Table 3.
Association between uncontrolled diastolic blood pressure and other factors
Factors | Univariate |
Multivariate* |
||
---|---|---|---|---|
OR (95% CI) | P-value | OR (95% CI) | P-value | |
Age (y) | ||||
<55 | 1.00 (ref) | 1.00 (ref) | ||
55–69 | 0.36 (0.27–0.48) | <0.001 | 0.45 (0.33–0.61) | <0.001 |
≥70 | 0.11 (0.07–0.16) | <0.001 | 0.15 (0.10–0.23) | <0.001 |
Sex (female) | 0.66 (0.52–0.84) | 0.001 | ||
Residential area (urban) | 1.24 (0.92–1.68) | 0.150 | ||
Education level (high school or higher) | 1.94 (1.51–2.47) | <0.001 | ||
Occupation type | ||||
White-collar | 1.00 (ref) | 1.00 (ref) | ||
Blue-collar | 0.44 (0.30–0.62) | <0.001 | 0.66 (0.45–0.96) | 0.029 |
No work | 0.23 (0.16–0.32) | <0.001 | 0.55 (0.37–0.83) | 0.004 |
House income (median or more) | 1.70 (1.33–2.17) | <0.001 | ||
Spouse (yes) | 1.95 (1.44–2.65) | <0.001 | ||
Stress (high) | 1.11 (0.83–1.48) | 0.477 | ||
Regular exercise (yes) | 0.90 (0.70–1.16) | 0.424 | ||
Sleep duration (<6 h) | 0.91 (0.68–1.22) | 0.522 | ||
Smoke (current) | 1.29 (0.92–1.81) | 0.145 | ||
Alcohol drinking (≥4 d/wk) | 1.44 (0.97–2.14) | 0.073 | ||
Heavy alcohol drinking (≥1 d/wk) | 2.68 (2.02–3.55) | <0.001 | 1.62 (1.19–2.21) | 0.002 |
Hypertension duration (y) | ||||
<10 | 1.00 (ref) | |||
10–24 | 0.72 (0.55–0.93) | 0.012 | ||
≥25 | 0.31 (0.14–0.67) | 0.002 | ||
Diabetes | 0.57 (0.41–0.79) | 0.001 | 0.71 (0.51–0.99) | 0.044 |
Myocardial infarction or angina | 0.69 (0.41–1.17) | 0.170 | ||
Stroke | 1.04 (0.67–1.61) | 0.876 | ||
Dyslipidemia | 0.84 (0.65–1.01) | 0.174 | ||
Thyroid disease | 0.56 (0.24–1.29) | 0.172 | ||
Depression | 0.82 (0.48–1.42) | 0.484 | ||
Chronic kidney disease | 0.24 (0.03–1.75) | 0.158 | ||
Liver cirrhosis | 0.92 (0.22–3.95) | 0.914 | ||
Antihypertensive medication on the day of examination (no) | 1.98 (0.92–4.27) | 0.082 | ||
Obesity (body mass index ≥25 kg/m2) | 1.50 (1.18–1.92) | 0.001 | ||
Abdominal obesity (yes) | 0.99 (0.78–1.26) | 0.940 |
OR, odds ratio; CI, confidence interval; ref, reference.
A stepwise method, iteratively adding and removing predictors to find a subset of variables in a data set, was used with all factors.