To evaluate trends in and risk factors for acquisition of antimicrobial-drug resistant nontyphoidal
Each year, nontyphoidal salmonellae (NTS) are responsible for >1 million infections in the United States and an estimated 98 million cases globally (
In the 1980s, studies demonstrated alarming increases in the prevalence of antimicrobial drug resistance among NTS infections (
During the past decade, few population-level analyses have identified risk factors for acquiring a resistant NTS infection outside of outbreak clusters and retail meat supplies. A recently identified risk factor is international travel (
The Oregon Health Authority conducts active, laboratory-based surveillance for all cases of NTS infection. Physicians and laboratories are required by law to report laboratory-confirmed and clinically suspected cases of salmonellosis to the patient’s local health department; reports should contain the patient’s date of birth, sex, diagnosis, date of symptom onset, date of specimen collection, and laboratory test results. All
During 2004–2009, the population of Oregon was 3.6–3.8 million persons, which is ≈1.2% of the US population (
For 2004 and 2005, all confirmed isolates were forwarded to the Oregon State University Veterinary Diagnostic Laboratory for susceptibility testing. From 2006 through 2009, susceptibility testing was performed by OSPHL. All isolates were tested by using broth microdilution to determine MICs for the following 10 antimicrobial agents: ampicillin, ceftriaxone, chloramphenicol, ciprofloxacin, gentamicin, nalidixic acid, nitrofurantoin, sulfamethoxazole, tetracycline, and trimethoprim/sulfamethoxazole. Susceptibilities were determined according to Clinical and Laboratory Standards Institute interpretative criteria (
Isolates were included in analyses only if they were cultured from specific specimens, such as feces, urine, or blood or other normally sterile tissues (i.e., cerebrospinal fluid). CIR was defined as resistance to at least 1 of the following: ampicillin, ceftriaxone, ciprofloxacin, gentamicin, or trimethoprim/sulfamethoxazole (
We sought to evaluate whether resistance was associated with increased disease severity, including hospitalization and invasive infection. Invasive infection was defined as isolation of
All analyses were performed by using SAS version 9.2 (SAS Institute Inc., Cary, NC, USA). Because this study involved more extensive analysis only of data collected routinely as part of public health surveillance, it was not considered human subjects research.
From 2004 through 2009, a total of 2,255 laboratory-confirmed cases of nontyphoidal salmonellosis were reported in Oregon. In accordance with Oregon law, 2,153 isolates were forwarded to OSPHL, and 2,127 (98.8% of all NTS isolates) were cultured from a specific source and had antimicrobial drug susceptibility testing information (
Culture-confirmed salmonellosis cases ascertained by statewide active surveillance and included in analyses, Oregon, USA, 2004–2009. CIR, clinically important resistance; OSPHL, Oregon State Public Health Laboratory.
The most common
| Variable | Resistance, no. (%) |
|---|---|
| Drug | |
| Ampicillin | 285 (13.4) |
| Ceftriaxone | 109 (5.1) |
| Chloramphenicol | 177 (8.3) |
| Ciprofloxacin | 13 (0.6) |
| Gentamicin | 84 (4.0) |
| Nalidixic acid | 135 (6.4) |
| Nitrofurantoin | 283 (13.3) |
| Sulfamethoxazole | 411 (19.3) |
| Tetracycline | 574 (27.0) |
| Trimethoprim/sulfamethoxazole | 60 (2.8) |
| Resistance profiles | |
| Pansusceptible | 1,213 (57.0) |
| CIR | 347 16.3) |
*CIR, clinically important resistance to
The proportion of isolates that were pansusceptible significantly decreased from 69.5% in 2004 to 53.6% in 2009 (p<0.01). CIR did not significantly increase during this study period (p = 0.27). Stratification by serotype revealed that CIR increased among the 3 most common serotypes: Enteritidis (3% to 8%, p = 0.02), Typhimurium (19% to 34%, p = 0.03), and Heidelberg (6% to 30%, p<0.01). Significant increases were identified for resistance to ciprofloxacin (p<0.05), nalidixic acid (p<0.01), sulfamethoxazole (p<0.01), tetracycline (p<0.01), and trimethoprim/sulfamethoxazole (p<0.01). Cephalosporin resistance increased, although not significantly (p = 0.06).
