ze was found to be 167 cases. All consecutive MDR-TB patients who were put on second line anti-tubercular drugs for atleast one month, and attending ALERT hospital were selected for the study. Similarly 167 bacteriologically confirmed pulmonary TB patients were included as controls.

2.3. Sampling Procedure

All patients who are enrolled for treatment at ALERT hospital were informed of the study objectives and were recruited into the study upon leaving the consultation rooms during their treatment follow-up phase. The data collection continued by enrolling all patients consecutively till completion of the required sample size. Similarly the control bacteriologically confirmed TB patients were recruited consecutively into the study at time of diagnosis at the respective health centres.

The interviews educed information on the socio-demographic information of the participants including age, sex, marital status, education level and occupation, and other information like history of previous treatment, focusing on treatment adherence, reasons for non-adherence to treatment, and about current medical problem, duration between diagnosis and commencement of treatment, etc. The patients’ medical files were also reviewed and appropriate data such as participants’ case investigation and treatment related information was retrieved.

2.4. Data Analysis

The data captured in the questionnaires was grouped and examined for errors, then cleaned, and entered into RedCap version 8.03. Data was analysed using STATA version 11 statistical software. Descriptive statistics were computed to get summary values. Association between variables were determined using odds ratio and 95% CI. Multivariate analysis was run by selecting those variables that appeared to have a P-value of <0.05 in the bivariate analysis to control the confounding effect of different variables while assessing the effect of each variable on the likelihood of MDR-TB development. P-value of <0.05 was considered as statistical significance.

The potential associated factors that were analysed in the model include:

・ Sociodemographic factors: focusing on marital status, education and occupation;

・ Living conditions: this includes size of the family, average household monthly income, number of rooms, number of windows, having a members of household who had TB;

・ Life style: this includes mainly about smoking and alcohol consumption;

・ Medical history: this includes BCG vaccination, history of visiting hospital and history of hospital admission.

2.5. Ethical Considerations

The research proposal was subjected to screening for scientific and ethical integrity by Ethical review committee at School of Public Health, and institutional review board of the College of Health Sciences, Addis Ababa University. Further screening was done by institutional review board of ALERT/AHRI and management of ALERT hospital, as well as Addis Ababa health bureau. A support obtained from these organizations gave a green light to carry out the study. The management of each of the selected health facilities were given orientation to ensure their support and facilitation of the data collection process.

Permission and consent to participate in the study was obtained from every individual respondent and patient‘s disease status were kept confidential. Every selected respondent had been briefed by the research team regarding the purpose of the study, any potential harms or benefits of the study, and were given full assurance that, under no circumstances findings of the interview and other information will be disclosed to any unauthorized persons or the authority other than the researcher. This was followed by seeking written agreement of the participant by the use of consent form. Those willing to participate signed an informed consent form and were then interviewed using a short pre-tested questionnaire.

2.6. Time Frame

The duration of the study was more than a year, commencing in July 2016. The data was collected in the period from 04 January to 30 December 2017.

3. Results

3.1. Socio-Demographic Characteristics of the Participants

The socio-demographic characteristics of the MDR-TB patient population that participated in the survey are presented in Table 1. More than half (53.3%) of the participants were males while 46.7% females for both cases and controls. A little over half of cases (55.1%) were in the age group 26 - 45 years, whereas 46.7% of controls were in this age group.

Close to half (47.9%) of the cases have never been married among and 52.1% were married, while among controls the married (48.5%) were less than those never married (51.5%).

About two third of the cases (60.2%) and controls (62.4%) had attained at least secondary level of education, and, only a third (31.7%) of cases and 43.7% of controls reported to have formal employment or merchants or daily wage.

3.2. Living Conditions, Life Style, Medical History

The median family size for cases was 4 with a range from 1 to 13, and it was 3 for controls with a range from 1 to 10. Many (41.3%) of the cases live in households with average monthly income of up to 1000 Birrs, while majority (51.1%) of controls live in households with more than 2000 birrs, as seen in Table 2. Less than a third (29.9%) of cases live in single room house, 34.7% live in a house with two rooms and 35.3% in a house of three or more rooms. The median was

Table 1. Socio-demographic characteristics of the study participants, at ALERT Hospital, and selected health centres, 2017 (n = 334).

two rooms. Regarding the controls 37.7% live in single room house, 37.1% have two rooms and 25.1% in houses with more rooms. In terms of number of windows, just over half of cases (52.1%) and 59.9% of controls live in houses without any window or single window.

