Skip to main content
. 2016 Jul 26;125(3):296–305. doi: 10.1289/EHP426

Table 2.

Agricultural drift: model parameters for predicting the GMs of dust pesticide concentrations in agricultural homes at varying distances from fields.

Model β (SE) Exp(β) (95% CI) Between-result variance, in ln μg/g (SE) Between-pesticide/paper variance, in ln μg/g (SE)
All summary measures (n = 52) 0.80 (0.21) 1.56 (0.66)
Intercept 0.15 (0.72) 1.2 (0.28, 4.8)
Ln(distance in feet) –0.43 (0.11) 0.65 (0.52, 0.81)
Herbicides/fungicides (n = 14) 2.0 (0.77) Not estimated
Intercept 0.68 (1.7) 2.0 (0.07, 52)
Ln(distance in feet) –0.64 (0.26) 0.53 (0.32, 0.88)
Insecticides (n = 38) 0.33 (0.10) 1.79 (0.75)
Intercept –0.22 (0.59) 0.80 (0.25, 2.6)
Ln(distance in feet) –0.30 (0.09) 0.74 (0.62, 0.88)
Chlorpyrifos (n = 10) 0.11 (0.06) ~ 0
Intercept –0.43 (0.55) 0.65 (0.22, 1.9)
Ln(distance in feet) –0.29 (0.08) 0.75 (0.64, 0.87)
Note: —, data not available; CI, confidence interval; GM, geometric mean; SE, standard error. Predicted GM at a given distance = dβslope exp(βintercept) (Equation 13). Percent (%) change between distances d1 and d2 = [1 – (d2/d1)βslope] × 100 (Equation 14).