| Literature DB >> 35720810 |
Nichola Jones1, Jessica Mitchell1, Paul Cooke2, Sushil Baral3, Abriti Arjyal3, Ashim Shrestha3, Rebecca King1.
Abstract
Antimicrobial resistance (AMR), the natural process by which bacteria become resistant to the medicines used to kill them, is becoming one of the greatest threats to health globally. AMR is accelerating at alarming rates due to behaviors across human, animal, and environmental health sectors as well as governance and policy shortfalls across each sector. Antimicrobial resistant infections occur through the same channels as other infectious diseases and are most common in countries/areas where there is limited access to improved sanitation facilities, reliable healthcare and health education. At the community level, much remains to be understood about the drivers of antimicrobial resistance and how to generate community-led, acceptable solutions. Gender can influence every part of an individual's health experiences; access to knowledge, healthcare facilities, financial resources and paid employment are all heavily gendered and influence behaviors relating to the procurement of antimicrobial and antibiotic agents. This analysis uses data gathered during a participatory video study designed to work with two communities in Nepal to understand drivers of antibiotic mis and over use from the perspective of the communities themselves. Findings reveal that gender impacts upon many aspects of AMR-driving behaviors within this community and stimulate essential discussion as to the importance of gender in future AMR research. This paper places a spotlight on gender in the wider AMR conversation, an area that is currently neglected, and improve our collective knowledge on the drivers of AMR from a gendered perspective.Entities:
Keywords: antibiotic resistance; antimicrobial resistance; community; community engagement; gender; participation; public health
Year: 2022 PMID: 35720810 PMCID: PMC9199426 DOI: 10.3389/fgwh.2022.745862
Source DB: PubMed Journal: Front Glob Womens Health ISSN: 2673-5059
Figure 1Final analysis framework.