Abstract
Objectives: Gender differences affect exposure to infections, including drug-resistant ones. However, data on the relationship between gender and antibiotic use are limited. This systematic review examines gender differences in antibiotic prescribing patterns in community and primary care settings. Study design: Systematic review. Methods: We searched Web of Science (Core Collection), PubMed, Scopus, Cochrane Database, and EMBASE for studies published between January 2014 and April 2024. We included studies of any design that analyzed antibiotic prescribing patterns for patients consulting general practitioners. We excluded studies that did not examine gender differences, unpublished reports, and non-English articles. We conducted a narrative synthesis of the findings. The review is registered in PROSPERO (CRD42023476119). Results: Our search identified 12,853 citations, from which we included 11 studies conducted in 10 countries. Most studies (n = 7) were cross-sectional. Gender analysis of antibiotic prescribing in the included studies did not show a consistent pattern in the likelihood of antibiotic prescription based on gender. The most commonly prescribed antibiotics were azithromycin, amoxicillin, cephalexins, penicillin, clarithromycin, and metronidazole, primarily for respiratory infections, sinusitis, bronchitis, pneumonia, COVID-19, skin, and musculoskeletal diseases. Most studies did not report dose compliance. Conclusions: Our systematic review identifies gender as a factor in antibiotic prescribing that remains insufficiently explored. Further research and policy discussions are needed to examine global prescribing patterns through a gender lens.
| Original language | English |
|---|---|
| Pages (from-to) | 311-318 |
| Number of pages | 8 |
| Journal | Public Health |
| Volume | 242 |
| DOIs | |
| Publication status | Published - May 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Antibiotic prescribing patterns
- Gender analysis
- Systematic review
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