Skip to main content

Meta-analysis on the global prevalence of Arcobacter in food-producing animals and humans

Abstract

The genus Arcobacter has been associated with illnesses in both animals and humans, where Arcobacter butzleri, Arcobacter cryaerophilus, and Arcobacter skirrowii have been linked to numerous cases of gastrointestinal diseases in humans. While isolated instances of Arcobacter infection have been reported in certain areas, comprehensive data reflecting the global impact of Arcobacter infection are lacking. This meta-analysis was conducted with the objective of assessing the aggregated prevalence of Arcobacter across diverse sources on a global scale. We conducted a thorough literature search of the Scopus, PubMed, and ScienceDirect databases to identify studies published from 1992 to 2022 on Arcobacter prevalence in humans and food-producing animals. We utilized multilevel random effects meta-analysis models to gauge the average occurrence of Arcobacter and to examine various factors that could influence incidence outcomes. Seventy-five articles were included in the meta-analysis. The pooled prevalence of Arcobacter spp. from different sources was 21.9% (95% CI: 18.0%–26.1%), and the mean prevalence of A. butzleri, A. cryaerophilus, and A. skirrowii was 15.1%, 2.8%, and 0.1%, respectively. Arcobacter spp. had the lowest prevalence in humans (1.8%; 95% CI: 0.7%–3.3%) and the highest in broilers (38.8%; 95% CI: 28.0%–50.1%). Among animal-derived food products, carcasses or carcass parts exhibited the highest Arcobacter spp. prevalence of 28.6% (28.6%; 95% CI: 23.7%–33.7%). This meta-analysis revealed that A. butzleri is the most prevalent Arcobacter species worldwide, with broilers, as well as seafood, being the primary hosts of Arcobacter spp. We recommend developing appropriate prevention strategies and conducting further local in-depth studies to establish the actual epidemiological burden of Arcobacter.

Introduction

Arcobacter spp. are considered important foodborne pathogens associated with both human and animal diseases [1]. The Arcobacter genus encompasses 29 identified species derived from various natural environments, including soil, freshwater, seawater, and hosts such as humans and animals [2,3,4]. Among these species, Arcobacter butzleri, Arcobacter cryaerophilus and Arcobacter skirrowii are clinically important for both animals and humans [5,6,7].

Poultry serves as a crucial reservoir for Arcobacter and a primary source of infection [8,9,10]. Poultry intestines, which harbor Arcobacter, can contaminate slaughterhouses during carcass processing, increasing the likelihood of further contamination [6]. Apart from poultry, Arcobacter has been recovered from various products of animal origin, including seafood, milk, beef, and pork [11,12,13,14,15]. Contaminated meat plays a crucial role in Arcobacter transmission [5, 16, 17]. In humans, severe illnesses, such as peritonitis, endocarditis, bacteremia, and prolonged watery gastroenteritis with abdominal cramps, have been reported following Arcobacter infection [18, 19]. Given the absence of daily diagnostic methods specifically designed for Arcobacter spp. detection, the importance and prevalence of infections are possibly underestimated. In a recent study, Arcobacter prevalence in diarrhea individuals and in raw chickens was 1.3% and 26.7%, respectively, in China [1]. Conversely, in Germany, Arcobacter is the second most prevalent bacterial pathogen detected in human stool samples, while in Belgium, it is the fourth most prevalent [5, 20].

To date, only a limited number of studies have investigated Arcobacter prevalence in both humans and food-producing animals on a global scale. Meta-analysis serves as the invaluable statistical methodology with the objective of synthesizing, integrating, and contrasting results from numerous primary studies investigating the same questions; it is essential when quantitative comparisons worldwide are necessary. In this study, we employed meta-analysis to quantitatively summarize and compared the prevalence of Arcobacter in humans and food-producing animals globally, providing a foundation for future Arcobacter disease surveillance.

Results

Excluded studies

The literature study identified 1142 scientific papers containing the terms "prevalence" or "incidence" along with "Arcobacter." The exclusion criteria included reviews, duplicated studies or data, investigations concentrating solely on laboratory techniques, and studies lacking adequate data for estimating Arcobacter prevalence (n = 1027; Fig. 1).

Fig. 1
figure 1

Flowchart depicting the study selection process for inclusion within meta-analysis

Included studies

Out of the 1142 scientific papers screened, seventy-five met all the inclusion criteria for estimating Arcobacter spp. prevalence, encompassing 176 prevalence studies. Additionally, 167, 145, and 136 studies evaluating the prevalence of Arcobacter butzleri, Arcobacter cryaerophilus and Arcobacter skirrowii, respectively, were included.

Among all studies estimating Arcobacter spp. prevalence, a notable majority were published in the period after 2006 (Fig. 2). After 2006, there was an increase in studies involving Arcobacter species, particularly with a greater focus on A. butzleri than on A. cryaerophilus or A. skirrowii. These studies were conducted across 34 different countries on 6 continents, with the majority located in Europe and Asia (Fig. 2).

Fig. 2
figure 2

Distribution of studies included in the meta-analysis on Arcobacter spp., categorized by year of publication and continent

Thermotolerant Arcobacter prevalence

Among the 75 scientific papers meeting the inclusion criteria, we identified 176 studies on the prevalence of Arcobacter spp. (analyzing 76,951 samples). From these 176 studies, the combined prevalence estimate for Arcobacter spp. was 21.9% (95% CI: 18.0%–26.1%). Notably, significant heterogeneity was detected across the studies (Q-statistic: p < 0.0001; I2-statistic = 98.91%).

