Prevalence, Antimicrobial Resistance Profiles, and Risk Factors Analysis of Campylobacter spp. from Dogs in Kelantan, Malaysia

Abstract

Background: Campylobacter represents a significant global public health threat, with rising prevalence and increasing concern over antimicrobial resistance (AMR). This study aims to assess the prevalence, evaluate the antimicrobial resistance profiles, and identify risk factors associated with infection in dogs from Kelantan, Malaysia. To the best of our knowledge, this is the first comprehensive investigation of Campylobacter spp. in dogs within this region. Methods: Campylobacter was isolated from rectal swabs of 50 dogs using modified charcoal cefoperazone deoxycholate agar (mCCDA) and confirmed biochemically, with Campylobacter identified via polymerase chain reaction (PCR). Antimicrobial resistance profile of the isolates was determined using the Kirby–Bauer disk diffusion method. Data on risk factors were assessed through a semi-structured questionnaire. Results: The results revealed an overall prevalence of Campylobacter spp. 28.0% (14/50) in dogs. C. helveticus was the predominant species in dogs (40.7%). The resistance rates of Campylobacter isolates showed notable resistance to ampicillin (85.71%), amoxicillin (71.43%), erythromycin (64.29%), tetracycline (57.14%), and sulfonamides (50%), respectively. Overall, multiple antimicrobial resistance (MAR) indices for all Campylobacter isolates were consistently above the 0.2 threshold, signifying multidrug resistance. Risk factors such as dogs that are semi-roamers and those fed homemade /raw feed were found to be associated with higher risk of Campylobacter (odds ratios: 1.180, p-value = 0.025 semi-roamers; odds ratio: 1.196, p-value = 0.019 fed homemade/raw feed). Conclusions: This study reveals significant prevalence and a remarkable antimicrobial resistance profile, thus advocating the need for improved pet management, responsible antimicrobial use, and targeted interventions to mitigate the spread of multidrug-resistant Campylobacter in companion animals.

1. Introduction

Campylobacter are Gram-negative, slender, curved rod-shaped bacteria characterized by a single polar flagellum that confers motility and are notable for their fastidious growth requirements [1]. Among the Campylobacter species, Campylobacter jejuni and Campylobacter coli are the most commonly associated with gastrointestinal infections in humans and animals, representing a significant public health concern [2]. Additionally, Campylobacter upsaliensis, Campylobacter helveticus, and Campylobacter lari have been isolated from both asymptomatic and diarrheic dogs, highlighting the potential role of dogs as reservoirs for Campylobacter species [3,4,5,6,7]. As companion animals, dogs may serve as reservoirs for Campylobacter spp., potentially contributing to zoonotic transmission via close human–animal interactions [4,5,6,7].

Previous studies have identified dogs as a potential reservoir for Campylobacter transmission, transmitting this pathogen to humans through close contact [5,6,8]. The research indicates that domestic dogs may serve as asymptomatic carriers, shedding the bacteria in feces and oral secretions, thereby increasing the risk of human infection [5,8]. Similarly, another study suggested that zoonotic transmission from cats to humans could occur via direct handling, petting, or exposure to contaminated food or water, underlining the importance of preventive measures, while also emphasizing the vulnerability of dogs to colonization because of underdeveloped immune systems and exploratory tendencies that expose them to polluted settings [5,9].

The emergence of antimicrobial resistance (AMR) poses a significant threat to public health, particularly in the context of zoonotic diseases [10]. AMR undermines the effectiveness of treatment by enabling bacteria to rapidly acquire and disseminate resistance genes, which facilitates the emergence of new, highly pathogenic clones and complicates antimicrobial therapy [11]. Although new antimicrobials continue to be developed, bacteria are adapting swiftly, evolving mechanisms to counter these agents and rendering them less effective [12]. In the case of Campylobacter spp., increasing resistance to fluoroquinolones, macrolides, and penicillin has been progressively reported in isolates from both humans and animals [3]. Dogs harboring resistant Campylobacter strains can serve as reservoirs, facilitating the spread of antimicrobial resistance (AMR) within the community [3]. This resistance complicates treatment options for affected individuals and poses significant challenges to public health systems [13]. While much attention has focused on AMR in livestock and human healthcare, increasing evidence suggests that companion animals, particularly dogs, also play a significant role in the development and dissemination of resistant pathogens [14]. Recent surveillance in Turkey found that 10.4% of healthy shelter dogs carried Campylobacter jejuni, with notable resistance to ciprofloxacin and nalidixic acid, demonstrating direct zoonotic potential from pets [15]. Notably, Campylobacter spp., including C. jejuni and C. upsaliensis, were frequently isolated from dogs and have been linked to human infection clusters, such as a US outbreak of extensively drug-resistant C. jejuni (ST2109) traced to pet-store puppies [16]. Similarly, a study by (Acke et al., 2009) [17] found that dogs can asymptomatically carry and shed Campylobacter, serving as a source of human infection through direct contact or environmental contamination. Studying Campylobacter prevalence and AMR is crucial despite the presence of other pathogens because it remains one of the most common zoonotic bacteria transmitted from dogs to humans, often causing severe gastroenteritis [17,18]. Alarmingly, rising resistance to critical antibiotics such as macrolides and fluoroquinolones has been documented, reducing treatment options in human medicine [16]. Its asymptomatic carriage in dogs increases unnoticed transmission risk, making it a key target for AMR surveillance and control within One Health frameworks [16,18]. In Malaysia, pet ownership, particularly of dogs, varies significantly across regions and communities, largely influenced by cultural, religious, and socioeconomic factors [19]. While national statistics on pet ownership may fluctuate annually, data from the National Health and Morbidity Survey (NHMS) 2020 indicate that approximately 44.5% of surveyed Malaysian households reported owning dogs [20].

