Skip to main content

Non-prescribed antimicrobial use and associated factors among customers in drug retail outlet in Central Zone of Tigray, northern Ethiopia: a cross-sectional study

Abstract

Background

Non-prescribed antimicrobial use and their resistance are among the main public health problems, worldwide. In Ethiopia, particularly in the northern part, the magnitude of non-prescribed antimicrobial use and its major determinants is not yet well known. Thus, this study was done to assess the magnitude of non-prescribed anti-microbial use and associated factors among customers in drug retail outlet in Central Zone, Tigray, Ethiopia.

Methods

A drug retail outlet based cross-sectional study was conducted among adults aged 18 years and above. A multistage sampling procedure was used to select study participants. Data were collected using a structured questionnaire by druggists under the supervision of pharmacists. Data were entered into EpiInfo software version 3.5.4. Binary logistic regression was used to identify independently associated variables in bivariate and multivariable analyses using SPSS version 21. Odds Ratios with 95% confidence intervals were estimated.

Results

From 829 study samples, a total of 780 respondents participated in this study with a response rate of 94.1%. Of 367 respondents who received non-prescribed antimicrobial, 249 (67.8%), 121 (33%), and 94 (25.6%) of them were males, secondary school and paid employed respectively. The magnitude of non-prescribed antimicrobial use was 47.1% (95% CI: 43.8, 50.5). The factors which were independently associated with non-prescribed antimicrobial use were male sex [AOR = 1.72, 95% CI = 1.21, 2.44], seeking modern health care in private/Non-Governmental Organization (NGO) [AOR =0.47, 95% CI; 0.23, 0.98], moderate waiting time in health care facilities [AOR = 1.92, 95% CI; 1.20, 3.09], delayed waiting time in health care facilities [AOR = 1.56, 95% CI; 1.03, 2.38], ever received antimicrobial [AOR = 3.51, 95% CI; 2.45, 5.02], and frequency of purchasing non-prescribed antimicrobial (1–3 times and 4 times, [AOR = 2.04, 95% CI; 1.36, 3.06] and [AOR = 2.66, 95% CI; 1.24, 5.68] respectively).

Conclusion

The magnitude of non-prescribed antimicrobial use was high. Familiarizing with health care utilization and delayed waiting time in health care facilities were the very important factors independently associated with non-prescribed antimicrobial use. Emphasis should be given to community education through involvement of the private health sector and health care providers. Regulation and policy enforcement are also necessary to promote the rational use of antimicrobial.

Background

Non-prescribed antimicrobial use refers to the use of medicines to treat self-diagnosed disorders without consulting a medical practitioner and any medical supervision [1]. These medicines are essential in medical health care system, especially in the resource scarcity settings where infectious diseases are common causes of deaths [2]. Low coverage in availability and accessibility of the healthcare delivery systems due to inequitable health care distribution, high costs, lack of health care professionals, unregulated and unmonitoring distribution of medicines, patient attitudes towards physicians are some of the key drivers of misuse of anti-microbials in the resource scarce settings [3, 4].

Globally, non-prescribed antimicrobial drugs use even for non-bacterial diseases are the most commonly practiced or oversight by health-care professionals [5, 6]. The immediate consequences of non-prescribed antimicrobial drugs use include; short duration of treatment, inadequate dose, sharing of medicines, stopping treatment upon the improvement of disease symptoms [7]; adverse drug reactions and masking of underlying infectious processes [3, 5, 8].

As a result, antimicrobial-resistance is a major emerging global public health problem in communities with frequent non-prescribed antimicrobial use [5, 9, 10]. World Health Organization (WHO) in 2014 examined that anti-microbial resistance, in particular, antibacterial resistance has health and economic burden [10]. Nowadays, non-prescribed antimicrobial use is widely affected by improvement in people’s education, general knowledge and socio-economic status [1]. In Low and Middle Income Countries (LMICs), educational interventions, improving access to quality of public healthcare, and enforcement of regulations on non-prescribed medicine use could help mitigate the challenge of antimicrobial use and resistance [5, 11].

A study in developing countries has evidenced that the magnitude of non-prescribed antimicrobial use is high (38.8%) [11]. Other similar studies from various countries support this irrational use of medicine, in India (50%–66.7%) [12, 13], Saudi Arabia (48%–77.6%) [14, 15], Uganda (75.7%) [16], Zambia (97%) [17] and in Ethiopia ranges from (14.5% - 43.24%) [18,19,20].

