Research Article

Pesticides and Health in Vegetable Production in Kenya

Table 4

Binomial Regression model for the acute symptoms estimations.

Model UnrestrictedRestricted

Variables (Coefficient)-value (Coefficient)-value

AGE0.04 (0.04)1.13
AGESQ−0.00 (0.00)−1.21
EDUCATION−0.16 (0.07)−2.13−0.14 (0.07)−1.94
GENDER−0.10 (0.16)−0.67
GLOBALGAP−0.33 (0.29)−1.11

RECORD−0.44 (0.17)−2.57−0.55 (0.15)−3.77

NPEST0.09 (0.05)1.880.10 (0.05)2.39
PWHOIab0.00 (0.00)1.28
PWHOII0.00 (0.00)0.68
PWHOIII−0.00 (0.00)−0.28
PWHOU−0.00 (0.00)−0.13

COAT−0.29 (0.16)−1.82−0.29 (0.15)−2.03
GLOVE−0.26 (0.21)−1.23
GUMBOOT0.32 (0.23)1.36
MASK−0.35 (0.20)−1.74−0.39 (0.17)−2.30

KIAMBU1.69 (0.36)4.671.63 (0.32)5.20
MAKUENI1.74 (0.49)3.551.50 (0.46)3.35
MERU CENTRAL1.18 (0.31)3.820.95 (0.25)3.77
MURANGA0.64 (0.46)1.40
NYANDARUA0.90 (0.34)2.660.80 (0.28)2.81
NYERI NORTH0.93 (0.30)3.070.79 (0.24)3.26
YEAR 2008−0.05 (0.21)−0.23
Constant−1.22 (1.06)−1.15−0.01 (0.48)−0.02
Log likelihood−518.85−535.52
Wald χ273.7460.96

Figures in parenthesis are robust standard errors, statistically significant at the 0.01 ), 0.05 ), and 0.1 ) levels of probability.
Source: this study.