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Article

International Travel as a Risk Factor for Carriage of Extended-Spectrum β-Lactamase-Producing Escherichia coli in a Large Sample of European Individuals—The AWARE Study

by
Daloha Rodríguez-Molina
1,2,3,*,†,
Fanny Berglund
4,5,
Hetty Blaak
6,
Carl-Fredrik Flach
4,5,
Merel Kemper
6,
Luminita Marutescu
7,8,
Gratiela Pircalabioru Gradisteanu
7,8,
Marcela Popa
7,8,
Beate Spießberger
9,10,11,
Laura Wengenroth
1,
Mariana Carmen Chifiriuc
7,8,
D. G. Joakim Larsson
4,5,
Dennis Nowak
1,12,
Katja Radon
1,
Ana Maria de Roda Husman
6,
Andreas Wieser
9,10,11 and
Heike Schmitt
6
1
Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, 80336 Munich, Germany
2
Institute for Medical Information Processing, Biometry and Epidemiology—IBE, LMU Munich, 81377 Munich, Germany
3
Pettenkofer School of Public Health, 81377 Munich, Germany
4
Department of Infectious Diseases, Institute of Biomedicine, The Sahlgrenska Academy, University of Gothenburg, 40530 Gothenburg, Sweden
5
Centre for Antibiotic Resistance Research (CARe), University of Gothenburg, 40530 Gothenburg, Sweden
6
Centre of Infectious Disease Control, National Institute for Public Health and the Environment, 3721 MA Bilthoven, The Netherlands
7
Department of Microbiology and Immunology, Faculty of Biology, University of Bucharest and the Academy of Romanian Scientists, 050657 Bucharest, Romania
8
Earth, Environmental and Life Sciences Section, Research Institute of the University of Bucharest, University of Bucharest, 030018 Bucharest, Romania
9
German Centre for Infection Research (DZIF), Partner Site Munich, 80336 Munich, Germany
10
Max von Pettenkofer Institute, Faculty of Medicine, LMU Munich, 81377 Munich, Germany
11
Department of Infectious Diseases and Tropical Medicine, LMU University Hospital Munich, 80802 Munich, Germany
12
Comprehensive Pneumology Center Munich (CPC-M), German Center for Lung Research (DZL), 80336 Munich, Germany
 
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*
Author to whom correspondence should be addressed.
†
Current address: Occupational and Environmental Epidemiology and NetTeaching Unit, Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, Ziemssenstr. 5, 80336 Munich, Germany.
Int. J. Environ. Res. Public Health 2022, 19(8), 4758; https://doi.org/10.3390/ijerph19084758
Submission received: 11 March 2022 / Revised: 10 April 2022 / Accepted: 13 April 2022 / Published: 14 April 2022
(This article belongs to the Special Issue Research on Antibiotic Resistance within One Health)
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Abstract

:
Antibiotic resistance (AR) is currently a major threat to global health, calling for a One Health approach to be properly understood, monitored, tackled, and managed. Potential risk factors for AR are often studied in specific high-risk populations, but are still poorly understood in the general population. Our aim was to explore, describe, and characterize potential risk factors for carriage of Extended-Spectrum Beta-Lactamase-resistant Escherichia coli (ESBL-EC) in a large sample of European individuals aged between 16 and 67 years recruited from the general population in Southern Germany, the Netherlands, and Romania. Questionnaire and stool sample collection for this cross-sectional study took place from September 2018 to March 2020. Selected cultures of participants’ stool samples were analyzed for detection of ESBL-EC. A total of 1183 participants were included in the analyses: 333 from Germany, 689 from the Netherlands, and 161 from Romania. Travels to Northern Africa (adjusted Odds Ratio, aOR 4.03, 95% Confidence Interval, CI 1.67–9.68), Sub-Saharan Africa (aOR 4.60, 95% CI 1.60–13.26), and Asia (aOR 4.08, 95% CI 1.97–8.43) were identified as independent risk factors for carriage of ESBL-EC. Therefore, travel to these regions should continue to be routinely asked about by clinical practitioners as possible risk factors when considering antibiotic therapy.

1. Introduction

Extended-spectrum β-lactamases (ESBLs) are plasmid-mediated enzymes that inactivate β-lactam antibiotics, posing a significant therapeutic challenge in the treatment of both hospital and community-acquired infections [1]. Infections with ESBL-producing E. coli (ESBL-EC) often require therapy with last-resort antibiotics, increasing both the risk of resistance and the associated healthcare costs [2,3]. Resistance to last resort antibiotics further limits treatment options and is associated with prolonged hospital stays and increased mortality [4]. An increase in the prevalence of ESBL-EC, in both community and healthcare settings, is now observed worldwide: the current global prevalence of healthy individuals with ESBL-EC from 2003 to 2018 is estimated to be 16.5%; having increased from 2.6% in 2003–2005 to 21.1% in 2015–2018 [5]. In 2019, we estimated the prevalence of these bacteria in the general population of three European countries, and we found it to be 13% in Romania, 8% in Germany, and 6% in the Netherlands [6]. For comparison, the current prevalence in Europe is 6% [5].
The development and spread of antibiotic resistance (AR) is correlated with the use of antibiotics in the healthcare sector and in the agriculture and husbandry sectors [1,3,7,8]. Antibiotic therapy is also a risk factor for carriage of AR by individuals. Other potential risk factors include: travels to high-risk areas for AR [2,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28], consumption of food contaminated with AR bacteria [29,30], a poorer health status that leads individuals into being treated with antibiotics or at healthcare facilities increasing their exposure to AR bacteria [23,26], and occupation where the workplace might potentially increase exposure to antibiotics or AR bacteria, such as working at animal markets, dairy facilities, farms, slaughterhouses, wastewater treatment plants, and healthcare facilities [31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46]. However, most of the studies examining potential risk factors focus on high-risk populations, such as travelers [10,12,16,20,22,26,27,47], healthcare workers and patients [40,45,46,48,49,50], swimmers [51,52,53], farmers [33,34,35,36,38,39,41,43,44], and slaughterhouse workers [32], and often use small, convenient samples of, e.g., students [2,18,19,23]. However, risk factors for AR in the general population have not yet been sufficiently investigated. This is of great importance for developing preventive measures and antibiotic therapy policies.
As part of the larger AWARE study [6,54], this study aimed to explore, describe, and characterize potential risk factors for carriage of ESBL-EC in a large sample of European individuals recruited from the general population in three countries with a different prevalence of AR, i.e., Germany, the Netherlands, and Romania.