Several studies evidenced that a number of risk factors for non-prescribed antimicrobial have been documented across the globe. Socio-demographic characteristics including; sex in Northern Uganda [16], Sudan [21], India [22] and Spain [23], age [21, 24,25,26,27], marital status [24, 25, 28], occupation [24, 29], income [21, 24], religion [24], residence [25], and educational status [21, 27, 30] have been documented as determinants of non-prescribed anti-microbial drugs use.

Chronic diseases [29], the severity of illness [11, 31,32,33,34] and repeated exposure to disease [35] were investigated as risk factors of non-prescribed anti-microbial use. Other important variables such as previous experience with antibiotics [36], waiting time in health facilities and distance of health care facility [37], knowledge-related factors (drug leaflets, awareness, adverse effect, previous exposure and past successful anti-microbial drug use) [11, 15, 16, 20, 31, 33] were identified as risk factors to non-prescribed anti-microbial drugs use. Abuse or misuse of antimicrobials causes considerable public health problems.

Almost all studies conducted in various countries and settings have focused on self-medication. Hence, measuring the magnitude of non-prescribed antimicrobial use (both self and caregiver medications) and its predictors could serve as points of intervention for the concerned bodies. Thus, this study was done to assess the magnitude of non-prescribed anti-microbial use and associated factors among customers in drug retail outlet in Central Zone, Tigray, Ethiopia.

Methods

Study design, setting and population

Drug retail outlet based cross-sectional study was conducted from October 1 to November 30/2016 among adults aged 18 years and above in the Central Zone of Tigray, Ethiopia. The Central Zone of Tigray covers area size of 9741 km2, and this Zone is administratively divided into nine districts and three major towns (Aksum, Adwa and Abyi Aadi). According to the 2007 population and housing census conducted by Central Statistical Agency of Ethiopia, the total population of Central Zone of Tigray was estimated to be 1,245,824. Of these 613,797 (49.3%) were males, 632,027 (50.7%) were females and 176,453 (14.2%) were urban inhabitants [38]. There are 1 zonal hospital, 1 referral hospital, 2 district hospitals, 57 health centers and around 53 drug retail outlets in the central zone. Adults aged 18 years and above living in Central Zone of Tigray were the source population of the study.

Sample size determination, sampling techniques and procedures

The sample size was computed using OpenEpi version 2.3 using the assumptions for a single population proportion formula; 43.24% prevalence of self-medication among health sciences students from a study by Gutema et al. in Mekelle University [18], 95% confidence interval, 5% margin of error, design effect of 2 and 10% non-response rate. The final computed sample size was 829. The study area was stratified into town and rural districts administrations (‘woredas’ in local administrative structure), and then two towns and three rural districts were selected by simple random sampling technique. Secondly, nine drug retail outlets from town and five drug retail outlets from rural district administrations were also selected using simple random sampling. The study employed proportional to sample size technique and finally, study participants were selected and recruited using consecutive sampling technique.

Customers who received antimicrobial drugs during the data collection period in the selected drug retail outlets were included in this study; whereas those who didn’t live in the study area for at least 6 months were excluded from the study.

Operational Definitions

Antimicrobial

The drugs are provided for the treatment of bacteria, parasites, viruses and fungi, including antibiotics, anti-parasitic, antifungal and anti-viral.

Non-prescribed antimicrobial use

Non-prescription-based inappropriate antimicrobial use for treatment of common infections without consulting a medical practitioner and any medical supervision.

Care giver medication practice

Non-prescription antimicrobial offers for other sick person to treat health problems of minors or other care seeking with perceived similar health problem.

Customers

Clients aged 18 years and above who received antimicrobial from private drug retail outlets.

Knowledgeable

When customers’ knowledge was above the computed mean of the ten dichotomized (yes/no) questions, otherwise not knowledgeable.

Drug retail outlet

A place used for the conduct of the drug sale, administering or dispensing and licensed by the responsible body as a place wherein the practice of pharmacy may lawfully occur.

Systemic infection

Pharmacy personnel diagnoses clinically the respondents’ self-reporting of symptoms of the whole body or disease for which antimicrobial medicines are used.

