Rational use of antimicrobials: a nationwide cross-sectional survey among people of Pakistan : IJS Global Health

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Rational use of antimicrobials: a nationwide cross-sectional survey among people of Pakistan

Khadka, Sitaram PharmD, MPhila,b,*; Hashmi, Furqan K. PhDa; Yadav, Gopal K. MBBSc; Lamichhane, Sabitri PhDd; Giri, Santoshi MSce; Tariq, Fatima PharmDa; Amin, Sabahat PharmDa; Zaheer, Warda PharmDa; Akram, Kiran PharmDa; Asghar, Ifra PharmDa; Zahra, Kainat PharmDa; Bajwa, Faiza PharmDa; Ul-ain, Noor PharmDa; Adnan, Muhammad A.J. PhDf

Author Information
International Journal of Surgery: Global Health 6(1):p e103, January 2023. | DOI: 10.1097/GH9.0000000000000103


Antibiotics have revolutionized the prevention and treatment of infectious diseases and proved to be the important life-saving drugs of the current time1. However, the inappropriate use of antibiotics is increasing day by day in the developing as well as the developed world. Such misuse of antibiotics is the leading cause of the emergence of antimicrobial resistance (AMR)2. AMR has been a global health threat, where the bacteria develop resistant genes and the emerging new strains of bacteria are immune to the currently available large spectrum of antibiotics2,3. The World Health Organization (WHO) has prognosticated 10 million deaths each year by 2050 in case of uncontrolled AMR4. Increased complexity of the disease, patient reattendance to the hospital, and increased health care costs and mortality rates are the major consequences of AMR5–7.

Lack of adequate knowledge, unawareness, over-the-counter availability of antibiotics, prophylactic use in livestock in bulk, and weak legislative efforts are the factors responsible for antimicrobial misuse leading to AMR8–14. Furthermore, social beliefs, socioeconomic status, and sociodemographic characteristics are other contributing factors to this global hazard.

Pakistan is a country with a low-income economy where AMR is getting escalated leading to the inefficacy of many previously potent antibiotics15,16. People generally take specific antibacterial for self-limiting diseases and diseases that are not caused by bacteria17. The only way to counter its detrimental effects is to ensure the rational use of medicines (RUM). Along with strict enforcement of the Drug Regulatory Authority of Pakistan (DRAP) Act 2012, Punjab Drug Rules 2007, and Pakistan’s National Action Plan (NAP) on AMR; quality improvement strategies using clinician training and public awareness campaigns might be efficient practice at reducing antimicrobial misuse18,19.

The objective of this study is to evaluate the knowledge, behavior, and practices of the Pakistani population towards antibiotic usage to understand the factors leading to the misuse of antimicrobials so that effective interventions can be implemented for rational drug therapy.


Ethics approval

The research has been performed following the Declaration of Helsinki. The ethics approval was granted by the Institutional Review Board (IRB), the University of Punjab, Lahore (Reg. No. D/255/FIMS). Informed consent was obtained from participants before participating in the study.

Study design, setting, and study population

A nationwide cross-sectional survey was carried out in Pakistan from March 2022 to August 2022, principally targeting the assessment of antimicrobial use patterns among the general population in Pakistan. It was conducted in accordance with the guidelines of Strengthening of the Reporting of Observational Studies in Epidemiology (STROBE)20. Pakistan is a country with a lower-middle-income economy that lies in the Eastern Mediterranean Region21. It has an estimated population of 230,146,924 as of 2022. The flow diagram depicting the participants’ inclusions has been drawn below and the final sample size was 385 (Fig. 1).

Figure 1:
Flow diagram showing the selection of participants.

Study tool and data collection

A questionnaire was developed in English as well as in the Urdu language comprising of 5 sections; information and informed consent, demographics of participants, knowledge (true or false), behavior, and practices on antimicrobial use on a 5-point Likert scale (strongly disagree, disagree, neutral, agree, strongly agree). The questionnaire was validated by the expert review team of University of the Punjab, Lahore, Pakistan. It was pretested on 20 participants, which were not included in the final data set. Then, the pretested and verified questionnaire was sent to the participants using the convenience sampling method via different online media (Messenger, Whatsapp, Viber, etc.) in the form of Google Forms. The first page of the “google form questionnaire” contained the “Information and informed consent sheet” to obtain e-consent after an explanation of the objectives of the study and the voluntary nature of participation. The subsequent pages contained questions on knowledge, behavior, and practices of antimicrobial use.

