Systematic Surveillance and Meta-Analysis of Antimicrobial Resistance and Food Sources from China and the USA
Abstract
:Highlights
- Systematic analyzation to assess the spread of AMR bacteria prevalence in retail food products and the subsequent exposure to antibiotic resistance.
- Out of 13,018 food samples, 5000 samples were contaminated.
- Meat shows high to medium potential of AMR exposure for Gram-positive and Gram-negative foodborne pathogens.
- Salmonella and Staphylococcus aureus were two predominant bacteria seen in China and the USA, respectively.
- Multidrug resistance was detected in most of the food samples from both countries.
- Food samples were more resistant to β-lactams and tetracyclines.
- Government bodies were formed to tackle AMR from food.
Abstract
1. Introduction
2. Materials and Methods
2.1. The Explication of the Field of Research
2.1.1. China
2.1.2. USA
2.2. Food Categories
2.3. Data Extraction
2.4. Search Strategy
2.5. Screening and Data Extraction Process
2.6. Data Analysis
3. Results
3.1. Descriptive Analysis of All Included Studies: General Findings
3.1.1. China
3.1.2. USA
3.2. Major Bacteria Groups and Their Relevant Food Product Categories with AMR
3.3. Gram-Positive Bacteria
3.3.1. Enterococcus
3.3.2. Staphylococcus
3.3.3. Listeria spp.
3.4. Gram-Negative Bacteria
3.4.1. Campylobacter
3.4.2. Escherichia coli
3.4.3. Salmonella
3.4.4. Cronobacter
3.4.5. Vibrio spp.
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Microbes | Chicken n = 1006 | Pork n = 558 | Egg n = 847 | Duck n = 41 | Beef n = 67 | Mutton n = 19 | Fish n = 1108 | Sea Food n = 1254 | Vegetables n = 1094 | Fruits n = 132 | Milk n = 216 | REF n = 622 | Total n = 6965 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
n and (%) | n and (%) | n and (%) | n and (%) | n and (%) | n and (%) | n and (%) | n and (%) | n and (%) | n and (%) | n and (%) | n and (%) | n and (%) | |
E. coli | 39 (3.9) | 62 (11.1) | 9 (1.1) | 4 (9.8) | 28 (41.8) | 11 (57.9) | 11 (1.0) | 14 (1.1) | 78 (7.1) | 19 (14.4) | 11 (5.1) | 8 (1.3) | 294 (4.2) |
C. jejuni | 63 (6.3) | - | - | - | - | - | - | - | - | - | - | - | 63 (0.9) |
C. coli | 98 (9.7) | - | - | - | - | - | - | - | - | - | - | - | 98 (1.4) |
Salmonella | 312 (31) | 316 (56.6) | 46 (5.4) | 3 (7.3) | - | - | - | - | 14 (1.3) | - | - | - | 691 (9.9) |
V. parahaemolyticus | - | - | - | - | - | - | 193 (17.4) | 352 (28.1) | - | - | - | 24 (3.9) | 569 (8.2) |
Enterococci | 28 (2.8) | 29 (5.2) | - | - | 29 (43.3) | - | 16 (1.4) | 53 (4.2) | 115 (10.5) | 79 (59.8) | - | - | 349 (5.0) |
Cronobacter spp. | - | - | - | - | - | - | - | - | 122 (11.2) | - | - | - | 122 (1.8) |
S. aureus | - | - | - | - | - | - | - | - | - | - | 90 (41.7) | - | 90 (1.3) |
Total infected | 540 (53.7) | 407 (72.9) | 55 (6.5) | 7 (17.1) | 57 (85.1) | 11 (57.9) | 220 (19.9) | 419 (33.4) | 329 (30.1) | 98 (74.2) | 101 (46.8) | 32 (5.1) | 2276 (32.7) |
Microbes | Chicken n = 1564 | Beef n= 1253 | Pork n = 1461 | Meat n = 396 | Turkey n = 299 | Fish n = 55 | Milk n = 465 | Vegetables n = 194 | Others n = 366 | Total n = 6053 |
---|---|---|---|---|---|---|---|---|---|---|
n and (%) | n and (%) | n and (%) | n and (%) | n and (%) | n and (%) | n and (%) | n and (%) | n and (%) | n and (%) | |
E. coli | - | - | - | 49 (12.4) | - | - | - | 23 (11.9) | - | 72 (1.2) |
Salmonella | - | - | - | 2 (0.5) | - | - | - | - | - | 2 (0.0) |