2. Materials and Methods

2.1. Study Design and Participants

The study population comes from participants enrolled in the large trans-European cross-sectional AWARE study (Antibiotic Resistance in Wastewater: Transmission Risks for Employees and Residents around Wastewater Treatment Plants). The full methodology of this project has been previously described [6,54]. The subset of the data used in these analyses corresponds to individuals from the general population living more than 1000 m away from a local WWTP, and, thus, not exposed to potential AR bacteria coming from such facilities. Data collection took place from September 2018 to March 2020 in Southern Germany, the Netherlands, and Romania. Having age between 16 and 67 years was an inclusion criterion.
In Southern Germany, we recruited participants using households as the unit of recruitment. We obtained household participant information from local civil registries. Invitation letters were mailed to all individuals older than 16 years of age within the household. For locations where we could not obtain participant information through the civil registries, invitation letters were dropped in household mailboxes by members of the study team. Aids in recruitment included two reminder letters, articles about the project in the local newspaper, recruitment campaigns via Facebook, and a raffle of shopping vouchers worth EUR 1500 in total for participants who completed the study. In the Netherlands, the offices of general practitioners served as recruitment points. We used ArcGis™ [55] to identify all postal addresses in a 500-m radius from 22 different General Practitioners’ (GP) practices and then we randomly retrieved contact information for 200–500 households per GP practice using the Dutch Personal Records Database. The invitation to participate was addressed to all members of these households aged over the age of 16 (conform the conditions for General Data Protection Regulation data use). All participants who completed the study received a shopping voucher worth EUR 20. In Romania, we identified participant households and invited participants through door-to-door visits.
Ethics approval was obtained from the Ethics Committee of the University of Munich (LMU) (Project-No. 17-734) and the Research Ethics Committee of the University of Bucharest (Registration-No. 164/05.12.2017). The ethics board in the Netherlands exempted this study for ethical approval under the Dutch Medical Research Involving Human Subjects Act (WMO; Committee: Medisch Ethische Toetsingscommissie, number of confirmation: 19-001/C). All subjects gave their informed consent for inclusion before they participated in the study. The study was conducted in accordance with the Declaration of Helsinki of 1975, revised in 2013.

2.2. Variables of Interest

Potential Risk Factors

Participants were asked to complete an online questionnaire [54] containing questions about socio-demographic characteristics, including date of birth (used to operationalize age in years), sex (female, male), educational level (according to the national educational system), and country of residence (Germany, the Netherlands, or Romania). The questionnaire also included questions about potential risk factors for carriage of ESBL-EC in the past year, such as: job history; hospital and farm visits (no, yes); contact with animals (no, yes); contact with patients or human tissues at work (never, rarely, sometimes, often, always); use of antibiotics and antacids (no, yes, do not know); self-reported health status (poor, fair, good, very good, excellent); self-reported frequency of diarrhea (never, rarely, sometimes, often, always); surgeries (no, yes); and international travel to Europe, Asia, North Africa, Sub-Saharan Africa, North America, Central America or Mexico, South America, and Australia or Oceania (never, once, 2–3 times, more than 3 times, do not know). The details on how these variables were chosen have been previously published [54].
Educational level was explored using national educational system levels and then dichotomized into low (pre-primary education to lower secondary education) or high educational level (upper secondary education to Doctoral or equivalent) according to the Standard Classification of Education (ISCED) [56,57,58]. Variables using a frequency scale with five levels were reduced to two levels in the case of frequency of diarrhea (never, rarely, or sometimes/often or always) and of self-reported health status (good, very good or excellent/fair or poor), and in the case of patient contact and of work with human tissues into three levels (never/rarely or sometimes/often or always). In questions including a “do not know” option (antibiotics and antacid intake, travels to Europe), this option was coded into the “no” category considering that the proportion of participants choosing this option was very low (3.1% for antibiotic intake, 2.9% for antacid intake, 0.1% for travels to Europe). We show descriptive counts for international travel variables as we collected the questionnaire data, i.e., using the following frequency scale for travel in the past 12 months: “never”, “once”, “2–3 times”, “more than 3 times”, “do not know”. For inferential analysis using regression models, these variables were collapsed into two levels: “never” and “at least once”. For the regression models, travels to Central and South America were collapsed into one variable. Additionally, we constructed a travel score considering travel to Asia, North Africa, Sub-Saharan Africa, Central America or Mexico, South America, and the European countries Italy, Bulgaria, Greece, and Slovenia as high-risk areas for AR. The travel score adds one point for travelling once, two points for travelling 2–3 times, and 3 points for travelling more than 3 times to any of these areas in the past year, while “never” was translated into zero points.