Data management and statistical analysis

The response to the online survey were extracted from google docs as excel 2019 v16.0 (Microsoft) and exported to IBM SPSS v21 (IBM) for further analysis.

The knowledge and behaviors item consists of 5 questions (maximum total score 5 and 25, respectively) while the practices item consists of 10 questions (maximum total score 50). The statements which opposed the notion of behaviors and/or practices were graded 5 points for strongly disagree and 1 point for strongly agree, and accordingly rest responses of disagree, neutral/unsure and agree to 4, 3, and 2 points in decremental order, respectively. Similarly, the statements which supported the notion of behavior and/or practices were graded 1 point for strongly disagree and 5 points for strongly agree, and accordingly rest responses of disagree, neutral/unsure, and agree to 2, 3, and 4 points, respectively.

The 60% cut-off was adapted from the original Bloom’s cut-off criteria and the total scores of behaviors, and practices were calculated and recoded into different categorical variables22. The knowledge was categorized into true and false categories. The behavior was categorized into good to moderate (≥60% of 25=15 score) and poor categories (<15 score). Similarly, the practice was categorized into good to moderate (≥60% of 50=30 score) and poor categories (<30 score). Sociodemographic characteristics of participants were presented as frequency and proportions. The χ2 test was used to test for group differences. For univariable logistic regression analyses, odds ratio (OR) was calculated at a 95% CI. Multivariable logistic regression was used to determine independent factors associated with good knowledge, moderate to a good attitude and moderate to good practice, and adjusted odds ratios (AOR) were calculated at 95% CI. All variables with P<0.20 were retained in the final multivariable model. Box plots were drawn for the distribution of knowledge, behavior, and practice scores based on education level and areas of work. Spearman rank correlation coefficient test was used to assess the relationships between two items of the knowledge, behavior, and/or practice scores.


A total of 1011 respondents participated in this survey. The majority of them were female 69.3% (n=701), younger than 40 years of age 89.1% (n=901), and in a state of good health 81.5% (n=824) without current smoking habit 93.2% (n=942). Most of the participants were from urban areas 84.7% (n=856) and educated with at least university degree 75.3% (n=761). Health care professionals as respondents were only 36.0% (n=364) as compared with other professionals and a majority of our respondents 54.7% (n=553) were earning <50,000 PKR per month in our study (Table 1).

Table 1 - Sociodemographic characteristics of the study population (N=1011).
Characteristics Particular n (%)
Age <40 901 (89.1)
40–59 83 (8.2)
≥60 27 (2.7)
Sex Male 310 (30.7)
Female 701 (69.3)
Educational status No formal education 61 (6.0)
School level 58 (5.7)
College level 131 (13.0)
University level 761 (75.3)
Occupational status Unemployed 753 (74.5)
Employed 258 (25.5)
Areas of work Health 364 (36.0)
Other than health 647 (64.0)
Residence Urban 856 (84.7)
Rural 155 (15.3)
Current smoking status No 942 (93.2)
Yes 69 (6.8)
Comorbidity No 824 (81.5)
Yes 187 (18.5)
Monthly income* <20k 206 (20.4)
20k–49,999 347 (34.3)
50k–99,999 289 (28.6)
≥100k 169 (16.7)

Knowledge assessment

The response to each question on the knowledge questionnaire was presented in Supplementary Table 1 (Supplemental Digital Content 1, https://links.lww.com/IJSGH/A19). The median knowledge score was 3 (25–75th percentiles: 2–4). More than half of the participants (559, 55.3%) had true knowledge regarding the rational use of antimicrobials. In the univariable model, the participants aged less than 40 had 1.92 times higher odds of true knowledge (OR: 1.92, 95% CI: 1.28–2.85, P=0.002) compared with those aged 40 years and above. Educated participants with university degrees had more than 2 times higher odds of true knowledge (OR: 2.64, 95% CI: 1.77–3.93, P<0.001) than those with only a college degree. The health professionals had 1.72 times higher odds of true knowledge (OR: 1.72, 95% CI: 1.32–2.24, P<0.001) than other professionals. Participants of urban areas had also more than 2 times higher odds of true knowledge (OR: 2.13, 95% CI: 1.67–3.03, P<0.001) than those residing in rural areas. Similarly, participants without comorbidity had also more than 2 times higher odds of true knowledge (OR: 2.38, 95% CI: 1.72–3.33, P<0.001) than those with comorbidities.