In recent years, several studies on Campylobacter have been conducted in selected Malaysian states [8,21]. These investigations have identified Campylobacter spp. in various animal species, with reported prevalence rates of up to 16.3% in stray dogs and 12.5% in pet dogs [8]. Furthermore, multidrug resistance in Campylobacter isolates from dogs has been reported at levels as high as 50% [21]. However, in Kelantan, Malaysia, detailed data on Campylobacter spp., including their prevalence and antimicrobial resistance profiles, remain limited. Therefore, this study aims to (1) determine the prevalence of Campylobacter spp. in dogs, (2) characterize their antimicrobial resistance profile, and (3) identify potential risk factors associated with Campylobacter spp. infections in this population.

2. Materials and Methods

2.1. Study Area and Design

A cross-sectional study was conducted from March 2023 to March 2024 in three districts of Kelantan, Malaysia (Kota Bharu, Bachok, and Kuala Krai), located on the east coast of Peninsular Malaysia. Sampling was performed at various sites, including private veterinary clinics and a veterinary teaching hospital. Rectal swabs were collected from dogs using a convenience sampling approach. Only animals whose owners agreed to participate in the study after completing a consent form were included. The study area experiences a humid tropical climate, with annual rainfall ranging from 2032 mm to 2540 mm. The wettest months occur from November to January, with ambient temperatures between 25 °C and 37 °C [22]. The sample size of 50 rectal swabs collected from dogs in Kelantan, Malaysia, was determined based on regional accessibility, the estimated population density of owned and stray dogs, and the logistical feasibility of conducting field sampling within the scope of the study. Additionally, the sample size was calculated using a simplified formula for estimating proportions in cross-sectional studies, as follows:

n = Z²P(1 − P)/d²,

where Z is the Z-score for 95% confidence (1.96), P is the expected prevalence of Campylobacter spp. (assumed at 20% based on prior studies in similar settings), and d is the desired precision (0.12) [23]. This yielded a minimum required sample size of approximately 43. To enhance representativeness and account for potential data loss, 50 samples were collected.

The choice was further informed by practical factors, including the manageable population size of companion and shelter dogs in Kelantan, which is lower than in more urbanized states, limiting large-scale sampling efforts [8]. Moreover, ethical considerations, resource constraints, and field accessibility influenced the selection of this figure, consistent with similar regional studies targeting Campylobacter spp. in companion animals [8,21].

2.2. Sample Collection

This study analyzed a total of 50 rectal swabs collected from dogs presented at veterinary clinics and hospitals in Kelantan, Malaysia. Pet owners were approached and invited to participate voluntarily. Those who consented were provided with an informed consent form and a questionnaire to complete. Samples were collected aseptically using sterile cotton-tipped rectal swabs, which were immediately placed in individual sterile plastic bags to prevent cross-contamination. The swabs were then transported to the laboratory in Cary–Blair transport medium within a cooler box maintained at 4 °C. All samples were processed within 24 h of arrival at the laboratory. The study protocol was reviewed and approved by the Animal Ethics Committee of the Faculty of Veterinary Medicine, Universiti Malaysia Kelantan (Approval Code: UMK/FPV/ACUE/PG/002/2023).