Almost fifth (18.0%) of the cases and 8.4% of controls had household members who had TB.

Some (9%) of the cases and 6.6% of controls smoke cigarettes, and just over a quarter (28.1%) of cases and 26.9% of controls reported alcohol consumption.

BCG vaccination was 46.7% for cases and 52.7% for controls as seen in Table 3. Majority (87.4%) of cases had history of visiting hospital during the 12 months before the diagnosis of current illness and 71.9% of controls had similar experience. More than half (55.7%) of cases reported history of hospital admission of different duration while only 7.2% of controls had history of admission.

3.3. Predictors of Developing MDR-TB

The bivariate analysis revealed that, being unemployed, household size of more than 4 people, history of visiting hospital in past 12 months and history of admission to health facility were found to have a crude association with developing

Table 2. Living conditions, life style and some medical history of the study participants, at ALERT Hospital, and selected health centres, 2017 (n = 334).

*Size of family: Cases: Mean = 4.24, Median = 4, Range 1 - 13; Controls: Mean = 3.6, Median = 3, Range 1 - 10. **Number of rooms: Cases: Mean = 2.35, Median = 2; Controls; Mean = 2, Median = 2.

MDR-TB (Table 3).

The Overall Predictors of Developing MDR-TB

All variables which had shown statistically significant association during the

Table 3. Bivariate analysis of study participants with MDR-TB, at ALERT Hospital, and selected health centres, 2017: cases = 167, Controls = 167.

Notes: *Variables that showed significant association during bivariate analysis at P < 0.05, COR. Abbreviations: MDR-TB, multidrug-resistant tuberculosis; TB, tuberculosis; COR, crude odds ratio; CI, confidence interval.

bivariate analysis, such as being unemployed, family size, having member of household member with TB, history of visiting hospital in past 12 months and history of admission to health facility were collectively entered in the multivariable logistic regression analysis. Accordingly, previous history of hospital admission was the only variable identified as an independent predictor for the occurrence of MDR-TB, after controlling possible confounders. Previous history of hospital admission was found to increase likelihood to develop MDR-TB by almost 20 times (AOR = 19.5; 95% CI: 9.17 - 41.62) and P-value of 0.00 (Table 4).

3.4. Medical Condition of the MDR-TB Patients

Additional information was gathered from the MDR-TB patients about history of previous TB treatment and current medical condition, and the findings are seen in Table 5 and Table 6 respectively.

Almost two third (59.3%) reported history of TB treatment while 40.7% had never been treated. Among those treated, majority (80.8%) were treated three or more times, 15.2% twice and 4.0% only once. Regarding the history of treatment adherence during the first time they were treated for TB, majority (74.7%) of the

Table 4. Multivariate analysis for the risk factors of multidrug-resistant tuberculosis at ALERT Hospital, 2017: cases = 167, controls = 167.

Notes: *Variables that showed significant association during bivariate analysis at P < 0.05, COR. Abbreviations: MDR-TB, multidrug-resistant tuberculosis; TB, tuberculosis; COR, crude odds ratio; AOR, adjusted odds ratio, CI, confidence interval.

Table 5. History of previous TB treatment among the MDR-TB study participants, at ALERT Hospital (n = 167).

participants reported that they took their medication regularly without interruption, while 23.2% confessed had they sometimes had interrupted treatment and 2.1% didn’t take the drugs most of the time. Majority (90.9%) of the patients had their previous treatment at government facilities and 9.1% in private health facilities. The most frequently perceived reasons for non-adherence according to the participants were developing drug side-effects (32%), improvement of symptoms and felt no need for completing treatment (28%), treatment facility was very far from residence (16%), health workers were not friendly (8%) and other reasons (16%).

