Assessment of Knowledge, Attitude and Practice (KAP) Regarding Antimicrobial Usage and Resistance Among Animal Health Professionals of East Wallaga Zone, Oromiya, Ethiopia

Figures & data

Figure 1 Map of the study Areas (Created by ArcGIS_WGS_1984).

Table 1 Socio-Demographic Profile of the Respondents

Variable	Categories	Frequency	Percentage
Sex	Male	77	64.17
	Female	43	35.83
Age (in years)	18–24	26	21.66
	25–34	73	60.83
	35–44	38	15.00
	45–54	3	2.50
Location	Sibu Sire	31	25.83
	Nekemte town	56	46.67
	Leka Dulecha	33	27.50
Professions	BVSc	39	32.50
	Diploma	59	49.17
	MSc/MPH	7	5.83
	Veterinary degree (DVM)	15	12.50
Experience (in years)	0 to <5 years	21	17.50
	5–10 years	66	55.00
	10–15	26	21.67
	15–20	7	5.83

Table 2 Knowledge of Participants About Antimicrobial Usage and Resistance

Variables (Knowledge Assessment)	Respondents Answer (Frequency (%))			Actuality
	True	False	I Do Not Know	Correct No (%)	Incorrect No (%)
Antibiotics kill virus	8 (6.63)	112 (93.33)	0	112 (93.33)	8 (6.67)
Antibiotics kill or stop the growth of both good and bad bacteria	101 (84.17)	19 (15.83)	0	101 (84.17)	19 (15.83)
A withdrawal period has to be strictly observed in treated poultry before any poultry product is passed as human consumption	88 (73.33)	29 (24.17)	3 (2.50)	88 (73.33)	32 (26.67)
Overuse of antibiotics makes them become ineffective	109 (90.83)	11 (9.17)	0	109 (90.83)	11 (9.17)
Bacteria can become resistant to antibiotics	102 (85.00)	18 (15.00)	0	102 (85.00)	18 (15.00)
Many infections are becoming increasingly resistant to treatment by antimicrobials	69 (57.50)	48 (40.00)	3 (2.50)	69 (57.50)	51 (42.50)
Withdrawal period does not have to be observed for milking cows treated with antibiotics such as penicillin before milk can be consumed	19 (15.83)	100 (83.33)	1 (0.83)	100 (83.33)	20 (16.67)
Over and under use of antimicrobials can cause antimicrobial resistance microorganism	115 (95.83)	5 (4.17)	0	115 (95.83)	5 (9.17)
Man can consume antibiotics as a result of eating meat/drinking milk	109 (90.83)	7 (5.83)	4 (3.33)	109 (90.83)	11 (9.17)
Even if man consumes antibiotics in meat/milk, it will only make him healthier	52 (43.33)	66 (55.00)	2 (1.67)	52 (43.33)	68 (56.67)
Use of antimicrobials in animals intended for food can result in resistant bacteria being transmitted to human	59 (49.17)	56 (46.67)	5 (4.17)	56 (46.67)	64 (53.33)
Antimicrobial resistant-microbes are found in people, animals, food, and the environment	52 (43.33)	66 (55.00)	2 (1.67)	52 (43.33)	68 (56.67)

Table 3 Knowledge of AHPs Toward AMU and AMR Based on the Likert Scale

Variables (Knowledge Assessment)	Respondents Answer (Freq. (%))			Mean ± SD
	A	N	DA
Biosecurity is important in food production	117 (97.50)	1 (0.83)	2 (1.67)	3.96±027
Healthy people and animals can carry antibiotic resistant bacteria	61 (50.83)	11 (9.17)	48 (40.00)	3.11±0.95
When there is poor biosecurity, prophylactic antibiotics are an appropriate alternative to protect animal health	61 (50.83)	22 (18.33)	37 (30.83)	3.20±0.88
Long duration of antibiotic treatments can lead into AMR	108 (90.00)	4 (3.33)	8 (6.67)	3.83±0.52
Under-dosing of antibiotics can cause antibiotic resistance	117 (97.50)	1 (0.83)	2 (1.67)	3.96±0.27
Less public awareness of antibiotic resistance contribute to ABR	104 (86.67)	13 (10.83)	3 (2.50)	3.84±0.43
Excessive use of antibiotics in livestock and food production contribute to ABR	105 (87.50)	9 (7.50)	6 (5.00)	3.83±0.50

Notes: Numeric bold in last column represents the mean and standard deviation of the knowledge rating scale based on the Likert scale.

