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\begin{document}

\title{Risk factors associated with drug-resistant tuberculosis in Ethiopia: A
systematic review and meta-analysis}



\author[1]{Ayinalem Alemu}%
\author[2]{Zebenay Workneh Bitew}%
\author[1]{Getu Diriba}%
\author[3]{Balako Gumi}%
\affil[1]{Ethiopian Public Health Institute Addis Ababa Ethiopia}%
\affil[2]{St Paul's Hospital Millennium Medical College}%
\affil[3]{Aklilu Lemma Institute of Pathobiology Addis Ababa University Addis Ababa Ethiopia}%


\vspace{-1em}



  
  \date{May 22, 2024}


\begingroup
\let\center\flushleft
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\endgroup





\selectlanguage{english}
\begin{abstract}
The emergence of drug-resistant tuberculosis (DR-TB) is becoming a
challenge to the national TB control programs including Ethiopia.
Different risk factors are associated with the emergence of DR-TB.
Identifying these risk factors in a local setting is important to
strengthen the effort to prevent and control DR-TB. Thus, this study
aimed to assess the risk factors associated with drug-resistant TB in
Ethiopia. The Preferred Reporting Items for Systematic Reviews and
Meta-analysis checklist was followed to conduct this study. We
systematically searched the articles from electronic databases and gray
literature sources. We used the Joanna Briggs Institute Critical
Appraisal tools to assess the quality of studies. Data were analyzed
using STATA version 15. We estimated the pooled OR along with 95\%CI for
each risk factor. The heterogeneity of the studies was assessed using
the forest plot and I \textsuperscript{2} heterogeneity test. Besides,
we explored the presence of publication bias through visual inspection
of the funnel plot and Egger's regression test. After intense searching,
we found 2238 articles, and 27 eligible studies were included in the
final analysis. Based on the pooled analysis of the odds ratio,
unemployment (OR; 2.71, 95\% CI; 1.64, 3.78), having a history of the
previous TB (OR; 4.83, 95\% CI; 3.02, 6.64), having contact with a known
TB patient (OR; 1.72, 95\% CI; 1.05, 2.40), having contact with a known
MDR-TB patient (OR; 2.54, 95\% CI; 1.46, 3.63), and having pulmonary TB
(OR; 1.80, 95\% CI; 1.14, 2.45) were found to be the risk factors of
drug-resistant TB. While older age TB patients (OR; 0.77, 95\% CI; 0.60,
0.95) including age above 45 years OR; (0.76, 95\% CI; 0.55, 0.97), and
males (OR; 0.86, 95\% CI; 0.76, 0.97) were found to had lower risk of
DR-TB compared to their counterparts. A previous history of TB treatment
is a major risk factor for acquiring DR-TB in Ethiopia that might be due
to poor adherence during the first-line anti TB treatment. Besides,
having contact with a known TB patient, having contact with a known
MDR-TB patient, having pulmonary TB, and being unemployed were the risk
factors of DR-TB in Ethiopia. Thus, active screening of TB contacts for
DR-TB might help to detect DR-TB cases as early as possible and could
help to mitigate its further transmission across the community.%
\end{abstract}%



\sloppy


\textbf{Title page}

\textbf{Risk factors associated with drug-resistant tuberculosis in
Ethiopia: A systematic review and meta-analysis}

Ayinalem Alemu*\textsuperscript{1,2}, Zebenay Workneh
Bitew\textsuperscript{3}, Getu Diriba\textsuperscript{1}, and Balako
Gumi\textsuperscript{2}

\textsuperscript{1}Ethiopian Public Health Institute, Addis Ababa,
Ethiopia.

\textsuperscript{2}Aklilu Lemma Institute of Pathobiology, Addis Ababa
University, Addis Ababa, Ethiopia.

\textsuperscript{3}St Paul's Hospital Millennium Medical College, Addis
Ababa, Ethiopia

