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Risk factors for fecal carriage of drug-resistant Escherichia coli: a systematic review and meta-analysis

Risk factors for fecal carriage of drug-resistant Escherichia coli: a systematic review and... studied risk factors for fecal carriage of Gram-negative After the databases were reviewed, the results were bacteria expressing extended-spectrum beta-lactamase exported and then compiled with the reference manage- (ESBL) reported by papers from OECD countries from ment software Covidence [30]. Duplicates were removed 1978 to 2015 [19], there has not been a comprehensive by automated process of Covidence, followed by a manual analysis of more recent literature reporting other resis- search to identify and remove additional duplicates. tance mechanisms of human commensal E. coli. The purpose of this review was to investigate risk fac- Study selection tors associated with intestinal carriage of drug-resistant All abstracts were screened first by author YH and then commensal E. coli in the recent five years. We also aimed by author YM to minimize omission of eligible studies. to identify risk factors related to food. We focused on Screening criteria were as follows: (1) examined bacteria the recent five years because of the increasing preva- must include E. coli or Enterobacteriaceae; (2) examined lence of multiple mechanisms of resistance among Gram- bacteria must be isolated from human feces, stool, or negative bacteria causing extraintestinal and intestinal rectal swab; (3) must report risk factors. Studies report- infections during this period, including mechanisms such ing risk factors for drug-resistant Enterobacteriaceae were as ESBL [25, 26], carbapenemase [27], and metallo-beta- considered eligible because E. coli is the most common lactamase production [26], and plasmid-mediated colistin Enterobacteriaceae. Studies that remained of interest were resistance [28]. then screened based on their full text by two indepen- dent reviewers, YH and YM. Disagreements were resolved Methods by consensus. Inclusion criteria were: (1) reported risk Data sources and search strategy factor(s); (2) reported measure of associations and accom- The protocol of this meta-analysis was not preregistered. panying 95% confidence intervals (95% CI) or its equiv- alent; (3) study population aged 18-65; (4) healthy study We performed a systematic review and meta-analysis following the PRISMA [Preferred Reporting Items for population; (5) survey conducted after 2010. Hu et al. Antimicrobial Resistance and Infection Control (2020) 9:31 Page 3 of 12 For the meta-analysis, we excluded studies that (1) did conductedwithRversion3.5.1 [35], with package ’meta’ not report risk factors commonly assessed in 3 or more version 4.9-6 [36]. studies or (2) did not offer sufficient data to create a contingency table. Results Study selection Data extraction Our search identified 395 unique studies that we assessed Data were first extracted by YH and checked by YM. for eligibility with title and abstract screening. Of these, The assessment measures extracted from the included 58 studies were forwarded to full-text article screen- studies were as follows: (1) publication data: lead author ing. Of the 58 full-text articles, we identified 15 rele- names, year of publication; (2) demographic and epi- vant articles that reported risk factors associated with demiological data: location of study, study population, drug-resistant Enterobacteriaceae (10) or E. coli (5) study design, sample size, outcome, prevalence of drug- carriage [37–51]. resistant bacteria, outcome measurement methods, sta- Twelve of 15 studies included in the systematic review tistical analysis methods; (3) risk-factor associated data: were eligible for inclusion in the meta-analysis, which risk factor(s) investigated, measure of associations (odds reported sufficient data to create contingency tables to ratios, risk ratios or prevalence ratios) and accompanying compare risk factors that were studied in at least three 95% CI. of the studies [37, 38, 40, 42–48, 50, 51]. Caudell et al. When enumerating risk factors from each eligible study, (2018) did not report risk factors commonly assessed in 3 we did not limit the analysis to statistically significant or more studies and Dohmen et al. (2017) and Sanneh et factors to avoid publication bias and to identify as many al. (2018) did not offer sufficient data to create a contin- factorsstudiedtodateaspossible. gency table [39, 41, 49]. See Fig. 1,Table 1, and Additional file 3: Table S2 for further details of search and reasons for Meta-analysis exclusion. For studies which provided enough data to allow for the creation of contingency tables, unless the Study characteristics authors reported an adjusted OR and corresponding The 15 studies represented 8 countries: England, Gambia, 95% CI, we manually calculated the OR and 95% Germany, Netherlands, Northern Cyprus, Singapore, CI. If there were insufficient data to create a contin- Sweden, and Tanzania (Table 1). None of the studies gency table, we excluded the study to calculate pooled reported randomization in participant selection. Eight estimates. studies sampled volunteers from healthy general pop- We performed random-effects meta-analysis under a ulationthatwereregisteredtoahospitalsystem. Five Mantel-Haenszel model with Hartung-Knapp adjustment were cohort studies of healthy travellers that compared to estimate the pooled effect of each commonly reported the prevalence of drug-resistant Enterobacteriaceae or E. risk factors for intestinal carriage of drug-resistant E. coli before and after the travel. Two studies surveyed pig coli. Mantel-Haenszel random-effects model estimates farmers. the amount of between-study variation by comparing Five studies reported prevalence of drug-resistant E. each study’s result with a fixed-effect meta-analysis result coli, while 10 studies investigated Enterobacteriaceae. The but avoids approximating Normal distributions [31, 32]. frequency of E. coli among Enterobacteriaceae ranged Hartung-Knapp adjustment provides a more conservative from 79-97% for 9 studies, while one study reported 29%. and robust pooled OR estimates and 95% CI, allowing for All studies collected information on demographic factors, any heterogeneity between studies even when the study behaviors, and past illness from participants. Some studies number is small and study size is unequal [33]. Forest excluded insufficient response from the surveys. plots were created to visualize the reported OR and 95% The prevalence of fecal drug-resistant Enterobacteri- CI from each studies and pooled ORs for each commonly aceae reported in the studies ranged from 1% to 51%. assessed risk factors. We assessed statistical heterogeneity The pooled prevalence was 14% (95% CI 8-23%) (Fig. 2a). between studies by the Chi test and variation due to het- Nine studies reported ESBL producing Enterobacteri- erogeneity across the studies by the I statistic. P < 0.10 aceae. The pooled prevalence of ESBL-producing Enter- was considered indicative of statistically significant het- obacteriaceae was 18% (95%CI 9-31%) (Fig. 2a). The 2 2 erogeneity in the Chi test, and I values of 25, 50 and prevalence among general population was 8% (95%CI 4- 75% were defined as low, moderate, and high estimates, 14%) (Fig. 2b) and among travellers was 37% (95%CI respectively. We evaluated the potential for publication 30-43%) (Fig. 2b). All studies followed established drug bias with funnel plots and Egger’s tests for meta-analyses susceptibility testing methods, disc diffusion tests, VITEK with at least 10 studies [34], which test for asymmetry of 2, or minimum inhibitory concentration (MIC) measure- the funnel plot and effects of small studies. Analyses were ment. Common statistical methods for risk factor analysis Hu et al. Antimicrobial Resistance and Infection Control (2020) 9:31 Page 4 of 12 Fig. 1 PRISMA Flow Diagram. Flow diagram of the systematic review process used to identify eligible studies included univariate and multivariate logistic regression, Six (46%) of 13 studies found antimicrobial use in the chi-squared test, and Fisher’s exact t test. previous 12 months, 4 (57%) of 7 studies found diar- rhea symptom, and 2 (40%) of 5 studies found vegetarian Commonly assessed risk factors diet to be significantly associated with the carriage of Commonly assessed risk factors identified in this review drug-resistant bacteria. are shown in Table 2. We identified fourteen risk factors Smoking, living with pet(s), gender, education level, pre- assessed in three or more studies. We assessed the pooled vious hospital admission, proton-pump inhibitor (PPI) ORs in the meta-analysis (Table 2,Fig. 3a, Additional use, chronic disease, international travel, travel to South- file 1: Figure S1a). east Asia and exposure to livestock were commonly Traveling to India was the only risk factor that all studies assessed but no significant pooled OR was found in these reported to be significantly associated with fecal carriage studies. Of these commonly assessed risk factors, three of drug-resistant E. coli. For the remaining risk factors, factors (PPI use, chronic disease, travel to Southeast Asia) ORs and accompanying 95% CI were found to vary among were reported as significant risks among half or more studies. There were three risk factors that showed signifi- studies included in this review. Two (67%) of 3 studies cant pooled ORs. These included antimicrobial use within found PPI use, 2 (67%) of 3 studies found chronic dis- the previous 12 months (OR 1.84 [95% CI 1.35-2.51]), ease, and 4 (50%) of 8 studies found travel to Southeast diarrhea symptoms (OR 1.56 [95% CI 1.09-2.25]), and veg- Asia to be significantly associated with the carriage of etarian diet (OR 1.60 [95% CI 1.00(1.0043)-2.56(2.5587)]). drug-resistant bacteria. Hu et al. Antimicrobial Resistance and Infection Control (2020) 9:31 Page 5 of 12 Table 1 Characteristics of studies included in review, 2014-2019 Author, year Country Study Study design Study period Sample size Pathogen type population Arcilla 2017 Netherlands Travellers Prospective 2012 Nov - 2013 Nov 1847 ESBL-PE, CPE cohort study Angelin 2015 Sweden Travellers Prospective 2010 Apr - 2014 Jan 99 E. coli study Caudell 2018* Tanzania General adult Prospective 2012 Mar - 2015 Jul 226* E. coli study Dohmen 2017 Netherlands Employees in a Prospective 2015 Jun 334 E. coli pig study slaughterhouse Dohmen 2017* Netherlands Pig farmers, Longitudinal 2011 Mar - 2011 Oct 146 ESBL-PE family members study and employees Lubbert 2015 Germany Travellers Prospective 2013 May - 2014 Apr 191 ESBL-PE cohort study McNulty 2018 England General adult Retrospective 2013 - 2014 2430 ESBL-PE cohort study Miranda 2016 Germany Travellers Retrospective 2013 Feb - 2014 Apr 211 ESBL-PE study Mo 2019 Singapore General adult Cross sectional 2016 Jun - 2017 Apr 305 ESBL-PE study Reuland 2016 Netherlands General adult Case control 2011 Jun - 2011 Nov 1695 ESBL-PE study Reuland 2015 Netherlands General adult Case control 2011 Aug - 2011 Dec 550 pAmpC producing E. coli study Ruh 2019 Northern Cyprus General adult Retrospective 2017 Sep - 2017 Dec 500 Enterobacteriaceae cohort study Sanneh 2018* Gambia Food handlers Cross sectional 2015 Jul - 2015 Sep 565 Enterobacteriaceae study Vading 2016 Sweden Travellers Prospective 2013 Apr - 2015 May 175 ESBL E. coli cohort study Wielders 2017 Netherlands General adult Cross sectional 2012 Nov 2432 ESBL-PE study Note: ** not included in meta-analysis. *indicates sample size was households (all others are individuals). ESBL-PE = Extended-spectrum beta-lactamase producing Enterobacteriaceae; CPE = Carbapenemase-producing Enterobacteriaceae Risk factors based on travelling status CI 2.23-6.47]) remained significant risk factors among Theprevalenceofdrug-resistant E. coli carriage suggested travellers. Among general population adults, antimicro- two distinct populations. We divided the population into bial use within the previous 12 months (OR 1.51 [95% CI travellers and other general population adults and repli- 1.17-1.94]), diarrhea symptoms (OR 1.53 [95% CI 1.27- cated the analysis (Table 3,Fig. 3b, c, and Additional 1.84]), and travelling to Southeast Asia (OR 1.67 [95% CI file 1: Figure S1b, c). Antimicrobial use within the pre- 1.02-2.73]) were significant risk factors. vious 12 months, diarrhea symptoms, gender, travelling to India, travelling to Africa, and travelling to South- Risk factors related to food east Asia were assessed fortravellers.Wealsoassessed Six of 15 studies reported risk factors related to food. antimicrobial use within the previous 12 months, diar- Five studies assessed the risk among vegetarians (Table 2). rhea symptoms, gender, travelling abroad, travelling to As stated above, pooled OR showed significant associa- Southeast Asia, education status, pet, and previous hos- tion with being a vegetarian (OR 1.60 [95% CI 1.00-2.56]). pitalization among general population adults. The results Two studies reported significant association, one with showed that antimicrobial use within the previous 12 unadjusted OR [37], and another with adjusted OR [44]. months (OR 2.81 [95% CI 1.47-5.36]), diarrhea symptoms Four studies reported potential food-associated risk fac- (OR 1.65 [95% CI 1.02-2.68]), vegetarian diet (OR 1.92 tors other than being a vegetarian. One study reported [95% CI 1.13-3.26]), and travelling to India (OR 3.80 [95% exposure to raw milk as significant risk factor for Hu et al. Antimicrobial Resistance and Infection Control (2020) 9:31 Page 6 of 12 AB Fig. 2 Forest plots for individuals and combined prevalence estimates of fecal carriage of drug-resistant bacteria. a Prevalence of drug-resistant Enterobacteriaceae and prevalence of ESBL-producing Enterobacteriaceae; b Prevalence of drug-resistant Enterobacteriaceae among travellers and general populations acquiring multi-drug-resistant E.coli (OR 7.54 [95% CI risk factors, no heterogeneity was observed, suggesting 2.41-23.45]) [39]. Two studies reported the effect of eat- that the evidence was of high quality. ing street food during travel. One of them was reported as For stratified estimates among travellers, travel to Africa significant risk (OR 2.09 [95% CI 1.30-3.38] for daily con- and travel to Southeast Asia were the only risk factors that sumption; OR was 1.37 [95% CI 1.08-1.73] for occasional showed high heterogeneity (chi 19.27 and 41.24, respec- consumption during travel) [37]. Another study did not tively, p < 0.01, and I 90%). Among general adults, travel find significant association (OR 0.92 [95% CI 0.49-1.74]) abroad and travel to Southeast Asia showed moderate het- [42]. Two studies assessed the effect of raw vegetable con- erogeneity (chi 10.73 and 5.56, respectively, p = 0.06, and sumption on the fecal carriage of drug-resistant E. coli. I 53-64%). The shapes of the funnel plots were approxi- One of them reported that raw vegetable consumption mately symmetrical for significant risk factors, and Egger’s during a trip to Southeast Asia significantly increased the test showed p = 0.42 for antimicrobial use within the risk of intestinal carriage of drug-resistant Enterobacte- previous 12 months among all populations included in riaceae (OR 2.18 [95% CI 1.29-3.68]), while exposure to this study (Fig. 4). This suggests that no publication bias raw vegetable in South Asia significantly decreased the existed for this factor. For all other risk factors, due to risk (OR 0.34 [95% CI 0.12-0.93]) [37]. The other study the insufficient number of studies (less than 10 studies did not find any significant association (OR 0.58 [95% CI for each), we did not evaluate the potential for publica- 0.33-1.07]) [43]. tion bias with funnel plots and Egger’s tests for small study effects [34]. Bias assessment and heterogeneity evaluation We evaluated heterogeneity among studies, and poten- Discussion tial extent of publication bias in meta-analysis (Table 2, This study summarizes risk factors associated with intesti- Table 3,Fig. 4,Fig. 3b, and c). Funnel plots of all studies nal carriage of drug-resistant Enterobacteriaceae, in par- reporting