Campylobacter spp. | - | - | - | - | - | - | 143 (30.8) | 12 (6.2) | - | 155 (2.6) |
C. jejuni | 69 (4.4) | - | - | - | - | - | - | - | - | 69 (1.1) |
C. coli | 66 (4.2) | - | - | - | - | - | - | - | - | 66 (1.1) |
Listeria spp. | - | - | - | - | - | - | - | 11 (5.7) | - | 11 (0.2) |
L. monocytogenes | - | - | - | - | - | - | - | 3 (1.5) | - | 3 (0.0) |
Staphylococcus aureus | 442 (28.3) | 1030 (82.2) | 510 (34.9) | 10 (2.5) | 86 (28.8) | 2 (3.6) | - | 4 (2.1) | 27 (7.4) | 2111 (34.9) |
Staphylococcus aureus MRSA | 16 (1.0) | 6 (0.5) | 21 (1.4) | 6 (1.5) | 42 (14.0) | - | - | 4 (2.1) | 19 (5.2) | 114 (1.9) |
Enterococcus | - | - | - | 121 (30.5) | - | - | - | - | - | 121 (2.0) |
Total infected | 593 (37.9) | 1036 (82.7) | 531 (36.3) | 188 (47.5) | 128 (42.8) | 2 (3.6) | 143 (30.8) | 57 (29.4) | 46 (12.6) | 2724 (45.0) |
S. No. | Country | Organizations | Role |
---|---|---|---|
1. | China | Bureau of Animal and Plant Health Inspection and Quarantine (BAPHIQ) https://www.baphiq.gov.tw/ (accessed on 24 April 2022) | Global Action Plan on Antimicrobial Resistance, and the OIE Strategy on Antimicrobial Resistance and the Prudent Use of Antimicrobials. |
2. | National Action Plan (NAP) http://www.gov.cn/xinwen/2016-08/25/content_5102348.htm (accessed on 24 April 2022) | Regulate antimicrobial agents and antimicrobial resistance control. | |
3. | China Antimicrobial Resistance Surveillance System (CARSS) http://www.carss.cn/ (accessed on 24 April 2022) | AMR surveillance. | |
4. | China Antimicrobial Surveillance Network (CHINET) https://www.chinets.com/ (accessed on 24 April 2022) | Help clinicians to better understand the current status and trends of AMR and to correct inappropriate antibiotic prescribing. | |
5. | USA | National Antimicrobial Resistance Monitoring System (NARMS) https://www.cdc.gov/narms/index.html (accessed on 24 April 2022) | Track changes in the antimicrobial susceptibility of enteric (intestinal) bacteria found in ill people. |
6. | Centers for Disease Control and Prevention https://www.cdc.gov/ (accessed on 24 April 2022) | Carry out scientific research on new and ongoing pathogen threats. | |
7. | Food and Drug Administration (FDA) https://www.fda.gov/ (accessed on 24 April 2022) | Protecting public health by assuring that foods are wholesome, sanitary, and properly labeled. | |
8. | US Department of Agriculture (USDA) https://www.usda.gov/ (accessed on 24 April 2022) | Safeguard food, agriculture, natural resources, rural development, nutrition, and related issues based on public policy. |
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Himanshu; R. Prudencio, C.; da Costa, A.C.; Leal, E.; Chang, C.-M.; Pandey, R.P. Systematic Surveillance and Meta-Analysis of Antimicrobial Resistance and Food Sources from China and the USA. Antibiotics 2022, 11, 1471. https://doi.org/10.3390/antibiotics11111471
Himanshu, R. Prudencio C, da Costa AC, Leal E, Chang C-M, Pandey RP. Systematic Surveillance and Meta-Analysis of Antimicrobial Resistance and Food Sources from China and the USA. Antibiotics. 2022; 11(11):1471. https://doi.org/10.3390/antibiotics11111471
Chicago/Turabian StyleHimanshu, Carlos R. Prudencio, Antonio Charlys da Costa, Elcio Leal, Chung-Ming Chang, and Ramendra Pati Pandey. 2022. "Systematic Surveillance and Meta-Analysis of Antimicrobial Resistance and Food Sources from China and the USA" Antibiotics 11, no. 11: 1471. https://doi.org/10.3390/antibiotics11111471