2.3. Outcome of Interest

In the Netherlands, all recruited participants were asked to provide a stool sample using a stool sample kit. In Germany and Romania, only participants who completed the online questionnaire were asked to provide a stool sample. After sampling, stool samples were kept refrigerated, transported in cooling boxes (2 °C to 8 °C), and processed within 24 h. Samples were inoculated directly into TBX (only in the Netherlands and Romania) or MacConkey (in Germany) agar plates (for E. coli), and on ChromID® ESBL (for ESBL-EC) and incubated at 36 °C ± 1 °C for 24–48 h. In case of positive results for ESBL-EC, 2 separate isolates per sample were collected from the selective ESBL plate for antibiotic resistance phenotype confirmation, and identification using MALDI-TOF MS (Matrix Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry). ESBL confirmatory tests were performed using cefotaxime and ceftazidime disks, alone and combined with clavulanate, following guidelines from the Clinical Laboratory Standards Institute (CLSI) [59]. The test was considered positive for strains showing a 5 mm increase in zone diameter in the presence of clavulanate. Stool sample results were coded binarily as positive or negative and included in the analyses.

2.4. Statistical Analyses

We used a Mann–Whitney test for observing differences in non-normally distributed numerical variables (age and travel score) and the Fisher’s exact test for differences in proportions (all the other variables). Variable selection was performed using a combination of bivariate analysis results (p-value ≤ 0.2) and expert opinion. We regressed carriage of ESBL-EC on a set of potential risk factors using two logistic regression models. The first model included sociodemographic variables (age, sex, educational level, and country of residence), frequency of diarrhea, antibiotics use, and travel score. The second model was similar to the first one, except that, instead of the travel score, it included each geographical area as we assessed them in the questionnaire, with “Central America or Mexico” and “South America” collapsed into one variable. We report both crude and adjusted estimates for both models. Missing values were handled by multiple imputation where the missing mechanism was missing at random (MAR) or missing completely at random (MCAR). MAR means that the probability of the data being missing is not due to unobserved data, conditional on the data that were collected. MAR is the second-best scenario for multiple imputation after MCAR, which occurs when the probability of the data being missing does not depend on the observed or unobserved data, and is, thus, the best scenario for multiple imputation [60]. Multiple imputation diagnostic tables can be found in the Supplementary Materials (Supplementary Tables S1 and S2). Inverse probability of sample weights was used to adjust for non-response by country [61,62]. We present model results in odds ratios (OR) with the corresponding 95% confidence intervals (CI). All analyses were performed in R version 4.1.0 [63].

3. Results

3.1. Study Population

In Germany, we invited 3153 residents (response 11%), while in the Netherlands we contacted 13,918 identified individuals by postal service, of which 10,448 were eligible by age (response 6%), and in Romania we invited 280 residents (response 54%). A total of 1183 participants were included in the analyses: 333 from Germany, 689 from the Netherlands, and 161 from Romania. The average prevalence of ESBL-EC carriage across the three countries was 7.5%, which corresponds to 8.4% in Germany, 6.1% in the Netherlands, and 12.6% in Romania. A total of 109 participants (95 in Germany, 3 in the Netherlands, and 11 in Romania) did not hand in a stool sample or had non-valid stool samples (9.2%). The large proportion of missing stool samples in Germany stems from having a short window for sample collection and transportation in this location, with which many participants failed to hand in the sample. This, however, did not happen in the Netherlands or Romania where samples were to be brought to GP practices within a 500-m distance from people’s homes collected by door-to-door visits.
The majority of participants in the overall sample were women (59.4%), middle-aged (median age 48 years, IQR 35–59), and highly educated (66.5%). Most participants reported no major risk factors for AR in the past year: no hospital visits neither as patient (92.9%), nor as professional (96.5%) or visitor (97.9%), no patient contact (73.6%), no use of antibiotics (76.1%) or antacids (77.2%), no surgeries (95.5%), no or infrequent diarrhea (94.2%), no work with human tissues (75.4%), no work with animals (96.5%), no work at a farm (99.0%), no work at a slaughterhouse (99.8%), no work with manure (97.0%), no farm visits (89.3%), and no animal contact (has no horses: 97.0%, has no dogs: 77.2%, has no cats: 75.7%). Additionally, most participants reported a health status from good to excellent (86.5%). Although a little more than two thirds of the study population reported travelling within Europe at least once in the past year (71.7%), they rarely traveled outside of the European continent: Australia or Oceania (1.0%), Central America (2.0%), South America (1.9%), Sub-Saharan Africa (2.4%), North America (3.6%), Northern Africa (4.2%), or Asia (7.2%). The proportion of population characteristics for individuals with a positive stool sample for ESBL-EC were similar as for the whole study population (Table 1 and Table 2).

