Table 3:
Model results for multivariable analysis of the association of BP parameters and odds of having hypertension with outdoor PM2.5 (per 10 μg/m3 increase), stratified by selected variables a
| No. samples | Systolic BP β (95% CI) | Diastolic BP β (95% CI) | Pulse Pressure β (95% CI) | Mean Arterial Pressure β (95% CI) | Hypertension Odds ratio (95% CI) | |
|---|---|---|---|---|---|---|
| Entire sample | 137809 | 0.13 (−0.24, 0.49) | 0.12 (−0.09, 0.33) | 0.0 (−0.26, 0.26) | 0.12 (−0.12, 0.36) | 1.04 (1.01, 1.07) |
| Gender | ||||||
| Female | 79950 | 0.11 (−0.29, 0.50) | 0.17 (−0.04, 0.39) | −0.07 (−0.35, 0.20) | 0.15 (−0.11, 0.41) | 1.03 (0.99, 1.07) |
| Male | 57859 | 0.26 (−0.09, 0.62) | 0.16 (−0.05, 0.38) | 0.1 (−0.16, 0.35) | 0.20 (−0.05, 0.44) | 1.05 (1.01, 1.09) |
| Residence | ||||||
| Urban | 74601 | 0.32 (−0.10, 0.73) | 0.17 (−0.08, 0.42) | 0.14 (−0.22, 0.49) | 0.22 (−0.05, 0.50) | 1.04 (1.00, 1.08) |
| Rural | 63208 | 0.19 (−0.37, 0.75) | 0.29 (−0.03, 0.61) | −0.11 (−0.48, 0.26) | 0.25 (−0.13, 0.63) | 1.07 (1.02, 1.12) |
| Hypertension | ||||||
| No | 82346 | 0.14 (−0.08, 0.36) | 0.15 (0.01, 0.29) | −0.01 (−0.19, 0.16) | 0.15 (0.00, 0.30) | na |
| Yes | 55463 | −0.05 (−0.35, 0.25) | 0.05 (−0.13, 0.22) | −0.12 (−0.45, 0.2) | 0.02 (−0.15, 0.19) | na |
| Anti-hypertensive medication use | ||||||
| No | 118721 | 0.16 (−0.20, 0.51) | 0.17 (−0.04, 0.37) | −0.01 (−0.27, 0.25) | 0.16 (−0.07, 0.40) | 1.03 (1.00, 1.07) |
| Yes | 19088 | −0.29 (−0.82, 0.25) | −0.22 (−0.51, 0.07) | −0.09 (−0.47, 0.28) | −0.26 (−0.60, 0.09) | na |
| Heart disease | ||||||
| No | 132058 | 0.12 (−0.24, 0.49) | 0.13 (−0.08, 0.33) | −0.01 (−0.27, 0.25 | 0.13 (−0.12, 0.37) | 1.03 (1.00, 1.07) |
| Yes | 5568 | 0.07 (−0.57, 0.72) | 0.15 (−0.19, 0.50) | −0.05 (−0.50, 0.40) | 0.11 (−0.30, 0.53) | 1.06 (1.00, 1.13) |
| Diabetes mellitus | ||||||
| No | 126536 | 0.13 (−0.23, 0.49) | 0.13 (−0.08, 0.33) | −0.01 (−0.27, 0.25) | 0.13 (−0.11, 0.37) | 1.03 (1.00, 1.07) |
| Yes | 11120 | 0.37 (−0.16, 0.91) | 0.35 (0.04, 0.65) | 0.03 (−0.37, 0.42) | 0.35 (0.00, 0.70) | 1.06 (1.01, 1.11) |
| BMI | ||||||
| Underweight | 7075 | 0.87 (0.27, 1.46) | 0.76 (0.40, 1.12) | 0.01 (−0.34, 0.36) | 0.80 (0.39, 1.21) | 1.17 (1.11, 1.25) |
| Normal weight | 58189 | 0.05 (−0.33, 0.42) | 0.1 (−0.11, 0.32) | −0.05 (−0.31, 0.22) | 0.08 (−0.17, 0.33) | 1.03 (0.99, 1.07) |
| Overweight | 47896 | 0.09 (−0.28, 0.46) | 0.12 (−0.1, 0.35) | −0.03 (−0.30, 0.23) | 0.11 (−0.14, 0.36) | 1.03 (1.00, 1.07) |
| Obese | 24649 | 0.10 (−0.33, 0.54) | 0.07 (−0.18, 0.33) | 0.02 (−0.31, 0.34) | 0.09 (−0.20, 0.38) | 1.05 (1.01, 1.09) |
| Smoking status | ||||||
| Never | 16094 | −0.08 (−0.55, 0.38) | −0.03 (−0.31, 0.25) | −0.08 (−0.4, 0.25) | −0.05 (−0.37, 0.27) | 1.01 (0.96, 1.06) |
| Ever | 121715 | 0.13 (−0.25, 0.50) | 0.14 (−0.07, 0.35) | −0.02 (−0.29, 0.25) | 0.13 (−0.11, 0.38) | 1.03 (1.00, 1.07) |
| Alcohol use | ||||||
| Never | 6292 | 0.00 (−0.54, 0.53) | −0.03 (−0.37, 0.31) | 0.05 (−0.32, 0.42) | −0.02 (−0.40, 0.36) | 0.98 (0.93, 1.03) |
| Ever | 131517 | 0.07 (−0.30, 0.44) | 0.1 (−0.11, 0.31) | −0.03 (−0.30, 0.23) | 0.09 (−0.15, 0.33) | 1.03 (0.99, 1.06) |
| Age (years) | ||||||
| ≤ 50 | 70376 | 0.30 (−0.05, 0.64) | 0.27 (0.06, 0.48) | 0.03 (−0.22, 0.28) | 0.28 (0.05, 0.52) | 1.06 (1.02, 1.10) |
| > 50 | 67433 | −0.03 (−0.46, 0.41) | 0.09 (−0.13, 0.32) | −0.12 (−0.43, 0.19) | 0.05 (−0.23, 0.32) | 1.01 (0.98, 1.05) |
| Healthy participants b | 108656 | 0.14 (−0.22, 0.49) | 0.16 (−0.04, 0.37) | −0.03 (−0.29, 0.23) | 0.15 (−0.08, 0.39) | 1.03 (1.00, 1.07) |
Model 3: age, sex and race/ethnicity, education (none, primary, secondary/high school/higher secondary, trade school, college/university, unknown), marital status (married, not married), and a household wealth index (based on household assets and the index calculated separately for each country), smoking status (never smoked, former smoker, current smoker), alcohol use (never used, former user, current user), body mass index (BMI; Kg/m2), alternative healthy eating index (an indicator for overall diet quality based on the dietary guidelines for Americans), temperature (oC), geographical latitude, country income-level, and location of residence (urban, rural), and use of BP lowering medication (medication use, no medication use).
All models included random intercepts for country and community.
Participants who were free of CVD, diabetes mellitus, and did not take BP medication