significant association (Fig. 4) were generated to ticular, E. coli among healthy adults. Our systematic assess the potential extent of publication bias. review and meta-analysis on studies published from 2014 For pooled estimates of all studies, risk factors related to 2019 identified several risk factors for intestinal car- 2 2 to travel showed high chi (11-81, P < 0.01) and I riage of drug-resistant E. coli. We found evidence for our value (53-94%) except for travel to India. This suggests hypothesis that commensal E. coli can acquire ARGs car- that there was substantially high heterogeneity among ried by Gram-negative bacteria that enter the intestinal studies that examined the effect of international travel, tract from contaminated food. travel to SoutheastAsia, andtraveltoAfrica, respectively. We should first note that the pooled prevalence of Smoking, PPI use, and chronic disease status also showed intestinal carriage of drug-resistant Enterobacteriaceae moderate to high heterogeneity (I 66-77%). For all other in our review (14% for all Enterobacteriaceae and 18% Hu et al. Antimicrobial Resistance and Infection Control (2020) 9:31 Page 7 of 12 Table 2 Commonly assessed risk factors for intestinal carriage of drug-resistant E. coli, 2014-2019. OR = Odds Ratio; CI = Confidence interval. Note: *indicates results from systematic review 2 2 Risk factor Number of Number of studies Number Number of samples Pooled OR (95%CI) χ (P-value) l studies finding significant of samples with drug resistant investigated* association* assessed bacteria General factors Gender 11 1 9836 1428 1.16 (0.98-1.36) 8.77 (0.46) 0 Diet restriction (vegetarian) 5 2 6802 989 1.60 (1.00-2.56) 3.22 (0.52) 0 Pet 4 1 5159 407 1.15 (0.33-4.06) 5.23 (0.16) 43 Education level 4 0 5067 925 0.93 (0.74-1.17) 0.98 (0.81) 0 Smoking 4 1 4497 712 0.77 (0.18-3.25) 6.37 (0.04) 69 Clinical factors Antimicrobial use 13 6 10079 1407 1.84 (1.35-2.51) 18.28 (0.05) 45 Previous hospital admission 7 2 6108 465 1.63 (0.84-3.18) 7.83 (0.17) 36 Diarrhea 7 4 5144 1079 1.56 (1.09-2.25) 5.76 (0.33) 13 Proton-pump inhibitor use 3 2 4111 359 1.31 (0.11-15.5) 5.81 (0.05) 66 Chronic disease 3 2 2323 766 0.91 (0.13-6.53) 8.68 (0.01) 77 Travel related factors International travel 6 2 6460 520 1.13 (0.67-1.91) 10.73 (0.06) 53 Travel to Southeast Asia 8 4 6632 1289 1.78 (0.64-4.98) 50.28 (<0.01) 86 Travel to Africa 5 2 6692 1105 1.29 (0.52-3.21) 81.34 (<0.01) 94 Travel to India 4 4 2953 423 4.15 (2.54-6.78) 2.50 (0.48) 0 OR = Odds Ratio; CI = Confidence interval. Note: *indicates results from systematic review for ESBL producing Enterobacteriaceae) has slightly led us to examine the pooled estimates of OR for increased from an earlier review (14% [95% CI 9-20%] each risk factor stratified by travellers vs general adult for ESBL producing Enterobacteriaceae) published in population. 2016 [19]. Karanika et al. conducted a systematic review In the general adult population, we found five risk fac- and meta-analysis on papers published from 1978 to tors significantly associated with intestinal carriage of 2015 under search terms “ESBL” or “extended-spectrum drug-resistant E. coli, prior antimicrobial drug use within beta-lactamase”, and limited the studies conducted in 12 months prior to stool culture, diarrhea symptoms, OECD countries. Our literature search was not limited travel to India, travel to Southeast Asia, and vegetarian to ESBL producing bacteria nor OECD countries. Some diet. Antimicrobial use, diarrhea symptoms, and travel studies reported carbapenemase-producing Enterobac- to India were also identified in previous reports [19, 20]. teriaceae (CPE), and extended-spectrum cephalosporin When controlled by travel status, we found antimicro- (ESC) resistant E. coli. High variability in the prevalence bial use, diarrhea, diet and travel to India significantly among studies could be explained by infections from associated with fecal carriage of drug-resistant E. coli for external sources such as the environment, contaminated travellers. Travel to Southeast Asia was significantly asso- food, and contaminated water, in addition to high vari- ciated with ARG carriage only among the general adult ability in antimicrobial usage in different regions of the population. We should note that due to the limited num- world. ber of studies, some risk factors commonly assessed for The high variability could also be explained by the entire population could not be assessed for stratified pop- types of populations studied. In our study, the preva- ulations. To the best of our knowledge, no previous review lence between travellers and general adult populations has found vegetarian diet to be significantly associated were significantly different (8% [95% CI 4-14%] and with intestinal carriage of drug-resistant E. coli.Butcher 37% [95% CI 30-43%], respectively), suggesting different et al. (2019) reported that unwashed vegetables could be mechanisms for acquiring drug-resistant gut Enterobac- a source for ESBL-producing extraintestinal pathogenic teriaceae organisms. It is possible that travel includes E. coli [52]. Multiple reports suggest association between distinct behavioral activities that affect exposure to urinary pathogenic E. coli and fecal E. coli [53, 54], and potential risk factors for acquiring ARGs. This assumption fecal carriage of drug-resistant E. coli. Although we should Hu et al. Antimicrobial Resistance and Infection Control (2020) 9:31 Page 8 of 12 AB Fig. 3 Forest plots for significant risk factors. a Individuals and combined OR of fecal carriage of drug-resistant E. coli among entire population; b Individuals and combined OR of fecal carriage of drug-resistant E. coli among travellers; c Individuals and combined OR of fecal carriage of drug-resistant E. coli among general population. OR, odds ratio note that our pooled ORs for drug-resistant E. coli intesti- more reviewed studies. These include gender, smoking, nal carriage were not controlled for potential confounding living with pet(s), education level, proton-pump inhibitor factors other than travel status, our findings suggest that use, previous hospital admission, chronic disease, inter- certain type of dietary practice could be a risk factor for national travel, travel to Southeast Asia, and travel to acquiring drug-resistant E. coli by the gut microbiota. Africa. None of these factors were significantly associated In addition to the five significant risk factors, we iden- with risk of intestinal carriage of drug-resistant E. coli. tified ten other risk factors commonly assessed in 3 or However, 50% or more of the studies reported significant Hu et al. Antimicrobial Resistance and Infection Control (2020) 9:31 Page 9 of 12 Table 3 Commonly assessed risk factors for intestinal carriage of drug-resistant E. coli, 2014-2019, stratified by travellers and general adults Travellers General adults 2 2 2 2 Risk Factor Number of Pooled OR χ (P-value) l (%) Number of Pooled OR χ (P-value) l (%) studies (95%CI) studies (95%CI) investigated* investigated* General factors Gender 4 1.14 (0.85-1.51) 2.17(0.54) 0 6 1.16 (0.90-1.50) 6.15 (0.29) 19 Diet restriction (vegetarian) 3 1.92 (1.13-3.26) 1.29 (0.52) 0 1 - - - Pet 1 - - - 3 0.93 (0.70-1.24) 0.94 (0.63) 0 Education level 1 - - - 3 0.92 (0.63-1.35) 0.98 (0.81) 0 Clinical factors Antimicrobial use 4 2.81 (1.47-5.36) 4.07 (0.25) 26 7 1.51 (1.17-1.94) 5.54 (0.48) 0 Previous hospital admission 1 - - - 5 1.47 (0.79-2.76) 5.54 (0.24) 28 Diarrhea 4 1.65 (1.02-2.68) 5.16 (0.16) 42 3 1.53 (1.27-1.84) 0.43 (0.80) 0 Travel related factors International travel 0 - - - 6 1.13 (0.73-1.74) 10.73 (0.06) 53 Travel to Southeast Asia 5 1.93 (0.46-8.12) 41.24 (<0.01) 90 8 1.67 (1.02-2.73) 5.56 (0.06) 64 Travel to Africa 3 0.75 (0.29-1.96) 19.27 (<0.01) 90 2 - - - Travel to India 3 3.80 (2.23-6.47) 1.62 (0.45) 0 1 - - - OR = Odds Ratio; CI = Confidence interval. Note: *indicates results from systematic review associations for proton-pump inhibitor use, chronic dis- in study region, target population, travel destination and ease, and travel to Southeast Asia. This suggests that