Systemic antibiotics

Are antimicrobials whose effects are manifested to the whole body.

Waiting time

The length of time from when the patient entered the outpatient clinic/department to the time the patient actually leaves the OPD (Fast = less than 1 h, Moderate = 1–2 h, and Delayed = more than 2 h).

Data collection tool and method

A pre-tested and structured questionnaire was employed. This tool was administered in Tigrigna (local language). The questionnaire included socio-demographic characteristics, disease, and medication, knowledge of antimicrobial drugs and its use and health care services. Interviewer- administered was used to collect the data. Fourteen druggists for data collection and three pharmacists for supervision were recruited and these were given two consecutive days training. Per the schedule, principal investigator had supervised and conducted certain meeting during the data collection period.

Data processing and analysis

Data were entered into EpiInfo version 3.5.4 and exported to SPSS version 21 software package. Coding and cleaning of data were performed for completeness and consistency. Descriptive statistics, frequencies with percentages were computed for categorical and median with Inter-Quartile Range (IQR) for non-normal continuous variables. In the present study, the outcome variable was non-prescribed antimicrobial use, which was dichotomized by assigning 1 for those who received the antimicrobial without prescription and 0 for those who received the antimicrobial with prescription during the data collection time. The binary logistic regression model was used to model the association between outcome and independent variables. Odds Ratio (OR) with 95% confidence interval (CI) was estimated to see the unadjusted (COR) and adjusted (AOR) effect of each factor on non-prescribed antimicrobial use. The candidate independent variables for multivariable analysis were selected at p-value of less than 0.20. The level of significance in multivariable analysis level was declared at P-value <0.05. The Hosmer and Lemeshow goodness-of-fit, and Omnibus tests of model coefficients were 0.35 and 0.00 respectively. The independent variables were tested for multicollinearity before entering them into the multivariable model, using the Variance Inflation Factor (VIF) test, the Tolerance test, and values of the standard error and acted accordingly.

Results

Socio-demographic characteristics

From 829 study sample, a total of 780 respondents participated in this study with a response rate of 94.1%. Out of 780 respondents, 367 (47.10%, 95% CI: 43.80, 50.50) had used non-prescribed antimicrobial during the study period. Nearly two-thirds (67.8%) of respondents who used non-prescribed antimicrobial were males. The median age of non-prescribed antimicrobial users was 30 years (IQR = 16). Out of these respondents who received non-prescribed antimicrobial, 149 (40.6%) were in the age group of 18 to 27 years. Out of these 367 non-prescribed antimicrobial users, 91.8, 79.8, 72.5 and 62.1% were Tigrians in ethnicity, Orthodox-Christians, urban and married, respectively. Pertaining to the educational and occupational status, 121 (33%) and 94 (25.6%) respondents who used non-prescribed antimicrobial were attended secondary school and paid employed, respectively. The median family size of non-prescribed antimicrobial users was 2 (IQR = 1). Nearly three-fifths, 218 (59.4%) of non-prescribed antimicrobial users had a monthly income of ≥32.51 US Dollar (Table 1).

Table 1 Socio-demographic characteristics of antimicrobial users in drug retailer outlets in Central Zone, Tigray, Ethiopia, 2016

Types of illnesses reported, non-prescribed antimicrobial use and its mechanism

Out of 367 non-prescribed antimicrobial users, 137 (37.3%) of respondents were given for respiratory system diseases. Three hundred thirty three (90.7%) of the respondents presented to the drug retail outlets with less than or equal to 1-month duration of illness. Two hundred thirty-seven (64.6%) of the non-prescribed antimicrobial were systemic antibiotics followed by 43 (11.7%) for ophthalmic/otic antibiotic. Regarding the mechanism of antimicrobial receiving, among these non-prescribed antimicrobial users, more than half (56.1%) of them got it by telling sign and symptoms of the illness or by providing of a written piece of paper without any signature (Table 2).