We suspected that these findings were confounded by serotype and therefore used logistic regression to model the odds of acquiring a resistant infection for each of the clinically important antimicrobial drugs (ampicillin, ceftriaxone, ciprofloxacin, gentamicin, or trimethoprim/sulfamethoxazole) as well as CIR. Serotype-adjusted log odds ratios were generated with year of infection entered as a discrete continuous variable. After adjusting for serotype, we found that with each subsequent year, patients were 30% more likely to acquire an infection that was resistant to quinolones (nalidixic acid or ciprofloxacin) and trimethoprim/sulfamethoxazole (
| Variable | Odds ratio (95% CI)† |
|---|---|
| Ampicillin | 1.1 (1.0–1.1) |
| Cephalosporins | 1.2 (1.0–1.6) |
| Gentamicin | 1.0 (0.9–1.2) |
| Quinolones‡ | |
| Trimethoprim/sulfamethoxazole | |
| CIR |
*Multiple logistic regression analysis of 2,127 isolates. Boldface indicates statistical significance at p<0.05. †Serotype adjusted; increased odds of resistance per year, 2004–2009. ‡Resistant to naladixic acid or ciprofloxacin. §p<0.01.
CIR was associated with hospitalization (odds ratio [OR] 1.5, 95% CI 1.1–2.0). This association was preserved after adjustment for serotype, patient age, patient race, and year (aOR 1.7, 95% CI 1.2–2.1). For patients with CIR infections, odds of invasive infection were increased, although not significantly, according to unadjusted or adjusted analyses (OR 1.4, 95% CI 0.9–2.2 and aOR 1.5, 95% CI 0.9–2.5, respectively).
Of the 2,127 patients included in the previous analyses, 1,813 (84.2% of all Oregon patients with NTS) were interviewed. For 305 (16.8%) of these patients, isolates had CIR, and for the remaining 1,508 (83.2%), isolates were susceptible to all clinically important antimicrobial drugs (
According to the unadjusted analysis, several serotypes were more likely than the referent serotype, Enteritidis, to be resistant to
| Variable | No. patients | % CIR isolates | Odds ratio (95%CI) | Adjusted odds ratio(95% CI) | |
|---|---|---|---|---|---|
| Patient travel history | |||||
| No international travel | 1,571 | 16.2 | Referent | ||
| Travel to Asia | |||||
| Case type | |||||
| Sporadic | 1407 | 18.6 | Referent | ||
| Outbreak | |||||
| Year (odds of CIR cases/y) | |||||
| Enteritidis | 334 | 6.0 | Referent | ||
| Typhimurium | |||||
| Heidelberg | |||||
| Typhimurium var. Copenhagen | |||||
| Newport | |||||
| I 4, 5, 12:i:- | |||||
| Montevideo | 72 | 4.2 | 0.7 (0.2–2.4) | 0.8 (0.2–2.7) | |
| Saintpaul | |||||
| Paratyphi B var. L+ Tartrate+ | |||||
| All other | 643 | 9.0 | 1.6 (0.9–2.6) | 1.5 (0.9–2.5) | |
| Patient age, y | |||||
| 18–64 | 999 | 16.0 | Referent | ||
| <1 | 122 | 18.9 | 1.2 (0.8–2.0) | 1.4 (0.9–2.4) | |
| 1–4 | 220 | 16.4 | 1.0 (0.7–1.5) | 0.8 (0.5–1.2) | |
| 5–17 | 279 | 20.1 | 1.3 (0.9–1.8) | 1.0 (0.7–1.5) | |
|
| 193 | 15.5 | 1.0 (0.6–1.5) | 0.9 (0.6–1.4) | |
| Patient race | |||||
| White | 1,662 | 16.7 | Referent | ||
| Not white | 151 | 18.5 | 1.1 (0.7–1.8) | 1.0 (0.6–1.6) | |
*Multiple logistic regression analysis of 1,813 patients; CIR, clinically important resistance to
CIR was not associated with any other demographic risk factors or high-risk food or animal exposures. However when international travel was examined by individual countries or applicable United Nations region, CIR was significantly associated with travel to Southeast Asia (
| Destination | No. patients | % CIR isolates | Odds ratio (95% CI) |
|---|---|---|---|
| None | 1,571 | 16.8 | Referent |
| Mexico | 119 | 9.2 | 0.5 (0.3–1.0) |
| Europe | 25 | 16.0 | 0.9 (0.3–2.8) |
| East Asia | 17 | 35.3 | 2.7 (1.0–7.4) |
| Caribbean | 16 | 12.5 | 0.7 (0.2–3.1) |
| Central America† | 16 | 6.3 | 0.3 (0.1–2.5) |