Regarding current medical condition, Majority (56.3%) of the MDR-TB patients were smear positive TB cases, 43.1% smear negative and only one patient had extra-pulmonary TB. Majority (85.6%) knew their HIV status, of whom 23.8% were reactive. Cough was the major symptom and it lasted up to one month (48.3%), 2 - 3 months (25.5%) and for more than three months (25.8%). The mean duration between date of confirmation of diagnosis of MDR-TB and commencement of treatment was 61 days, with range from 16 to 251 days. After put on second line anti-TB treatment, 65.3% had developed adverse drug reaction, and great majority (82.6%) had it more than 3 times. In terms of severity,

Table 6. Current medical problem of the study Participants, at ALERT Hospital, 2017 (n = 167).

NB. *Duration between date of confirmation of diagnosis and date of commencement of treatment: Mean = 61, range 16 - 251.

41.2% had moderate, 32.1% minor and 26.6% severe.

According to the body mass index, which was calculated based on the weight and height measured at the time of diagnosis, 51.45% of the participants were normal and 44.93% were underweight.

4. Discussion

There is a high burden of multidrug-resistant Tuberculosis in many countries which may be attributed to its demographic and socio-economic profile like poverty, lack of knowledge, attitude and practice, overcrowding, malnutrition, care during illness and lack of social security. Adequate information on risk factors for MDR-TB, such as epidemiological factors is essential in formulating a national policy and to redirect health resources in order to control the transmission of MDR-TB as well as ensure better patient management. As no single factor can be attributable for emergence of MDR-TB, and study regarding its risk factor is scarce, this study has tried to explore different socio-demographic, life style and medical related factors.

Ethiopia is among the 30 high burden countries for TB, TB/HIV as well as drug resistant TB that collectively contribute about 85% - 89% of the global burden (11). The socio-demographic characteristics of the study participants indicated that 55.1% were in the 26 - 45 years age bracket, which is the most agile and economically active age group. This is similar to another study among MDR-TB patient in North Ethiopia, Gondar and Borumeda, which showed (54.9%) of the cases were within the age ranges of 26 - 45 years [16]. Whereas other study at St Peter hospital, Addis Ababa, showed that 29.9% were in the age bracket 26 - 45 [17]. This finding is consistent with other studies, which reported a rapid rise in TB morbidity and mortality among this young adult population mostly between 15 - 44 years of age [18]. High risk of infection in this age group relates to having a higher number of social contacts in the community during young adulthood [19].

Majority (87.4%) of MDR-TB cases had history of visiting hospital during the 12 months before the diagnosis of current illness while 71.9% of controls had similar experience. Although the bivariate analysis demonstrated statistically significant association between history of visiting health facility in past 12 months and development of MDR-TB, this was not confirmed by multivariate analysis. However another study demonstrated a strong association where visiting hospital was identified as important predictor of MDR-TB (AOR = 3.34, P = 0.044) [20].

More than half (55.7%) of cases reported history of hospital admission of different duration while only 7.2% of controls had such history. The multivariable logistic regression analysis demonstrated that, respondents who had previous history of hospital admission were almost twenty times more likely to develop MDR-TB compared to those who had no previous history of hospital admission (AOR = 19.5; 95% CI: 9.17 - 41.62) and P-value of <<0.05. Similar finding was reported in other studies where hospital admission increased risk of MDR-TB by more than threefold (AOR = 3.49, P = 0.005) [20] and more than fourfold (AOR: 4.4 95% CI: 2.2 - 7.8) [21]. The findings were also in line with other studies in other countries (AOR: 3.8 and 2.08) [22] [23]. This has important implication that hospital-acquired infection of MDR-TB strains is common, and it requires concerted effort to cut the chain of transmission.