Table 2 Type of illness reported, anti-microbial drug received and its mechanism among customers in drug retailer outlets in Central Zone, Tigray, Ethiopia, 2016

Antimicrobial and health care service use

Of the 367 non-prescribed antimicrobial users, 326 (88.8%) respondents had visited health facilities for seeking health care in their life; of these, 53.7% received the service from public health facilities, and 175 (53.7%) of these respondents received the service from public health care facilities. Three hundred five (83.1%) of non-prescribed antimicrobial users reported that the respective public health care facilities were found within 5 km radius from their home. Regarding respondents perception of waiting time in health care facilities, 183 (49.9%) and 117 (31.9%) of them reported that they had been served with moderate and delayed waiting time, respectively. Concerning antimicrobial use practice, 280 (76.3%) and 221 (60.2%) of the current non-prescribed antimicrobial users had reported a history of exposure to antimicrobial and non-prescribed antimicrobial use in their life, respectively. One hundred sixty nine (46%) of non-prescribed antimicrobial users had received 1–3 times non-prescribed antimicrobial in the last 6 months. More than half, 152 (54.3%) of non-prescribed antimicrobial users were ever experiencing disease/symptoms in the last 6 months. Out of these 367 respondents who reported non-prescribed antimicrobial use, 230 (62.7%) of them received the drugs for self-medication (Tables 3 and 4).

Table 3 Health care services use among customers in drug retailer outlets in Central Zone, Tigray, Ethiopia, 2016
Table 4 Antimicrobial use among customers in drug retailer outlets in Central Zone, Tigray, Ethiopia, 2016

Knowledge on antimicrobial use

The magnitude of non-prescribed antimicrobial use was 47.1% (95% CI: 43.80, 50.50). Of the total respondents included in this study, 741 (95.0%) respondents knew that antimicrobial cannot be taken with alcohol. Similarly, 719 (92.1%) of respondents knew that placing of antimicrobial in a safe and unreachable area to children have benefits. More than three-fourth (79.9%) of respondents reported that drug resistance can occur when antimicrobial users do not complete the full course of treatment in the prescribed dose. Out of the total respondents, 697 (89.3%) of them knew that antimicrobial prescribed for adults should not be given to children, and 703 (90.1%) of them knew that all antimicrobial do not be given to pregnant and lactating mothers. Four hundred sixty four (59.5%) of respondents knew that the expiry date of the antimicrobial should be checked before using it. Based on the composite mean score of knowledge, 405 (51.9%) of the respondents were knowledgeable regarding to antimicrobial use (Table 5).

Table 5 Knowledge of antimicrobial among customers in drug retailer outlets in Central Zone, Tigray, Ethiopia, 2016

Factors associated with non-prescribed antimicrobial use

In the bivariate analysis, sex, age group, residence, marital status, monthly income, group of illnesses, place of seeking modern healthcare services, distance of health facility from home, self perceived of waiting time in health care facilities, ever received antimicrobial drug and frequency of non- prescribed antimicrobial drugs purchased in the past 6 months were associated with non-prescribed antimicrobial use.

The multivariable analysis being male, receiving health care services from private/NGO, moderate waiting time, delayed waiting time, ever received antimicrobial in life, 1–3 times and ≥4 times frequency of purchasing of antimicrobial in the last 6 months were independently associated factors with non-prescribed antimicrobial use.

Being male [AOR = 1.72, 95% CI = 1.21, 2.44] was about 1.72 times more likely to have non-prescribed antimicrobial use compared to their counterparts. Receiving health care services from private/NGO [AOR = 0.47, 95% CI; 0.23, 0.98] was about 53% less likely to use non-prescribed anti-microbial than those who received the services from public health facilities. Perceived waiting time in health care facilities was also associated with non-prescribed antimicrobial use; respondents who reported that moderate waiting time [AOR = 1.92, 95% CI; 1.20, 3.09] and delayed waiting time [AOR = 1.56, 95% CI; 1.03, 2.38] were almost two folds and 1.56 times, respectively more likely to use non-prescribed antimicrobial compared to those who reported fast waiting time in health care facilities.

Respondents who ever have received antimicrobial were nearly four times to have non-prescribed anti-microbial use compared to those who never received antimicrobial in life, [AOR = 3.51, 95% CI; 2.45, 5.02].

Regarding the frequency of purchasing non-prescribed antimicrobial in the past 6 months, those respondents who purchased 1–3 times [AOR = 2.04, 95% CI; 1.36, 3.06] and who purchased ≥4 times (AOR = 2.66, 95% CI; 1.24, 5.68) in the last 6 months were 2.04 and 2.66 times, respectively more likely to currently practice non-prescribed antimicrobial use than those who never have used non-prescribed antimicrobial at this period (Table 6).

