Table 3:
Binary logistics regression analysis for cardiovascular risk factors
| Variable | n | Obesity a | Low HDL b | High total cholesterol c | Smoking d | ||||
|---|---|---|---|---|---|---|---|---|---|
| % | OR (95% CI, P value) | % | OR (95% CI, P value) | % | OR (95% CI, P value) | % | OR (95% CI, P value) | ||
| Gender | |||||||||
| Male | 90 | 51.1 | 1.0 | 38.9 | 1.0 | 21.1 | 1.0 | 41.6 | – |
| Female | 170 | 32.4 | 0.246 (0.082–0.740, 0.013 e) | 36.7 | 1.014 (0.581–1.770, 0.923) | 29.4 | 0.557 (0.293–1.057, 0.073) | 1.8 | – |
| Race | |||||||||
| Malay | 84 | 46.4 | 1.0 | 31.0 | 1.0 | 30.6 | 1.0 | 11.9 | 1.0 |
| Iban | 90 | 46.3 | 0.928 (0.364–2.365, 0.875) | 33.3 | 0.516 (0.270–0.985, < 0.05 e) | 22.2 | 1.133 (0.561–2.288, 0.727) | 21.1 | 1.272 (0.499–3.245, 0.615) |
| Bidayuh | 86 | 23.3 | 0.775 (0.289–2.075, 0.611) | 47.7 | 0.524 (0.281–0.978, < 0.05 e) | 26.7 | 0. 615 (0.298–1.270, 0.189) | 12.8 | 0.510 (0.223–1.167, 0.111) |
| Age | |||||||||
| ≤ 45 years | 138 | 50.7 | 1 | 36.2 | 1.0 | 19.6 | 1.0 | 14.5 | 1.0 |
| ≥ 46 years | 122 | 52.5 | 1.235 (0.560–2.772, 0.601) | 38.5 | 0.894 (0.530–1.508, 0.674) | 34.4 | 0.395 (0.220–0.712, < 0.05 e) | 16.4 | 0.827 (0.348–1.968, 0.667) |
| Income | |||||||||
| ≤ RM830 | 189 | 34.9 | 1.0 | 39.7 | 1.0 | 27.0 | 1.0 | 12.7 | 1.0 |
| > RM830 | 71 | 49.3 | 0.655 (0.286–1.498, 0.316) | 40.0 | 1.411 (0.773–2.574, 0.262) | 25.4 | 1.146 (0.589–2.229, 0.689) | 22.5 | 2.471 (1.171–5.218, 0.018 e) |
Obesity was defined as BMI ≥ 30 kg/m2. High total cholesterol was defined as total cholesterol ≥ 5.1 mmol/L. Low HDL was defined as HDL ≤ 1.4 mmol/L.
a After adjusting for age, χ2 (5, 260) = 10.303, P = 0.05, Cox and Snell R square = 0.039, Nagelkerke R squared = 0.075, able to classify 88.1% of the cases.
b After adjusting for age, χ2 (5, 260) = 7.47, P = 0.188, Cox and Snell R square = 0.028, Nagelkerke R squared = 0.039, able to classify 63.1% of the cases.
c After adjusting for age, χ2 (5, 260) = 13.824, P = 0.017, Cox and Snell R square = 0.052, Nagelkerke R squared = 0.076, able to classify 73.5% of the cases.
d After adjusting for age, χ2 (5, 260) = 8.891, P < 0.001, Cox and Snell R square = 0.34, Nagelkerke R squared = 0.58, able to classify 84.6% of the cases.
e Significant (P < 0.05) by binary logistic regression test.