A total of 167 studies on A. butzleri prevalence were selected (76,525 samples were analyzed). The prevalence estimate for A. butzleri was 15.1% (95% CI: 12.4%–18.5%), and notable heterogeneity was detected (Q-statistic: p < 0.0001; I2-statistic = 98.51%).

We identified 145 studies on the prevalence of A. cryaerophilus (analyzing 72,516 samples). The prevalence estimate for A. cryaerophilus was 2.8% (95% CI: 1.7%–4.1%), with notable heterogeneity detected (Q-statistic: p < 0.0001; I2-statistic = 95.69%).

Finally, 136 studies on A. skirrowii prevalence were identified (comprising 71,673 samples), with a prevalence estimate of 0.1% (95% CI: 0.0%‐0.4%). Significant heterogeneity was observed across these 136 studies (Q-statistic: p < 0.0001; I2-statistic = 80.43%).

Evolution of Arcobacter prevalence over the analyzed period

In this meta-analysis, we opted to focus on publication year rather than the year of the study. This decision was based on the conventional alignment between the publication year of scientific articles and the actual year of study, which typically falls within a range of 2 to 3 years.

Arcobacter spp. prevalence within all humans and food-producing animals included in this meta-analysis varied based on publication year (Fig. 3a). The prevalence ranged from 0.064 to 0.273 over the analyzed period. The highest prevalence appeared within published studies from 2006 to 2010 (27.3%; 95% CI: 18.1%‐37.5%; p < 0.001). This pattern remained consistent when considering the prevalence among bivalves, bovines, and cows. Cumulative analysis and meta-regression analysis revealed no evidence of a shift in prevalence over time (Table 1) for all Arcobacter spp. or for either subtype reviewed.

Fig. 3
figure 3

Subgroup analysis comparing Arcobacter prevalence over years in food-producing animals and humans. a Arcobacter spp.; b Arcobacter butzleri; c Arcobacter cryaerophilus; d Arcobacter skirrowii

Table 1 Overview of Random weighted meta-regression analysis

A. butzleri prevalence within all humans and food-producing animals included in this meta-analysis varied depending on the study publication year (Fig. 3b). The highest prevalence was noted within published studies during 2001–2005 (25.3%; 95% CI: 6.3%–50.6%; p < 0.001), while the prevalence of A. butzleri ranged from 4.6% to 25.3% throughout publication years (Table 1).

In comparison to discovered all Arcobacter spp. prevalences and A. butzleri, A. cryaerophilus and A. skirrowii prevalence in all humans and food-producing animals included in the meta-analysis was low, with no isolation data available before 2000 (Fig. 3c and d). A. cryaerophilus and A. skirrowii prevalence ranged from 1.8% to 5.8% and from 0.0% to 0.8%, respectively, throughout the years of publication. The highest prevalence of A. cryaerophilus was observed during 2006–2010 (5.8%; 95% CI: 2.0%–10.8%; p < 0.001), and for A. skirrowii, it was during 2011–2015 (0.8%; 95% CI: 0.2%–1.7%; p < 0.001).

Prevalence of Arcobacter across different regions

North America-located studies (33.0%; 95% CI: 8.6%–63.8%) and South America studies (29.8%; 95% CI: 13.5%–49.0%) detected the highest Arcobacter spp. prevalence (p < 0.001), with highest prevalence found in other birds (85.4% and 55.7%, respectively). Moreover, the lowest Arcobacter spp. prevalence. was observed in Asia (16.6%; 95% CI: 11.9%–21.8%) and Africa (17.0%; 95% CI: 9.1%–26.8%; Fig. 4a). Arcobacter spp. prevalence in broilers surpassed that in Oceania countries (72.7%; 95% CI: 51.9%–89.6%; n = 22), South America (69.7%; 95% CI: 62.7%–76.3%; n = 175), Europe (47.4%; 95% CI: 24.0%–71.4%; n = 1499), and North America (35.5%; 95% CI: 6.9%–71.8%; n = 1002) than in the countries of Asia (33.0%; 95% CI: 20.1%–47.3%; n = 1956) and Africa (17.7%; 95% CI: 5.0%–35.9%; n = 450). However, the prevalence in humans was lower in Europe (0.7%; 95% CI: 0.2%–1.4%; n = 54,147), South America (0.9%; 95% CI: 0.0%–3.5%; n = 339), Oceania (1.2%; 95% CI: 0.7%–1.8%; n = 1380), Asia (2.1%; 95% CI: 0.3%–5.0%; n = 3748), and North America (2.9%; 95% CI: 0.0%–9.7%; n = 1703) than in Africa (15.8%; 95% CI: 12.8%–19.2%; n = 505).

Fig. 4
figure 4

Subgroup analysis comparing Arcobacter prevalence across continents in food-producing animals and humans. a Arcobacter spp.; b Arcobacter butzleri; c Arcobacter cryaerophilus; d Arcobacter skirrowii

Studies located within countries of Oceania and North America identified the highest A. butzleri prevalence (p < 0.001; Fig. 4b), while Oceania, South America, and Europe had the highest A. cryaerophilus prevalence (p < 0.001; Fig. 4c). Africa and Asia had the lowest A. butzleri and A. cryaerophilus prevalence. A. skirrowii prevalence in Oceania was 3.2% (95% CI: 0.0%–25.3%; p < 0.001; Fig. 4d) compared to the close-to-zero prevalence rate of A. skirrowii in other continents.

