| Literature DB >> 31489183 |
Dishon Muloi1,2,3,4, Eric M Fèvre5,3,4, Judy Bettridge5,3, Robert Rono3, Daniel Ong'are3, James M Hassell5,3, Maurice K Karani3, Patrick Muinde3, Bram van Bunnik1,2, Alice Street6, Margo Chase-Topping2,7, Amy B Pedersen8, Melissa J Ward2,9, Mark Woolhouse1,2.
Abstract
BACKGROUND: Antimicrobial resistance (AMR) driven by antibiotic consumption is a growing global health threat. However, data on antimicrobial consumption patterns in low- and middle-income countries (LMICs) is sparse. Here, we investigate the patterns of antibiotic sales in humans and livestock in urban Nairobi, Kenya, and evaluate the level of awareness and common behaviours related to antibiotic use and AMR amongst human and veterinary pharmacists.Entities:
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Year: 2019 PMID: 31489183 PMCID: PMC6708591 DOI: 10.7189/jogh.09.020412
Source DB: PubMed Journal: J Glob Health ISSN: 2047-2978 Impact factor: 4.413
Figure 1Map of Nairobi county indicating locations of study sites.
Participant demographics and baseline clinical characteristics
| Characteristic | Human drug stores | Veterinary drug stores |
|---|---|---|
| 40 (67%) | 19 (33%) | |
| Female | 21 (52.5%) | 9 (47.4%) |
| Male | 19 (47.5%) | 10 (52.6%) |
| Primary | 0 | 1 (5.2%) |
| Secondary | 4 (10%) | 5 (26.3%) |
| Certificate | 4 (10%) | 5 (26.3%) |
| Diploma | 24 (60%) | 7 (36.8%) |
| Degree | 8 (20%) | 1 (5.3%) |
| Owner | 11 (27.5%) | 5 (26.3%) |
| Worker | 29 (72.5%) | 14 (73.7) |
| 30 | 30 | |
| Present | 36 (90%) | 11 (57%) |
| None | 4 (10%) | 8 (42.1%) |
| Clinical training only | 16 (40%) | 3 (15.8%) |
| CPD | 20 (50%) | 8 (41.1%) |
| None | 4 (10%) | 8 (42.1%) |
AMR – antimicrobial resistance, CPD – continuing professional development
Figure 2Proportion of the 15 antibiotic classes reported in human (n = 40) and/or veterinary drug stores (n = 19). Data arranged in order of the average proportion of antibiotic classes.
Figure 3Proportion of drug stores reporting the most commonly purchased antibiotics by different types of farmers based on the primary animal on the farm.
Figure 4Terms used to describe antimicrobial resistance.
Results of a multivariable regression examining the influence of sociodemographic factors on knowledge about AMR in a sample of 40 and 19 human and veterinary drug stores respectively.
| Variable | Estimate | Standard error | χ2 | df | |
|---|---|---|---|---|---|
| Veterinary drug store | 0.07 | 0.02 | 0.3 | 1 | 0.59 |
| Range of antibiotics | -0.01 | 0.02 | 0.31 | 1 | 0.58 |
| Clinical/veterinary training | 0.3 | 0.14 | 4.86 | 1 | 0.02 |
| High education level | 0.04 | 0.12 | 0.13 | 1 | 0.72 |