2.3. Bacterial Isolation and Identification

Rectal swabs were directly inoculated onto modified charcoal cefoperazone deoxycholate agar (mCCDA) supplemented with CCDA selective supplement (Oxoid, Basingstoke, UK) for the primary isolation of Campylobacter spp. Inoculated plates were incubated at 42 °C for 48 h under microaerophilic conditions generated using anaerobic jars containing gas-generating packs (Oxoid, Basingstoke, UK). Presumptive Campylobacter colonies, characterized by flat, grey, and swarming morphology, were sub-cultured onto blood agar plates supplemented with 5% defibrinated sheep blood and incubated under similar conditions. Colonies displaying thin, spiral-shaped, Gram-negative rods with a characteristic seagull-wing appearance were considered suspicious. Suspected colonies were further examined by Gram staining and motility assessment under a dark-field microscope to observe the characteristic darting motility and seagull-wing morphology typical of Campylobacter spp. Further biochemical identification was performed to differentiate Campylobacter spp., those positive for catalase, oxidase, and hippurate and negative for urease were presumptively identified as Campylobacter jejuni positive while those positive for catalase and oxidase, negative for urease, and negative for hippurate were presumptively identified as Campylobacter helviticus positive. Phenotypically confirmed isolates were preserved in Müller–Hinton broth supplemented with 20% glycerol and stored at −80 °C for further analysis [24,25]. Molecular confirmation of Campylobacter isolates was performed using polymerase chain reaction (PCR) [26].

2.4. Polymerase Chain Reaction (PCR) for the Molecular Confirmation of Campylobacter

The presence of Campylobacter spp. in presumptive isolates was confirmed using polymerase chain reaction (PCR) targeting the 16S rRNA gene. A known Campylobacter positive control strain ATCC 33,560 provided by the Department of Medical Microbiology and Parasitology, Universiti Sains Malaysia, was included as a quality control reference throughout the assay. PCR amplification was carried out using genus-specific primers as previously described [27]. The total reaction volume of 25 μL reaction mixture consisted of 12.5 μL of GoTaq^® Green Master Mix (Promega, Madison, WI, USA), 1 μL of each primer (10 μM), 5.5 μL of nuclease-free water, and 5 μL of template DNA. Amplification was performed using a Bio-Rad T100™ Thermal Cycler (Bio-Rad Laboratories, Hercules, CA, USA) with the following thermal cycling conditions: initial denaturation at 95 °C for 10 min; 30 cycles of denaturation at 95 °C for 20 s, annealing at 58 °C for 20 s, and extension at 72 °C for 1 min; followed by a final extension at 72 °C for 7 min. PCR products were analyzed by electrophoresis on a 1.5% agarose gel stained with a DNA-safe dye. Electrophoresis was conducted in 1 × Tris–borate–EDTA (TBE) buffer at 100 V for 45 min. A 100 bp DNA ladder was used as a molecular size marker to estimate amplicon sizes. The primer sequences and their respective amplification conditions are summarized in

Table 1. List of primers used for the detection of Campylobacter spp.

Genes	Specie	Primer Sequence	PCR Conditions	Product Size	References
16SrRNA	Campylobacter	F-GGATGACACTTTTCGGAGC R-CATTGTAGCACGTGTGTC	Initial denaturation: 95 °C for 10 min, 30 cycles each of 95 °C for 20 s, annealing: 58 °C for 20 s, elongation: 72 °C for 1 min, and final extension time: 72 °C for 7 min.	816	[28]
cj0414 gene	C. jejuni	F-CAAATAAAGTTAGAGGTAGAATGT R- CCATAAGCACTAGCTAGCTGAT	Initial denaturation: 95 °C for 15 min, 25 cycles each of 95 °C for 30 s, annealing: 58 °C for 1.5 min, elongation: 72 °C for 1 min, and final extension time: 72 °C for 7 min.	161	[29]
gyrB gene	C. helviticus	F-AGACAAGAATTTTCTAAAGGTCTAATTGCA R-TTTTAAAATTTTATCCAGCCTTGCTTTTTC	Initial denaturation: 94 °C for 30 s, 30 cycles each of 94 °C for 20 s, annealing: 69 °C for 20 s, elongation: 72 °C for 7 min, and final extension time: 72 °C for 7 min.	251	[30]

.

2.5. Risk Factor Analysis

Risk factor analysis was conducted in this study to identify epidemiological and management-related variables significantly associated with Campylobacter spp. infection in dogs, with the goal of informing effective control strategies and minimizing the risk of zoonotic transmission. The variables assessed included location, pet roaming management, household density, age, sex, breed, antibiotic exposure, duration of antibiotic use within the past month, contact with other animals, and water source [31,32]. To explore these associations, univariable logistic regression analysis was first applied to all variables to screen for potential predictors [33]. Variables with a p-value ≤ 0.20 were then included in multivariable mixed-effects logistic regression models [33,34]. A statistical significance level of α < 0.05 was adopted in the final multivariable analysis [3].

