Skip to main content
. 2022 Apr 8;17(4):e0266829. doi: 10.1371/journal.pone.0266829

Table 5. Logistic regression modelsa,b,c assessing the association between source type and the occurrence of select plasmid incompatibility types and antimicrobial resistance genes in phenotypically resistant Escherichia coli isolates collected from wildlife, swine manure pits, and environmental sources in southern Ontario, 2011−2013 (n = 200, dataset A).

tet(A) a tet(B) b , c bla TEM-1 b sul1 b
Source type OR (95%CI) p-value OR (95%CI) p-value OR (95%CI) p-value OR (95%CI) p-value
Swine manure pit REF 0.216 (global) REF 0.021 (global) REF 0.029 (global) REF 0.161 (global)
Water 0.61 (0.17−2.19) 0.433 0.92 (0.26−3.19) 0.892 4.03 (1.01−16.18) 0.050 0.72 (0.05−9.63) 0.805
Wildlife 1.27 (0.53−3.03) 0.593 0.28 (0.11−0.74) 0.010 2.11 (0.74−6.01) 0.161 3.76 (0.75−18.84) 0.107
Other environmentald 1.72 (0.73−4.09) 0.215 0.32 (0.13−0.79) 0.013 0.88 (0.31−2.54) 0.815 1.75 (0.34−9.05) 0.504
sul2 a ant(3”)-Ia a aph(3”)-Ib b aph(6)-Id b
Source type OR (95%CI) p-value OR (95%CI) p-value OR (95%CI) p-value OR (95%CI) p-value
Swine manure pit REF <0.001 (global) REF 0.810 (global) REF 0.379 (global) REF 0.379 (global)
Water 30.00 (3.40−264.50) 0.002 0.60 (0.14−2.68) 0.508 1.85 (0.51−6.66) 0.347 1.85 (0.51−6.66) 0.347
Wildlife 9.82 (1.25−77.20) 0.030 0.61 (0.21−1.75) 0.357 0.73 (0.28−1.91) 0.518 0.73 (0.28−1.91) 0.518
Other environmentald 8.00 (1.01−63.23) 0.049 0.77 (0.28−2.15) 0.624 0.91 (0.36−2.32) 0.847 0.91 (0.36−2.32) 0.847
IncFIB(AP001918) a IncI1(1-alpha) b , e IncFII a
Source type OR (95%CI) p-value OR (95%CI) p-value OR (95%CI) p-value
Swine manure pit REF 0.186 (global) REF 0.594 (global) REF 0.425 (global)
Water 2.80 (0.83−9.49) 0.097 0.23 (0.01−4.40) 0.331 0.86 (0.21−3.41) 0.827
Wildlife 2.39 (0.91−6.26) 0.076 1.39 (0.28−7.00) 0.689 0.42 (0.14−1.29) 0.130
Other environmentald 2.63 (1.01−6.85) 0.047 1.09 (0.22−5.39) 0.917 0.52 (0.18−1.52) 0.232

a The random intercept to account for clustering by site or animal was not retained in the model, thus ordinary logistic regression was used.

b Included a random intercept for clustering by site. Variance components were: tet(B) 0.10 (95%CI: 0.00−4.12); blaTEM-1 0.24 (95%CI: 0.03−1.80); sul1 0.27 (95%CI: 0.02−3.12); aph(3’’)-Ib 0.05 (95%CI: 0.00−28.92); aph(6)-Id 0.05 (95%CI: 0.00−28.92); IncI1(1-alpha) 0.93 (95%CI: 0.13−6.49).

c Adjusted for confounding by year of sampling

d Includes soil and dumpster isolates.

e A random intercept to account for clustering of isolates obtained from the same animal/dumpster/manure pit was retained in this model (variance components 0.54, 95%CI: 0.00−301.89).