Prevalence of Arcobacter in human stools and food-producing animal species

Arcobacter spp. prevalence in humans (1.8%; 95% CI: 0.7%–3.3%; p < 0.001; Fig. 5a) was significantly lower than that in food-producing animal species. Similar results were observed when independently analyzing the prevalence of A. butzleri, A. cryaerophilus and A. skirrowii (Fig. 5b and d). Broilers exhibited the highest prevalence of Arcobacter spp. (38.8%; 95% CI: 28.0%–50.1%), followed by seafood such as bivalves (35.4%; 95% CI: 24.0%–47.6%) and fish (33.1%; 95% CI: 14.6%–54.4%). In contrast, among the sampled food-producing animals, goats and ovines presented the lowest prevalence (9.6%; 95% CI: 1.2%–23.7%). Broilers and fish samples also exhibited the highest A. butzleri prevalence (p < 0.001), while the greatest A. cryaerophilus and A. skirrowii prevalence was observed in bivalves.

Fig. 5
figure 5

Subgroup analysis comparing Arcobacter prevalence across food-producing animals and humans. a Arcobacter spp.; b Arcobacter butzleri; c Arcobacter cryaerophilus; d Arcobacter skirrowii

Prevalence of Arcobacter within various types of food samples

This subgroup analysis excluded human stool samples. The highest Arcobacter spp. prevalence was detected when specimens were collected from carcasses or parts of carcasses (28.6%; 95% CI: 23.7%–33.7%; Fig. 6a) and milk and milk products (18.3%; 95% CI: 10.2%–28.1%). However, there were no reports of Arcobacter spp. positive detection in sausages or other foods. Similar results were observed when analyzing A. butzleri, A. cryaerophilus and A. skirrowii prevalence individually (Fig. 6b and d).

Fig. 6
figure 6

Subgroup analysis comparing Arcobacter prevalence based on sample type. a Arcobacter spp.; b Arcobacter butzleri; c Arcobacter cryaerophilus; d Arcobacter skirrowii

Prevalence of Arcobacter considering storage time and method

When samples were stored using any freezing method or stored (refrigerated or ambient) for 2–7 days before Arcobacter isolation, the prevalence of Arcobacter spp. was lower than that with other storage and sampling practices. In contrast, when samples were refrigerated or Arcobacter was isolated on the same day or after overnight storage, the prevalence of Arcobacter spp. was higher (Fig. 7a). Samples kept in ambient storage showed a higher prevalence of Arcobacter spp. than those kept in refrigerated storage when bacteria were isolated on the same day (p < 0.001). In contrast, there was a greater Arcobacter spp. prevalence among samples kept in refrigerated storage overnight than those in ambient storage overnight (p = 0.033). However, when samples were stored for 2–7 days, ambient or refrigerated storage had no influence on Arcobacter spp. prevalence rate (p = 0.270).

Fig. 7
figure 7

Subgroup analysis comparing Arcobacter prevalence considering the storage method. a Arcobacter spp.; b Arcobacter butzleri; c Arcobacter cryaerophilus; d Arcobacter skirrowii

Studies involving the same-day Arcobacter spp. collected from samples stored under ambient conditions illustrated the highest A. butzleri prevalence (p < 0.001; Fig. 7b); however, this was only verified in swine. The highest A. cryaerophilus and A. skirrowii prevalence was observed in refrigerated samples, followed by refrigerated samples when bacteria were isolated after storage overnight (Fig. 7c, d).

Prevalence of Arcobacter considering isolation method

We compared the prevalence of Arcobacter spp. based on whether a membrane filter was utilized on the selective medium. The prevalence of Arcobacter spp. (25.5%; 95% CI: 19.4%–32.2%; n = 50,274; Fig. 8a) was higher in studies that used a membrane filter on selective media than in those that used selective media without a membrane filter (19.3%; 95% CI: 14.3%–24.8%; n = 26,427; p < 0.001). Reports not specifying the isolation method indicated the lowest prevalence rate (10.4%; 95% CI: 6.9%–14.5%; n = 250). Similar results were observed when analyzing A. cryaerophilus and A. butzleri prevalence independently (Fig. 8b and c). However, the prevalence of A. skirrowii (0.1%; 95% CI: 0.0%–0.5%; Fig. 8d) was lower in studies that used a membrane filter on selective media than in those that used selective media without a membrane filter (0.2%; 95% CI: 0.0%–0.6%; p < 0.001).

Fig. 8
figure 8

Subgroup analysis comparing Arcobacter prevalence considering the isolation method. a Arcobacter spp.; b Arcobacter butzleri; c Arcobacter cryaerophilus; d Arcobacter skirrowii

Publication bias

None of the individual studies significantly influenced the summary prevalence estimate of Arcobacter, as indicated by sensitivity and cumulative analyses.

To assess publication bias among the included studies, we employed Egger's regression test, the Begg and Mazumdar rank correlation test, and the fail-safe N method, as detailed in Table 2. Our findings revealed a prevalent tendency toward publication bias across most Arcobacter species. Nonetheless, the extensive inclusion of scientific articles in this meta-analysis ensures the validity of our results, mitigating the impact of potential bias.