3.2. Risk Factors for ESBL-EC Carriage

Descriptive analyses including data from all study centers showed that ESBL-EC positive participants had higher education and were less likely to have a dog as a pet (Table 1). Furthermore, they were more likely to have had traveled at least once in the past year to Sub-Saharan Africa, Northern Africa, Asia, or North America according to bivariate analyses.
Country-specific analyses showed that travels to Northern Africa were associated with ESBL-EC carriage in the German sub-population, while an association was identified in the Dutch sub-population for traveling to Northern Africa, Sub-Saharan Africa, or Asia. In the Romanian subpopulation, high educational level, not having a dog as a pet, and working with human tissues were factors associated with ESBL-EC carriage. The travel score for travel to geographical areas with a known high-risk for AR, was significantly higher in the overall and Dutch ESBL-EC positive populations (p-value 0.02 and 0.001, respectively), compared to participants without ESBL-EC carriage (Table 2).
Confirming descriptive and bivariate results, self-reported travel to North Africa, Sub-Saharan Africa, and Asia at least once in the past year were identified as independent risk factors for ESBL-EC carriage in our study population, both in crude and adjusted models (Figure 1). A summary of the adjusted estimates for travel to different geographical areas can be seen in Figure 2.
On average, participants were about four times more likely to be carriers of ESBL-EC after travelling at least once in the past year to Northern Africa (adjusted OR 4.03, 95% CI 1.67–9.68), Sub-Saharan Africa (adjusted OR 4.60, 95% CI 1.60–13.26), and Asia (adjusted OR 4.08, 95% CI 1.97–8.43, Supplementary Table S4), compared with no travels to these regions. Although participants were twice as likely to be ESBL-EC carriers after traveling to North America, we could only identify a statistically significant association in the crude model (OR crude 2.79, 95% CI 1.17–6.67 vs. OR adjusted 2.40, 95% CI 0.94–6.09). The model including the travel score confirms these findings (Figure 1, Supplementary Table S3): Participants were 28% more likely to be ESBL-EC carriers when their travel score increased by one point, i.e., when they traveled at least once to any of the pre-specified high-risk areas for AR (adjusted OR 1.28, 95% CI 1.01–1.64, Supplementary Table S3).