2.6. Antimicrobial Susceptibility Testing

Antimicrobial susceptibility testing (AST) for Campylobacter isolates was performed using the Kirby–Bauer disk diffusion method on enriched Mueller–Hinton agar (Oxoid, Manchester, UK). Briefly, well-isolated colonies of the same morphological type were selected from an agar plate culture and suspended in 10 mL of sterile saline buffer (0.9% NaCl). Following homogenization, 2 mL of a bacterial suspension, adjusted to a turbidity equivalent of 0.5 McFarland standard, was evenly distributed using a sterile cotton swab on Mueller–Hinton agar surface enriched with 5% defibrinated sheep blood. After allowing the inoculum to dry for 5 min, antibiotic discs were placed on the agar. The plates were then incubated under microaerophilic conditions at 37 °C for 48 h. The diameters of the inhibition zones were measured using calipers, and the results interpreted in accordance with criteria set forth previously [35]. Isolates were assessed for susceptibility to a selection of 12 antimicrobial agents frequently used in both human and veterinary medicine in Malaysia. The antimicrobial agents tested included ampicillin (10 µg), amoxicillin- clavulanic acid (20/10 µg), chloramphenicol (30 µg), gentamicin (10 µg), tetracycline (30 µg), erythromycin (30 µg), kanamycin (30 µg), trimethoprim- sulfamethoxazole (25 µg), nalidixic acid (30 µg), ciprofloxacin (5 µg), cefoxitin (30 µg), and sulfonamides (300 µg). Susceptibility was evaluated following Clinical and Laboratory Standards Institute guidelines [35]. Breakpoints for categorizing isolates as sensitive, intermediate, or resistant were established based on CLSI criteria [35]. The antibiogram was defined as the resistance profile of an isolate to the tested antimicrobials, with the antibiogram length representing the number of antimicrobials to which the isolate displayed phenotypic resistance.

2.7. Determination of Multiple Antimicrobial Resistance (MAR) Index

Bacterial isolates exhibiting resistance to three or more classes of antimicrobial agents were classified as multidrug-resistant (MDR), following the criteria described by Gaddafi et al., 2023 [36]. The multiple antibiotic resistance (MAR) index for each isolate was calculated by dividing the number of antibiotics to which the isolate was resistant by the total number of antibiotics tested. This index indicates exposure to high-risk contamination sources, with values >0.2 suggesting environments with frequent antibiotic use [37].

2.8. Statistical Analysis

Statistical analysis was performed using SPSS (Version 29.0; SPSS Inc., Chicago, IL, USA) after the data were entered into Microsoft Excel. Descriptive statistics for reporting categorical variables were used to describe the frequency of occurrence of Campylobacter spp. To identify potential risk factors for the prevalence of Campylobacter spp. Univariable logistic regression was initially performed on all variables. Multivariable models for each outcome were created using the variables identified as significant at (α ≤ 0.20) in univariable logistic regression. Each variable was tested for statistical significance (α ≤ 0.05) in the model using manual backward selection with likelihood ratio tests. In all analyses, statistical significance was set at p-value < 0.05.

3. Results

3.1. Occurrence of Campylobacter in Dogs

A total of 50 rectal swab samples were processed in this study. Of these, 27 samples (54.0%) yielded presumptive Campylobacter spp. isolates based on cultural and morphological characteristics. Subsequent molecular confirmation using polymerase chain reaction (PCR) analysis validated 14 of these 27 isolates as Campylobacter spp. Based on the PCR results, the overall prevalence of Campylobacter spp. among the sampled population was 28.0% (14/50). Confirmation of Campylobacter species was performed using species-specific polymerase chain reaction (PCR) assays. Amplification of the cj0414 gene, specific to Campylobacter jejuni (161 bp) was confirmed. Additionally, amplification of the gyrB gene (251 bp) was used to confirm the presence of Campylobacter helveticus.

3.2. Antimicrobial Resistance Profile

All 14 Campylobacter isolates were assessed for their susceptibility to a panel of 12 antibiotics, revealing notable resistance patterns (Figure 1). The isolates exhibited the highest resistance to five antibiotics across four different classes. High resistance rates were observed against ampicillin (85.71%, 12/14), amoxicillin (71.43%, 10/14), erythromycin (64.29%, 9/14), tetracycline (57.14%, 8/14), and sulfonamides (50%, 7/14). Lower resistance rates were recorded for cefoxitin (28.57%, 4/14), gentamicin (21.43%, 3/14), trimethoprim (21.43%, 3/14), ciprofloxacin (14.29%, 2/14), nalidixic acid (14.29%, 2/14), chloramphenicol (7.14%, 1/14), and kanamycin (7.14%, 1/14). All isolates demonstrated varying levels of resistance to the antibiotics tested. Notably, 85.71% (12/14) of the Campylobacter isolates from dogs were resistant to antibiotics from at least one class, while 64.29% (9/14) exhibited multidrug resistance. The antimicrobial resistance profiles of Campylobacter helveticus and Campylobacter jejuni were broadly similar (

Table 2. Antimicrobial resistance profiles of Campylobacter species isolated from dogs in Kelantan, Malaysia.

