Alistair Anderson
Antibiotic Self-Medication and Antibiotic Resistance: Multilevel Regression Analysis of Repeat Cross-Sectional Survey Data in Europe
Anderson, Alistair
Authors
Abstract
Antibiotic resistance is a global public health issue with several anthropogenic drivers, including antibiotic consumption. Recent studies have highlighted that the relationship between antibiotic consumption and antibiotic resistance is contextualised by a variety of socioeconomic, cultural, and governance-related drivers of consumption behaviour and contagion that have been underexamined. A potential complication for research and policy is that measures of antibiotic consumption are often reliant on prescribing or sales data which may not easily take into account the dynamics of community consumption that include self-medication; for example, the preservation and use of leftover medication or the obtaining of antibiotics without a prescription. This study uses repeated cross-sectional survey data to fulfil two core aims: firstly, to examine the individual-level and national-contextual determinants of self-medication among antibiotic consumers in European countries, and secondly, to examine the relationship between self-medication behaviour and antibiotic resistance at the national level. This study is particularly novel in its application of a multilevel modelling specification that includes individual-level factors with both time-variant and persistent national characteristics to examine antibiotic consumption behaviours. The key findings of the study are that survey respondents in countries with persistently higher levels of inequality, burdens of out-of-pocket health expenditure, and corruption have an increased probability of self-medicating with antibiotics. The study also highlights that overall levels of antibiotic consumption and antibiotic self-medication do not correlate and are associated heterogeneously with changes in different pathogen/antibiotic pairs. In summary, the study emphasises that antibiotic stewardship and antibiotic resistance, whilst related by biological mechanisms, are also inherently social issues. Attempts to improve antibiotic stewardship and address the challenge of antibiotic resistance should also attend to structural challenges that underlie challenges to antibiotic stewardship in the community, such as the effects of inequality and reduced access to healthcare services.
Citation
Anderson, A. (2021). Antibiotic Self-Medication and Antibiotic Resistance: Multilevel Regression Analysis of Repeat Cross-Sectional Survey Data in Europe. REGION, 8(2), 121-145. https://doi.org/10.18335/region.v8i2.339
Journal Article Type | Article |
---|---|
Acceptance Date | Nov 15, 2021 |
Online Publication Date | Dec 6, 2021 |
Publication Date | Dec 31, 2021 |
Deposit Date | Dec 10, 2021 |
Publicly Available Date | Mar 28, 2024 |
Journal | REGION |
Print ISSN | 2409-5370 |
Electronic ISSN | 2409-5370 |
Publisher | European Regional Science Association |
Peer Reviewed | Peer Reviewed |
Volume | 8 |
Issue | 2 |
Pages | 121-145 |
DOI | https://doi.org/10.18335/region.v8i2.339 |
Keywords | Economics and Econometrics; Geography, Planning and Development |
Public URL | https://nottingham-repository.worktribe.com/output/6916492 |
Publisher URL | https://openjournals.wu.ac.at/ojs/index.php/region/article/view/339 |
Files
Antibiotic Self-Medication and Antibiotic Resistance: Multilevel Regression Analysis of Repeat Cross-Sectional Survey Data in Europe
(898 Kb)
PDF
Publisher Licence URL
https://creativecommons.org/licenses/by-nc/4.0/
You might also like
“Refugees from practice”? Exploring why some vets move from the clinic to the laboratory
(2021)
Journal Article
Regional and neighbourhood-based variation in three types of vaccine attitude in Britain
(2023)
Journal Article
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: digital-library-support@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search