In the multivariable model, the employed participants had 2.12 times higher odds of true knowledge (AOR: 2.12, 95% CI: 1.51–2.98, P<0.001) than unemployed participants. The health professionals had 1.64 times higher odds of true knowledge (AOR: 1.64, 95% CI: 1.25–2.17, P<0.001) than other professionals. Participants of urban areas had also higher odds of true knowledge (AOR: 1.61, 95% CI: 1.12–2.38, P<0.011) than those residing in rural areas. Similarly, participants without comorbidity had also more than 2 times higher odds of true knowledge (AOR: 1.89, 95% CI: 1.32–2.70, P<0.001) than those with comorbidities (Tables 2, 3).

Table 2 - Knowledge, behavior, and practice scores of the participants.
Characteristics N=1011
Knowledge Scores/values
 Median (min-max) 3 (0–5)
 Q1–Q3 2–4
 Mean±SD 2.8±1.3
 True knowledge 559 (55.3%)
 Median (min-max) 18 (8–25)
 Q1–Q3 16–20
 Mean±SD 18.0±3.1
 Moderate to good behavior 896 (88.6%)
 Median (min-max) 29 (10–50)
 Q1–Q3 23–34
 Mean±SD 28.3±8.1
 Moderate to good practice 484 (47.9%)

Table 3 - Factors affecting the knowledge of the participants about the rational use of antimicrobials.
Knowledge Univariable regression model Multivariable regression model
Characteristics False/poor (%) True/good (%) OR 95% CI P AOR 95% CI P
Age (y) 0.001*
 <40 387 (43.0) 514 (57.0) 1 (Ref) 1 (Ref)
 ≥40 65 (59.1) 45 (40.9) 0.52 0.35–0.78 0.002 0.63 0.39–1.03 0.065
Sex 0.048*
 Male 153 (49.4) 157 (50.6) 1 (Ref) 1 (Ref)
 Female 299 (42.7) 402 (57.3) 1.31 1.01–1.71 0.048 1.35 1.00–1.83 0.050
Educational status <0.001*
 Up to college 78 (65.5) 41 (34.5) 1 (Ref) 1 (Ref)
 University degree 374 (41.9) 518 (58.1) 2.64 1.77–3.93 <0.001 1.46 0.91–2.35 0.116
Occupational status 0.008*
 Unemployed 355 (47.1) 398 (52.9) 1 (Ref) 1 (Ref)
 Employed 97 (37.6) 161 (62.4) 1.48 1.11–1.98 0.008 2.12 1.51–2.98 <0.001
Areas of work <0.001*
 Health 132 (36.3) 232 (63.7) 1.72 1.32–2.24 <0.001 1.64 1.25–2.17 <0.001
 Other than health 320 (49.5) 327 (50.5) 1 (Ref) 1 (Ref)
Resident areas <0.001*
 Urban 358 (41.8) 498 (58.2) 1 (Ref) 1 (Ref)
 Rural 94 (60.6) 61 (39.4) 0.47 0.33–0.66 <0.001 0.62 0.42–0.89 0.011
Current smoker <0.001*
 No 406 (43.1) 536 (56.9) 1 (Ref) 1 (Ref)
 Yes 46 (66.7) 23 (33.3) 0.38 0.23–0.64 <0.001 0.52 0.29–0.92 0.024
Co-morbid status <0.001*
 No 336 (40.8) 488 (59.2) 1 (Ref) 1 (Ref)
 Yes 116 (62.0) 71 (38.0) 0.42 0.30–0.58 <0.001 0.53 0.37–0.76 <0.001
Monthly income <0.001*
 <50k 276 (49.9) 277 (50.1) 1 (Ref) 1 (Ref)
 ≥50k 176 (38.4) 282 (61.6) 1.60 1.24–2.05 0.001 1.43 1.09–1.88 0.009
Significance values are in bold.
*Chi-sqaure tests.
AOR indicates adjusted odds ratio; OR, odds ratio; Ref, reference.