Antimicrobial Group	Antimicrobial Agent	Resistant Isolates (%)
		C. helviticus	C. jejuni	Total
		(n = 11)	(n = 3)	(n = 14)
β-Lactams	Amoxicillin	8 (72.72)	2 (66.66)	10 (71.43)
	Ampicillin	10 (90.90)	2 (66.66)	12 (85.71)
Aminoglycosides	Gentamicin	2 (18.18)	1 (33.33)	3 (21.43)
	Kanamycin	1 (9.09)	-	1 (7.1)
Quinolones	Nalidixic acid	1 (9.09)	1 (33.33)	2 (14.23)
	Ciprofloxacin	1 (9.09)	1 (33.33)	2 (14.29)
Folate pathway	Trimethoprim	2 (18.18)	1 (33.33)	3 (21.43)
Inhibitors	Sulfonamides	6 (54.54)	1 (33.33)	7 (50)
Macrolides	Erythromycin	7 (63.63)	2 (66.66)	9 (64.29)
Cephems	Cefoxitin	3 (27.27)	1 (33.33)	4 (28.57)
Tetracyclines	Tetracycline	6 (54.54)	2 (66.66)	8 (57.14)
Phenicol	Chloramphenicol	1(9.09)	-	1 (7.14)

), though differences were noted in resistance to specific agents. Among the C. helveticus isolates (n = 11), high resistance rates were observed for ampicillin (90.9%, 10/11), amoxicillin (72.7%, 8/11), erythromycin (63.6%, 7/11), and both tetracycline and sulfonamides (54.5%, 6/11 each). In comparison, C. jejuni isolates (n = 3) also exhibited considerable resistance, with 66.7% (2/3) resistant to ampicillin, amoxicillin, ciprofloxacin, erythromycin, and tetracycline.

3.3. Multiple Antimicrobial Resistance Indices of Campylobacter spp. from Dogs

The multiple antibiotic resistance (MAR) index was calculated for each Campylobacter isolate using the formula MAR = a/b, where ‘a’ denotes the number of antibiotics to which the isolate exhibited resistance, and ‘b’ represents the total number of antibiotics tested for susceptibility [38]. Analysis of the MAR index for 14 Campylobacter isolates from dogs revealed that all isolates (100%) had MAR index values surpassing 0.2, signifying multidrug resistance attributable to higher exposure to antimicrobials. From the 12 antimicrobials tested, six distinct multidrug resistance patterns were observed across Campylobacter species. The most common pattern involved resistance to Amp, Amo, Ery, Tet, and Sulf, observed in three isolates (33.33%) for Campylobacter helviticus (

Table 3. MAR indices and Patterns of antimicrobial resistance phenotypes observed in MDR Campylobacter helviticus from dogs in Kota Bharu, Kelantan, Malaysia (n = 9).

Number of Antimicrobials	Antibiotic-Resistant Pattern	Number of Isolates	MAR Index
4	AMP + AMO + ERY + TET	1	0.3
5	AMP + AMO + ERY + TET + SULF	3	0.4
6	AMP + ERY + SULF + GEN + TET + AMO	1	0.5
7	AMP + AMO + ERY + CEF + TET + TRI + SULF	1	0.58

TET: Tetraycline; TRI: trimethoprim; SULF: Sulfonamides; ERY: Erythromycin; AMP: Ampicillin; GEN: Gentamycin; AMO: amoxicillin; and CEF: cefoxitin.

). This was followed by Amp, Tet, Ery, and Amo observed in two isolates (22.22%) for Campylobacter jejuni (

Table 4. MAR indices and Patterns of antimicrobial resistance phenotypes observed in MDR Campylobacter jejuni from dogs in Kota Bharu, Kelantan, Malaysia (n= 9).

Number of Antimicrobials	Antibiotic-Resistant Pattern	Number of Isolates	MAR Index
4	AMP + TET + ERY + AMO	2	0.3
8	AMP + AMO + ERY + SULF + TET + GEN + TRI + CIP	1	0.66

TET: Tetraycline; TRI: trimethoprim; SULF: Sulfonamides; ERY: Erythromycin; AMP: Ampicillin; GEN: Gentamycin; CIP: Ciprofloxacin; AMO: amoxicillin.

).