*ayinalemal@gmail.com, ayinalem.alemu@aau.edu.et

\textbf{Abstract}

The emergence of drug-resistant tuberculosis (DR-TB) is becoming a
challenge to the national TB control programs including Ethiopia.
Different risk factors are associated with the emergence of DR-TB.
Identifying these risk factors in a local setting is important to
strengthen the effort to prevent and control DR-TB. Thus, this study
aimed to assess the risk factors associated with drug-resistant TB in
Ethiopia. The Preferred Reporting Items for Systematic Reviews and
Meta-analysis checklist was followed to conduct this study. We
systematically searched the articles from electronic databases and gray
literature sources. We used the Joanna Briggs Institute Critical
Appraisal tools to assess the quality of studies. Data were analyzed
using STATA version 15. We estimated the pooled OR along with 95\%CI for
each risk factor. The heterogeneity of the studies was assessed using
the forest plot and I\textsuperscript{2} heterogeneity test. Besides, we
explored the presence of publication bias through visual inspection of
the funnel plot and Egger's regression test. After intense searching, we
found 2238 articles, and 27 eligible studies were included in the final
analysis. Based on the pooled analysis of the odds ratio, unemployment
(OR; 2.71, 95\% CI; 1.64, 3.78), having a history of the previous TB
(OR; 4.83, 95\% CI; 3.02, 6.64), having contact with a known TB patient
(OR; 1.72, 95\% CI; 1.05, 2.40), having contact with a known MDR-TB
patient (OR; 2.54, 95\% CI; 1.46, 3.63), and having pulmonary TB (OR;
1.80, 95\% CI; 1.14, 2.45) were found to be the risk factors of
drug-resistant TB. While older age TB patients (OR; 0.77, 95\% CI; 0.60,
0.95) including age above 45 years OR; (0.76, 95\% CI; 0.55, 0.97), and
males (OR; 0.86, 95\% CI; 0.76, 0.97) were found to had lower risk of
DR-TB compared to their counterparts. A previous history of TB treatment
is a major risk factor for acquiring DR-TB in Ethiopia that might be due
to poor adherence during the first-line anti TB treatment. Besides,
having contact with a known TB patient, having contact with a known
MDR-TB patient, having pulmonary TB, and being unemployed were the risk
factors of DR-TB in Ethiopia. Thus, active screening of TB contacts for
DR-TB might help to detect DR-TB cases as early as possible and could
help to mitigate its further transmission across the community.

\textbf{Keywords:} Risk factors, Determinants, Drug-resistant
tuberculosis, Ethiopia

\textbf{INTRODUCTION}

National tuberculosis (TB) control programs are challenged by the
emergence of drug-resistance to more anti-TB drugs resulting in
multi-drug resistant tuberculosis (MDR-TB), pre-extensively
drug-resistant TB (pre-XDR-TB), and extensively drug-resistant TB
(XDR-TB). Globally, about 465, 000 population have rifampicin-resistant
TB (RR/TB) (78\% MDR-TB), were about 3.5\% among new cases and 18\%
among previously treated cases developed RR/MDR-TB. In addition, about
9\% of RR/MDR-TB patients develop XDR-TB (WHO, 2020). The problem is
also worse high burden countries including Ethiopia. In Ethiopia, based
on the 2019 global TB report there were about 1600 RR/MDR-TB estimated
cases where only 741 were laboratory confirmed, and 747 enrolled in
treatment (WHO, 2019). In the country, about 12\% among previously
treated and 0.71\% among the new TB cases are estimated to have
RR/MDR-TB (WHO, 2020).

The poor treatment adherence during anti-TB treatment such that not
taking TB drugs regularly or not taking the full dose of TB drugs result
in the emergence of DR-TB. During anti-TB treatment, if there is a poor
treatment adherence there is a selective pressure where the drug only
kills the drug-susceptible \emph{Mycobacterial} strain is leaving the
resistant ones that could cause a DR-TB onwards (Petrini et al., 1999).
The other major mechanism of acquiring DR-TB is through the transmission
of drug-resistant \emph{Mycobacterial} strains among the community.
Someone who had contact with a person with DR-TB becomes easily got the
disease (WHO, 2012). However, the transmission of DR-TB among the
community can be favored by different factors such as demographic,
behavioral, clinical, and environmental factors (Li et al., 2015). These
risk factors vary from setting to setting and from community to
community. Therefore, assessing the major associated risk factors
contributing to the emergence of DR-TB based on data-driven from the
local setting is important to take appropriate action. Even though there
are individual studies that assessed the risk factors of DR-TB in
different settings in Ethiopia, their finding is inconclusive and there
is limited information that addressed the risk factors of DR-TB at the
national level. However, identifying these factors at the national level
would be an important input to aid the national TB control program in
preventing and controlling the emergence of DR-TB in the country. Thus,
this study aimed to assess the risk factors associated with DR-TB in
Ethiopia by performing a pooled estimate from individual studies.