Table 6 Bivariable and multivariable logistic regression analysis of factors associated with non-prescribed antimicrobial use among customers in drug retailer outlets in Central Zone, Tigray, Ethiopia, 2016

Discussion

This study has assessed the magnitude and factors associated with non-prescribed antimicrobial use. As a result, the magnitude of non-prescribed antimicrobial use was 47.1%, and the independently associated factors with non-prescribed antimicrobial use were being male, receiving health care services from private/NGO, moderate waiting time, delayed waiting time, ever received antimicrobial in life, 1–3 times and ≥4 times frequency of purchasing of antimicrobial in the last 6 months.

The magnitude of non-prescribed antimicrobial use reported by this study is in line with studies conducted in various countries across the world; in Ethiopia (43.24%), [18], in Yemen, Saudi Arabia, and Uzbekistan (48%) [15] and in Northern India (50%) [13]. However, it is higher than the findings reported from southwestern Ethiopia (39%) [20], South Ethiopia (14.5%) [19], in a systematic and meta-analysis study in low and middle income countries, the overall estimate of antimicrobial use is 38.8% [11] and Saudi Arabia (35.4%) [26]. The finding of this study is lower than findings documented in several studies; in northern Uganda (75.7%) [16], in Zambia (97%) [17], in Bangalore, India (66.7%) [12] and in Riyadh, Saudi Arabia (77.6%) [14]. The possible explanation could be due to these studies varying in the nature of definitions used; the present study used non-prescribed antimicrobial (both self and caregiver medication practices) whereas these studies included as comparison with the current finding applied only self-medication as outcome variable. Regarding to recall period considered for definition, in this study, respondents were interviewed whether received non-prescribed antimicrobial or not at time of data collection period. However, studies conducted in Riyadh, Saudi Arabia, respondents were asked about practicing of self-medication in the last 2 weeks and in Sudan, 1–2 months. Additionally, the observed discrepancy could be due to geographical variation of the region selected, methodology adopted and the characteristics of study populations.

In the present study male sex was 1.7 times more likely to practice non-prescribed antimicrobial use compared to their female counterparts. Similar findings have been evidenced in Northern Uganda [16], in Indonesia [39], in Urban Puducherry, India [22], in Yogyakarta City Indonesia [28], in Riyadh, Saudi Arabia [26], in Sudan [40]. This finding is contrary to other studies done in Sudan [21], in Spain [23] and South India [32]. This difference may be due to in the current study context, males have a better health seeking behavior compared to females.

In this study those respondents who previously received health care services from private clinic/NGOs were less likely to practice non-prescribed antimicrobial compared to those who received health care from public health facilities. This finding is in line with study conducted in Riyadh, Saudi Arabia [26]; reporting inconvenient access or dissatisfied with public health care were more likely to practice self-medication. The above finding might be also related with longer waiting time in health facilities effect on perception of respondents for consuting physicians for every health complaints. In this study, perceived moderate and delayed waiting time in health care facilities was documented as a risk factor for practicing of non-prescribed antimicrobial compared to perceived fast waiting time. Even though less literature available on the relationship between treatment-seeking behavior and self-medication or self-care in the populations of developing countries [41]. Studies in Tanzania and Sudan also revealed that reasons for self-medication were shortages of drugs, long waiting time, long distance at/to health facilities, inability to pay for health care charges and the freedom to choose the preferred drugs [33, 42, 43].

Respondents who ever have received antimicrobial before the study period were more likely to use non-prescribed antimicrobial currently than their counterparts. This is in line with the finding of similar study in University of Gondar, Ethiopia [31], in post-conflict Northern Uganda [16] and in a multi-center study in five cities of Pakistan revealed that prior or previous experience was a predictor of self-medication [41].

Moreover, pertaining to frequency of purchasing non-prescribed antimicrobials; those who purchased non-prescribed antimicrobials 1–3 times and greater or equal to four times in the past 6 months were statistically associated with non-prescribed anti-microbial use. Similar finding was documented in rural China that revealed purchasing antibiotics without physicians prescription has effect on behavior of self-medicating children with antibiotics [44].

This study has its own limitations as it did not consider attitude variable, and possible availability of social desirability bias might have a negative effect on the findings of the study.

