Evidence map›Paper›PMID 38155204›Full record

ArticleScientific reports2023

Antibiotic quality and use practices amongst dairy farmers and drug retailers in central Kenyan highlands.

Dishon M Muloi, Peter Kurui, Garima Sharma, Linnet Ochieng, Fredrick Nganga, Fredrick Gudda, John Maingi Muthini, Delia Grace, Michel Dione, Arshnee Moodley and 1 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.9field-weighted citation impact, top 31% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 4 institutions in 3 countries.

Dishon M Muloi *Animal and Human Health Department, International Livestock Research Institute, Nairobi, Kenya. D.Muloi@cgiar.org.
Peter Kurui *Department of Biochemistry, Microbiology and Biotechnology, Kenyatta University, Nairobi, Kenya.
Garima SharmaAnimal and Human Health Department, International Livestock Research Institute, Nairobi, Kenya.
Linnet OchiengAnimal and Human Health Department, International Livestock Research Institute, Nairobi, Kenya.
Fredrick NgangaAnimal and Human Health Department, International Livestock Research Institute, Nairobi, Kenya.
Fredrick GuddaAnimal and Human Health Department, International Livestock Research Institute, Nairobi, Kenya.
John Maingi MuthiniDepartment of Biochemistry, Microbiology and Biotechnology, Kenyatta University, Nairobi, Kenya.
Delia GraceAnimal and Human Health Department, International Livestock Research Institute, Nairobi, Kenya.
Michel DioneAnimal and Human Health Department, International Livestock Research Institute, Dakar, Senegal.
Arshnee Moodley *Animal and Human Health Department, International Livestock Research Institute, Nairobi, Kenya. a.moodley@cgiar.org.
Caroline Muneri *Department of Veterinary Surgery, Theriogenology and Medicine, Egerton University, Njoro, Kenya.
International Livestock Research Institute · KEKenyatta University · KEEgerton University · KENatural Resources Institute · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding antibiotic use in dairy systems is critical to guide antimicrobial stewardship programs. We investigated antibiotic use practices in small-holder dairy farms, antibiotic quality, and antimicrobial resistance (AMR) awareness among veterinary drug retailers in a mixed farming community in the central Kenyan highlands. Data were collected from 248 dairy farms and 72 veterinary drug stores between February 2020 and October 2021. A scale was developed to measure knowledge about AMR and antibiotic use using item response theory, and regression models were used to evaluate factors associated with antibiotic use and AMR knowledge. The active pharmaceutical ingredient (API) content of 27 antibiotic samples was determined using high-performance liquid chromatography (HPLC). The presence and levels of 11 antibiotic residues in 108 milk samples collected from the study farms were also investigated using liquid chromatography tandem mass spectrometry (LC-MS/MS). Almost all farms (98.8%, n = 244) reported using antibiotics at least once in the last year, mostly for therapeutic reasons (35.5%). The most used antibiotics were tetracycline (30.6%), penicillin (16.7%), and sulfonamide (9.4%), either individually or in combination, and predominantly in the injectable form. Larger farm size (OR = 1.02, p < 0.001) and history of vaccination use (OR = 1.17, p < 0.001) were significantly associated with a higher frequency of antibiotic use. Drug retailers who advised on animal treatments had a significantly higher mean knowledge scores than those who only sold drugs. We found that 44.4% (12/27) of the tested antibiotics did not meet the United States Pharmacopeial test specifications (percentage of label claim). We detected nine antibiotics in milk, including oxytetracycline, sulfamethoxazole, and trimethoprim. However, only three samples exceeded the maximum residue limits set by the Codex Alimentarius Commission. Our findings indicate that antibiotics of poor quality are accessible and used in small-holder dairy systems, which can be found in milk. These results will aid future investigations on how to promote sustainable antibiotic use practices in dairy systems.

Indexed as

Anti-Bacterial AgentsVeterinary DrugsAnimalsChromatography, LiquidDairyingFarmersFarmsHumansKenyaTandem Mass SpectrometryAnti-Bacterial AgentsVeterinary Drugs

Identifiers

PMID38155204
PMCPMC10754936
OpenAlexW4390336533

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.