Behavior assessment

The response to each question on the behavior questionnaire was presented in Supplementary Table 2 (Supplemental Digital Content 1, https://links.lww.com/IJSGH/A19). The median behavior score was 18 (25–75 percentiles: 16–20). More than four-fifths of the participants (896, 88.6%) had moderate to good behavior regarding the rational use of antimicrobials.

In the univariable model, the female participants had 1.73 times higher odds of moderate to good behavior (OR: 1.73, 95% CI: 1.17–2.58, P=0.007) than male participants. Similarly, participants with a university degree (OR: 2.22, 95% CI: 1.35–3.66, P=0.002), those without current smoking habit (OR: 2.32, 95% CI: 1.27–4.35, P=0.006), and without comorbidity (OR: 1.75, 95% CI: 1.12–2.70, P=0.014) had a significant association with moderate to good behavior.

In the multivariable model, none of the factors had a significant association with the behavior of the participants (Tables 2, 4).

Table 4 - Factors affecting the behavior of the participants about the rational use of antimicrobials.
Behavior Univariable regression mode Multivariable regression model
Characteristics Poor (%) Moderate to good (%) OR 95% CI P AOR 95% CI P
Age (y) 0.636*
 <40 101 (11.2) 800 (88.8) 1 (Ref)
 ≥40 14 (12.7) 96 (87.3) 0.87 0.48–1.57 0.636
Sex 0.006*
 Male 48 (15.5) 262 (84.5) 1 (Ref) 1 (Ref)
 Female 67 (9.6) 634 (90.4) 1.73 1.17–2.58 0.007 1.45 0.95–2.23 0.086
Educational status 0.001*
 Up to college 24 (20.2) 95 (79.8) 1 (Ref) 1 (Ref)
 University degree 91 (10.2) 801 (89.8) 2.22 1.35–3.66 0.002 1.66 0.96–2.89 0.070
Occupational status 0.049*
 Unemployed 77 (10.2) 676 (89.8) 1 (Ref) 1 (Ref)
 Employed 38 (14.7) 220 (85.3) 0.66 0.43–1.00 0.051 0.82 0.52–1.27 0.367
Areas of work 0.265*
 Health 36 (9.9) 328 (90.1) 1.27 0.84–1.92 0.266
 Other than health 79 (12.2) 568 (87.8) 1 (Ref)
Resident areas 0.140*
 Urban 92 (10.7) 764 (89.3) 1 (Ref) 1 (Ref)
 Rural 23 (14.8) 132 (85.2) 0.69 0.42–1.31 0.142 0.87 0.51–1.47 0.615
Current smoker 0.005*
 No 100 (10.6) 842 (89.4) 1 (Ref) 1 (Ref)
 Yes 15 (21.7) 54 (78.3) 0.43 0.23–0.79 0.006 0.66 0.34–1.29 0.226
Co-morbid status 0.013*
 No 84 (10.2) 740 (89.8) 1 (Ref) 1 (Ref)
 Yes 31 (16.6) 156 (83.4) 0.57 0.37–0.89 0.014 0.76 0.47–1.25 0.287
Monthly income 0.857*
 <50k 62 (11.2) 491 (88.8) 1 (Ref)
 ≥50k 53 (11.6) 405 (88.4) 0.96 0.65–1.42 0.857
*χ2 tests.
AOR indicates adjusted odds ratio; OR, odds ratio; Ref, reference.

Practice assessment

The response to each question on the practice questionnaire was presented in Supplementary Table 3 (Supplemental Digital Content 1, https://links.lww.com/IJSGH/A19). The median practice score was 29 (25–75th percentiles: 23–34). Almost half of the participants (484, 47.9%) demonstrated moderate to good practice regarding the rational use of antimicrobials.

In the univariable model, the participants with age 40 years and above (OR: 1.53, 95% CI: 1.03–2.28, P=0.038), male participants (OR: 1.47, 1.12–1.92, P=0.005), lower educational degree, that is, those with education up to college level (OR: 2.50, 95% CI: 1.64–3.70, P<0.001), other than health professionals (OR: 1.30, 95% CI: 1.01–1.69, P0.046), current smokers (OR: 3.61, 95% CI: 2.06–6.34, P<0.001), and monthly income <50 PKR (OR: 1.72, 95% CI: 1.35–2.22, P<0.001) had a significant association with moderate to good practice.