these sanitation conditions among studies. One study reported factors could serve as risks for drug-resistant E. coli colo- conflicting ORs for raw vegetable consumption between nization under certain situations. In fact, travel to South- Southeast Asia (Brunei Darussalam, Cambodia, Indone- east Asia was a significant risk factor for general adult sia, Lao People’s Democratic Republic, Malaysia, Myan- populations. Previous hospitalization and travel to Africa mar, Philippines, Singapore, Thailand, Timor-Leste, Viet were also assessed in the review by Karanika et al. [19]. Nam) and South Asia (Afghanistan, Bangladesh, Bhutan, In agreement with our findings, previous hospitalization India, Iran (Islamic Republic of), Maldives, Nepal, Pak- and travel to Africa were not significant risks. Stratifica- istan, and Sri Lanka) [37]. Geographic differences in food tion based on location of studies such as OECD countries production methods and antimicrobial drug usage could to non-OECD countries and features of travel destination exist. Although further studies on vegetable consumption such as sanitation system and antibiotics usage in food among general population are required, this observation production can alter the pooled ORs. suggests that dietary habit can affect fecal carriage of Multiple studies reported food as potential sources of drug-resistant E. coli, which supports our hypothesis that E. coli infections [10–13, 52]. To the best of our knowl- ARGs may be acquired via contaminated food in addi- edge, we found no other reviews that examined the effect tion to healthcare-associated acquisition and person-to- of food on fecal carriage of drug-resistant E. coli.Being person transmission. a vegetarian was significantly associated with the car- There are limitations associated with this systematic riageofdrug-resistant E. coli among overall population literature review. First, 10 of 15 studies investigated Enter- and travellers. Pooled estimate among general adult pop- obacteriaceae instead of E. coli alone. Still, the frequency ulations could not be obtained due to limited number of E. coli found among studies that examined Enterobac- of studies. Several recent studies have reported con- teriaceae was high (79-97%) for 9 of 10 studies. One study tamination of leafy green vegetables with saprophytic that had low frequency (29%) of E. coli was not eligible for bacteria harboring ARGs that occur in human Gram- meta-analysis. Therefore, we can assume that risk factors negative bacterial pathogens [12, 55, 56]. Four studies identified in this review would apply to E. coli.Also,we reported the effect of street food, raw vegetables, and cannot determine whether the identified risk factors have raw milk consumption [37, 39, 42, 43]. However, these causal effects on fecal carriage of drug-resistant E. coli. factors showed high variance in reported ORs among For example, an episode of diarrhea among participants studies. This variance could be explained by differences could have prompted the use of antibiotics, which could Hu et al. Antimicrobial Resistance and Infection Control (2020) 9:31 Page 10 of 12 Fig. 4 Funnel plots. Funnel plots for studies reporting antimicrobial use, diarrhea, vegetarian diet, and travel to India as risk factors have selected for drug-resistant E. coli in the host intesti- investigated were different among studies, and there was a nal microbiota. Still, identification of factors significantly high variation in disease incidence within the studies [37, associated with the carriage of drug-resistant E. coli will be 45, 50]. Furthermore, there were three studies reporting useful for identifying individuals with high risk and early association for PPI use as risk factors for fecal carriage focused interventions. Another limitation of our study is of drug-resistant E. coli [46, 50, 51], and McNulty et al. that there was no study from North America included (2018) stated in their limitation that they did not collect in this review. Karanika et al. (2016) reported the same data on the use of PPI [43]. Since PPI use is one of the indi- limitation [19]. Since North America is a major food- cators of chronic disease, larger studies related to PPI use exporting region in which antibiotics are heavily used and other chronic diseases may alter the result. in food animal husbandry and agriculture, if food is an important reservoir for drug-resistant bacteria that enter Conclusion our intestines, more studies in this geographic region are In this review, we found five significant risk factors needed. Also, although we did not observe publication associated with intestinal carriage of drug-resistant E. bias for risk factors identified in this study, we found coli, antimicrobial use, diarrhea, vegetarian diet, travel to high heterogeneity among studies that reported the risk India, and travel to Southeast Asia. Due to the high het- of chronic disease and travel related factors on intestinal erogeneity of the studies, other factors may indeed serve carriage of drug-resistant bacteria. This high heterogene- as risks under certain circumstances. Further studies, ity could be explained by differences in sampling methods, especially those that examine food and other environ- chronic diseases reported, travel destinations, and sanita- mental exposures will be essential for identifying public tion conditions examined in the studies. These differences health interventions that can be devised to decrease could have affected the pooled OR estimates. Particularly, human intestinal colonization with drug-resistant we should note that the chronic diseases three studies bacteria. Hu et al. Antimicrobial Resistance and Infection Control (2020) 9:31 Page 11 of 12 Supplementary information 4. Colello R, Etcheverría AI, Di Conza JA, Gutkind GO, Padola NL. Antibiotic Supplementary information accompanies this paper at resistance and integrons in shiga toxin-producing Escherichia coli (STEC). https://doi.org/10.1186/s13756-020-0691-3. Braz J Microbiol. 2015;46(1):1–5. 5. Begum J, Mir NA, Dev K, Khan IA. Dynamics of antibiotic resistance with special reference to Shiga toxin-producing Escherichia coli infections. J Additional file 1: Forest plots of insignificant risk factors. Individuals and Appl Microbiol. 2018;125(5):1228–37. combined ORs of fecal carriage of drug-resistant E. coli.A:entire 6. CDC. E. coli (Escherichia coli) Prevention. Atlanta: U.S. Department of population; B: travellers; C: general adults. Health and Human Services, CDC; 2017. Available online at https://www. cdc.gov/ecoli/ecoli-prevention.html. Additional file 2: PRISMA 2009 Checklist 7. Thaden JT, Fowler VG, Sexton DJ, Anderson DJ. Increasing Incidence of Additional file 3: Excluded articles with reasons Extended-Spectrum β -Lactamase-Producing Escherichia coli in Reference information for excluded articles and reasons for exclusion. Community Hospitals throughout the Southeastern United States. Infect Control Hosp Epidemiol. 2016;37(1):49–54. Abbreviations 8. Allocati N, Masulli M, Alexeyev MF, Di Ilio C. Escherichia coli in Europe: An ARG: Antimicrobial resistant genes; CI: Confidence Interval; ESBL: overview. Int J Environ Res Public Health. 2013;10(12):6235–54. Extended-spectrum beta-lactamase organisms; HAI: Healthcare-associated 9. Kaushik M, Kumar S, Kapoor RK, Gulati P. Integrons and antibiotic infection; ICU: Intensive care unit; OR: Odds ratio; PPI: Proton-pump inhibitor; resistance genes in water-borne pathogens: threat detection and risk PRISMA: Preferred reporting items for systematic reviews and meta analyses assessment. J Med Microbiol. 2019;68(5):679–92. 10. Saliu E, Vahjen W, Zentek J. Types and prevalence of extended–spectrum Acknowledgements beta–lactamase producing Enterobacteriaceae in poultry. Anim Health Not applicable. Res Rev. 2017;18(1):46–57. 11. Yamaji R, Friedman CR, Rubin J, Suh J, Thys E, McDermott P. A Population-Based Surveillance Study of Shared Genotypes of Escherichia Authors’ contributions coli Isolates from Retail Meat and Suspected Cases of Urinary Tract YH conceptualized and designed the study; performed the literature search; Infections. mSphere. 