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Meta-analytical study on the effects of antibiotic growth promoters on productive pig performance

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Antibiotic growth promoters (AGP) are used as additives in animal feed to prevent diseases
and to increase productive performance. However, the use of AGP has been criticized
because of the possibility of residues in food and microbial resistance development. The main
purpose of this meta-analytical study was to quantify the impacts of the withdrawal of AGP
from feed, analyzing how it affects productive pig performance. Studies addressing
authorized AGP in feeding stuffs for pigs (Brazilian regulation, CPAA/DFIP/MAPA,
April/2015) were selected. Data were compiled from 67 articles, which involve 90
experiments and 40,592 pigs. Regarding these studies, 83% were about nursery pigs while
only 17% about growing-finishing pigs. Codes were used to consider the variability among
the compiled experiments and the qualitative grouping criteria in the analytical models.
Under this item later, the main codes were applied for the AGP presence in diets (nonsupplemented
diets, AGP-; or supplemented diets, AGP+). The meta-analysis followed three
sequential analyzes: graphic (to evaluate the quality database), correlation (to identify the
factors that should be considered in the statistical models), and variance-covariance (to
compare groups). Negative impacts of the withdrawal of AGP on productive pig performance
were observed in most of the treatments of the database (e.g., worse feed conversion in 73%
of the comparisons between treatments AGP- with their respective treatments AGP+). The
feed intake did not differ (P > 0.05) between animals fed diets AGP+ or AGP-. However, the
withdrawal of AGP decreased 4.5% the weight gain (AGP+: 443 g/d, AGP-: 423 g/d; P 0.05) and also increased 4% the feed conversion (AGP+: 1.82 g/g, AGP-: 1.89 g/g; P compared to the AGP+ treatment. This meta-analysis quantified the negative impacts of the
withdrawal of AGP from feed on the productive performance of pigs. These data can be used
to define feeding programs or growth models adjusted for specific production scenarios.