Conclusion

The magnitude of non-prescribed antimicrobial use was high. Male sex, receiving health care services from private/NGO, waiting time in health care facilities, ever received antimicrobial, and frequency of purchasing non-prescribed anti-microbial was independently associated with non-prescribed antimicrobial use. Community education through the involvement of the private health sector and health care providers should be given an emphasis. Regulation and policy enforcement are necessary to promote the rational use of antimicrobial.

Abbreviations

AOR:

Adjusted Odds Ratio

CI:

Confidence Interval

COR:

Crude Odds Ratio

IQR:

Inter Quartile Range

LMICs:

Low and Middle Income Countries

NGOs:

Non-Governmental Organizations

WHO:

World Health Organization

References

  1. World Health Organization. Guidelines for the regulatory assessment of Medicinal Products for use in self-medication. 2000.

  2. Mathers C, Fat DM, Boerma JT. The global burden of disease: 2004 update: World Health Organization; 2008.

    Google Scholar 

  3. Esimone CO, Nworu CS, Udeogaranya OP. Utilization of antimicrobial agents with and without prescription by out-patients in selected pharmacies in South-eastern Nigeria. Pharm World Sci. 2007;29(6):655–60.

    Article  PubMed  Google Scholar 

  4. Yousef A-MM, Al-Bakri AG, Bustanji Y, Wazaify M. Self-medication patterns in Amman, Jordan . Pharm World Sci 2008;30(1):24-30.

  5. Morgan DJ, Okeke IN, Laxminarayan R, Perencevich EN, Weisenberg S. Non-prescription antimicrobial use worldwide: a systematic review. Lancet Infect Dis. 2011;11(9):692–701.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Tünger Ö, Dinç G, Özbakkaloglu B, Atman ÜC, Algün Ü. Evaluation of rational antibiotic use. Int J Antimicrob Agents. 2000;15(2):131–5.

    Article  PubMed  Google Scholar 

  7. Skliros E, Merkouris P, Papazafiropoulou A, Gikas A, Matzouranis G, Papafragos C, et al. Self-medication with antibiotics in rural population in Greece: a cross-sectional multicenter study. BMC Fam Pract. 2010;11(1):58.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Okeke IN, Klugman KP, Bhutta ZA, Duse AG, Jenkins P, O'Brien TF, et al. Antimicrobial resistance in developing countries. Part II: strategies for containment. Lancet Infect Dis. 2005;5(9):568–80.

    Article  PubMed  Google Scholar 

  9. Goossens H, Ferech M, Vander Stichele R, Elseviers M, Group EP. Outpatient antibiotic use in Europe and association with resistance: a cross-national database study. Lancet. 2005;365(9459):579–87.

    Article  PubMed  Google Scholar 

  10. World Health Organization. Antimicrobial resistance global report on surveillance: 2014 summary. 2014.

  11. Ocan M, Obuku EA, Bwanga F, Akena D, Richard S, Ogwal-Okeng J, et al. Household antimicrobial self-medication: a systematic review and meta-analysis of the burden, risk factors and outcomes in developing countries. BMC Public Health. 2015;15(1):1.

    Article  Google Scholar 

  12. Shet A, Sundaresan S, Forsberg BC. Pharmacy-based dispensing of antimicrobial agents without prescription in India: appropriateness and cost burden in the private sector. Antimicrob Resist Infect Control. 2015;4(1):55.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Ahmad A, Patel I, Mohanta G, Balkrishnan R. Evaluation of self medication practices in rural area of town Sahaswan at Northern India. Ann Med Health Sci Res. 2014;4(8):73–8.

    Article  Google Scholar 

  14. Abdulhak AAB, Al Tannir MA, Almansor MA, Almohaya MS, Onazi AS, Marei MA, et al. Non prescribed sale of antibiotics in Riyadh, Saudi Arabia: a cross sectional study. BMC Public Health 2011;11(1):1.

  15. Belkina T, Al Warafi A, Eltom EH, Tadjieva N, Kubena A, Vlcek J. Antibiotic use and knowledge in the community of Yemen, Saudi Arabia, and Uzbekistan. J Infect Dev Ctries. 2014;8(04):424–9.