4. Discussion

In this study, we found that destination for travels made during the past year is an important personal risk factor for carriage of ESBL-EC in the general population, especially North Africa, Sub-Saharan Africa, Asia, and—to some extent—North America. Other studies in risk populations have found similar results: some of these studies indicate that the prevalence of ESBL-EC acquisition is worryingly high in visitors returning from India, China and Southeast Asia, Middle East, Northern Africa, and Central and South America [64,65]. For European residents, travel outside of Europe was identified as a major travel risk factor [17]. A 2017 prospective study performed on Dutch travelers (n = 2001) found out that 34.3% of participants who were ESBL negative before travel, became positive for ESBL-EC during their travels, with the highest number being among participants travelling to Southern Asia [13].
We also found some differences in the country-specific travel patterns. By having collected a large sample size in The Netherlands, we were able to identify that this sub-population is at higher risk of ESBL-EC carriage when travelling to North Africa, Sub-Saharan Africa, and Asia within the past year. These results are comparable to those of a recently published large cross-sectional study of the Dutch general population, which identified traveling to Africa and Asia as independent risk factors for ESBL-EC carriage [66]. We found similar patterns in our German study population, where participants are at higher risk of ESBL-EC carriage after travels to Northern Africa and North America within the past year. Given that the national estimated prevalence of ESBL-EC causing urinary tract infections in the U.S. is 15.7%, ranging from 10.6% in the West North Central states to as high as 29.6% in the Mid-Atlantic states [67], our finding that travelers to North America were also at increased risk is not surprising. Conversely, in Romania, although the prevalence is already high, we found that the travel frequency is lower, therefore limiting our ability to analyze the effect of travel on ESBL-EC carriage in this subpopulation. Most of the Romanian participants reported not having travelled internationally at all within the past year. These findings suggest that the role of travel is country or context dependent.
The sewage surveillance data regarding the AR are in line with the estimated global burden of this threat. Current estimates indicate that the presence of AR genes found in the sewage is alarmingly at the highest level in Africa followed by Asia [68]. Models from sewage surveillance data show that the predicted clinical resistance to aminopenicillin, fluoroquinolones, and third generation cephalosporins are also at the highest resistance levels in Africa, followed by Asia [69]. These results from sewage surveillance data are in line with estimated global burden of disease from AR. The percentage of resistant isolates and the estimated death rate from AR E. coli have been reported to be at the highest in South Asia, followed by Sub-Saharan Africa [70]. Even though there have been some efforts in starting and maintaining clinical and sewage surveillance of AR bacteria in some countries of Africa and Asia [71], data on AR in these areas are still lacking to a large extent [70]. Some of these efforts include stewardship and surveillance programs in Ethiopia [72] and Ghana [73], or more generally in the African [74,75] and Asian regions [76,77,78]. The World Health Organization Global Antimicrobial Resistance and Use Surveillance System (WHO-GLASS) Report in 2021 states that out of 47 African countries, territories, and areas, only half (23/47, 49%) are enrolled in GLASS and only a third (15/47, 32%) reported information from the national surveillance system to GLASS [79]. The South East Asia region provides a better outlook: out of 11 countries, territories, and areas in South East Asia, all of them are enrolled in GLASS, and nine of them (81%) reported information from the national surveillance system [79]. However, some of the challenges to these programs include bias in sampling and data collection in these areas, which leads to gaps in knowledge about the AR situation at the global level.
Our findings have implications for clinical practice. Asking patients about their travel history in the past year might help clinicians in their decision-making process for choosing specific antibiotic protocols as the first-, second-, or third-line of treatment. Further, the use of a travel score, such as the one we have constructed, might be a straightforward way of quantifying the degree of risk due to travel. However, our travel score is still far from ready to be used in clinical practice in its current form. On the one hand, it does not include other details about the travel experience, such as reason for travel, length of stay, or place of residence within the visited location. It might be that individuals who travel abroad for business reasons are exposed to a very different set of environmental factors than those who travel to visit friends or family, partly because their consumption patterns might be different. Additionally, closer interactions with locals might increase the risk of direct or indirect exposure to AR bacteria such as ESBL-EC when sharing toilets with friends or family members, as opposed to staying at a hotel with private toilet facilities and frequent cleaning and disinfection.
According to our data, no other risk factor explored besides travels posed an effect on carriage of ESBL-EC. Antibiotics use is a risk factor for AR commonly mentioned in the literature [23,26]. We believe that one of the reasons why we were not able to estimate an effect for antibiotics use in our study is that, although these effects are relatively easy to identify in high-risk populations such as travelers, farmers, slaughterhouse workers, healthcare providers, or patients, the sample size needed to detect an effect in the general population would be considerably higher. Another potential reason is that the effect of antibiotics use on AR might not be detectable more than 6 months after travel. A recent study by Bunt et al. [66] in 4177 Dutch participants from the general population (four times the size of our study) showed a positive effect of antibiotics use for ESBL-EC carriage up to 6 months before study participation, but not at 6 to 12 months, nor more than a year before participation.
The main strength of our study is that, to our knowledge, this is the first international study across several countries that confirms travel risks for AR in the general population. Whereas many previously published studies have indeed reported travel as a risk factor for ESBL-EC carriage, our study was performed on a large sample stemming from the general population. These are generally healthy, working adults that were recruited without considering any specific high-risk factor for AR. Yet, we have found that travel is a risk factor for carriage of ESBL-EC, have characterized high-risk geographical areas for travels, and have estimated the magnitude of the effect of travelling to these areas. Additionally, although the study population was enrolled as part of the large trans-European cross-sectional AWARE study, it was assumed that individuals from the general population living more than 1000 m away from a local WWTP were not exposed to potential AR bacteria coming from such facilities. Therefore, we have a relatively large sample of participants drawn from the general population in Southern Germany, the Netherlands, and Romania. In contrast, other similar studies explored risk factors in large sample sizes from only one country [66], in specific high-risk populations, such as farmers [33,34,35,36,38,39,41,43,44] and slaughterhouse workers [32], healthcare workers and patients [40,45,46,48,49,50], or travelers [8,10,14,18,20,25,26,46], or in convenient samples of students [2,18,19,23]. Further, when exploring frequency of travel, we considered all areas of the globe, and did not limit ourselves to low-and-middle income countries or other areas that would have been otherwise considered a priori as high-risk areas for AR.
Some of the limitations of our study include a low response, especially in Germany and in the Netherlands, and a high proportion of missing values, especially in Germany, which lead to a relatively low statistical power for some potential risk factors and might limit the representativeness of our sample. We have used analytical tools, such as inverse probability of sampling weights, based on the response and multiple imputation to address these issues. Our potential risk factors were assessed by a questionnaire instead of by direct measurement or by cross-referencing with medical data, which might lead to recall bias and, thus, misclassification based on the risk factors. If this was the case, we would be erring on the conservative side by underestimating potential effects. Further, our sample might not be exempt from selection effects as our population was relatively young and highly educated. Age and socio-economic status (SES) might also play a role in our estimation of results from travel variables because we might assume that younger people travel more often and to different regions of the globe than older people, or because people of a higher SES might have the financial resources and freedom to travel more often than people of lower SES. In our study, we have included age and educational level (as a proxy for SES) in our regression models, thus adjusting for these potential confounders.

5. Conclusions

In our study, we have identified travel to Northern Africa, Sub-Saharan Africa, Asia, and—to some extent—North America as independent risk factors for ESBL-EC carriage in a large sample of European individuals residing in Southern Germany, the Netherlands, and Romania. With our data, we were not able to identify other potential risk factors for carriage of ESBL-EC frequently mentioned in the literature such as the use of antibiotics within the past year, probably because the sample size needed to detect such effects in the general population would have to be at least about four times as large as ours. Further, we have developed a travel score that, although it needs refining to include information, such as reason for travel, length of stay, or place of residence, could be developed as a valuable tool in clinical practice when dealing with patients in need of an empirical treatment protocol with antibiotics. Questions about travel to Africa and Asia should continue to be routinely asked in clinical practice, as these travels are risk factors when considering antibiotic therapy.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijerph19084758/s1, Table S1: Multiple imputation diagnostics—Traditional (unweighted) logistic regression models, complete cases vs. imputed for model with personal travel score, AWARE Study, 2022; Table S2: Multiple imputation diagnostics—Traditional (unweighted) logistic regression models, complete cases vs. imputed for model with individual travel areas, AWARE Study, 2022; Table S3: Models comparing risk factors for ESBL-producing E. coli in stool samples, with personal travel score, AWARE Study, 2022; Table S4: Models comparing risk factors for ESBL-producing E. coli in stool samples, with individual travel areas, AWARE Study, 2022.