| Africa | 10 | 20.0 | 1.2 (0.3–5.9) |
| Oceania | 5 | 20.0 | 1.2 (0.1–11.1) |
| Canada | 5 | 40.0 | 3.3 (0.5–19.8) |
| Any travel | 242 | 16.9 | 1.0 (0.7–1.4) |
*CIR, clinically important resistance to
Patients who were part of identified outbreak clusters were significantly less likely than patients with sporadic infections to have a resistant infection (OR 0.5, 95% CI 0.4–0.8). During our study period, 131 outbreaks (406 cases) occurred, and for 25 of these outbreaks a causative vehicle was successfully identified. To assess whether oversampling of cases from outbreak clusters could explain this association, we first restricted cases to 1 isolate per outbreak where a causative vehicle was implicated while retaining all cases from outbreaks for which a vehicle was not implicated (302 cases). Second, we further restricted cases to 1 isolate per outbreak, regardless whether a vehicle was identified (131 cases). In each of these analyses the magnitude, direction, and significance of the association was preserved (OR 0.6, 95% CI 0.4–0.8 and OR 0.5, 95% CI 0.3–0.9, respectively), suggesting that oversampling could not have explained this association. Furthermore, 53.6% of outbreaks had intra-outbreak cases for which the antimicrobial drug susceptibility profiles of the isolates differed.
The resultant main-effects model included the fixed variables of serotype, patient age, year of onset, and patient race, along with travel to eastern or Southeast Asia, and outbreak association (
| Variable | No. patients | % CIR isolates | Odds ratio (95% CI) | Adjusted odds ratio (95% CI) |
|---|---|---|---|---|
| Patient travel to Asia | ||||
| No | 1,363 | 17.9 | Referent | |
| Yes | ||||
| Year ( odds of CIR cases/y) | ||||
| Enteritidis | 254 | 7.5 | Referent | |
| Typhimurium | ||||
| Heidelberg | ||||
| Typhimurium var. Copenhagen | ||||
| Newport | ||||
| I 4, 5, 12:i:- | ||||
| Montevideo | 48 | 2.1 | 0.3 (0.0–2.0) | 0.3 (0.0–2.2) |
| Saintpaul | 35 | 14.3 | 2.1 (0.7–5.9) | 2.3 (0.8–6.7) |
| Paratyphi B var. L+ Tartrate+ | ||||
| All other | 542 | 9.2 | 1.3 (0.7–2.2) | 1.2 (0.7–2.1) |
| Patient age, y | ||||
| 18–64 | 785 | 17.7 | Referent | |
| <1 | 94 | 21.3 | 1.3 (0.7–2.1) | 1.6 (0.9–2.8) |
| 1–4 | 156 | 18.0 | 1.0 (0.6–1.6) | 0.7 (0.4–1.2) |
| 5–17 | 209 | 21.1 | 1.2 (0.8–1.8) | 0.9 (0.6–1.4) |
|
| 163 | 18.4 | 1.0 (0.7–1.6) | 1.1 (0.7–1.7) |
| Patient race | ||||
| White | 1,295 | 18.1 | Referent | |
| Not white | 112 | 24.1 | 1.4 (0.9–2.3) | 1.3 (0.8–2.2) |
*Multiple logistic regression analysis. CIR, clinically important resistance to
| Variable | No. patients | % CIR isolates | Odds ratio (95% CI) | Adjusted odds ratio (95% CI) |
|---|---|---|---|---|
| Enteriditis | 232 | 4.3 | Referent | |
| Typhimurium | ||||
| Heidleberg | ||||
| Typhimurium var. Copenhagen | ||||
| Newport | ||||
| I 4, 5, 12:i:- | ||||
| Montevideo | 70 | 4.3 | 0.7 (0.2–2.8) | 1.0 (0.3–3.8) |
| Saintpaul | ||||
| Paratyphi B var. L+ Tartrate+ | ||||
| All other | 561 | 8.0 | 1.6 (0.8–3.3) | 1.8 (0.9–3.6) |
| Case type | ||||
| Sporadic | 1190 | 18.7 | Referent | |
| Outbreak | ||||
| Year ( odds of CIR cases/y) | ||||
| Age, y | ||||
| 18–64 | 817 | 16.5 | Referent | |
| <1 | 119 | 18.5 | 1.1 (0.7–1.9) | 1.3 (0.8–2.3) |
| 1–4 | 204 | 16.2 | 0.9 (0.6–1.4) | 0.8 (0.5–1.2) |
| 5–17 | 245 | 18.8 | 1.1 (0.8–1.6) | 0.9 (0.6–1.4) |
|
| 186 | 15.1 | 0.8 (0.5–1.3) | 0.8 (0.5–1.4) |
| Race | ||||
| White | 1662 | 16.7 | Referent | |
| Not white | 151 | 18.5 | 1.2 (0.7–1.9) | 1.1 (0.7–1.8) |
*Multiple logistic regression analysis. CIR, clinically important resistance to >1 of the following: ampicillin, ceftriaxone, ciprofloxacin, gentamicin, or trimethoprim/sulfamethoxazole.clinically important resistance. Boldface indicates statistical significance at p<0.05.