In the multivariable model, participants with lower education (AOR: 1.69, 95% CI: 1.06–2.70, P=0.028), rural residents (AOR: 2.06, 95% CI: 1.42–3.01, P<0.001) and those with lower monthly income <50 PKR (AOR: 1.67, 95% CI: 1.28–2.17, P<0.001) were significant factors affecting practice about the rational use of antimicrobials. (Tables 2, 5).

Table 5 - Factors affecting the practice of the participants regarding the rational use of antimicrobials.
Practice Univariable logistic regression Multivariable regression model
Characteristics Poor Moderate to good OR 95% CI P AOR 95% CI P
Age (y) 0.037*
 <40 480 (53.3) 421 (46.7) 1 (Ref) 1 (Ref)
 ≥40 47 (42.7) 63 (57.3) 1.53 1.03–2.28 0.038 1.08 0.67–1.72 0.754
Sex 0.005*
 Male 141 (45.5) 169 (54.5) 1 (Ref) 1 (Ref)
 Female 386 (55.1) 315 (44.9) 0.68 0.52–0.89 0.005 0.76 0.60–1.01 0.062
Educational status <0.001*
 Up to college 39 (32.8) 80 (67.2) 1 (Ref) 1 (Ref)
 University degree 488 (54.7) 404 (45.3) 0.40 0.27–0.61 <0.001 0.59 0.37–0.94 0.028
Occupational status 0.612*
 Unemployed 389 (51.7) 364 (48.3) 1 (Ref)
 Employed 138 (53.5) 120 (46.5) 0.93 0.70–1.23 0.612
Areas of work 0.045*
 Health 205 (56.3) 159 (43.7) 0.77 0.59–0.99 0.046 0.83 0.63–1.09 0.173
 Other than health 322 (49.8) 325 (50.2) 1 (Ref) 1 (Ref)
Resident areas <0.001*
 Urban 476 (55.6) 380 (44.4) 1 (Ref) 1 (Ref)
 Rural 51 (32.9) 104 (67.1) 2.55 1.78–3.67 <0.001 2.06 1.42–3.01 <0.001
Current smoker <0.001*
 No 510 (54.1) 432 (45.9) 1 (Ref) 1 (Ref)
 Yes 17 (24.6) 52 (75.4) 3.61 2.06–6.34 <0.001 2.81 1.54–5.12 <0.001
Co-morbid status 0.089*
 No 440 (53.4) 384 (46.6) 1 (Ref) 1 (Ref)
 Yes 87 (46.5) 100 (53.5) 1.32 0.96–1.81 0.090 0.88 0.61–1.26 0.478
Monthly income <0.001*
 <50k 254 (45.9) 299 (54.1) 1 (Ref) 1 (Ref)
 ≥50k 273 (59.6) 185 (40.4) 0.58 0.45–0.74 <0.001 0.60 0.46–0.78 <0.001
Significance values are in bold.
*Chi-square tests.
AOR indicates adjusted odds ratio; OR, odds ratio; Ref, reference.

Distribution of knowledge, behavior, and practice scores based on the education level

Those participants with a college degree and above educational levels had higher median knowledge and behavior scores as compared with those with lower educational levels. However, there was no statistical difference across both groups in terms of knowledge, behavior, and practice scores (Fig. 2).

Figure 2:
Distribution of knowledge, behavior, and practice scores based on the education level. 1=Up to school; 2=college level and above.

Distribution of knowledge, behavior, and practice scores based on areas of work

There was no statistical difference across both groups (health professionals vs. others) in terms of knowledge, behavior, and practice scores (Fig. 3).

Figure 3:
Distribution of knowledge, behavior, and practice scores based on areas of work. 1=Health areas; 2=other than health areas.

Correlation between scores

There was a significant correlation between knowledge and behavior scores (Spearman rho= 0.332; P ≤0.001). Similarly, the knowledge and practice scores (Spearman rho=−0.527; P <0.001), and behavior and practice scores were negatively correlated (Spearman rho=−0.379; P≤0.001).


Overuse of antibiotics contributes to the development of AMR, which is a severe public health burden. It could result in the emergence of multidrug-resistant bacteria, meaning the bacteria develop resistance to multiple antibiotics and cause life-threatening infections23. Currently, AMR is a major setback in treating infectious diseases; therefore, evaluating parameters that cause the improper use of antibiotics is mandatory for antibiotic stewardship. This study evaluates antibiotic misuse by considering the knowledge, practice, and behavior of the Pakistani population and determining the causes of AMR.