Author Contributions

Study conception and design: M.C.C., D.G.J.L., K.R., D.N., A.W., A.M.d.R.H. and H.S. Fieldwork and data collection: D.R.-M., H.B., M.P., M.K., L.M., G.P.G. and L.W. Microbiology: H.B., M.P., M.K., L.M., G.P.G., M.C.C., B.S., A.W., A.M.d.R.H. and H.S. Data cleaning and analysis: D.R.-M., H.B. and M.P. Interpretation of the data: D.R.-M., F.B., H.B., C.-F.F., L.W., D.G.J.L., K.R., A.M.d.R.H. and H.S. Drafting of the manuscript: D.R.-M. All authors have read and agreed to the published version of the manuscript.

Funding

AWARE (Antibiotic Resistance in Wastewater: Transmission Risks for Employees and Residents around Wastewater Treatment Plants) is supported by the European Commission (JPI-EC-AMR ERA-Net Cofund grant no 681055), the Bundesministerum für Bildung und Forschung, DLR Projektträger (01KI1708), UEFISCDI project ERANET-JPI-EC-AMR-AWARE-WWTP No. 26/2017, the Netherlands Organisation for Health Research and Development, The Hague, the Netherlands (ZonMw, grant 547001007), and the Swedish Research Council VR Grant No. 2016-06512.

Institutional Review Board Statement

Ethics approval was obtained from the Ethics Committee of the University of Munich (LMU) (Project-No. 17-734) and the Research Ethics Committee of the University of Bucharest (Registration-No. 164/05.12.2017). The ethics board in the Netherlands exempted this study for ethical approval under the Dutch Medical Research Involving Human Subjects Act (WMO; Committee: Medisch Ethische Toetsingscommissie, number of confirmation: 19-001/C).

Informed Consent Statement

All subjects gave their informed consent for inclusion before they participated in the study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy reasons.

Acknowledgments

AWARE (Antibiotic Resistance in Wastewater: Transmission Risks for Employees and Residents around Wastewater Treatment Plants) is supported by the European Commission (JPI-EC-AMR ERA-Net Cofund grant no 681055), the Bundesministerum für Bildung und Forschung, DLR Projektträger (01KI1708), UEFISCDI project ERANET-JPI-EC-AMR-AWARE-WWTP No. 26/2017, the Netherlands Organisation for Health Research and Development, The Hague, the Netherlands (ZonMw, grant 547001007), and the Swedish Research Council VR Grant No. 2016-06512.

Conflicts of Interest

The authors declare no conflict of interest.