Almost two-third (59.3%) of MDR-TB patients had history of TB treatment, among them significant majority (96%) were treated twice or more times. Most (90.9%) of the treatment happened at government facilities. Other studies reported very high percentage of patients with previous history of TB treatment, 91.1% [19], 75.65% [16] and 100% [17]. In all of these cases, over three quarters of the patients were treated at least twice. A quarter (25%) of the MDR-TB patients had history of irregular treatment during the previous treatment. Similar history of treatment irregularity was also reported by other study 14.4% in rural setting [16], in urban area 16.7% [20], and in some studies even higher rate of 60.5% [17]. Case-control studies observed that respondents who had previous history of treatment for TB were 21 times more likely to develop MDR-TB compared to those who had no previous history of TB treatment (AOR = 21; 95% CI: 17.80% - 28.80%) [24], (AOR = 5.47; 95% CI 3.87% - 7.74%) [25]. TB therapy requires more than 90% adherence to facilitate cure [26], hence individuals who do not take anti-TB medication regularly have increased risk for MDR-TB created by inadequate or improper administration of drugs. Because of the length of treatment required for TB, as patients start to feel better, they stop taking their medication. The TB bacteria not fully eradicated from the body so the bacteria builds resistance to the first-line drugs that the patient has already taken. When the patients fall ill again, their TB strain will not respond to first line drugs.

Based on a meta-analysis of 16 studies in Ethiopia, the pooled prevalence of MDR-TB among newly diagnosed and previously treated TB cases was 2% (95% CI 1% - 2%) and 15% (95% CI 12% - 17%), respectively, with odds ratio of 8.1 (95% CI 7.5% - 8.7%) [27]. Similarly, according to a nationwide anti-TB drug resistance survey conducted in 2005, 1.6% of newly diagnosed TB cases had MDR-TB, while 11.8% previously treated TB cases had the MDR-TB [28].

Unlike many other studies, the current study showed that 40.7% of participants did not have any history of TB. This could be due to high prevalence of primary MDR-TB which results from transmission of resistant TB bacilli. It entails further big scale research to understand the dynamics of the MDR-TB transmission at population level.

The study has its own limitation and generalizability of the findings should be cognizant of this. Some of the data elements could have been better verified through observation in a house visits and with additional detail, such as practice of how often the windows are opening, the volume of house, frequency of visit to health facilities, duration of hospital admission, etc. The study team has tried its best to minimize recall bias by allowing respondents sufficient time to provide most reliable information. The study could have benefited by expanding the list of potential risk factors, including the type of TB of the household member they had contact with, information related to access barriers, however gathering such level of detail require big scale research with appropriate design and resource. The study was conducted in urban setting where hospital are overcrowded, poorly designed old buildings, limited space, poor ventilation etc., and this compromises generalizability of the findings to other settings.

5. Conclusions

The study assessed the risk factors and characteristics of MDR-TB patients at hospital level in Addis Ababa, where sociodemographic factors, life style, living condition, previous medical history and current medical problem were the variables of the study.

Many of the study participants had history of contact with a household member who suffered from TB, and hence transmission among close contacts concerns. This shows the importance of contact tracing for early detection of cases, and ensures timely treatment and containing transmission. According to the multivariable logistic regression analysis, previous history of hospital admission was found to be independent predictors for the occurrence of MDR-TB.

Therefore it is imperative that infection control in health care facilities is an important intervention to prevent transmission of MDR-TB in order to protect visitors, patients as well as health care providers. This needs to be implemented across the health system.


This research was conducted under school of public health, college of health sciences at Addis Ababa University and it was funded by Armauer Hanson research Institute in Addis Ababa, Ethiopia.

The authors wish to thank the research participants for their cooperation and willingness to participate in the study. We thank the research team members for their hard work and amazing support throughout the process. We appreciate staff and management of ALERT hospital, MDR-TB ward, the twenty study health centers and Armaer Hanson Research Institute for their support in data collection and data management. The valuable contributions of professors at school of public health and experts at AHRI in overall assistance and technical support are highly acknowledged. We thank Addis Ababa health bureau and regional laboratory and research unit for their cooperation.

Ethics and Approval and Consent to Participate

The research proposal was subjected to screening for scientific and ethical integrity and approved by Ethical review committee at institutional review board of ALERT/AHRI with Project Reg. No. PO30/16.

Consent for Publication

Not applicable.

Availability of Data and Materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.


The research was fully funded by Armauer Hanson’s Research Institute, Addis Ababa, Ethiopia.