    Article  PubMed  Google Scholar 

  16. Ocan M, Bwanga F, Bbosa GS, Bagenda D, Waako P, Ogwal-Okeng J, et al. Patterns and predictors of self-medication in northern Uganda. PLoS One. 2014;9(3):e92323.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Kalungia AC, Burger J, Godman B, Costa JO, Simuwelu C. Non-prescription sale and dispensing of antibiotics in community pharmacies in Zambia. Expert Rev Anti-Infect Ther. 2016;14(12):1215–23.

    Article  CAS  PubMed  Google Scholar 

  18. Gutema GB, Gadisa DA, Kidanemariam ZA, Berhe DF, Berhe AH, Hadera MG, et al. Self-medication practices among health sciences students: The case of Mekelle University. J Appl Pharm Sci. 2011;1(10):183.

    Google Scholar 

  19. Wabe NT, Ahmed D, Angamo MT. Self-medication with antibiotics and antimalarials in the community of Silte zone, South Ethiopia. TAF Prev Med Bull. 2012;11(5):529–36.

    Article  Google Scholar 

  20. Suleman S, Ketsela A, Mekonnen Z. Assessment of self-medication practices in Assendabo town, Jimma zone, southwestern Ethiopia. Res Soc Adm Pharm. 2009;5(1):76–81.

    Article  Google Scholar 

  21. Awad A, Eltayeb I, Matowe L, Thalib L. Self-medication with antibiotics and antimalarials in the community of Khartoum State, Sudan. J Pharm Pharm Sci. 2005;8(2):326–31.

    PubMed  Google Scholar 

  22. Selvaraj K, Kumar SG, Ramalingam A. Prevalence of self-medication practices and its associated factors in Urban Puducherry, India. Perspect Clin Res. 2014;5(1):32.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Figueiras A, Caamano F, Gestal-Otero JJ. Sociodemographic factors related to self-medication in Spain. Eur J Epidemiol. 2000;16(1):19–26.

    Article  CAS  PubMed  Google Scholar 

  24. Afolabi A. Self Medication, Drug Dependency and Self-Managed Health Care-A Review: INTECH Open Access Publisher; 2012.

    Google Scholar 

  25. Agbor M, Azodo C. Self medication for oral health problems in Cameroon. Int Dent J. 2011;61(4):204.

    Article  PubMed  Google Scholar 

  26. Alghanim S. Self-medication practice among patients in a public health care system/Pratique de l'automédication chez les patients bénéficiant d'un système de soins de santé public. East Mediterr Health J. 2011;17(5):409.

    CAS  PubMed  Google Scholar 

  27. Garofalo L, Di Giuseppe G, Angelillo IF. Self-medication practices among parents in Italy. Biomed Res Int. 2015;2015

  28. Widayati A, Suryawati S, de Crespigny C, Hiller JE. Self medication with antibiotics in Yogyakarta City Indonesia: a cross sectional population-based survey. BMC Res Notes. 2011;4(1):1.

    Article  Google Scholar 

  29. Berzanskyte A, Valinteliene R, Haaijer-Ruskamp F, Gurevicius R, Grigoryan L. Self-medication with antibiotics in Lithuania. Int J Occup Med Environ Health. 2006;19(4):246–53.

    Article  PubMed  Google Scholar 

  30. Sapkota AR, Coker ME, Goldstein RER, Atkinson NL, Sweet SJ, Sopeju PO, et al. Self-medication with antibiotics for the treatment of menstrual symptoms in southwest Nigeria: a cross-sectional study. BMC Public Health. 2010;10(1):1.

    Article  Google Scholar 

  31. Abay S, Amelo W. Assessment of Self-medication practices among medical, pharmacy, health science students in Gondar University, Ethiopia. J Young Pharm. 2010;2(3):306–10.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Balamurugan E, Ganesh K. Prevalence and pattern of self medication use in coastal regions of South India. Br J Med Pract. 2011;4(3):a428.

    Google Scholar 

  33. Eldalo AS, El-Hadiyah TM, Yousif M. Sudanese parents’ knowledge, attitudes and practice about self-medication to their children: Qualitative study. Saudi J Health Sci. 2013;2(2):103.

    Article  Google Scholar 

  34. Bekele SA, Argaw MD, Yalew AW. Magnitude and Factors Associated with Self-Medication Practices among University Students: The Case of Arsi University, College of Health Science, Asella, Ethiopia: Cross-Sectional Survey Based Study. Open Access Libr J. 2016;3(06):1.