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Ijerph 19 04758 g001 550
Figure 1. Risk factor analysis for carriage of ESBL-producing E. coli in stool samples.
Figure 1. Risk factor analysis for carriage of ESBL-producing E. coli in stool samples.
Ijerph 19 04758 g001
Ijerph 19 04758 g002 550
Figure 2. Travel areas as risk factors for ESBL-EC carriage (adjusted OR). Note: The European spot in South America corresponds to French Guiana.
Figure 2. Travel areas as risk factors for ESBL-EC carriage (adjusted OR). Note: The European spot in South America corresponds to French Guiana.
Ijerph 19 04758 g002
Table
Table 1. Categorical descriptive characteristics of ESBL-producing E. coli carriers by country, n = 1183.
Table 1. Categorical descriptive characteristics of ESBL-producing E. coli carriers by country, n = 1183.
Overall,
n = 1074		Germany,
n = 238		The Netherlands,
n = 686		Romania,
n = 150
Missing Values for Stool Samples, n10995311
VariableMissingLevelESBL_EC+,
n (%)		pESBL_EC+,
n (%)		pESBL_EC+,
n (%)		pESBL_EC+,
n (%)		p
ESBL-EC positives 81 (8) 20 (8) 42 (6) 19 (13)
Sex4Female47 (7)0.81412 (9)1.00025 (6)0.87119 (13)1.000
Male34 (8) 8 (8) 17 (6) 9 (13)
Highest educational level obtained a2Low19 (5)0.0506 (10)0.60213 (5)0.1960 (0)0.217
High62 (9) 14 (8) 29 (7) 19 (14)
Work with animals in the past year35No75 (7)0.75218 (8)1.00040 (6)0.65917 (12)0.555
Yes3 (8) 0 (0) 2 (8) 1 (17)
Work at a farm in the past year25No77 (7)0.19718 (8)1.00040 (6)0.10419 (13)NA
Yes2 (18) 0 (0) 2 (22) --- (---)
Work at a slaughterhouse in the past year20No79 (7)1.00018 (8)NA42 (6)1.00019 (13)1.000
Yes0 (0) --- (---) 0 (0) 0 (0)
Work with manure in the past year22No76 (7)1.00018 (8)1.00041 (6)1.00017 (12)0.482
Yes2 (6) 0 (0) 1 (5) 1 (20)
Patient contact or work with human tissues in the past year b20No52 (7)1.00012 (8)1.00029 (7)0.73811 (10)0.133
Yes26 (7) 6 (7) 13 (6) 7 (21)
Patient contact in the past year20Never58 (7)0.48113 (8)0.55231 (6)0.87214 (12)0.672
Rarely or sometimes11 (9) 3 (12) 5 (7) 3 (18)
Often or always9 (6) 2 (5) 6 (5) 1 (12)
Work with human tissues in the past year16Never57 (7)0.70413 (8)1.00032 (6)0.92812 (10)0.097
Rarely or sometimes13 (9) 3 (8) 6 (7) 4 (25)
Often or always8 (7) 2 (7) 4 (5) 2 (20)
Hospital visits as a patient in the past year0No76 (8)0.67216 (8)0.51741 (6)0.50719 (13)0.597
Yes5 (6) 4 (11) 1 (2) 0 (0)
Hospital visits as a professional in the past year0No78 (8)0.76119 (9)1.00041 (6)1.00018 (12)0.336
Yes3 (8) 1 (5) 1 (7) 1 (33)
Hospital visits as a visitor in the past year0No79 (8)0.69018 (8)0.16942 (6)1.00019 (13)1.000
Yes2 (9) 2 (22) 0 (0) 0 (0)
Farm visits in the past year4No71 (7)0.57817 (9)0.77335 (6)0.09719 (13)0.596
Yes10 (9) 3 (7) 7 (11) 0 (0)
Owning horses in the past year139No77 (8)0.72220 (10)0.60540 (7)1.00017 (15)1.000
Yes1 (4) 0 (0) 1 (7) 0 (0)
Having dogs as pets in the past year70No70 (9)0.01120 (11)0.08434 (7)0.26716 (16)0.156
Yes9 (4) 0 (0) 7 (4) 2 (6)
Having cats as pets in the past year75No65 (9)0.13017 (10)0.41834 (7)0.34814 (15)0.558
Yes13 (5) 3 (5) 7 (5) 3 (9)
Use of antibiotics in the past year0No60 (7)0.68513 (8)1.00036 (6)0.54411 (11)0.289
Yes21 (8) 7 (8) 6 (5) 8 (17)
Use of antacids in the past year2No64 (8)0.78312 (7)0.29736 (7)0.25316 (13)1.000
Yes17 (7) 8 (12) 6 (4) 3 (11)
Surgeries in the past year1No80 (8)0.25519 (9)1.00042 (6)0.40319 (13)1.000
Yes1 (2) 1 (6) 0 (0) 0 (0)
Self-reported frequency of diarrhea in the past year4Never, rarely or sometimes74 (7)0.22317 (8)0.06938 (6)0.34719 (13)1.000
Often or always7 (11) 3 (25) 4 (9) 0 (0)
Self-reported health status in the past year5Good, very good or excellent69 (7)0.73418 (8)0.36534 (6)0.52317 (13)1.000
Fair or poor12 (8) 2 (13) 8 (7) 2 (11)
Travel to high-risk areas for AR in the past year c8No36 (6)0.0126 (6)0.33617 (4)0.00413 (13)0.791
Yes42 (10) 13 (10) 24 (10) 5 (10)
Travels to Europe in the past year5Never27 (9)0.4985 (12)0.37811 (6)0.71811 (13)0.498
Once18 (8) 1 (2) 12 (7) 5 (18)
2–3 times22 (6) 8 (8) 12 (5) 2 (8)
More than 3 times12 (7) 5 (10) 7 (7) 0 (0)
Travels to Bulgaria, Greece, Italy, or Slovenia in the past year7No59 (8)0.51410 (8)1.00034 (6)0.56115 (15)0.182
Yes19 (6) 9 (8) 7 (5) 3 (6)
Travels to Sub-Saharan Africa in the past year5Never73 (7)0.01019 (8)1.00036 (5)0.00218 (12)NA
Once4 (19) 0 (0) 4 (22) --- (---)
2–3 times1 (33) --- (---) 1 (33) --- (---)
More than 3 times1 (50) --- (---) 1 (50) --- (---)
Travels to Northern Africa in the past year6Never69 (7)0.00117 (7)0.01335 (5)0.01917 (12)0.324
Once8 (20) 2 (25) 5 (17) 1 (33)
2–3 times2 (50) 1 (100) 1 (33) --- (---)
More than 3 times0 (0) --- (---) 0 (0) --- (---)
Travels to Asia in the past year4Never63 (6)<0.00115 (7)0.11631 (5)<0.00117 (12)0.408
Once13 (20) 3 (16) 9 (22) 1 (25)
2–3 times2 (18) 1 (25) 1 (14) --- (---)
More than 3 times1 (50) --- (---) 1 (50) --- (---)
Travels to North America in the past year4Never73 (7)0.03617 (8)0.04138 (6)0.14618 (12)NA
Once5 (17) 2 (20) 3 (16) --- (---)
2–3 times2 (25) 1 (50) 1 (17) --- (---)