Abbreviations: A, Agree; N, Neutral; DA, Disagree; SD, Standard deviation.

Table 4 Attitude of Healthcare Professionals Toward Antimicrobial Usage and Antimicrobial Resistance

Variables (Attitude Related)	Respondents Answer (Frequency) (%))					Mean ±SD
	SD	DA	N	A	SA
Prescribing unnecessary antibiotics is professionally unethical	6 (5.00)	0	2 (1.67)	90 (75.00)	22 (18.33)	4.01±0.81
Inappropriate antimicrobial use can lead to resistance	0	3 (2.50)	1 (0.83)	87 (72 0.50)	29 (24.17)	4.18±0.56
We have enough antibiotics under development at the moment to keep up with the problem of resistance	8 (6.67)	69 (57.50)	11 (9.17)	31 (25.83)	1 (0.83)	2.58±1.00
Antibiotic resistance is a national problem	9 (0.83)	47 (39.17)	7 (5.83)	58 (48.33)	7 (5.83)	3.11±0.99
The antibiotics you prescribe may contribute to the problem of antibiotic resistance	0	24 (20.0)	2 (1.67)	87 (72.50)	7 (5.83)	3.63±0.88
Antibiotic resistance will be a greater problem later in your career than it is today	1 (0.83)	59 (49.17)	9 (7.50)	38 (31.67)	13 (10.83)	3.03±1.12
Antimicrobial resistance is worldwide problem	2 (1.67)	14 (11.67)	7 (5.83)	88 (73.33)	9 (7.50)	4.14±0.49
Do you feel you have sufficient knowledge on antibiotic use?	1 (0.83)	17 (14.17)	2 (1.67)	95 (79.17)	5 (4.17)	3.72±0.79
The more antibiotics I give to my animal, the healthier the animal becomes	20 (16.67)	69 (57.50)	3 (2.50)	26 (21.67)	2 (1.67)	2.34±1.05
If antibiotics are given too much to animals, it can cause any serious problem to man through meat and milk	4 (3.33)	9 (7.50)	2 (1.67)	94 (78.33)	11 (9.17)	3.83 ± 0.83
Antimicrobial resistance is problem in Ethiopia	1 (0.83)	2 (1.67)	0	98 (82.50)	18 (15.00)	4.09±0.53
Application of one health approach is important to control antimicrobial resistance	1 (0.83)	0	3 (2.50)	90 (75.00)	26 (21.67)	4.17±0.54
Antimicrobial use and antimicrobial resistance Surveillance in humans is important to control antimicrobial resistance in animals	0	6 (5.00)	9 (7.50)	87 (72.50)	18 (15.00)	3.98±0.65
Doctor’s prescription for drug use is important	0	0	1 (0.83)	58 (48.33)	61 (50.83)	4.50±0.52
Drug can transferred to human by consumption meat of animal treat recently	0	6 (5.00)	4 (3.33)	76 (63.33)	34 (28.33)	4.15±0.71
You need to have more knowledge and understanding on antibiotic usage	1 (0.83)	1 (0.83)	1 (0.83)	63 (52.50)	54 (45.00)	4.40±0.64
Overuse of antibiotics can lead to development of resistant organisms	1 (0.83)	3 (2.50)	5 (4.17)	92 (76.67)	19 (15.83)	4.04±0.61
As health professional, you have a role to play in preventing public health threats posed by antibiotic resistance	2 (1.67)	1 (0.83)	1 (0.83)	91 (75.83)	25 (20.83)	4.13±0.62
More cautious use of antimicrobials would decrease antimicrobial resistance	29 (24.17)	54 (45.00)	9 (7.50)	19 (15.83)	9 (7.50)	2.38±1.22
Broad spectrum antibiotics should be used in place of narrow spectrum antibiotics to reduce resistance	5 (4.17)	60 (50.00)	44 (36.67)	7 (5.83)	4 (3.33)	2.54±0.81

Notes: Numeric bold in last column represents the mean and standard deviation of the attitude rating scale based on the Likert scale.