3.4. Potential Risk Factors Associated with the Prevalence of Campylobacter spp.

Descriptive statistics for individual variables and their univariable associations with the presence of Campylobacter spp. are summarized in

Table 5. Univariable Logistic Regression Analysis of Potential Risk Factors for Dogs in Kelantan, Malaysia (p ≤ 0.20).

Variable	Category/Group	No of Samples	No Positive (%)	Crude Odds Ratio	p-Value	CI 95%
Location	Veterinary hospital	35	11 (78.6)	0.364	0.409	0.234–0.981
	Veterinary clinics	15	3 (21.4)	Ref
Pet roaming	Outdoor	14	5 (35.7)	0.410	0.220	0.275–0.998
Management	Indoor	8	2 (14.3)	Ref
	Semi roamers	28	7 (50)	1.180	0.025 *	1.178–1.725
Household	Multi-pet	38	8 (57.1)	0.286	0.581	0.172–0.924
Density	Single	12	6 (42.9)	Ref
Age	Puppy	12	3 (21.4)	0.342	0.496	0.194–0.965
	Juvenile	30	10 (71.4)	0.355	0.489	0.210–0.976
	Adult	8	1 (7.1)	Ref
Sex	Male	23	3 (21.4)	Ref
	Female	27	11 (78.6)	0.261	0.591	0.162–0.892
Breed	Local	35	10 (71.4)	0.785	0.190 *	0.437–1.234
	Pedigree	15	4 (28.6)	Ref
Antibiotic exposure	Yes	35	10 (71.4)	0.298	0.551	0.186–0.948
	No	15	4 (28.6)	Ref
Duration of antibiotic	Yes	35	11 (78.6)	0.248	0.572	0.152–0.882
Within a month	No	12	3 (21.4)	Ref
Contact with another	Yes	38	12 (85.7)	0.382	0.316	0.242–0.992
Animals	No	12	2 (14.3)	Ref
Water source	Unfiltered	35	8 (57.1)	0.909	0.125 *	0.613–1.254
	Filtered	15	6 (42.9)	Ref
Food	Homemade/raw feed	28	6 (42.9)	1.196	0.019 *	1.202–1.839
	Pet food	8	3 (21.4)	Ref
	Mixed home/pet food	14	5 (35.7)	0.402	0.230	0.264–0.994
Vaccination status	Up-to-date	40	11 (78.6)	0.538	0.216	0.429–1.220
	Not up-to-date	10	3 (21.4)	Ref
Deworming status	Up-to-date	35	8 (57.1)	0.418	0.212	0.283–1.102
	Not up-to-date	15	6 (42.9)	Ref

*, Variables identified as significant at (α ≤ 0.20).

. Variables with p-values < 0.05 were considered significant and included in the multivariable logistic regression model. Univariable logistic regression analysis identified four variables associated with the prevalence of Campylobacter spp. in dogs at a significance level of α ≤ 0.20. These included semi-roaming behavior (odds ratio [OR] = 1.180; p = 0.025), local breed status (OR = 0.785; p = 0.190), access to unfiltered water (OR = 0.909; p = 0.125), and consumption of homemade or raw feed (OR = 1.196; p = 0.019). Subsequent multivariable logistic regression analysis identified two factors significantly associated with Campylobacter spp. positivity at p < 0.05. These include semi-roaming behavior (OR = 1.180; p = 0.025) and feeding of homemade or raw food (OR = 1.196; p = 0.019), as presented in

Table 6. Multivariable Mixed Effects Logistic Regression Analysis of Significantly Associated Explanatory Variables for Dogs in Kota Bharu, Kelantan, Malaysia (p < 0.05).

Variables	Levels	Odds Ratio	p-Value	95% C.I.
Origin/Household	Semi-roamers	1.180	0.025 *	1.178–1.725
	Indoor	NA	Ref	NA
Food	Homemade raw feed	1.196	0.019 *	1.202–1.839
	Pet food	NA	Ref	NA

*, Variables identified as significant at (α ≤ 0.20); NA, Not available.

.

4. Discussion

The occurrence of Campylobacter spp. in domestic animals, particularly companion animals such as dogs, holds significant public health relevance due to their established zoonotic potential [39]. Identifying these bacteria in pets offers critical epidemiological insights and informs risk assessment strategies for zoonotic transmission. In the present study, a cross-sectional survey was conducted to determine the prevalence, antimicrobial resistance profiles, and potential risk factors of Campylobacter spp. in dogs in Kelantan, Malaysia. The overall prevalence of Campylobacter spp. was found to be 28%. This prevalence aligns with earlier reports from Malaysia [8], which reported a prevalence rate of 16.3% in dogs, comparable to the current findings. The slightly elevated rate observed in the current study may be attributable to variations in sampling methodology, geographical location, or seasonal differences. In contrast, a study in China by (Zhang et al., 2023) [30] found a prevalence of 35.0% in dogs and 30.1% in cats. This indicates a slightly higher prevalence in dogs compared to studies in Malaysia, reflecting potential differences in environmental conditions, animal management practices, and diagnostic methodologies. The relatively high prevalence observed in this study may indicate increased carriage of Campylobacter spp. within the canine population in the study area. While these findings are generally in line with previous data, these findings suggest a potential upward trend in Campylobacter colonization or a previous underestimation of its presence in domestic dogs, highlighting the need for continued surveillance, enhanced diagnostic standardization, and public awareness to mitigate the zoonotic risks associated with companion animals.