2018;3(4):1–12. participated in data collection, extraction, and interpretation; prepared tables and figures; performed the statistical analysis; wrote and drafted the 12. Raphael E, Wong LK, Riley LW. Extended-Spectrum Beta-Lactamase Gene manuscript; approved the final manuscript as submitted; and agreed to be Sequences in Gram-Negative Saprophytes on Retail Organic and accountable for all aspects of the work by ensuring that questions related to Nonorganic Spinach. Appl Environ Microbiol. 2011;77(5):1601–7. the accuracy or integrity of any part of the work were appropriately 13. Sapkota S, Adhikari S, Pandey A, Khadka S, Adhikari M, Kandel H, et al. investigated and resolved. YM participated in data collection, extraction, and Multi-drug resistant extended-spectrum beta-lactamase producing E. coli interpretation; drafted the manuscript. LWR reviewed and revised the and Salmonella on raw vegetable salads served at hotels and restaurants manuscript, approved the final manuscript as submitted, and agreed to be in Bharatpur, Nepal. BMC Res Notes. 2019;12(1):516. accountable for all aspects of the work by ensuring that questions related to 14. Weiner LM, Webb AK, Limbago B, Dudeck MA, Patel J, Kallen AJ, et al. the accuracy or integrity of any part of the work were appropriately Antimicrobial-Resistant Pathogens Associated With investigated and resolved. All authors read and approved the final manuscript. Healthcare-Associated Infections: Summary of Data Reported to the National Healthcare Safety Network at the Centers for Disease Control and Prevention, 2011–2014. Infect Control Hosp Epidemiol. 2016;37(11): Funding 1288–301. None. 15. Donskey CJ. 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Relating knowledge, attitude and practice of antibiotic use to extended-spectrum beta-lactamase-producing Enterobacteriaceae carriage: results of a cross-sectional community survey. BMJ open. 2019;9(3):e023859. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Antimicrobial Resistance & Infection Control Springer Journals

Risk factors for fecal carriage of drug-resistant Escherichia coli: a systematic review and meta-analysis

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Abstract

studied risk factors for fecal carriage of Gram-negative After the databases were reviewed, the results were bacteria expressing extended-spectrum beta-lactamase exported and then compiled with the reference manage- (ESBL) reported by papers from OECD countries from ment software Covidence [30]. Duplicates were removed 1978 to 2015 [19], there has not been a comprehensive by automated process of Covidence, followed by a manual analysis of more recent literature reporting other resis- search to identify and remove additional duplicates. tance mechanisms of human commensal E. coli. The purpose of this review was to investigate risk fac- Study selection tors associated with intestinal carriage of drug-resistant All abstracts were screened first by author YH and then commensal E. coli in the recent five years. We also aimed by author YM to minimize omission of eligible studies. to identify risk factors related to food. We focused on Screening criteria were as follows: (1) examined bacteria the recent five years because of the increasing preva- must include E. coli or Enterobacteriaceae; (2) examined lence of multiple mechanisms of resistance among Gram- bacteria must be isolated from human feces, stool, or negative bacteria causing extraintestinal and intestinal rectal swab; (3) must report risk factors. Studies report- infections during this period, including mechanisms such ing risk factors for drug-resistant Enterobacteriaceae were as ESBL [25, 26], carbapenemase [27], and metallo-beta- considered eligible because E. coli is the most common lactamase production [26], and plasmid-mediated colistin Enterobacteriaceae. Studies that remained of interest were resistance [28]. then screened based on their full text by two indepen- dent reviewers, YH and YM. Disagreements were resolved Methods by consensus. Inclusion criteria were: (1) reported risk Data sources and search strategy factor(s); (2) reported measure of associations and accom- The protocol of this meta-analysis was not preregistered. panying 95% confidence intervals (95% CI) or its equiv- alent; (3) study population aged 18-65; (4) healthy study We performed a systematic review and meta-analysis following the PRISMA [Preferred Reporting Items for population; (5) survey conducted after 2010. Hu et al. Antimicrobial Resistance and Infection Control (2020) 9:31 Page 3 of 12 For the meta-analysis, we excluded studies that (1) did conductedwithRversion3.5.1 [35], with package ’meta’ not report risk factors commonly assessed in 3 or more version 4.9-6 [36]. studies or (2) did not offer sufficient data to create a contingency table. Results Study selection Data extraction Our search identified 395 unique studies that we assessed Data were first extracted by YH and checked by YM. for eligibility with title and abstract screening. Of these, The assessment measures extracted from the included 58 studies were forwarded to full-text article screen- studies were as follows: (1) publication data: lead author ing. Of the 58 full-text articles, we identified 15 rele- names, year of publication; (2) demographic and epi- vant articles that reported risk factors associated with demiological data: location of study, study population, drug-resistant Enterobacteriaceae (10) or E. coli (5) study design, sample size, outcome, prevalence of drug- carriage [37–51]. resistant bacteria, outcome measurement methods, sta- Twelve of 15 studies included in the systematic review tistical analysis methods; (3) risk-factor associated data: were eligible for inclusion in the meta-analysis, which risk factor(s) investigated, measure of associations (odds reported sufficient data to create contingency tables to ratios, risk ratios or prevalence ratios) and accompanying compare risk factors that were studied in at least three 95% CI. of the studies [37, 38, 40, 42–48, 50, 51]. Caudell et al. When enumerating risk factors from each eligible study, (2018) did not report risk factors commonly assessed in 3 we did not limit the analysis to statistically significant or more studies and Dohmen et al. (2017) and Sanneh et factors to avoid publication bias and to identify as many al. (2018) did not offer sufficient data to create a contin- factorsstudiedtodateaspossible. gency table [39, 41, 49]. See Fig. 1,Table 1, and Additional file 3: Table S2 for further details of search and reasons for Meta-analysis exclusion. For studies which provided enough data to allow for the creation of contingency tables, unless the Study characteristics authors reported an adjusted OR and corresponding The 15 studies represented 8 countries: England, Gambia, 95% CI, we manually calculated the OR and 95% Germany, Netherlands, Northern Cyprus, Singapore, CI. If there were insufficient data to create a contin- Sweden, and Tanzania (Table 1). None of the studies gency table, we excluded the study to calculate pooled reported randomization in participant selection. Eight estimates. studies sampled volunteers from healthy general pop- We performed random-effects meta-analysis under a ulationthatwereregisteredtoahospitalsystem. Five Mantel-Haenszel model with Hartung-Knapp adjustment were cohort studies of healthy travellers that compared to estimate the pooled effect of each commonly reported the prevalence of drug-resistant Enterobacteriaceae or E. risk factors for intestinal carriage of drug-resistant E. coli before and after the travel. Two studies surveyed pig coli. Mantel-Haenszel random-effects model estimates farmers. the amount of between-study variation by comparing Five studies reported prevalence of drug-resistant E. each study’s result with a fixed-effect meta-analysis result coli, while 10 studies investigated Enterobacteriaceae. The but avoids approximating Normal distributions [31, 32]. frequency of E. coli among Enterobacteriaceae ranged Hartung-Knapp