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Socioeconomic Factors Associated with Antimicrobial Resistance Of 01 Pan American Journal Original research of Public Health 02 03 04 05 06 Socioeconomic factors associated with antimicrobial 07 08 resistance of Pseudomonas aeruginosa, 09 10 Staphylococcus aureus, and Escherichia coli in Chilean 11 12 hospitals (2008–2017) 13 14 15 Kasim Allel,1 Patricia García,2 Jaime Labarca,3 José M. Munita,4 Magdalena Rendic,5 Grupo 16 6 5 17 Colaborativo de Resistencia Bacteriana, and Eduardo A. Undurraga 18 19 20 21 Suggested citation Allel K, García P, Labarca J, Munita JM, Rendic M; Grupo Colaborativo de Resistencia Bacteriana; et al. Socioeconomic fac- 22 tors associated with antimicrobial resistance of Pseudomonas aeruginosa, Staphylococcus aureus, and Escherichia coli in 23 Chilean hospitals (2008–2017). Rev Panam Salud Publica. 2020;44:e30. https://doi.org/10.26633/RPSP.2020.30 24 25 26 27 ABSTRACT Objective. To identify socioeconomic factors associated with antimicrobial resistance of Pseudomonas aeru- 28 ginosa, Staphylococcus aureus, and Escherichia coli in Chilean hospitals (2008–2017). 29 Methods. We reviewed the scientific literature on socioeconomic factors associated with the emergence and 30 dissemination of antimicrobial resistance. Using multivariate regression, we tested findings from the literature drawing from a longitudinal dataset on antimicrobial resistance from 41 major private and public hospitals and 31 a nationally representative household survey in Chile (2008–2017). We estimated resistance rates for three pri- 32 ority antibiotic–bacterium pairs, as defined by the Organisation for Economic Co-operation and Development; 33 i.e., imipenem and meropenem resistant P. aeruginosa, cloxacillin resistant S. aureus, and cefotaxime and 34 ciprofloxacin resistant E. coli. 35 Results. Evidence from the literature review suggests poverty and material deprivation are important risk 36 factors for the emergence and transmission of antimicrobial resistance. Most studies found that worse socio- 37 economic indicators were associated with higher rates of antimicrobial resistance. Our analysis showed an 38 overall antimicrobial resistance rate of 32.5%, with the highest rates for S. aureus (40.6%) and the lowest for 39 E. coli (25.7%). We found a small but consistent negative association between socioeconomic factors (income, 40 education, and occupation) and overall antimicrobial resistance in univariate (p < 0.01) and multivariate anal- 41 yses (p < 0.01), driven by resistant P. aeruginosa and S. aureus. 42 Conclusion. Socioeconomic factors beyond health care and hospital settings may affect the emergence and 43 dissemination of antimicrobial resistance. Preventing and controlling antimicrobial resistance requires efforts 44 above and beyond reducing antibiotic consumption. 45 46 47 Keywords Drug resistance, microbial; antibacterial agents; social conditions; social determinants of health; Latin America. 48 49 50 51 52 53 1 Millennium Initiative for Collaborative Research in Bacterial Resistance 4 Facultad de Medicina Clínica Alemana, Universidad del Desarrollo, Las 54 (MICROB-R), Santiago, Chile Condes, Chile 55 2 Departamento de Laboratorios Clínicos, Escuela de Medicina, Facultad de 5 Escuela de Gobierno, Pontificia Universidad Católica de Chile, Santiago, Chile. 56 Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile * Eduardo A. Undurraga, [email protected] 3 Departamento de Enfermedades Infecciosas, Escuela de Medicina, Facultad de 6 Grupo Colaborativo de Resistencia Bacteriana de la Sociedad Chilena de Infec- 57 Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile tología, Chile 58 59 This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 IGO License, which permits use, distribution, and reproduction in any medium, provided the 60 original work is properly cited. No modifications or commercial use of this article are permitted. In any reproduction of this article there should not be any suggestion that PAHO or this article endorse any specific organization or products. The use of the PAHO logo is not permitted. This notice should be preserved along with the article’s original URL. N61 Rev Panam Salud Publica 44, 2020 | www.paho.org/journal | https://doi.org/10.26633/RPSP.2020.30 1 Original research Allel et al. • Socioeconomic factors in antimicrobial resistance The emergence and spread of antimicrobial resistance is one for our qualitative synthesis, and included articles from our of the most urgent global public health threats (1, 2). Infections research on antimicrobial resistance (e.g., not indexed, book caused by resistant bacteria produce greater morbidity and chapters, government reports, policy briefs). We excluded edi- mortality, complicate treatments, and often result in