Table 3.
Regression associations between PM2.5 and NO2 with diabetes-related metabolic traits among 1,023 BetaGene participants
| Exposure outcomes | PM2.5 |
NO2 |
||||
|---|---|---|---|---|---|---|
| Short-term* |
Annual average† |
Short-term* |
Annual average† |
|||
| Lagged period* | β (P)‡ | β (P)§ | Lagged period* | β (P)‡ | β (P)§ | |
| Measurements obtained from FSIGT | ||||||
| SI (×10−5 min−1 per pmol/L)‖ | 40 | −4.60 (0.003) | −1.63 (0.32) | 7 | −3.81 (0.023) | −1.84 (0.29) |
| AIRg (pmol/L × 10 min)‖ | 34 | 1.23 (0.30) | −0.05 (0.97) | 37 | 1.08 (0.42) | −0.54 (0.68) |
| DI (SI × AIRg)‖ | 8 | −1.25 (0.32) | −0.40 (0.76) | 3 | −1.13 (0.40) | −1.37 (0.33) |
| Insulin MCR (mL/min/m2)‖ | 36 | −5.65 (0.004) | −3.86 (0.06) | 37 | −6.55 (0.003) | −5.06 (0.017) |
| Insulin FDR (min−1 × 100)‖ | 58 | −5.77 (0.003) | −5.06 (0.012) | 37 | −7.93 (<0.001) | −6.87 (0.001) |
| Measurements obtained from oGTT | ||||||
| Fasting glucose (mmol/L) | 7 | 0.04 (0.036) | 0.08 (<0.001) | 12 | 0.06 (0.012) | 0.07 (0.005) |
| 2-h glucose (mmol/L) | 3 | 0.06 (0.36) | −0.05 (0.51) | 56 | −0.11 (0.18) | −0.07 (0.37) |
| Fasting insulin (pmol/L)‖ | 40 | 9.31 (0.003) | 5.84 (0.07) | 32 | 8.41 (0.013) | 4.48(0.18) |
| 2-h insulin (pmol/L)‖ | 57 | 2.92 (0.24) | 0.78 (0.76) | 4 | 2.90 (0.26) | 2.48 (0.35) |
| HOMA-IR (mmol/L × mU/L)‖ | 40 | 6.99 (0.002) | 5.81 (0.016) | 32 | 6.63 (0.009) | 4.58 (0.07) |
| Lipids** | ||||||
| Cholesterol (mg/dL)†† | 3 | 2.25 (0.034) | 1.98 (0.10) | 4 | 1.09 (0.35) | 0.45 (0.72) |
| HDL-C (mg/dL)†† | 4 | −0.35 (0.32) | −0.15 (0.70) | 45 | −0.80 (0.058) | −0.72 (0.08) |
| LDL-C (mg/dL)†† | 4 | 2.66 (0.003) | 2.07 (0.043) | 5 | 1.58 (0.12) | 1.04 (0.33) |
| HDL-C–to–LDL-C ratio × 100‖ | 7 | −3.17 (0.005) | −2.38 (0.06) | 30 | −2.10 (0.12) | −2.56 (0.05) |
| Triglycerides (mg/dL)‖‡‡ | 14 | −1.59 (0.40) | −2.35 (0.26) | 17 | −2.12 (0.31) | −1.56 (0.47) |
Boldface P values indicate regression estimates were statistically significant (P < 0.05).
*Various cumulative average daily lagged periods were selected for different outcomes as short-term exposures using AIC to achieve best model fitting.
†12-month average ambient air pollutant exposures were selected as representative of long-term exposures.
‡Associations of short-term exposures to air pollutants with metabolic traits were adjusted for age, sex, percent body fat, seasonality, and contextual variables. For outcomes including fasting and 2-h glucose, total cholesterol, HDL-C, and LDL-C, β represents the absolute changes in the outcome associated with 1-SD change of the exposure variables. For other log-transformed outcomes, β represents the percent change in the outcome associated with 1-SD change of the exposure variables. P values were derived from likelihood ratio tests.
§Associations between 12-month average pollutants levels and metabolic traits were adjusted for age, sex, percent body fat, and contextual variables.
‖Variables were log transformed in the association analysis.
**Lipid concentrations were measured using fasting blood.
††For conversion of measurements from conventional units to Système International (SI) units, multiply by a conversion factor of 0.02586.
‡‡For conversion of measurements from conventional units to Système International units, multiply by a conversion factor of 0.01129.