More than 3 times0 (0) --- (---) 0 (0) --- (---)
Travels to Central America or Mexico in the past year6Never78 (7)0.19019 (8)1.00041 (6)0.17118 (12)NA
Once0 (0) 0 (0) 0 (0) --- (---)
2–3 times0 (0) 0 (0) --- (---) --- (---)
More than 3 times1 (50) --- (---) 1 (50) --- (---)
Travels to South America in the past year6Never77 (7)0.14918 (8)0.28741 (6)0.12618 (12)NA
Once1 (6) 1 (25) 0 (0) --- (---)
2–3 times0 (0) --- (---) 0 (0) --- (---)
More than 3 times1 (100) --- (---) 1 (100) --- (---)
Travels to Australia or Oceania in the past year6Never78 (7)0.57219 (8)0.46541 (6)1.00018 (12)NA
Once1 (10) 1 (17) 0 (0) --- (---)
2–3 times0 (0) 0 (0) --- (---) --- (---)
More than 3 times--- (---) --- (---) --- (---) --- (---)
Notes: a Educational level according to the International Standard Classification of Education (ISCED): Low = ISCED 0–2 (Pre-primary education to Lower secondary education), High = ISCED ≥ 3 (Upper secondary education to Doctoral or equivalent). b Work with human tissues in the past year: Includes self-reported contact with human tissues (e.g., blood, urine, sputum, feces, vomit, saliva, or primary cell lines). c Travels to high-risk areas for AR in the past year: Includes travels to North Africa, Sub-Saharan Africa, Asia, Central and South America, as well as the European countries Italy, Greece, Bulgaria and Slovenia. ESBL_EC+: Positive stool sample for Extended-Spectrum Beta-Lactamase-Producing E. coli; AR: Antibiotic Resistance. Bold highlighting means statistically significant at the p ≤ 0.05 level. Shown are the number of ESBL-EC carriers per variable and the percentage of ESBL-EC carriers relative to the total participants within the same level of that variable.
Table
Table 2. Numerical descriptive characteristics of ESBL-producing E. coli carriers by country.
Table 2. Numerical descriptive characteristics of ESBL-producing E. coli carriers by country.
Overall,
n = 1074		Germany,
n = 238		The Netherlands,
n = 686		Romania,
n = 151
Missing Values for Stool Samples, n10995311
VariableMissingsESBL_EC+ESBL_EC−pESBL_EC+ESBL_EC−pESBL_EC+ESBL_EC−pESBL_EC+ESBL_EC−p
n 81993 20218 42644 19131
Age, years (median [IQR])047 [34, 57]51 [37, 60]0.17238 [31, 50]49 [36, 58]0.14655 [42, 61]54 [39, 61]0.96439 [34, 44]40 [33, 50]0.739
Travel score (mean ± SD, median [min, max]) a120.86 ± 1.60,
1 [0, 13]		0.46 ± 0.79,
0 [0, 15]		0.0201 ± 0.94,
1 [0, 3]		0.64 ± 0.74,
1 [0, 6]		0.0811.05 ± 2.07,
1 [0, 13]		0.42 ± 0.84,
0 [0, 15]		0.0010.28 ± 0.46,
0 [0, 1]		0.38 ± 0.56,
0 [0, 3]		0.533
Notes: a Travel score was constructed based on frequency of personal travels to high risk areas for antibiotic resistance in the past year: Includes travels to North Africa, Sub-Saharan Africa, Asia, Central and South America, as well as the European countries Italy, Greece, Bulgaria, and Slovenia. The score is the sum of: zero points for not travelling to these areas in the past year, one point for travelling once to these areas in the past year, two points for travelling to these areas two or three times in the past year, and three points for travelling to these areas more than three times in the past year. Test used for bivariate hypothesis testing: Mann–Whitney test. ESBL_EC+: Positive stool sample for Extended-Spectrum Beta-Lactamase-Producing E. coli; ESBL_EC−: Negative stool sample for Extended-Spectrum Beta-Lactamase-Producing E. coli. IQR: Inter-quartile range. Bold highlighting means statistically significant at the p ≤ 0.05 level.
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Rodríguez-Molina, D.; Berglund, F.; Blaak, H.; Flach, C.-F.; Kemper, M.; Marutescu, L.; Pircalabioru Gradisteanu, G.; Popa, M.; Spießberger, B.; Wengenroth, L.; et al. International Travel as a Risk Factor for Carriage of Extended-Spectrum β-Lactamase-Producing Escherichia coli in a Large Sample of European Individuals—The AWARE Study. Int. J. Environ. Res. Public Health 2022, 19, 4758. https://doi.org/10.3390/ijerph19084758

AMA Style

Rodríguez-Molina D, Berglund F, Blaak H, Flach C-F, Kemper M, Marutescu L, Pircalabioru Gradisteanu G, Popa M, Spießberger B, Wengenroth L, et al. International Travel as a Risk Factor for Carriage of Extended-Spectrum β-Lactamase-Producing Escherichia coli in a Large Sample of European Individuals—The AWARE Study. International Journal of Environmental Research and Public Health. 2022; 19(8):4758. https://doi.org/10.3390/ijerph19084758

Chicago/Turabian Style

Rodríguez-Molina, Daloha, Fanny Berglund, Hetty Blaak, Carl-Fredrik Flach, Merel Kemper, Luminita Marutescu, Gratiela Pircalabioru Gradisteanu, Marcela Popa, Beate Spießberger, Laura Wengenroth, and et al. 2022. "International Travel as a Risk Factor for Carriage of Extended-Spectrum β-Lactamase-Producing Escherichia coli in a Large Sample of European Individuals—The AWARE Study" International Journal of Environmental Research and Public Health 19, no. 8: 4758. https://doi.org/10.3390/ijerph19084758

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