Table 2 Outcomes of publication bias detection outcomes

Discussion

Arcobacter spp. are significant pathogens of growing interest for public health and food safety due to their frequent detection in various foods and the clinical relevance of A. butzleri, A. cryaerophilus and A. skirrowii in humans [5]. Consequently, over the last decade, the number of studies investigating the prevalence and incidence of Arcobacter in both humans and food-producing animals has increased [1, 4, 7, 13, 14]. We analyzed Arcobacter spp. presence within humans and various animal food products globally. According to the meta-analysis, approximately 21.9% of the samples analyzed contained Arcobacter: 1.80% in human stools and 25.9% in animal food products, regardless of the animal species. Among Arcobacter spp., A. butzleri served as the dominant type, while the prevalence of A. skirrowii and A. cryaerophilus was low. This discovery holds significant importance because it underscores the widely acknowledged transmission route of pathogens through the food chain, particularly notable for A. butzleri, a primary causative agent of human Arcobacter disease [20].

Although our study did not reveal a surge in Arcobacter prevalence across the years, numerous reports have highlighted a growing number of human Arcobacter disease cases globally [1, 4, 16]. This trend might be attributed to data stemming from outbreaks or epidemiological studies, which could introduce biases, particularly regarding unreported cases. An increase in case reporting could inflate prevalence estimates without necessarily reflecting an increase in disease incidence. Conversely, the heightened incidence of human Arcobacter disease might stem from enhanced surveillance and identification of microbial agents responsible for foodborne illnesses previously categorized as acute gastroenteritis [21, 22].

The prevalence of Arcobacter varies across continents. Africa and Asia exhibit the lowest prevalence of Arcobacter spp., but an exceptionally high prevalence is observed in human stools in Africa. This phenomenon may be linked to the dietary and hygiene habits prevalent in developing countries. Higher prevalence of Arcobacter has been reported in animal food samples (25.9%) than in human samples, likely because most domestic animals can serve as reservoirs for Arcobacter. Notably, we detected a greater prevalence of Arcobacter in North America and South America than in other continents, especially in other birds, predominantly turkey. Poultry seems to be a crucial host for Arcobacter, similar to Campylobacter [23].

Furthermore, poultry intestines frequently incur damage during slaughter, leading to the contamination of carcasses with pathogens. In contrast, the slaughter processes for other species, such as cattle and swine, are typically more tightly controlled to mitigate the risk of intestinal perforation. This meta-analysis also identified broilers as the most pivotal Arcobacter source, highlighting the significance of poultry in the global transmission of Arcobacter [24]. Numerous investigations have reported the persistence and diffusion of Arcobacter in poultry meat [25,26,27] and seafood [28,29,30] production chains.

Numerous Arcobacter species are recognized as indigenous to aquatic habitats, whereas the occurrence of A. cryaerophilus, A. skirrowii, A. butzleri, might be linked to fecal contamination of water bodies originating from animal waste [29]. Given their filter-feeding ability, marine bivalve mollusks can accumulate bacterial pathogens from water sources, thereby posing a substantial health risk to consumers, particularly when consumed raw or undercooked [31]. This phenomenon could elucidate the elevated prevalence of Arcobacter spp. observed in seafood as reported in this meta-analysis.

Arcobacter spp. can be transmitted to humans through routes other than those involving meat. An Arcobacter outbreak has been linked to the consumption of milk [32]. Arcobacter presence within milk typically results from fecal contamination within the milking procedure [33], potentially leading to human infection in cases of incomplete sterilization or post-pasteurization cross-contamination. Arcobacter prevalence in milk and milk products was 18.3%, indicating that this genus is another significant source of contamination. Similarly, eggs, sausages, and other foods showed a low prevalence of Arcobacter spp., suggesting a lower likelihood of causing infection in humans. Despite originating from the same animals, the environment in which these products are sourced and stored can significantly impact Arcobacter prevalence.

Furthermore, this meta-analysis investigated the impact of storage time and method on Arcobacter prevalence. We detected a higher Arcobacter spp. prevalence in samples stored refrigerated or isolated on the same day or after overnight storage than in samples stored via other methods. When bacteria were isolated on the day of sample collection, the prevalence rate was highest when the samples were stored at ambient temperature. On the second day after sample collection, refrigerated storage resulted in the highest Arcobacter isolation rate. However, for food safety considerations, long-term frozen storage has emerged as an effective method for reducing the survival of Arcobacter spp. Studies also indicate that freezing affects the isolation rate of both Campylobacter and Arcobacter [34, 35].

This meta-analysis facilitated a comparison of the prevalence with and without the use of a membrane filter on selective medium. The filtration method, which was originally developed for detecting Campylobacter in clinical human stool specimens containing a high concentration of background bacteria [36], has been gradually applied in the isolation of Campylobacter in food [37]. In 2019, the Chinese Preventive Medicine Association included the membrane filter method in the group standard for identifying Campylobacter jejuni and Campylobacter coli [38]. Moreover, membrane filters have been utilized in many studies to isolate Arcobacter [4, 13, 14, 28, 39]. Our meta-analysis revealed a higher prevalence of Arcobacter spp. when membrane filters were used than when membrane filters were not used, demonstrating that the use of membrane filters is an effective method for improving the isolation rate of Arcobacter.

We acknowledge some limitations to our study. The meta-analysis is limited by heterogeneity among studies and potential publication bias. Differences in study design and quality can affect the reliability of synthesized results. Publication bias may lead to an overrepresentation of studies with significant findings, overlooking those with lower prevalence rates or nonsignificant outcomes.

