A multivariable analysis of the contribution of socioeconomic and environmental factors to blood culture Escherichia coli resistant to fluoroquinolones in high- and middle-income countries

Abstract

Background Antimicrobial resistance (AMR) is a public health concern. We wanted to determine if various environmental and socioeconomic variables as well as markers of antimicrobial use impacted on the level of AMR in countries of different income levels. Methods We performed cross-national univariate and multivariable analyses using the national proportion of quinolone-resistant Escherichia coli (QREC) in blood culture as the dependent variable. Access to safe water and sanitation, other socioeconomic variables, and human and animal antimicrobial consumption were analysed. Results In middle-income countries, unsafely managed sanitation, corruption and healthcare access and quality were significantly associated with the national proportion of blood culture QREC (%) in univariate analyses, whereas no variables remained significant in the multivariable models. For the multivariable high-income country model, corruption and healthcare access and quality were significantly associated with blood culture QREC (%) levels. For the model including all countries, human fluoroquinolone use, corruption level, livestock and crop production index were significantly associated with blood culture QREC (%) levels in the univariate analyses. Conclusion Corruption is a strong predictor of AMR, likely reflecting a multitude of socioeconomic factors. Sanitation quality contributed to increased blood culture QREC (%) levels in middle-income countries, although was not an independent factor, highlighting the need to also focus on infrastructure such as sanitation services in the context of AMR.

Non-Canonical Aspects of Antibiotics and Antibiotic Resistance

“…Some of the papers compared the aforementioned socioeconomic factors to the use of antibiotics regarding their impact on AR prevalence. The conclusions included the following: (a) antibiotic consumption is overshadowed by specific socioeconomic factors, with governance being “potentially as important a determinant of AR as is antibiotic usage in people” [ 407 ]; (b) corruption is the main socioeconomic factor behind AR prevalence, so that “once the control of corruption indicator is included as an additional explanatory variable, 63% of the total variation in AR is explained by the regression, while only 28% of the total variation in AR is attributable to variation in antibiotic usage in people” [ 407 ]; (c) antibiotic consumption is not strongly associated with AR levels [ 408 ]; (d) antibiotic usage was positively associated with AR in only one out of three pathogens analyzed [ 409 ]; (e) the use of fluoroquinolones in humans was positively associated with the prevalence of fluoroquinolone-resistant E. coli in HICs, but not in MICs [ 410 ]; and (f) the positive effect of ambulatory consumption of antibiotics upon AR prevalence decreased in importance in a multivariate analysis [ 411 ] and usage “only explained a minor part of the occurrence of AR across the world” [ 412 ]. As a worthy comparison, the prevalence of AR in isolates from livestock also does not correlate with antimicrobial usage alone: usage history, mobile populations, environmental reservoirs, etc., also contribute to the persistence of resistant bacteria in animals [ 413 ].…”

“…Total GDP [414] None GNI per capita [410] High GDP per capita [408] GDP per capita [415,416] a Negative GNI [417,418] Income inequality [419] Positive GDP per capita [407,416] a…”

“…Corruption control [407] Negative Lower corruption, political stability, rule of law, absence of violence [408] Corruption control, rule of law [414] Corruption control, voice and accountability, political stability and absence of violence/terrorism, government effectiveness, regulatory quality, rule of law [420] Corruption perception (high perception = low corruption) [410] Voice and accountability, government effectiveness, regulatory quality, rule of law, corruption control [415] Higher levels of corruption [409] Positive…”

“…Improved infrastructure (sanitation, safe water, internet accessibility, urbanization, access to electricity) [408] Negative Improving sanitation [412] Unsafe water sanitation and hygiene [410,420] None…”

“…Lower density of health facilities, larger numbers of beds in fewer facilities [409] Positive Lower physician density [416] Healthcare access or quality [410] Negative Access to immunization obstetric care [420] GDP: gross domestic product; GNI: gross national income. a .…”