Abbreviations: A, Agree; N, Neutral; DA, Disagree; SD, Standard deviation.

Table 5 Number of Questions, Range, Scores, and Level of Knowledge and Attitude of the Participants

Variables	Number of Questions	Range of Score	Mean ± SD	Minimum Value	Maximum Value
Knowledge score	7	0–100	66.88±6.90	46.43	75.00
Attitude score	20	0–100	66.17±6.89	47.50	93.75

Table 6 Practice of Professionals Toward Antibiotic Usage, Resistance, and Residue Development

Factors on Practice of AHPs	Always	Sometimes	Never
	No. (%)	No. (%)	No. (%)
Usage of antibiotics without doctor’s prescription	89 (74.17)	31 (25.83)	0 (0)
How often do you give antibiotics to your animals?	3 (2.50)	115 (95.83)	2 (1.67)
Repeatedly use of same drugs for a disease with similar clinical sign	18 (15.00)	92 (76.67)	10 (8.33)
Have a standardized protocol for treating sick animals with antibiotics	16 (13.33)	104 (86.67)	0 (0)
How often do you encounter owner-initiated antibiotic treatment before presentation?	46 (38.33)	64 (53.33)	10 (8.33)
How often do you undertake antimicrobial sensitivity testing before starting antibiotic treatment?	1 (0.83)	20 (16.67)	99 (82.50)
Factors influence your decision the most important when selecting an antibiotic to use	Frequency (%)
Owner preference for a specific antibiotic	13 (10.83)
My own previous experience	104 (86.67)
Advice from colleagues	3 (2.50)
Factors influence your decision the most important when selecting an antibiotic to use
Cost of antibiotic drug	65 (54.17)
Owner ability to pay	43 (35.83)
Marketing offers	8 (6.67)
Advertisement by drug representative	3 (2.50)
Profit margin to veterinarian	1 (0.83)

Table 7 Association of Knowledge and Attitude, and Influencing Factors

Variables	Categories	Number of Respondents	Knowledge, Freq. (%)			X^2	P-value
			Good	Moderate	Poor
Location	Sibu Sire	31	15 (48.39)	16 (51.61)	(0)	14.13	0.007
	Leka Dulecha	33	5 (15.15)	23 (69.70)	5 (15.15)
	Nekemte town	56	11 (19.64)	40 (71.43)	5 (8.93)
Sex	Female	43	10 (23.26)	30 (69.77)	3 (6.98)	0.47	0.787
	Male	77	21 (27.27)	49 (63.64)	7 (9.09)
Age	18–24	26	7 (26.92)	18 (69.23)	1 (3.85)	1.99	0.920
	25–34	72	18 (25.00)	46 (63.89)	8 (11.11)
	35–44	18	5 (27.78)	12 (66.67)	1 (5.56)
	45–54	23	1 (25.00)	3 (75.00)	0 (0.00)
Educational Level	Diploma	59	12 (20.34)	42 (71.19)	5 (8.47)	3.334	0.764
	BVS	39	12 (30.77)	25 (64.10)	2 (5.13)
	DVM	15	5 (33.33)	8 (53.33)	2 (13.33)
	MSc	7	2 (28.57)	4 (57.14)	1 (14.29)
Experience (in years)	(0–5)	21	6 (28.57)	14 (66.67)	1 (4.76)	6.68	0.351
	(5–10)	66	20 (30.30)	38 (57.58)	8 (12.12)
	(10–15)	26	4 (15.38)	21 (80.77)	1 (3.85)
	>15	7	1 (14.29)	6 (85.71)	0 (0.00)
Employment	Gov’t	67	22 (32.84)	40 (59.70)	5 (7.46)	5.62	0.229
	NGO	4	0 (0.00)	3 (75.00)	1 (25.00)
	Private	49	9 (18.37)	36 (73.47)	4 (8.16)