longer torials, qualitative reports, opinions, and duplicated studies. hospitalizations, imposing higher costs to health systems (2, 3). Last, we only considered articles related to antimicrobial resist- Antimicrobial resistance occurs naturally as an adaptive mech- ance in general, or those that included the following bacteria: anism of bacteria; global increases in antibiotic use in humans, P. aeruginosa, S. aureus, and E. coli. animals (e.g., food production), and agriculture (e.g., use of copper as a bactericide), have increased the selective pressure Empirical analysis: Chile as a case study that drives the development of resistance, dramatically accel- erating this natural phenomenon (4–6). A recent estimate for We combined two datasets. We used antimicrobial resistance 76 countries by Klein et al. (7) shows overall antibiotic con- rates from 41 tertiary care hospitals (i.e., high complexity) in sumption, in defined daily doses (DDD), increased about 65% Chile, and socioeconomic data from the Encuesta de Caracter- and antibiotic consumption rate (DDDs per 1 000 inhabitants ización Socioeconómica Nacional (CASEN). More specifically, per day) increased about 39% between 2000 and 2015. This antimicrobial resistance data were collected annually (2008– increase in antibiotic consumption was largely driven by low- 2017) by the Grupo Colaborativo de Resistencia Bacteriana and middle-income countries (7). (GCRB) from the Chilean Society of Infectious Diseases (17); Although frequently overlooked, the emergence and dis- data include 67% of public and private tertiary hospitals in semination of antimicrobial resistance is also affected by Chile. The GCRB hospital network began with 19 hospitals socioeconomic and environmental factors, including inade- in 2008 and has increased in size, to more than 50 hospitals in quate water, sanitation, and hygiene (WASH) infrastructure, 2019. We included observations from all hospitals reporting living conditions, waste management, education and aware- at least one observation (resistance rate) over time for each ness, economic activities, and other factors such as climate, antibiotic–bacterium pair considered in our analysis (n = 41). health care quality, and migration (8–12). In addition, the lack of For comparability, we estimated resistance proportions based incentives has limited the development of new antibiotics; the on three OECD-defined priority antibiotic–bacterium pairs in process is expensive and expected profits are limited compared 2015, i.e., cefotaxime and ciprofloxacin resistant E. coli; cloxacil- to other medications, largely because the clinical benefits of lin resistant S. aureus; and imipenem and meropenem resistant antibiotics decrease in time and their use needs to be restricted P. aeruginosa (14). GCRB is an unbalanced panel; on average, to prevent resistance (13). hospitals reported 4.6 years of antimicrobial resistance data Recent estimates indicate that antimicrobial resistance in Latin between 2008 and 2017 (n = 190) in 24 municipalities in Chile. American countries ranges from 21% in Chile to 40% in Brazil, GCRB is a collaborative clinical surveillance network; partici- in contrast to an average antimicrobial resistance rate of 17% pant hospitals annually report the average susceptibility of a for countries from the Organisation for Economic Co-operation series of antibiotic–bacterium pairs from clinical samples, fol- and Development (OECD) (14). Socioeconomic factors could be lowing Clinical and Laboratory Standards Institute (CLSI) important predictors of antimicrobial resistance spread in Latin recommendations (17, 18). Antibiotic resistance rates were cal- America, a region with several competing health priorities, lim- culated by dividing the number of laboratory tests that showed ited health resources, deficient WASH infrastructure, uneven bacterial resistance to antibiotics by the total number of tests. health care access, South-South migration, extreme poverty, a We characterized the population attended by hospitals at large food industry, and ubiquitous economic inequality (15, 16). the municipality level, based on the CASEN survey for 2008– The objective of our study was to identify socioeconomic 2017. CASEN is a nationally representative household survey, factors associated with imipenem and meropenem resistant applied every two or three years since 1985 by the Chilean Pseudomonas aeruginosa, cloxacillin resistant Staphylococcus Ministry of Social Development, to socioeconomically char- aureus, and cefotaxime and ciprofloxacin resistant Escherichia acterize households. With an emphasis on poverty and social coli in Chilean hospitals (2008–2017). vulnerability, CASEN collects data on education, health, hous- ing, work, and income. We
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