Table 3.
Univariate and multivariate regression analysis of the relationship between waist circumference category and the risk of hypertension, classified according to sex
| n | Incidence, n (%) | Crude analysis |
Multivariate analysis |
|||
|---|---|---|---|---|---|---|
| OR (95% CI) | p | OR (95% CI) | p | |||
| Men | ||||||
| Waist (per 1 cm) | 1.06 (1.03–1.09) | <0.001 | 1.04 (1.01–1.07) | 0.018 | ||
| Waist <90 cm | 436 | 57 (13.1) | 1 | 1 | ||
| Waist ≥90 cm | 168 | 40 (23.8) | 2.08 (1.32–3.26) | 0.001 | 1.79 (1.10–2.91) | 0.019 |
| Women | ||||||
| Waist (per 1 cm) | 1.07 (1.04–1.09) | <0.001 | 1.04 (1.02–1.07) | <0.001 | ||
| Waist <85 cm | 1,060 | 107 (10.1) | 1 | 1 | ||
| Waist ≥85 cm | 263 | 51 (19.4) | 2.14 (1.49–3.09) | <0.001 | 1.61 (1.09–2.40) | 0.018 |
The data were adjusted for age, estimated glomerular filtration rate, current smoking, current drinking, diabetes, dyslipidemia, baseline systolic blood pressure, cardiovascular disease, antidiabetic drug use, and lipid-lowering drug use.