adjustment provides a more conservative from 79-97% for 9 studies, while one study reported 29%. and robust pooled OR estimates and 95% CI, allowing for All studies collected information on demographic factors, any heterogeneity between studies even when the study behaviors, and past illness from participants. Some studies number is small and study size is unequal [33]. Forest excluded insufficient response from the surveys. plots were created to visualize the reported OR and 95% The prevalence of fecal drug-resistant Enterobacteri- CI from each studies and pooled ORs for each commonly aceae reported in the studies ranged from 1% to 51%. assessed risk factors. We assessed statistical heterogeneity The pooled prevalence was 14% (95% CI 8-23%) (Fig. 2a). between studies by the Chi test and variation due to het- Nine studies reported ESBL producing Enterobacteri- erogeneity across the studies by the I statistic. P < 0.10 aceae. The pooled prevalence of ESBL-producing Enter- was considered indicative of statistically significant het- obacteriaceae was 18% (95%CI 9-31%) (Fig. 2a). The 2 2 erogeneity in the Chi test, and I values of 25, 50 and prevalence among general population was 8% (95%CI 4- 75% were defined as low, moderate, and high estimates, 14%) (Fig. 2b) and among travellers was 37% (95%CI respectively. We evaluated the potential for publication 30-43%) (Fig. 2b). All studies followed established drug bias with funnel plots and Egger’s tests for meta-analyses susceptibility testing methods, disc diffusion tests, VITEK with at least 10 studies [34], which test for asymmetry of 2, or minimum inhibitory concentration (MIC) measure- the funnel plot and effects of small studies. Analyses were ment. Common statistical methods for risk factor analysis Hu et al. Antimicrobial Resistance and Infection Control (2020) 9:31 Page 4 of 12 Fig. 1 PRISMA Flow Diagram. Flow diagram of the systematic review process used to identify eligible studies included univariate and multivariate logistic regression, Six (46%) of 13 studies found antimicrobial use in the chi-squared test, and Fisher’s exact t test. previous 12 months, 4 (57%) of 7 studies found diar- rhea symptom, and 2 (40%) of 5 studies found vegetarian Commonly assessed risk factors diet to be significantly associated with the carriage of Commonly assessed risk factors identified in this review drug-resistant bacteria. are shown in Table 2. We identified fourteen risk factors Smoking, living with pet(s), gender, education level, pre- assessed in three or more studies. We assessed the pooled vious hospital admission, proton-pump inhibitor (PPI) ORs in the meta-analysis (Table 2,Fig. 3a, Additional use, chronic disease, international travel, travel to South- file 1: Figure S1a). east Asia and exposure to livestock were commonly Traveling to India was the only risk factor that all studies assessed but no significant pooled OR was found in these reported to be significantly associated with fecal carriage studies. Of these commonly assessed risk factors, three of drug-resistant E. coli. For the remaining risk factors, factors (PPI use, chronic disease, travel to Southeast Asia) ORs and accompanying 95% CI were found to vary among were reported as significant risks among half or more studies. There were three risk factors that showed signifi- studies included in this review. Two (67%) of 3 studies cant pooled ORs. These included antimicrobial use within found PPI use, 2 (67%) of 3 studies found chronic dis- the previous 12 months (OR 1.84 [95% CI 1.35-2.51]), ease, and 4 (50%) of 8 studies found travel to Southeast diarrhea symptoms (OR 1.56 [95% CI 1.09-2.25]), and veg- Asia to be significantly associated with the carriage of etarian diet (OR 1.60 [95% CI 1.00(1.0043)-2.56(2.5587)]). drug-resistant bacteria. Hu et al. Antimicrobial Resistance and Infection Control (2020) 9:31 Page 5 of 12 Table 1 Characteristics of studies included in review, 2014-2019 Author, year Country Study Study design Study period Sample size Pathogen type population Arcilla 2017 Netherlands Travellers Prospective 2012 Nov - 2013 Nov 1847 ESBL-PE, CPE cohort study Angelin 2015 Sweden Travellers Prospective 2010 Apr - 2014 Jan 99 E. coli study Caudell 2018* Tanzania General adult Prospective 2012 Mar - 2015 Jul 226* E. coli study Dohmen 2017 Netherlands Employees in a Prospective 2015 Jun 334 E. coli pig study slaughterhouse Dohmen 2017* Netherlands Pig farmers, Longitudinal 2011 Mar - 2011 Oct 146 ESBL-PE family members study and employees Lubbert 2015 Germany Travellers Prospective 2013 May - 2014 Apr 191 ESBL-PE cohort study McNulty 2018 England General adult Retrospective 2013 - 2014 2430 ESBL-PE cohort study Miranda 2016 Germany Travellers Retrospective 2013 Feb - 2014 Apr 211 ESBL-PE study Mo 2019 Singapore General adult Cross sectional 2016 Jun - 2017 Apr 305 ESBL-PE study Reuland 2016 Netherlands General adult Case control 2011 Jun - 2011 Nov 1695 ESBL-PE study Reuland 2015 Netherlands General adult Case control 2011 Aug - 2011 Dec 550 pAmpC producing E. coli study Ruh 2019 Northern Cyprus General adult Retrospective 2017 Sep - 2017 Dec 500 Enterobacteriaceae cohort study Sanneh 2018* Gambia Food handlers Cross sectional 2015 Jul - 2015 Sep 565 Enterobacteriaceae study Vading 2016 Sweden Travellers Prospective 2013 Apr - 2015 May 175 ESBL E. coli cohort study Wielders 2017 Netherlands General adult Cross sectional 2012 Nov 2432 ESBL-PE study Note: ** not included in meta-analysis. *indicates sample size was households (all others are individuals). ESBL-PE = Extended-spectrum beta-lactamase producing Enterobacteriaceae; CPE = Carbapenemase-producing Enterobacteriaceae Risk factors based on travelling status CI 2.23-6.47]) remained significant risk factors among Theprevalenceofdrug-resistant E. coli carriage suggested travellers. Among general population adults, antimicro- two distinct populations. We divided the population into bial use within the previous 12 months (OR 1.51 [95% CI travellers and other general population adults and repli- 1.17-1.94]), diarrhea symptoms (OR 1.53 [95% CI 1.27- cated the analysis (Table 3,Fig. 3b, c, and Additional 1.84]), and travelling to Southeast Asia (OR 1.67 [95% CI file 1: Figure S1b, c). Antimicrobial use within the pre- 1.02-2.73]) were significant risk factors. vious 12 months, diarrhea symptoms, gender, travelling to India, travelling to Africa, and travelling to South- Risk factors related to food east Asia were assessed fortravellers.Wealsoassessed Six of 15 studies reported risk factors related to food. antimicrobial use within the previous 12 months, diar- Five studies assessed the risk among vegetarians (Table 2). rhea symptoms, gender, travelling abroad, travelling to As stated above, pooled OR showed significant associa- Southeast Asia, education status, pet, and previous hos- tion with being a vegetarian (OR 1.60 [95% CI 1.00-2.56]). pitalization among general population adults. The results Two studies reported significant association, one with showed that antimicrobial use within the previous 12 unadjusted OR [37], and another with adjusted OR [44]. months (OR 2.81 [95% CI 1.47-5.36]), diarrhea symptoms Four studies reported potential food-associated risk fac- (OR 1.65 [95% CI 1.02-2.68]), vegetarian diet (OR 1.92 tors other than being a vegetarian. One study reported [95% CI 1.13-3.26]), and travelling to India (OR 3.80 [95% exposure to raw milk as significant risk factor for Hu et al. Antimicrobial Resistance and Infection Control (2020) 9:31 Page 6 of 12 AB Fig. 2 Forest plots for individuals and combined prevalence estimates of fecal carriage of drug-resistant bacteria. a Prevalence of drug-resistant Enterobacteriaceae and prevalence of ESBL-producing Enterobacteriaceae; b Prevalence of drug-resistant Enterobacteriaceae among travellers and general populations acquiring multi-drug-resistant E.coli (OR 7.54 [95% CI risk factors, no heterogeneity was observed, suggesting 2.41-23.45]) [39]. Two studies reported the effect of eat- that the evidence was of high quality. ing street food during travel. One of them was