Food-producing animals stand out as the most crucial reservoirs and sources of Arcobacter, posing a serious challenge for public health in terms of pathogen transmission from farm to table [40, 41]. Subsequent research endeavors should prioritize the epidemiology and transmission of Arcobacter, particularly in food production. Investigating effective prevention and control measures is crucial for reducing Arcobacter transmission along the food chain, enhancing food safety and public health. Consequently, we advocate for stricter food safety control strategies by food manufacturers to prevent Arcobacter contamination in food. Simultaneously, we propose the inclusion of Arcobacter in international or national food safety monitoring systems to determine appropriate risk assessment measures aimed at curbing the prevalence of Arcobacter and the resulting Arcobacter disease in humans.

Conclusion

The meta-analysis revealed a pooled prevalence of 21.9% for Arcobacter spp., showing a higher prevalence in animal food samples, with A. butzleri emerging as the predominant species. Varied prevalence levels of Arcobacter were detected in humans and food-producing animals across different regions. Notably, some food-producing animals, particularly broilers, bivalves, and fish, exhibited a higher prevalence of Arcobacter than others. A. butzleri demonstrated higher prevalence in broilers and lower prevalence in goats, ovines, and swines. Conversely, A. cryaerophilus and A. skirrowii were predominantly found in bivalves.

This meta-analysis further highlighted a substantial prevalence of Arcobacter spp. in animal food products, particularly in carcasses and parts of carcasses from diverse animal species and in milk and milk products. Egg products and processed meat items, such as sausages, did not emerge as significant Arcobacter spp. sources. Moreover, although refrigeration is widely acknowledged as a method for food preservation, it seems to have little impact on reducing Arcobacter spp. prevalence in animal food products. The use of membrane filters on selective media influenced the amount of Arcobacter spp. detected.

In light of these findings, it is imperative for researchers to swiftly devise tools aimed at diminishing the prevalence of Arcobacter in primary production, disrupting its fecal–oral cycle, particularly in intensive production systems.

Materials and methods

Data sources

Scientific papers published in English since the Arcobacter spp. via the nomenclature were identified through comprehensive searches of the Scopus, PubMed, and ScienceDirect databases. The search terms for each database included "prevalence" or "incidence" and "Arcobacter." Abstracts and titles were meticulously evaluated, and articles that adhered to the predetermined inclusion criteria were chosen. Data extraction from the selected studies was carried out independently by two authors. In instances of disagreement, resolution transpired through discussions between the two reviewers and thorough examination of the trial information. If necessary, contact with the trial authors was established to seek clarification.

Criteria for study selection

The evaluation of scientific articles for inclusion in the meta-analysis involved several stages. Initially, articles were screened for adherence to selection criteria, with a focus on identifying duplicates, reviews, studies involving humans, animals, and foods, as well as diagnostic methodology validations. Each scientific article underwent a thorough examination, with a specific focus on extracting the statistical data necessary for meta-analysis. Furthermore, the references cited within these articles were scrutinized to identify any additional relevant studies that met the selection criteria. The data were extracted by one author and independently verified by another investigator.

The following eligibility criteria for the inclusion of scientific papers included within the meta-analysis were outlined: (1) Observational study design, specifically prevalence studies. (2) Publication in peer-reviewed journals.

In instances where a scientific paper included humans, different animal species, and food, each animal was treated as an individual "study" within the meta-analysis. Likewise, if a scientific paper reported findings under different circumstances (such as country of origin, sample type, or methodology for confirming Arcobacter spp.), each circumstance was treated as an individual study. As a result, one scientific paper could contribute multiple studies to the analysis.

For inclusion, studies needed to provide data on both the total sample size (population) and sample quantity that tested positive for Arcobacter. Arcobacter spp. identification relies on typical morphology, biochemical confirmation, or, in some instances, PCR detection. Whenever possible, details regarding Arcobacter species identification were incorporated into the analysis.

Exclusions from the meta-analysis encompassed various criteria such as assorted reviews, duplicate reports, non-peer-reviewed articles (e.g., theses, opinion articles, conference papers, and letters to editors), articles not in English, and those describing Arcobacter detection within artificially contaminated specimens. Additionally, articles involving direct PCR identification without bacterial culture experiments or focusing solely on laboratory techniques were excluded.

Outcomes and definitions

The prevalence of the genus Arcobacter and its constituent species (A. skirrowii, A. butzleri, and A. cryaerophilus.) was determined by calculating the ratio of positive samples to the total number of samples. The study population included humans and various food-producing animal species investigated in each study. A pivotal criterion for differentiation was the concept of harvesting, serving as the delineation between animal samples and food samples. Notably, samples derived from animal feces and swabs were excluded from the classification of food samples (i.e., this study).

Data extraction

Details encompassing the study design, country, years under consideration, isolate source, sample type, origin of samples, sample storage method, methodology employed for bacterial isolation and confirming Arcobacter identity, and outcomes (including the number of positive Arcobacter samples and the total sample count for humans, animals, or food) were meticulously extracted from each research paper. Notably, the exclusion of studies did not rely on the utilization of scores [42].

Quality assessment

Two authors autonomously evaluated the risk of bias in each original study. The quality of each study was evaluated utilizing the Newcastle–Ottawa scale, which was adapted for cross-sectional studies [43], and grades ranging up to 10 points. This tool comprises three key sections: methodological quality (8 points), comparability of the study (1 point), and outcomes related to statistical analysis (1 point). The final decision was based on the mean score from the two authors, and studies with a score equal to or greater than five were deemed eligible for meta-analysis and systematic review (Table S1).