Patients with a history of recent travel to eastern or Southeast Asia were >5 times more likely to acquire a CIR infection than were patients with no history of recent international travel. The most common serotypes acquired among persons with a history of travel to Asia were Enteriditis (n = 13, 54% CIR), Typhimurium (n = 5, 60% CIR), Newport (n = 4, 25% CIR), I 4, 5, 12:i:- (n = 4, 50% CIR), Stanley (n = 3, 33% CIR), and Typhimurium var. Copenhagen (n = 2, 100% CIR). Patients with outbreak-associated infections were half as likely as those with sporadic infections to have CIR (
To identify risk factors for resistance to individual antimicrobial drugs, we constructed models with each of the clinically important antimicrobial drugs. Travel to eastern or Southeast Asia was significantly associated with resistance to ampicillin, quinolones (nalidixic acid or ciprofloxacin), and trimethoprim/sulfamethoxazole (
| Drug | Adjusted odds ratio (95% CI)† |
|---|---|
| Ampicillin | |
| Cephalosporins | 1.0 (0.2–5.4) |
| Gentamicin | 0.7 (0.1–5.3) |
| Quinolones‡ | |
| Trimethoprim/sulfamethoxazole |
*Multiple logistic regression analysis for 1,813 patients, comparing odds of resistance for those with a history of travel to Asia with those with no history of international travel. Boldface indicates statistical significance at p<0.05. †Adjusted by serotype, year, patient age, patient race, and outbreak status. ‡Resistance to nalidixic acid or ciprofloxacin.
We found that NTS infections were more likely to have CIR with each subsequent year of our study. In Oregon during 2004–2009, the proportion of isolates susceptible to all antimicrobial drugs significantly decreased. Travel to eastern and Southeast Asia was associated with acquisition of
Our analysis was performed by using
Widespread quinolone resistance in Southeast Asia has been reported (
Increasing antimicrobial drug resistance has widespread implications for human health. We confirm the results of Varma et al. and Lee et al., who found antimicrobial drug resistance to be associated with increased likelihood of hospitalization (
The association between resistance and outbreak cases persisted after restricting the data in unadjusted and adjusted analyses. The lack of effect modification between outbreak cases and a history of travel to Asia in the multiple logistic regression modeling suggests that this finding is independent of travel. Resistant isolates might be less infectious and therefore less likely to cause recognizable outbreaks. Alternatively, common sources of resistant isolates might be less likely to cause widespread contamination.
Our study had limitations. We did not have information about previous antimicrobial drug use (
This study demonstrates that antimicrobial drug resistance among NTS is increasing and has clinical and public health implications. Our analyses elucidated that travel to Asia is strongly associated with antimicrobial drug resistance. When considering antimicrobial drug therapy, providers should evaluate patient travel history and
We thank Julie Hatch for helping with serotype classifications and legacy data abstraction, Steven Fiala for providing statistical advice, and Hillary Booth for helping with retrieval of outbreak case information.
This research was supported in part by the Pacific Northwest Regional Center of Excellence for Biodefense and Emerging Infectious Diseases Research and by Cooperative Agreement no. 3U01CI000306 from the Centers for Disease Control and Prevention.
Mr Barlow is a graduate student in the Departments of Immunology and Global Health, University of Washington, Seattle, Washington, USA. His research interests include host–pathogen interactions and disease surveillance relating to emerging infectious diseases.