Several factors, such as age, sex, educational status, occupational status, areas of work, residence, monthly income, and current smoking status, were considered predictors for knowledge, behavior, and practice of antibiotics. Most respondents demonstrated good knowledge (55.3%) and behavior (88.6%) towards antibiotics misuse, whereas almost half of the participants (47.9%) showed moderate to good practice. Even though most of the respondents were well educated, a better understanding of the rational use of antimicrobials could be expected from them, given their low practice scores. The unawareness and chances of malpractice were suspected from such findings24. The awareness could be accomplished through educational programs and public campaigns.

The present study found that people with higher education levels, health care profession, employed, no comorbid conditions, and those living in urban areas are associated with better knowledge. Whereas, people with an education level up to a college degree rather than a university degree, health care profession, and rural residence demonstrated good practice of antimicrobial use. However, none of the demographic factors were found significantly associated with good behavior. Such findings are comparable with the reports shown by previous studies in which those who were highly educated and those having health care-related occupations were likely to have better knowledge, more appropriate attitudes, and better practice of antibiotics usage25,26. In addition, people living in urban areas had more knowledge than those residing in rural areas, consistent with other studies. This can be explained by the fact that these people have better access and exposure to information, and health facilities27.

Our study revealed a positive correlation between adequate knowledge of antibiotics and an education degree at the university level and the involvement of participants in a health profession. Such findings are comparable with previously published data in Serbia, Italy, Hong Kong, and Sweden, where here they reported educational status and having a family member in a health-related job are the key determining factors for good knowledge of antimicrobials28–31.

We found that females are more likely to have good behavior regarding antibiotics use than males; comparable results were obtained from studies in Hong Kong and Nepal. Other factors that impacted the behavior were the smoking habit and the presence of comorbid conditions. We observed that nonsmokers and those without co-morbidities show good behaviors26,30.

Although not statistically significant, higher median knowledge and behavior scores were obtained in the respondents with college and above levels in terms of education. Adequate knowledge of respondents on antibiotics was positively correlated with behavior. This finding aligns with previous studies’ observations32–34. There was no statistically significant relationship between health and other professionals in knowledge, behavior, and practice. This explains that although health professionals gain some knowledge and information on antibiotics, it is inadequate. Efforts from educational and health care institutions should be made to enhance the knowledge of health care professionals and students on the prudent use of antibiotics and AMR.

Nonprescription use of antibiotics, self-medication, use of left-over antibiotics, incomplete course of the antibiotic regimen, etc., are some examples of misuse of antibiotics. Misuse of antibiotics is a big issue worldwide that needs to be addressed from the policy-making level and strictly implemented, reaching even towards the grass-root level. The health care personnel: physicians and pharmacists in interprofessional and intraprofessional coordination should ensure proper prescribing, counseling, and dispensing for the safe and effective drug therapy that optimizes the outcome of the therapy. Existing laws such as strict enforcement of the Drug Regulatory Authority of Pakistan (DRAP) Act 2012, Punjab Drug Rules 2007, and Pakistan’s National Action Plan (NAP) on AMR are mandatory and should be given high priority. Lack of awareness of the people is also highly responsible for the misuse of antibiotics, potentially leading to the emergence of AMR. Regular training, seminars, and mock drills should be arranged to address the problems regarding the misuse of antibiotics and AMR stewardship practices35. Similarly, conducting education and awareness campaigns through audio-visual media and face-to-face communication with the public is also a dire need for proper stewardship. Antibiotics should be prescribed and dispensed only when needed, and such practices must be according to the current guidelines. Patients and the public should have basic knowledge about the adverse effects of misuse of antibiotics so that they may ask health care professionals about major counseling points regarding adequate antibiotic use. If this issue is uncontrolled, the AMR can spread and threaten the health care community globally with the new and advanced types of infectious diseases difficult to treat with the existing antibiotics36,37.


Our study is not devoid of limitations. Due to the coronavirus disease (COVID-19) pandemic, we adopted convenience sampling methods and utilized the snowball method according to the possibility as well. Similarly, most of the data were collected online which were filled up mostly by educated persons with internet facility. The majority of the people representing the underprivileged population might have been missed. Therefore, selection bias might have occurred in this study.


