Comparison of different approaches to antibiotic restriction in food-producing animals: stratified results from a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: We have previously reported, in a systematic review of 181 studies, that restriction of antibiotic use in food-producing animals is associated with a reduction in antibiotic-resistant bacterial isolates. While informative, that report did not concretely specify whether different types of restriction are associated with differential effectiveness in reducing resistance. We undertook a sub-analysis of the systematic review to address this question. METHODS: We created a classification scheme of different approaches to antibiotic restriction: (1) complete restriction; (2) single antibiotic-class restriction; (3) single antibiotic restriction; (4) all non-therapeutic use restriction; (5) growth promoter and prophylaxis restriction; (6) growth promoter restriction and (7) other/undetermined. All studies in the original systematic review that were amenable to meta-analysis were included into this substudy and coded by intervention type. Meta-analyses were conducted using random effects models, stratified by intervention type. RESULTS: A total of 127 studies were included. The most frequently studied intervention type was complete restriction (n=51), followed by restriction of non-therapeutic (n=33) and growth promoter (n=19) indications. None examined growth promoter and prophylaxis restrictions together. Three and seven studies examined single antibiotic-class and single antibiotic restrictions, respectively; these two intervention types were not significantly associated with reductions in antibiotic resistance. Though complete restrictions were associated with a 15% reduction in antibiotic resistance, less prohibitive approaches also demonstrated reduction in antibiotic resistance of 9%-30%. CONCLUSION: Broad interventions that restrict global antibiotic use appear to be more effective in reducing antibiotic resistance compared with restrictions that narrowly target one specific antibiotic or antibiotic class. Importantly, interventions that allow for therapeutic antibiotic use appear similarly effective compared with those that restrict all uses of antibiotics, suggesting that complete bans are not necessary. These findings directly inform the creation of specific policies to restrict antibiotic use in food-producing animals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.044 | 0.093 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.026 | 0.066 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".