Author’s Contributions

ES conceived and designed the study, prepared protocol, coordinated data collection, conducted data analysis, and drafted manuscripts. FE, AA provided technical supported with the preparation of the proposal and the interpretation of data, advising on participated in data analysis, and critically reviewed the manuscript. MT, AM, GW supported preparation of protocol, coordinated field work, supported data analysis and interpretation. TH coordinated data entry and analysis.

All authors read and approved the final manuscript. All authors participated in critical appraisal and revision of the manuscript.

List of Acronyms

AHRI Armauer Hanson Research Institute

AOR Adjusted odds ratio

CI Confidence interval

COR Crude odds ratio

DOT Direct observation of treatment

EPTB Extra-pulmonary tuberculosis

FDC Fixed dose combinations

HIV Human immunodeficiency virus

MDR-TB Multi-drug-resistant tuberculosis

RR/MDR-TB Rifampicin resistant or Multi-drug-resistant tuberculosis

TB Tuberculosis

WHO World Health Organization

Cite this paper
Shimeles, E. , Enquselassie, F. , Tilahun, M. , Mekonnen, A. , Wondimagegn, G. , Hailu, T. and Aseffa, A. (2019) Risk Factors for Multidrug-Resistant Tuberculosis and Characteristics of Cases: A Case-Control Study of Patients Attending ALERT General Hospital in Addis Ababa, Ethiopia. Open Journal of Respiratory Diseases, 9, 1-17. doi: 10.4236/ojrd.2019.91001.
[1]   Maher, D. and Raviglione, M. (2005) Global Epidemiology of Tuberculosis. Clinics in Chest Medicine, 26, 167-182. https://doi.org/10.1016/j.ccm.2005.02.009

[2]   Raviglione, M.C., Snider, D. and Kochi, A. (1995) Global Epidemiology of Tuberculosis: Morbidity and Mortality of a Worldwide Epidemic. JAMA, 273, 220-226.

[3]   Dye, C., Watt, C.J., Bleed, D.M., Hosseini, S.M. and Raviglione, M.C. (2005) Evolution of Tuberculosis Control and Prospects for Reducing Tuberculosis Incidence, Prevalence and Deaths Globally. JAMA, 293, 2767-2775.

[4]   Schim van der Loeff, M.F., Sarge-Njie, R., Cessay, S., Awasana, A.A., Jaye, P., Sam, O., Jaiteh, K.O., Cubitt, D., Milligan, P. and Whittle, H.C.L. (2003) Regional Differences in HIV Trends in the Gambia: Results from Sentinel Surveillance among Pregnant Women. AIDS, 17, 1841-1846.

[5]   Zignol, M., Hosseini, M.S., Wright, A., Lambregts-van Weezenbeek, C., Nunn, P., Watt, C.J., Williams, B.G. and Dye, C. (2006) Global Incidence of Multi-Drug Resistant Tuberculosis. Journal of Infectious Diseases, 194, 479-485.

[6]   Chan, E.D., Laurel, V., Strand, M.J., Chan, J.F., Mai-Lan, N.H., Goble, M. and Iseman, M.D. (2004) Treatment and Outcome Analysis of 205 Patients with Multidrug-Resistant Tuberculosis. American Journal of Respiratory and Critical Care Medicine, 169, 1103-1109.

[7]   Faustini, A., Hall, A.J. and Perucci, C.A. (2005) Risk Factors for Multi-Drug Resistant Tuberculosis in Europe: A Systematic Review. Thorax, 61, 158-163.

[8]   World Health Organization (2008) Guidelines for the Programmatic Management of Drug-Resistant Tuberculosis. Emergency Update 2008. WHO/HTM/TB/2008.402.

[9]   World Health Organization (2016) WHO Treatment Guidelines for Drug-Resistant Tuberculosis 2016 Update. https://www.who.int/

[10]   Slama, K., Tachfouti, N., Obtel, M. and Nejjari, C. (2013) Factors Associated with Treatment Default by Tuberculosis Patients in Fez, Morocco. Eastern Mediterranean Health Journal, 19, 687-693. https://doi.org/10.26719/2013.19.8.687

[11]   WHO High TB Burden Country Lists 2016-2020.