Statistical analysis and subgroup analysis

Statistical analysis was performed utilizing Comprehensive Meta-Analysis version 2.2 (2011). Given the binary nature of the measured outcome (i.e., whether human, food-producing animal, or food samples tested positive or negative for the pathogen) and its reporting solely for individual groups, the most applicable parameter for effect size measurement was the raw proportion 'p' (accompanied by 95% CIs) utilizing a random-effects model [44]. Heterogeneity among studies was assessed utilizing the DerSimonian and Laird test (Q-statistic). The extent of heterogeneity was quantified using the inconsistency index (I2-statistic) [45].

To assess the impact of outliers or highly influential studies on the analysis outcome, sensitivity analyses were conducted [42]. This process entailed iteratively performing the same analysis while excluding one study in each iteration. Furthermore, a cumulative meta-analysis was performed to evaluate how the outcomes varied with the publication year.

Subgroup analyses were preplanned to investigate potential factors influencing Arcobacter prevalence: (1) continent (geographic distribution), (2) human stool and food-producing animal species, (3) food types (sausages; other food product samples; milk and milk products; carcasses or part of carcasses; eggs), (4) storing time and methodology (isolation the same day or after overnight or storage for 2–7 days; ambient, refrigerated, or frozen), and (5) methodology for isolation (selective medium; selective medium plus filter) and identification of Arcobacter species. In the subgroup analysis for the time period considered, publication year was used instead of the study year. Typically, the publication year of a scientific article closely aligns with the study year (within 2 or 3 years).

Furthermore, a meta-regression analysis was conducted to investigate sources of heterogeneity by examining the association between Arcobacter prevalence and publication year, employing the method of moments. To assess the significance of covariates and measure the strength of their relationship with effect size, an index based on the percentage reduction in true variance was employed, similar to the R2 index utilized in primary studies [44].

Publication bias was assessed through the use of funnel plots. Adjusted rank correlation tests, the Egger method [46], Begg’s test [47], and the fail-safe N method were used to assess publication bias.

Availability of data and materials

Not applicable.

References

  1. Wang YY, Zhou GL, Li Y, Gu YX, He M, Zhang S, et al. Genetic characteristics and antimicrobial susceptibility of Arcobacter butzleri isolates from raw chicken meat and patients with diarrhea in China. Biomed Environ Sci. 2021;34(12):1024–8.

    CAS  PubMed  Google Scholar 

  2. Fernandez H, Villanueva MP, Mansilla I, Gonzalez M, Latif F. Arcobacter butzleri and A. cryaerophilus in human, animals and food sources, in southern Chile. Braz J Microbiol. 2015;46(1):145–7.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Niedermeyer JA, Miller WG, Yee E, Harris A, Emanuel RE, Jass T, et al. Search for Campylobacter spp. reveals high prevalence and pronounced genetic diversity of Arcobacter butzleri in floodwater samples associated with hurricane florence in North Carolina, USA. Appl Environ Microb. 2020;86(20):e01118–20.

    Article  CAS  Google Scholar 

  4. Uljanovas D, Gölz G, Brückner V, Grineviciene A, Tamuleviciene E, Alter T, et al. Prevalence, antimicrobial susceptibility and virulence gene profiles of Arcobacter species isolated from human stool samples, foods of animal origin, ready-to-eat salad mixes and environmental water. Gut Pathog. 2021;13(1):76.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Brückner V, Fiebiger U, Ignatius R, Friesen J, Eisenblätter M, Höck M, et al. Prevalence and antimicrobial susceptibility of Arcobacter species in human stool samples derived from out- and inpatients: the prospective German Arcobacter prevalence study Arcopath. Gut Pathog. 2020;12:21.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Khodamoradi S, Abiri R. The incidence and antimicrobial resistance of Arcobacter species in animal and poultry meat samples at slaughterhouses in Iran. Iran J Microbiol. 2020;12(6):531–6.

    PubMed  PubMed Central  Google Scholar 

  7. Vidal-Veuthey B, Jara R, Santander K, Mella A, Ruiz S, Collado L. Antimicrobial resistance and virulence genes profiles of Arcobacter butzleri strains isolated from back yard chickens and retail poultry meat in Chile. Lett Appl Microbiol. 2021;72(2):126–32.

    Article  CAS  PubMed  Google Scholar 

  8. Dekker D, Eibach D, Boahen KG, Akenten CW, Pfeifer Y, Zautner AE, et al. Fluoroquinolone-resistant Salmonella enterica, Campylobacter spp., and Arcobacter butzleri from local and imported poultry meat in Kumasi. Ghana Foodborne Pathog Dis. 2019;16(5):352–8.

    Article  CAS  PubMed  Google Scholar 

  9. Kanaan MHG. Prevalence, resistance to antimicrobials, and antibiotypes of Arcobacter species recovered from retail meat in Wasit Marketplaces in Iraq. Int J One Health. 2021;7(1):142–50.

    Article  Google Scholar 

  10. Noto A, Sciortino S, Cardamone C, Ciravolo C, Napoli C, Alio V, et al. Detection of Arcobacter spp. in food products collected from Sicilia region: a preliminary study. Ital J Food Saf. 2018;7(2):7171.