In the present study, Campylobacter helveticus was the most prevalent species, detected in 40.7% of isolates, followed by C. jejuni at 11.1%. Although C. helveticus has historically been reported less frequently, emerging evidence suggests that it may play a significant pathogenic role in dogs, potentially influenced by environmental or dietary factors [40]. A study by Goni et al. (2017) [8] reported lower prevalence rates of C. helveticus (20%) and C. jejuni (6.7%) in canine populations compared to the findings of the current study. These variations reflect the evolving patterns of environmental exposure or microbial community dynamics attributable to differences in geographic location, climate, sampling periods, host populations, or environmental and ecological conditions influencing bacterial transmission and colonization [41].

This study investigated the prevalence and phenotypic antimicrobial resistance (AMR) profiles of Campylobacter isolates obtained from dogs in Kelantan, Malaysia. The observed resistance patterns reflect commonly used antimicrobials in veterinary medicine, particularly those administered to companion animals [42]. A high prevalence of AMR was observed in this study, with 85.71% of isolates displaying resistance to at least one antimicrobial agent. This finding is consistent with prior studies in Malaysia, by (Haulisah et al., 2022) [43], who reported an AMR prevalence of 76.5% among Campylobacter isolates from dogs, albeit slightly lower than the current study. The variation may be attributed to factors such as differences in antibiotic usage practices, environmental exposure, and overall animal health management. In contrast, Goni et al. (2017) [8] reported substantially lower resistance rates of around 50% in similar canine populations, highlighting the variability of AMR prevalence across different regions. Such differences could reflect disparities in antimicrobial stewardship, regulatory oversight, and surveillance efforts [44]. These findings highlight the growing concern of antimicrobial resistance among Campylobacter species in companion animals, emphasizing the need for continued monitoring, responsible antimicrobial use in veterinary practices, and targeted research in specific geographic or demographic populations [45].

The multiple antibiotic resistance (MAR) index is a useful epidemiological tool to assess the risk associated with the origin of bacterial isolates. Values exceeding 0.2 are generally indicative of environments with extensive antibiotic usage, such as those associated with veterinary or agricultural settings [46]. In this study, all Campylobacter isolates exhibited MAR index values ranging from 0.3 to 0.6, clearly surpassing the 0.2 threshold. These findings suggest a substantial level of antimicrobial exposure and a high prevalence of multidrug resistance (MDR), raising concerns about potential overuse or inappropriate antibiotic administration in companion animals [46]. Six distinct MDR patterns were observed among the isolates. The most prevalent pattern—ampicillin (Amp), amoxicillin (Amo), erythromycin (Ery), tetracycline (Tet), and sulfonamides (Sulf)—was detected in three isolates (33.33%) and was consistent with previous reports identifying tetracycline and macrolide resistance as common in Campylobacter spp. from dogs [47]. The second most frequent resistance pattern, involving Amp, Amo, Tet, and Ery, was observed in two isolates (22.22%), reinforcing the hypothesis of selective pressure driven by veterinary antimicrobial use [16]. Additionally, a previous study from (Shakir et al., 2021) [48] reported that 97.2% of Campylobacter isolates from poultry had MAR index values exceeding 0.3, indicating a widespread issue across multiple animal reservoirs. Similarly, Kadri et al. (2020) [49] documented high levels of resistance in Campylobacter strains in Malaysia, particularly to first-line antibiotics such as tetracyclines, macrolides, and β-lactams. The findings from this study emphasize the urgent need for improved antimicrobial stewardship and surveillance systems, particularly within the veterinary sector. The high MAR indices and varied resistance profiles indicate the potential for zoonotic transmission of resistant Campylobacter strains. Proactive monitoring and regulatory interventions are critical for mitigating the escalation of antimicrobial resistance in both animal and human health contexts.