    Google Scholar 

  35. Afzal S, Salman F, Hayat T, Sherwani UK, Siddiqui UA, Ishtiaq Q, et al. The Determinants of Self Medications. Annals of King Edward Medical University. 2013;19(1):73-74.

  36. Sawair FA, Baqain ZH, Abu Karaky A, Abu ER. Assessment of self-medication of antibiotics in a Jordanian population. Med Princ Pract. 2008;18(1):21–5.

    Article  PubMed  Google Scholar 

  37. Deressa W, Ali A, Enqusellassie F. Self-treatment of malaria in rural communities, Butajira, southern Ethiopia. Bull World Health Organ. 2003;81(4):261–8.

    PubMed  PubMed Central  Google Scholar 

  38. Population Census Commission. The 2007 Population and Housing Census of Ethiopia: Statistical Report for Tigray Region.

  39. Hadi U, Duerink DO, Lestari ES, Nagelkerke NJ, Werter S, Keuter M, et al. Survey of antibiotic use of individuals visiting public healthcare facilities in Indonesia. Int J Infect Dis. 2008;12(6):622–9.

    Article  PubMed  Google Scholar 

  40. Awad AI, Eltayeb IB. Self-medication practices with antibiotics and antimalarials among Sudanese undergraduate university students. Ann Pharmacother. 2007;41(7–8):1249–55.

    Article  PubMed  Google Scholar 

  41. Hussain S, Malik F, Ashfaq KM, Parveen G, Hameed A, Ahmad S, et al. Prevalence of self-medication and health-seeking behavior in a developing country. Afr J Pharm Pharmacol. 2011;5(7):972–8.

    Google Scholar 

  42. Manzi F, Schellenberg JA, Hutton G, Wyss K, Mbuya C, Shirima K, et al. Human resources for health care delivery in Tanzania: a multifaceted problem. Hum Resour Health. 2012;10(1):3.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Chipwaza B, Mugasa JP, Mayumana I, Amuri M, Makungu C, Gwakisa PS. Self-medication with anti-malarials is a common practice in rural communities of Kilosa district in Tanzania despite the reported decline of malaria. Malar J. 2014;13(1):252.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Yu M, Zhao G, Lundborg CS, Zhu Y, Zhao Q, Xu B. Knowledge, attitudes, and practices of parents in rural China on the use of antibiotics in children: a cross-sectional study. BMC Infect Dis. 2014;14(1):112.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgments

Aksum University is acknowledged for funding this research work. Our gratitude goes to supervisors, data collectors, respondents who participated on this study and Aksum, Adwa, Ahferom, Laylay Machew and Mereb-Leke woreda health offices.

Funding

Aksum University is funder of this study. The sponsor of the study had no role in study design, data collection, data analysis or interpretation, but did review this report prior to submission for publication. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication.

Availability of data and materials

All the data supporting the findings is contained within the manuscript, no additional data is needed.

Author information

Authors and Affiliations

Authors

Contributions

NHG: conception, design, analysis, manuscript preparation, BDW, YSG, KHM, NBW, MGW and HSB designed the study, analyzed the data, drafted the manuscript and critically reviewed the article. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Yosef Sibhatu Gebregiorgis.

Ethics declarations

Ethical clearance was approved by the Institutional Research Review Board of College of Health Sciences and Referral Hospital, Aksum University. Permission letter was also obtained from Tigray regional health bureau, then after, from Aksum, Adwa, Ahferom, Laylay Machew and Mereb-Leke woreda health offices. Moreover, all study participants were informed about the purpose of the study and written consent was obtained from each study participant before data collection. Confidentiality was kept by using a questionnaire identification number that was immediately detached and filed separately in a private manner.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

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

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gebrekirstos, N.H., Workneh, B.D., Gebregiorgis, Y.S. et al. Non-prescribed antimicrobial use and associated factors among customers in drug retail outlet in Central Zone of Tigray, northern Ethiopia: a cross-sectional study. Antimicrob Resist Infect Control 6, 70 (2017). https://0-doi-org.brum.beds.ac.uk/10.1186/s13756-017-0227-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://0-doi-org.brum.beds.ac.uk/10.1186/s13756-017-0227-7

Keywords