Antibiotic misuse is a serious issue that leads to AMR which is an emerging global public health threat. Lack of execution of existing laws and unawareness of the public are responsible for the extravagant use of antimicrobials. This study demands strict enforcement of the Drug Regulatory Authority of Pakistan Act 2012, Punjab Drug Rules 2007, and Pakistan’s National Action Plan on AMR. Training and seminars from the policy-making level to the health care professionals on RUM are required. Similarly, education and awareness campaign to the public on the same topic through audio-visual media and face-to-face communication campaigns are also important for rationalization of therapeutic outcome that leads to a better health care system.

Ethical approval

The ethics approval was granted by the institutional review board (IRB), University of the Punjab, Lahore (Reg. No. D/255/FIMS). Informed consent to participate in the study was obtained from participants after giving an explanatory statement with the study objectives. All procedures performed in studies involving human participants were in accordance with the ethical standards of IRB of the University of the Punjab and with the Declaration of Helsinki, 1964 and its later amendments or comparable ethical standards.

Sources of funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author contribution

S.K.: conceptualization, resources, validation, investigation, and writing-reviewing and editing. F.K.H.: conceptualization, methodology, investigation, and reviewing and editing. G.K.Y., S.L., and S.G.: formal analysis, literature review, writing—reviewing and editing. F.T., S.A., and W.Z.: data curation, literature search, and writing—original draft preparation. K.A., I.A., K.Z., F.B., and N.U.-a.: data curation, literature search, and investigation. M.A.J.A.: conceptualization, visualization, and project administration.

Conflict of interest disclosures

The authors declare that they have no financial conflict of interest with regard to the content of this report.

Research registration unique identifying number (UIN)



Sitaram Khadka.


The authors are highly grateful to the participants who responded in this cross-sectional study.