    PubMed  PubMed Central  Google Scholar 

  11. Aydin F, Yağiz A, Abay S, Müştak HK, Diker KS. Prevalence of Arcobacter and Campylobacter in beef meat samples and characterization of the recovered isolates. J Verbraucherschutz Lebensmittelsicherh. 2020;15(1):15–25.

    Article  CAS  Google Scholar 

  12. Caruso M, Latorre L, Santagada G, Fraccalvieri R, Difato LM, Miccolupo A, et al. Arcobacter spp. in bovine milk: an emerging pathogen with potential zoonotic risk. Ital J Food Saf. 2018;7(4):7685.

    CAS  PubMed  Google Scholar 

  13. Mudadu AG, Melillo R, Salza S, Mara L, Marongiu L, Piras G, et al. Detection of Arcobacter spp. in environmental and food samples collected in industrial and artisanal sheep’s milk cheese-making plants. Food Control. 2021;126:108100.

    Article  CAS  Google Scholar 

  14. Mudadu AG, Salza S, Melillo R, Mara L, Piras G, Spanu C, et al. Prevalence and pathogenic potential of Arcobacter spp. isolated from edible bivalve molluscs in Sardinia. Food Control. 2021;127:108139.

    Article  CAS  Google Scholar 

  15. Zhang X, Alter T, Gölz G. Characterization of Arcobacter spp. isolated from retail seafood in Germany. Food Microbiol. 2019;82:254–8.

    Article  CAS  PubMed  Google Scholar 

  16. Chukwu MO, Abia A, Ubomba-Jaswa E, Dewar JB, Obi CL. Mixed aetiology of diarrhoea in infants attending clinics in the North-West province of South Africa: potential for sub-optimal treatment. Pathogens. 2020;9(3):198.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Webb AL, Boras VF, Kruczkiewicz P, Selinger LB, Taboada EN, Inglis GD. Comparative detection and quantification of Arcobacter butzleri in stools from diarrheic and nondiarrheic people in Southwestern Alberta. Canada J Clin Microbiol. 2016;54(4):1082–8.

    Article  CAS  PubMed  Google Scholar 

  18. Figueras MJ, Levican A, Pujol I, Ballester F, Rabada QM, Gomez-Bertomeu F. A severe case of persistent diarrhoea associated with Arcobacter cryaerophilus but attributed to Campylobacter sp. and a review of the clinical incidence of Arcobacter spp. New Microb New Infec. 2014;2(2):31–7.

    Article  CAS  Google Scholar 

  19. Ferreira S, Queiroz JA, Oleastro M, Domingues FC. Insights in the pathogenesis and resistance of Arcobacter: a review. Crit Rev Microbiol. 2016;42(3):364–83.

    CAS  PubMed  Google Scholar 

  20. Van den Abeele AM, Vogelaers D, Van Hende J, Houf K. Prevalence of Arcobacter species among humans, Belgium, 2008–2013. Emerg Infect Dis. 2014;20(10):1731–4.

    PubMed  PubMed Central  Google Scholar 

  21. Mandisodza O, Burrows E, Nulsen M. Arcobacter species in diarrhoeal faeces from humans in New Zealand. New Zeal Med J. 2012;125(1353):40–6.

    PubMed  Google Scholar 

  22. Vandenberg O, Dediste A, Houf K, Ibekwem S, Souayah H, Cadranel S, et al. Arcobacter species in humans. Emerg Infect Dis. 2004;10(10):1863–7.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Wang Y, Dong Y, Deng F, Liu D, Yao H, Zhang Q, et al. Species shift and multidrug resistance of Campylobacter from chicken and swine, China, 2008–14. J Antimicrob Chemoth. 2016;71(3):666–9.

    Article  CAS  Google Scholar 

  24. Ruiz De Alegría Puig C, Fernández Martínez M, Pablo Marcos D, Agüero Balbín J, Calvo Montes J. Outbreak of Arcobacter butzleri? An emerging enteropathogen. Enferm Infec Micr Cl. 2021;41(3):169–72.

    Article  Google Scholar 

  25. Atabay HI, Wainø M, Madsen M. Detection and diversity of various Arcobacter species in Danish poultry. Int J Food Microbiol. 2006;109(1–2):139–45.

    Article  PubMed  Google Scholar 

  26. Aydin F, Gümüşsoy KS, Atabay HI, Iça T, Abay S. Prevalence and distribution of Arcobacter species in various sources in Turkey and molecular analysis of isolated strains by ERIC-PCR. J Appl Microbiol. 2007;103(1):27–35.

    Article  CAS  PubMed  Google Scholar 

  27. Bodhidatta L, Srijan A, Serichantalergs O, Bangtrakulnonth A, Wongstitwilairung B, McDaniel P, et al. Bacterial pathogens isolated from raw meat and poultry compared with pathogens isolated from children in the same area of rural Thailand. Se Asian J Trop Med. 2013;44(2):259–72.

    Google Scholar 

  28. Collado L, Jara R, Vásquez N, Telsaint C. Antimicrobial resistance and virulence genes of Arcobacter isolates recovered from edible bivalve molluscs. Food Control. 2014;46:508–12.

    Article  CAS  Google Scholar 

  29. Nelapati S, Tumati SR, Thirtham MR, Ramani PR, Kamisetty AK, Ch BK. Occurrence, virulence gene and antimicrobial susceptibility profiles of Arcobacter sp. isolated from catla (Catla catla) in India. Lett Appl Microbiol. 2020;70(5):365–71.