reported as For stratified estimates among travellers, travel to Africa significant risk (OR 2.09 [95% CI 1.30-3.38] for daily con- and travel to Southeast Asia were the only risk factors that sumption; OR was 1.37 [95% CI 1.08-1.73] for occasional showed high heterogeneity (chi 19.27 and 41.24, respec- consumption during travel) [37]. Another study did not tively, p < 0.01, and I 90%). Among general adults, travel find significant association (OR 0.92 [95% CI 0.49-1.74]) abroad and travel to Southeast Asia showed moderate het- [42]. Two studies assessed the effect of raw vegetable con- erogeneity (chi 10.73 and 5.56, respectively, p = 0.06, and sumption on the fecal carriage of drug-resistant E. coli. I 53-64%). The shapes of the funnel plots were approxi- One of them reported that raw vegetable consumption mately symmetrical for significant risk factors, and Egger’s during a trip to Southeast Asia significantly increased the test showed p = 0.42 for antimicrobial use within the risk of intestinal carriage of drug-resistant Enterobacte- previous 12 months among all populations included in riaceae (OR 2.18 [95% CI 1.29-3.68]), while exposure to this study (Fig. 4). This suggests that no publication bias raw vegetable in South Asia significantly decreased the existed for this factor. For all other risk factors, due to risk (OR 0.34 [95% CI 0.12-0.93]) [37]. The other study the insufficient number of studies (less than 10 studies did not find any significant association (OR 0.58 [95% CI for each), we did not evaluate the potential for publica- 0.33-1.07]) [43]. tion bias with funnel plots and Egger’s tests for small study effects [34]. Bias assessment and heterogeneity evaluation We evaluated heterogeneity among studies, and poten- Discussion tial extent of publication bias in meta-analysis (Table 2, This study summarizes risk factors associated with intesti- Table 3,Fig. 4,Fig. 3b, and c). Funnel plots of all studies nal carriage of drug-resistant Enterobacteriaceae, in par- reporting significant association (Fig. 4) were generated to ticular, E. coli among healthy adults. Our systematic assess the potential extent of publication bias. review and meta-analysis on studies published from 2014 For pooled estimates of all studies, risk factors related to 2019 identified several risk factors for intestinal car- 2 2 to travel showed high chi (11-81, P < 0.01) and I riage of drug-resistant E. coli. We found evidence for our value (53-94%) except for travel to India. This suggests hypothesis that commensal E. coli can acquire ARGs car- that there was substantially high heterogeneity among ried by Gram-negative bacteria that enter the intestinal studies that examined the effect of international travel, tract from contaminated food. travel to SoutheastAsia, andtraveltoAfrica, respectively. We should first note that the pooled prevalence of Smoking, PPI use, and chronic disease status also showed intestinal carriage of drug-resistant Enterobacteriaceae moderate to high heterogeneity (I 66-77%). For all other in our review (14% for all Enterobacteriaceae and 18% Hu et al. Antimicrobial Resistance and Infection Control (2020) 9:31 Page 7 of 12 Table 2 Commonly assessed risk factors for intestinal carriage of drug-resistant E. coli, 2014-2019. OR = Odds Ratio; CI = Confidence interval. Note: *indicates results from systematic review 2 2 Risk factor Number of Number of studies Number Number of samples Pooled OR (95%CI) χ (P-value) l studies finding significant of samples with drug resistant investigated* association* assessed bacteria General factors Gender 11 1 9836 1428 1.16 (0.98-1.36) 8.77 (0.46) 0 Diet restriction (vegetarian) 5 2 6802 989 1.60 (1.00-2.56) 3.22 (0.52) 0 Pet 4 1 5159 407 1.15 (0.33-4.06) 5.23 (0.16) 43 Education level 4 0 5067 925 0.93 (0.74-1.17) 0.98 (0.81) 0 Smoking 4 1 4497 712 0.77 (0.18-3.25) 6.37 (0.04) 69 Clinical factors Antimicrobial use 13 6 10079 1407 1.84 (1.35-2.51) 18.28 (0.05) 45 Previous hospital admission 7 2 6108 465 1.63 (0.84-3.18) 7.83 (0.17) 36 Diarrhea 7 4 5144 1079 1.56 (1.09-2.25) 5.76 (0.33) 13 Proton-pump inhibitor use 3 2 4111 359 1.31 (0.11-15.5) 5.81 (0.05) 66 Chronic disease 3 2 2323 766 0.91 (0.13-6.53) 8.68 (0.01) 77 Travel related factors International travel 6 2 6460 520 1.13 (0.67-1.91) 10.73 (0.06) 53 Travel to Southeast Asia 8 4 6632 1289 1.78 (0.64-4.98) 50.28 (<0.01) 86 Travel to Africa 5 2 6692 1105 1.29 (0.52-3.21) 81.34 (<0.01) 94 Travel to India 4 4 2953 423 4.15 (2.54-6.78) 2.50 (0.48) 0 OR = Odds Ratio; CI = Confidence interval. Note: *indicates results from systematic review for ESBL producing Enterobacteriaceae) has slightly led us to examine the pooled estimates of OR for increased from an earlier review (14% [95% CI 9-20%] each risk factor stratified by travellers vs general adult for ESBL producing Enterobacteriaceae) published in population. 2016 [19]. Karanika et al. conducted a systematic review In the general adult population, we found five risk fac- and meta-analysis on papers published from 1978 to tors significantly associated with intestinal carriage of 2015 under search terms “ESBL” or “extended-spectrum drug-resistant E. coli, prior antimicrobial drug use within beta-lactamase”, and limited the studies conducted in 12 months prior to stool culture, diarrhea symptoms, OECD countries. Our literature search was not limited travel to India, travel to Southeast Asia, and vegetarian to ESBL producing bacteria nor OECD countries. Some diet. Antimicrobial use, diarrhea symptoms, and travel studies reported carbapenemase-producing Enterobac- to India were also identified in previous reports [19, 20]. teriaceae (CPE), and extended-spectrum cephalosporin When controlled by travel status, we found antimicro- (ESC) resistant E. coli. High variability in the prevalence bial use, diarrhea, diet and travel to India significantly among studies could be explained by infections from associated with fecal carriage of drug-resistant E. coli for external sources such as the environment, contaminated travellers. Travel to Southeast Asia was significantly asso- food, and contaminated water, in addition to high vari- ciated with ARG carriage only among the general adult ability in antimicrobial usage in different regions of the population. We should note that due to the limited num- world. ber of studies, some risk factors commonly assessed for The high variability could also be explained by the entire population could not be assessed for stratified pop- types of populations studied. In our study, the preva- ulations. To the best of our knowledge, no previous review lence between travellers and general adult populations has found vegetarian diet to be significantly associated were significantly different (8% [95% CI 4-14%] and with intestinal carriage of drug-resistant E. coli.Butcher 37% [95% CI 30-43%], respectively), suggesting different et al. (2019) reported that unwashed vegetables could be mechanisms for acquiring drug-resistant gut Enterobac- a source for ESBL-producing extraintestinal pathogenic teriaceae organisms. It is possible that travel includes E. coli [52]. Multiple reports suggest association between distinct behavioral activities that affect exposure to urinary pathogenic E. coli and fecal E. coli [53, 54], and potential risk factors for acquiring ARGs. This assumption fecal carriage of drug-resistant E. coli. Although we should Hu et al. Antimicrobial Resistance and Infection Control (2020) 9:31 Page 8 of 12 AB Fig. 3 Forest plots for significant risk factors. a Individuals and combined OR of fecal carriage of drug-resistant E. coli among entire population; b Individuals and combined OR of fecal carriage of drug-resistant E. coli among travellers; c Individuals and combined OR of fecal carriage of drug-resistant E. coli among general population. OR, odds ratio note that our pooled ORs for drug-resistant E. coli intesti- more reviewed studies. These include gender, smoking, nal carriage were not controlled for potential confounding living with pet(s), education level, proton-pump inhibitor factors other than travel status, our