1. Adedeji WA. The treasure called antibiotics. Ann Ib Postgrad Med 2016;14:56–7.
2. WHO. Antimicrobial resistance: implementing the global action plan in the Region. East Mediterr Heal J 2016;22:156-157.
3. WHO. Antimicrobial resistance. WHO. Accessed June 4, 2022. 2020. https://www.who.int/news-room/fact-sheets/detail/antimicrobial-resistance.
4. Ali M, Abbasi BH, Ahmad N, et al. Over-the-counter medicines in Pakistan: misuse and overuse. Lancet 2020;395:116.
5. Llor C, Bjerrum L. Antimicrobial resistance: risk associated with antibiotic overuse and initiatives to reduce the problem. Ther Adv drug Saf 2014;5:229–41.
6. Cosgrove SE, Carmeli Y. The impact of antimicrobial resistance on health and economic outcomes. Clin Infect Dis 2003;36:1433–7.
7. Alumran A, Hou X-Y, Sun J, et al. Assessing the construct validity and reliability of the Parental Perception on Antibiotics (PAPA) scales. BMC Public Health 2014;14:73.
8. Rather IA, Kim B-C, Bajpai VK, et al. Self-medication and antibiotic resistance: crisis, current challenges, and prevention. Saudi J Biol Sci 2017;24:808–12.
9. Saleem Z, Hassali M, Hashmi F, et al. Medical and pharmacy students’ knowledge, attitude and perception concerning antimicrobial use and resistance in Pakistan. Pharm Educ 2019;19:199–205.
10. Aslam B, Wang W, Arshad MI, et al. Antibiotic resistance: a rundown of a global crisis. Infect Drug Resist 2018;11:1645–58.
11. Malik B, Bhattacharyya S. Antibiotic drug-resistance as a complex system driven by socio-economic growth and antibiotic misuse. Sci Rep 2019;9:9788.
12. Andleeb S, Majid M, Sardar S Hashmi MZ. Environmental and public health effects of antibiotics and AMR/ARGs. Antibiotics and Antimicrobial Resistance Genes in the Environment Volume 1, Advances in Environmental Pollution Research series. Elsevier; 2020:269–91.
13. Woolhouse M, Ward M, van Bunnik B, et al. Antimicrobial resistance in humans, livestock and the wider environment. Philos Trans R Soc London Ser B, Biol Sci 2015;370:20140083.
14. Zaman S Bin, Hussain MA, Nye R, et al. A review on antibiotic resistance: alarm bells are ringing. Cureus 2017;9:e1403.
15. The World Bank Group. Data. Accessed June 4, 2022. 2021. https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups
16. Bilal H, Khan MN, Rehman T, et al. Antibiotic resistance in Pakistan: a systematic review of past decade. BMC Infect Dis 2021;21:244.
17. Naveed S, Qamar F, Maqsood A, et al. Prevalence and consequences of misuse of antibiotics, survey based study in Karachi. J Bioequiv Availab 2015;7:202.
18. Hashmi F, Khadka S, Khan S, et al. Antimicrobial dispensing sans legitimate prescription from community pharmacies in Lahore, Pakistan: implications for antimicrobial resistance. Res Sq 2021. https://www.researchsquare.com/article/rs-152711/v1
19. Ranji SR, Steinman MA, Shojania KG, et al. Interventions to reduce unnecessary antibiotic prescribing: a systematic review and quantitative analysis. Med Care 2008;46:847–62.
20. Vandenbroucke JP, von Elm E, Altman DG, et al. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration. Int J Surg 2014;12:1500–24.
21. The World Bank. World Bank Country and Lending Groups. The World Bank; 2022.
22. Seid MA, Hussen MS. Knowledge and attitude towards antimicrobial resistance among final year undergraduate paramedical students at University of Gondar, Ethiopia. BMC Infect Dis 2018;18:312.
23. Prestinaci F, Pezzotti P, Pantosti A. Antimicrobial resistance: a global multifaceted phenomenon. Pathog Glob Health 2015;109:309–18.
24. Rehman IU, Asad MM, Bukhsh A, et al. Knowledge and practice of pharmacists toward antimicrobial stewardship in Pakistan. Pharm (Basel, Switzerland) 2018;6.
25. Karuniawati H, Hassali MAA, Suryawati S, et al. Assessment of knowledge, attitude, and practice of antibiotic use among the population of boyolali, indonesia: a cross-sectional study. Int J Environ Res Public Health 2021;18
26. Nepal A, Hendrie D, Robinson S, et al. Knowledge, attitudes and practices relating to antibiotic use among community members of the Rupandehi District in Nepal. BMC Public Health 2019;19:1558.
27. Al-Shibani N, Hamed A, Labban N, et al. Knowledge, attitude and practice of antibiotic use and misuse among adults in Riyadh, Saudi Arabia. Saudi Med J 2017;38:1038–44.
28. Horvat OJ, Tomas AD, Paut Kusturica MM, et al. Is the level of knowledge a predictor of rational antibiotic use in Serbia? PLoS One 2017;12:e0180799.
29. Napolitano F, Izzo MT, Di Giuseppe G, et al. Public knowledge, attitudes, and experience regarding the use of antibiotics in Italy. PLoS One 2013;8:e84177.
30. You JHS, Yau B, Choi KC, et al. Public knowledge, attitudes and behaviour on antibiotic use: a telephone survey in Hong Kong. Infection 2008;36:153–7.
31. Vallin M, Polyzoi M, Marrone G, et al. Knowledge and attitudes towards antibiotic use and resistance—a latent class analysis of a Swedish population-based sample. PLoS One 2016;11:e0152160.
32. Lim KK, Teh CC. A cross sectional study of public knowledge and attitude towards antibiotics in Putrajaya, Malaysia. South Med Rev 2012;5:26–33.
33. Kim SS, Moon S, Kim EJ. Public knowledge and attitudes regarding antibiotic use in South Korea. J Korean Acad Nurs 2011;41:742–9.
34. Awad AI, Aboud EA. Knowledge, attitude and practice towards antibiotic use among the public in Kuwait. PLoS One 2015;10:e0117910.
35. Khadka S, Saleem M, Usman M, et al. Medical preparedness and response aspect: role of pharmacists in disaster management. Disaster Med Public Health Prep 2021;16:1–2.
36. Desai A, Gayathri G, Mehta D. Public’s perception, knowledge, attitude and behaviour on antibiotic resistance—a survey in Davangere city, India. J Prev Med Holist Heal 2016;2:17–23.
37. Dixit A, Kumar N, Kumar S, et al. Antimicrobial resistance: progress in the decade since emergence of New Delhi metallo-β-lactamase in India. Indian J community Med 2019;44:4–8.

Antibacterial agents; Pakistan; Drug resistance; Bacterial; Health status

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