[12]   Ministry of Health (2017) Annual Report of National Tuberculosis and Leprosy Control Program. Addis Ababa.

[13]   World Health Organization (2017) Global TB Tuberculosis Report.

[14]   World Health Organization (2016) Global Tuberculosis Report.

[15]   World Health Organization (2015) Global Tuberculosis Report.

[16]   Mulu, W., Mekonnen, D., Yimer, M., Admassu, A. and Abera, B. (2015) Risk Factors for Multidrug Resistant Tuberculosis Patients in Amhara National Regional State. African Health Sciences, 15, 368-377. https://doi.org/10.4314/ahs.v15i2.9

[17]   Hirpa, S., Medhin, G., Girma, B., Melese, M., Mekonen, A., Suarez, P. and Ameni, G. (2013) Determinants of Multidrug-Resistant Tuberculosis in Patients Who Underwent First-Line Treatment in Addis Ababa: A Case Control Study. BMC Public Health, 13, 782. https://doi.org/10.1186/1471-2458-13-782

[18]   Zignol, M., Dara, M., Dean, A.S., Falzon, D., et al. (2013) Drug-Resistant Tuberculosis in the WHO European Region: An Analysis of Surveillance Data. Drug Resistance Updates: Reviews and Commentaries in Antimicrobial and Anticancer Chemotherapy, 16, 108-115. https://doi.org/10.1016/j.drup.2014.02.003

[19]   Middelkoop, K., Bekker, L.-G., Liang, H., et al. (2011) Force of Tuberculosis Infection among Adolescents in a High HIV and TB Prevalence Nity: A Cross-Sectional Observation Study. BMC Infectious Diseases, 11, 156.

[20]   Mesfin, E.A., Beyene, D., Tesfaye, A., Admasu, A., Addise, D., Amare, M., et al. (2018) Drugresistance Patterns of Mycobacterium Tuberculosis Strains and Associated Risk Factors among Multi Drug-Resistant Tuberculosis Suspected Patients from Ethiopia. PLoS ONE, 13, e0197737.

[21]   Assefa, D., Seyoum, B. and Oljira, L. (2017) Determinants of Multidrug-Resistant Tuberculosis in Addis Ababa, Ethiopia. Infection and Drug Resistance, 10, 209-213.

[22]   Weyer, K., Brand, J., Lancaster, J., Levin, J. and van der Walt, M. (2007) Determinants of Multidrug-Resistant Tuberculosis in South Africa: Results from a National Survey. South African Medical Journal, 97, 1120-1128.

[23]   Andrews, J.R., Shah, N.S., Weissman, D., Moll, A.P., Friedland, G. and Gandhi, N.R. (2010) Predictors of Multidrug- and Extensively Drug-Resistant Tuberculosis in a High HIV Prevalence Community. PLoS ONE, 5, 1-6.

[24]   Workicho, A., Kassahun, W. and Alemseged, F. (2017) Risk Factors for Multidrug-Resistant Tuberculosis among Tuberculosis Patients: A Case-Control Study. Infection and Drug Resistance, 10, 91-96. https://doi.org/10.2147/IDR.S126274

[25]   Balaji, V., Daley, P., Anand, A.A., et al. (2010) Risk Factors for MDR and XDR-TB in a Tertiary Referral Hospital in India. PLoS ONE, 5, e9527.

[26]   Awofeso, N. (2008) Anti-Tuberculosis Medication Side-Effects Constitute Major Factor for Poor Adherence to Tuberculosis Treatment. Bulletin of the World Health Organization, 86, 161-240. https://doi.org/10.2471/BLT.07.043802

[27]   Eshetie, S., Gizachew, M., Dagnew, M., Kumera, G., Woldie, H., Ambaw, F., Tessema, B. and Moges, F. (2017) Multidrug Resistant Tuberculosis in Ethiopian Settings and Its Association with Previous History of Anti-Tuberculosis Treatment: A Systematic Review and Meta-Analysis. BMC Infectious Diseases, 17, 219.

[28]   World Health Organization (2011) Report on Global Tuberculosis Control. Geneva.