I. for OR |
|
Lower |
Upper |
||||||
Age |
|
9.016 |
4 |
.061 |
|
|
|
26 – 35 years |
2.544 |
2.169 |
1 |
.141 |
12.735 |
.431 |
376.369 |
36 – 45 years |
-.566 |
.118 |
1 |
.731 |
.568 |
.022 |
14.340 |
46 – 55 years |
.726 |
.220 |
1 |
.639 |
2.067 |
.100 |
42.923 |
> 55 years |
1.097 |
.535 |
1 |
.464 |
2.996 |
.158 |
56.656 |
Gender |
.265 |
.798 |
1 |
.372 |
1.303 |
.729 |
2.331 |
Income |
|
2.322 |
3 |
.508 |
|
|
|
<= R1000 |
-.825 |
1.202 |
1 |
.273 |
.438 |
.100 |
1.915 |
R1001 – R2000 |
.287 |
.409 |
1 |
.523 |
1.333 |
.552 |
3.216 |
R2001 – R3000 |
21.438 |
.000 |
1 |
.999 |
2044494676.054 |
.000 |
. |
Education |
|
3.752 |
4 |
.441 |
|
|
|
1-5 years schooling |
.204 |
.432 |
1 |
.511 |
1.226 |
.667 |
2.254 |
6-11 years schooling |
-1.210 |
2.901 |
1 |
.089 |
.298 |
.074 |
1.200 |
Matric |
21.003 |
.000 |
1 |
.999 |
1322387848.687 |
.000 |
. |
Post Matric or Higher education |
-.058 |
.010 |
1 |
.919 |
.944 |
.311 |
2.870 |
Employment Situation |
|
5.602 |
2 |
.061 |
|
|
|
Full-time employed |
1.003 |
5.562 |
1 |
.018 |
2.727 |
1.185 |
6.278 |
Part-time employed |
.535 |
1.584 |
1 |
.208 |
1.707 |
.742 |
3.924 |
Total Practice |
.134 |
1.109 |
1 |
.292 |
1.143 |
.891 |
1.466 |
Total attitude |
.279 |
1.346 |
1 |
.246 |
1.322 |
.825 |
2.118 |
Total Knowledge |
.103 |
1.700 |
1 |
.192 |
1.109 |
.949 |
1.295 |
Constant |
-4.367 |
3.213 |
1 |
.073 |
.013 |
|
|
a. Variable(s) entered on step 1: Age, Gender, Income, Education, Employment Situation, Total Practice, Total attitude, Total Knowledge.