This study identified two significant risk factors for Campylobacter carriage in dogs: dietary practices (specifically, the feeding of homemade or raw food) and household lifestyle (semi-roaming behavior). Semi-roaming behavior was found to be significantly associated with Campylobacter infection in dogs. This finding is consistent with previous studies in Malaysia [8], which reported that semi-roaming dogs had increased exposure to environmental contaminants and pathogens, including Campylobacter spp. On a global scale, studies by (Acke et al., 2009) [17] documented the association between semi-roaming and increased risk of Campylobacter infection by demonstrating that dogs with outdoor access and unrestricted roaming had higher rates of infection due to greater environmental exposure, reinforcing the role of lifestyle as a critical determinant of zoonotic pathogen carriage. Similarly, (Salam et al., 2023) [50] emphasized that unrestricted environmental access contributes to increased contact with contaminated sources, promoting the acquisition of antimicrobial-resistant organisms. Feeding practices were another significant factor influencing Campylobacter prevalence. In particular, dogs fed homemade or raw food exhibited higher rates of Campylobacter positivity. This observation aligns with findings from Goni et al. (2017) [8], who noted that non-commercial feeding practices such as leftover or raw food diets were associated with increased risk of bacterial contamination. Globally, similar trends have been observed. A previous study by Fredriksson-Ahomaa et al. (2017) [51] reported that dogs consuming raw meat diets had a significantly higher prevalence of Campylobacter in their feces than those fed commercially prepared dry food. Similarly, studies by (Corbee et al., 2025) [52] also emphasized the public health risks of raw feeding, underlining the importance of appropriate food hygiene and handling in reducing zoonotic pathogen transmission. The impact of Campylobacter infection on human health is substantial, particularly among children. It often causes acute gastroenteritis, presenting with diarrhea, fever, and abdominal pain. Transmission mainly occurs from animals to humans through contaminated broiler chickens. Severe cases may lead to complications such as Guillain-Barré syndrome, warranting strict food safety practices [53,54]. Recent molecular and epidemiological studies have confirmed identical resistant Campylobacter strains circulating between companion animals and humans, highlighting bidirectional spread [16,17]. The emergence of multidrug-resistant Campylobacter spp., especially from pet-store puppies, highlights the urgent need for One Health–oriented surveillance and interventions to mitigate cross-species AMR risks [55,56]. Notably, during the COVID-19 pandemic, there was a notable rise in the use of non-specific antibiotics, often without confirmed bacterial infections [57]. This widespread and inappropriate usage contributed significantly to the global increase in antimicrobial resistance (AMR) [57]. Future strategies to combat antimicrobial resistance (AMR) in bacteria will rely on innovative therapeutic approaches that move beyond conventional antibiotics. Promising developments include the “Trojan Horse” strategy, which exploits bacterial nutrient uptake pathways, and the targeting of bacterial metallophores essential for metal acquisition and survival [58,59]. These novel methods represent a paradigm shift in antimicrobial therapy. Advancing research and clinical application of such targeted interventions is crucial to preserving treatment efficacy and tackling the global AMR crisis.

The findings of the present study contribute significantly to both public and veterinary health by demonstrating the presence of antimicrobial-resistant Campylobacter spp. in dogs, highlighting a potential risk of zoonotic transmission, thereby raising awareness about the zoonotic risks associated with pet ownership to mitigate transmission risk. While many pathogens contribute to the growing concern of antimicrobial resistance, Campylobacter is particularly important due to its high carriage rates in animals, asymptomatic shedding, and its role as a leading cause of bacterial gastroenteritis in humans [55]. High levels of antimicrobial resistance (AMR) in companion animals have serious implications for both veterinary and public health [60]. In veterinary practice, reduced antibiotic efficacy compromises the ability to treat common infections, leading to prolonged illness in animals, increased treatment costs, and animal welfare concerns [61]. Resistant bacteria carried by animals, especially pets and food-producing stock, can be transmitted to humans through close contact, contaminated food products, or environmental exposure [62]. This cross-species transmission intensifies the overall AMR burden, limiting effective therapeutic options and increasing healthcare costs for humans [16,56]. Resistant bacteria like Campylobacter, E. coli, and Salmonella found in pets often share genetic similarity with human strains, complicating clinical management [63]. These findings highlights the need for integrated surveillance and antimicrobial stewardship across sectors to limit zoonotic spread and safeguard treatment efficacy under the One Health framework [18].

5. Conclusions

These findings highlight the influence of environmental and dietary factors on the prevalence of Campylobacter spp. in companion animals and the need for targeted public health interventions to reduce exposure risks in household settings. Limitations of this study include its exclusive focus on Campylobacter spp. without investigating potential co-infections or other zoonotic pathogens that may also impact the health of companion animals and their human contacts. Future research should prioritize investigating transmission dynamics, conducting genetic studies to identify resistance genes, and analyzing the impact of antimicrobial usage on the development of resistance.