    Article  CAS  PubMed  Google Scholar 

  30. Vicente-Martins S, Oleastro M, Domingues FC, Ferreira S. Arcobacter spp. at retail food from Portugal: prevalence, genotyping and antibiotics resistance. Food Control. 2018;85:107–12.

    Article  CAS  Google Scholar 

  31. Patyal A, Rathore RS, Mohan HV, Dhama K, Kumar A. Prevalence of Arcobacter spp. in humans, animals and foods of animal origin including sea food from India. Transbound Emerg Dis. 2011;58(5):402–10.

    Article  CAS  PubMed  Google Scholar 

  32. Lappi V, Archer JR, Cebelinski E, Leano F, Besser JM, Klos RF, et al. An outbreak of foodborne illness among attendees of a wedding reception in Wisconsin likely caused by Arcobacter butzleri. Foodborne Pathog Dis. 2013;10(3):250–5.

    Article  CAS  PubMed  Google Scholar 

  33. Ramees TP, Rathore RS, Bagalkot PS, Mohan HV, Kumar A, Dhama K. Detection of Arcobacter butzleri and Arcobacter cryaerophilus in clinical samples of humans and foods of animal origin by cultural and multiplex PCR based methods. Asian J Anim Vet Adv. 2014;9(4):243–52.

    Article  CAS  Google Scholar 

  34. Merga JY, Leatherbarrow AJH, Winstanley C, Bennett M, Hart CA, Miller WG, et al. Comparison of Arcobacter isolation methods, and diversity of Arcobacter spp. in Cheshire. United Kingdom Appl Environ Microb. 2011;77(5):1646–50.

    Article  CAS  Google Scholar 

  35. Bojanić K, Midwinter AC, Marshall JC, Biggs PJ, Acke E. Isolation of emerging Campylobacter species in working farm dogs and their frozen home-killed raw meat diets. J Vet Diagn Invest. 2019;31(1):23–32.

    Article  PubMed  Google Scholar 

  36. Engberg J, On SLW, Harrington CS, Gerner-Smidt P. Prevalence of Campylobacter, Arcobacter, Helicobacter, and Sutterella spp. in human fecal samples as estimated by a reevaluation of isolation methods for campylobacters. J Clin Microbiol. 2000;38(1):286–91.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Barakat A, El-Razik K, Elfadaly HA, Rabie NS, Sadek S, Almuzaini AM. Prevalence, molecular detection, and virulence gene profiles of Campylobacter species in humans and foods of animal origin. Vet World. 2020;13(7):1430–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Zhang M, Gu Y, Li Y, Ju C, Zhou G, Guo Y, et al. Interpretation for the group standards of the isolation and identification of Campylobacter jeiuni and Campylobacter coli. Chin J Epidemiol. 2019;40(09):1052–4.

    CAS  Google Scholar 

  39. Yesilmen S, Vural A, Erkan ME, Yildirim IH. Prevalence and antimicrobial susceptibility of Arcobacter species in cow milk, water buffalo milk and fresh village cheese. Int J Food Microbiol. 2014;188:11–4.

    Article  CAS  PubMed  Google Scholar 

  40. Iwu CD, Ekundayo TC, Okoh AI. A Systematic Analysis of research on Arcobacter: public health implications from a food-environment interphase perspective. Foods. 2021;10(7):1673.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Venâncio I, Luís Â, Domingues F, Oleastro M, Pereira L, Ferreira S. The prevalence of Arcobacteraceae in aquatic environments: a systematic review and meta-analysis. Pathogens. 2022;11(2):244.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Lean IJ, Rabiee AR, Duffield TF, Dohoo IR. Invited review: use of meta-analysis in animal health and reproduction: methods and applications. J Dairy Sci. 2009;92(8):3545–65.

    Article  CAS  PubMed  Google Scholar 

  43. Lo CKL, Mertz D, Loeb M. Newcastle-Ottawa scale: comparing reviewers’ to authors’ assessments. BMC Med Res Method. 2014;14:1–5.

    Article  Google Scholar 

  44. Borenstein M, Hedges LV, Higgins JPT, Rothstein HR. Introduction to Meta‐analysis. Oxford: Wiley; 2009. https://onlinelibrary.wiley.com/doi/book/10.1002/9780470743386.

  45. Higgins JPT, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002;21:1539–58.

    Article  PubMed  Google Scholar 

  46. Egger M, Smith GD, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. British Med J. 1997;315(7109):629–34.

    Article  CAS  Google Scholar 

  47. Begg CB, Mazumdar M. Operating characteristics of a rank correlation test for publication bias. Biometrics. 1994;50(4):1088–101.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

This work was supported by the National Natural Science Foundation of China (Grant No. 32225048) and the Capital High-level Public Health Technical Talent Development Project (2022–3–027).

Author information

Authors and Affiliations

Authors

Contributions

P.Z. and Y.L. performed data extraction, while P.Z. and M.F. established the research selection criteria. P.Z., X.M., and B.W. conducted the statistical and subgroup analysis. S.D., Z.S. and X.Z. provided guidance for this study. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Xiaoai Zhang or Zhangqi Shen.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, P., Liu, Y., Fu, M. et al. Meta-analysis on the global prevalence of Arcobacter in food-producing animals and humans. One Health Adv. 2, 13 (2024). https://doi.org/10.1186/s44280-024-00046-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s44280-024-00046-y

Keywords