findings suggest that use, previous hospital admission, chronic disease, inter- certain type of dietary practice could be a risk factor for national travel, travel to Southeast Asia, and travel to acquiring drug-resistant E. coli by the gut microbiota. Africa. None of these factors were significantly associated In addition to the five significant risk factors, we iden- with risk of intestinal carriage of drug-resistant E. coli. tified ten other risk factors commonly assessed in 3 or However, 50% or more of the studies reported significant Hu et al. Antimicrobial Resistance and Infection Control (2020) 9:31 Page 9 of 12 Table 3 Commonly assessed risk factors for intestinal carriage of drug-resistant E. coli, 2014-2019, stratified by travellers and general adults Travellers General adults 2 2 2 2 Risk Factor Number of Pooled OR χ (P-value) l (%) Number of Pooled OR χ (P-value) l (%) studies (95%CI) studies (95%CI) investigated* investigated* General factors Gender 4 1.14 (0.85-1.51) 2.17(0.54) 0 6 1.16 (0.90-1.50) 6.15 (0.29) 19 Diet restriction (vegetarian) 3 1.92 (1.13-3.26) 1.29 (0.52) 0 1 - - - Pet 1 - - - 3 0.93 (0.70-1.24) 0.94 (0.63) 0 Education level 1 - - - 3 0.92 (0.63-1.35) 0.98 (0.81) 0 Clinical factors Antimicrobial use 4 2.81 (1.47-5.36) 4.07 (0.25) 26 7 1.51 (1.17-1.94) 5.54 (0.48) 0 Previous hospital admission 1 - - - 5 1.47 (0.79-2.76) 5.54 (0.24) 28 Diarrhea 4 1.65 (1.02-2.68) 5.16 (0.16) 42 3 1.53 (1.27-1.84) 0.43 (0.80) 0 Travel related factors International travel 0 - - - 6 1.13 (0.73-1.74) 10.73 (0.06) 53 Travel to Southeast Asia 5 1.93 (0.46-8.12) 41.24 (<0.01) 90 8 1.67 (1.02-2.73) 5.56 (0.06) 64 Travel to Africa 3 0.75 (0.29-1.96) 19.27 (<0.01) 90 2 - - - Travel to India 3 3.80 (2.23-6.47) 1.62 (0.45) 0 1 - - - OR = Odds Ratio; CI = Confidence interval. Note: *indicates results from systematic review associations for proton-pump inhibitor use, chronic dis- in study region, target population, travel destination and ease, and travel to Southeast Asia. This suggests that these sanitation conditions among studies. One study reported factors could serve as risks for drug-resistant E. coli colo- conflicting ORs for raw vegetable consumption between nization under certain situations. In fact, travel to South- Southeast Asia (Brunei Darussalam, Cambodia, Indone- east Asia was a significant risk factor for general adult sia, Lao People’s Democratic Republic, Malaysia, Myan- populations. Previous hospitalization and travel to Africa mar, Philippines, Singapore, Thailand, Timor-Leste, Viet were also assessed in the review by Karanika et al. [19]. Nam) and South Asia (Afghanistan, Bangladesh, Bhutan, In agreement with our findings, previous hospitalization India, Iran (Islamic Republic of), Maldives, Nepal, Pak- and travel to Africa were not significant risks. Stratifica- istan, and Sri Lanka) [37]. Geographic differences in food tion based on location of studies such as OECD countries production methods and antimicrobial drug usage could to non-OECD countries and features of travel destination exist. Although further studies on vegetable consumption such as sanitation system and antibiotics usage in food among general population are required, this observation production can alter the pooled ORs. suggests that dietary habit can affect fecal carriage of Multiple studies reported food as potential sources of drug-resistant E. coli, which supports our hypothesis that E. coli infections [10–13, 52]. To the best of our knowl- ARGs may be acquired via contaminated food in addi- edge, we found no other reviews that examined the effect tion to healthcare-associated acquisition and person-to- of food on fecal carriage of drug-resistant E. coli.Being person transmission. a vegetarian was significantly associated with the car- There are limitations associated with this systematic riageofdrug-resistant E. coli among overall population literature review. First, 10 of 15 studies investigated Enter- and travellers. Pooled estimate among general adult pop- obacteriaceae instead of E. coli alone. Still, the frequency ulations could not be obtained due to limited number of E. coli found among studies that examined Enterobac- of studies. Several recent studies have reported con- teriaceae was high (79-97%) for 9 of 10 studies. One study tamination of leafy green vegetables with saprophytic that had low frequency (29%) of E. coli was not eligible for bacteria harboring ARGs that occur in human Gram- meta-analysis. Therefore, we can assume that risk factors negative bacterial pathogens [12, 55, 56]. Four studies identified in this review would apply to E. coli.Also,we reported the effect of street food, raw vegetables, and cannot determine whether the identified risk factors have raw milk consumption [37, 39, 42, 43]. However, these causal effects on fecal carriage of drug-resistant E. coli. factors showed high variance in reported ORs among For example, an episode of diarrhea among participants studies. This variance could be explained by differences could have prompted the use of antibiotics, which could Hu et al. Antimicrobial Resistance and Infection Control (2020) 9:31 Page 10 of 12 Fig. 4 Funnel plots. Funnel plots for studies reporting antimicrobial use, diarrhea, vegetarian diet, and travel to India as risk factors have selected for drug-resistant E. coli in the host intesti- investigated were different among studies, and there was a nal microbiota. Still, identification of factors significantly high variation in disease incidence within the studies [37, associated with the carriage of drug-resistant E. coli will be 45, 50]. Furthermore, there were three studies reporting useful for identifying individuals with high risk and early association for PPI use as risk factors for fecal carriage focused interventions. Another limitation of our study is of drug-resistant E. coli [46, 50, 51], and McNulty et al. that there was no study from North America included (2018) stated in their limitation that they did not collect in this review. Karanika et al. (2016) reported the same data on the use of PPI [43]. Since PPI use is one of the indi- limitation [19]. Since North America is a major food- cators of chronic disease, larger studies related to PPI use exporting region in which antibiotics are heavily used and other chronic diseases may alter the result. in food animal husbandry and agriculture, if food is an important reservoir for drug-resistant bacteria that enter Conclusion our intestines, more studies in this geographic region are In this review, we found five significant risk factors needed. Also, although we did not observe publication associated with intestinal carriage of drug-resistant E. bias for risk factors identified in this study, we found coli, antimicrobial use, diarrhea, vegetarian diet, travel to high heterogeneity among studies that reported the risk India, and travel to Southeast Asia. Due to the high het- of chronic disease and travel related factors on intestinal erogeneity of the studies, other factors may indeed serve carriage of drug-resistant bacteria. This high heterogene- as risks under certain circumstances. Further studies, ity could be explained by differences in sampling methods, especially those that examine food and other environ- chronic diseases reported, travel destinations, and sanita- mental exposures will be essential for identifying public tion conditions examined in the studies. These differences health interventions that can be devised to decrease could have affected the pooled OR estimates. Particularly, human intestinal colonization with drug-resistant we should note that the chronic diseases three studies bacteria. Hu et al. Antimicrobial Resistance and Infection Control (2020) 9:31 Page 11 of 12 Supplementary information 4. Colello R, Etcheverría AI, Di Conza JA, Gutkind GO, Padola NL. Antibiotic Supplementary information accompanies this paper at resistance and integrons in shiga toxin-producing Escherichia coli (STEC). https://doi.org/10.1186/s13756-020-0691-3. Braz J Microbiol. 2015;46(1):1–5. 5. 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