2.6 Summary measures and statistical analysis
We estimated the overall pooled prevalence of NTS and the prevalence of
antimicrobial resistance in poultry samples with a meta-analysis of
proportions using the Freeman-Tukey double arcsine transformation with
95% exact confidence intervals (95% CI) (Chaidez-Ibarra et al., 2021).
Due to expected heterogeneity across studies, we defined a prioria random effects model (DerSimonian & Kacker, 2007). To estimate the
prevalence of NTS: first, we performed independent meta-analyses
according to the type of sample (birds, products, and environmental)
with subgroup analysis aggregating the studies by the level of sampling
(individual or flock/collective), and second, we performed independent
meta-analysis according to the type of sample aggregating the studies by
country (considering both individual and flock/collective data). To
estimate the prevalence of antimicrobial resistance, we performed
independent meta-analyses according to the number of antibiotics (1,
2-3, or ≥4) to which the NTS isolates were resistant and aggregated the
studies by the type of sample. The overall effect of the model was
assessed with the z statistic assuming an effect size = 0, whereas the
Cochran’s Q statistic (X 2 test) was used to
assess significant heterogeneity across trials and theI 2 statistic was used to measure the proportion
of variation in the effects caused by heterogeneity in the true effects
rather than sampling error (Diaz et al., 2019; Romo-Barron et al.,
2019). All analyses were performed on Stata 12 (StataCorp, TX, USA) and
the graphs were constructed on Prism 9 (GraphPad Inc., CA, USA). In all
the cases, we considered a value of p < 0.05 as
significant.