\textbf{METHODS}

\textbf{Search strategy}

The study was conducted by following the Preferred Reporting Items for
Systematic Reviews and Meta-analysis (PRISMA) checklist designed for
systematic review and meta-analysis studies (Hutton et al., 2015;
Knobloch et al., 2011) \textbf{(Additional file 1).} A systematic
article searching was conducted using an electronic database (PubMed).
The search was also performed using the gray literature sources such
that WorldCat, Google Scholar and Google. The search was conducted
regardless of the publication year. The searching was conducted up to 20
August 2021. Predictors, determinates, risk factors, drug-resistant,
multi-drug resistant, rifampicin-resistant, extensively drug-resistant,
tuberculosis, and Ethiopia were the keywords used during the searching
process. The Boolean operators AND and OR were used accordingly. The
search string of the PubMed was (((((((determinants) OR (Predictors)) OR
(``Risk Factors'' {[}Mesh{]})) AND (``Drug Resistance'' {[}Mesh{]} OR
``Tuberculosis, Multidrug-Resistant'' {[}Mesh{]})) OR (rifampicin
resistant)) AND (``Tuberculosis'' {[}Mesh{]})) OR (TB) AND (``Ethiopia''
{[}Mesh{]}) \textbf{(Additional file 2).} Two authors (AA, GD) who have
previous experience in conducting a systematic review and meta-analysis
studies performed the article searching independently under the guidance
of a senior librarian at the Ethiopian Public Health Institute. The
inconsistencies that arose between two authors were resolved by the
third author (ZWB).

\textbf{Study selection procedure}

In the current study, original studies that assessed the risk
factors/determinates/predictors of drug-resistant TB at different
settings of Ethiopia that are published in the English language were
included. Drug-resistant TB in the current study includes either
resistance to any of the anti-TB drugs or rifampicin-resistant TB or
MDR-TB. While articles that did not reported the risk factors in mixed
TB patients both drug-suceptible and drug-resistant TB, incomplete
outcomes, commentaris, and without full--text were excluded from the
present study. After conducting intense article searching in the
available databases and gray literature sources, article screening was
conducted through different stages. Primarily the duplicates were
removed using the Endnote 8 citation manager. In the second stage, we
assessed the articles by title and abstract, and in the third stage,
those articles that passed screening by title and abstract were assessed
for full-text review. Finally, the eligibility of the individual studies
to be included in the final analysis was performed by two independent
authors (AA, GD), and the inconsistencies were resolved by the third
author (ZWB) through discussion \textbf{(Figure 1).} The PICOS criteria
(participants, interventions, comparison, outcome, and study setting)
were used to assess the eligibility of the individual studies.

\textbf{PICOS criteria}

Participants: Tuberculosis patients

Interventions: Drug-\emph{resistant tuberculosis}

Comparators: drug-susceptible tuberculosis

Outcomes: Risk factors of drug-resistant tuberculosis

Study type: Cross-sectional and case-control studies.

Study setting: Any setting in Ethiopia

\textbf{Data extraction}

Independent data extraction was performed by two authors (AA, ZWB), and
the inconsistencies were resolved by the third author (GD). The
extracted data includes; study characteristics (author, publication
year, study area per regional state, study setting, data collection
period), study age-group, the type of drug-resistant-TB (any
drug-resistant TB, RR-TB, MDR-TB), the sample size (cases, controls),
and different risk factors of DR-TB using the odds ratio along with the
95\% CI. We summarized the extracted data using Microsoft Excel 2016

\textbf{(Table 1).}

\textbf{Quality assessment}

We assessed the quality of studies using the Joanna Briggs Institute
Critical Appraisal (JBI) tools designed for cross-sectional and
case-control studies (Moola et al., 2020). The critical appraisal
checklist for the cross-sectional and case-control studies contains
eight and ten questions respectively. Each question was scored out of
100\% and finally, the sum of all questions was turned into 100\%. The
quality score was graded as low if \textless{} 60\%, medium if 60--80\%
and high if \textgreater{} 80\% (Porritt et al., 2014; Munn et al.,
2019). Two authors (AA, GD) independently assessed the quality of the
studies and the third author (ZWB) resolved the inconsistencies through
discussion \textbf{(Additional file 3)} .

\textbf{Outcomes}

The primary outcome of this systematic review and meta-analysis study
was drug-resistant TB. Whereas, the risk factors associated with DR-TB
were the secondary outcomes. The pooled odds ratio along with their 95\%
CIs were estimated to assess the risk factors associated with DR-TB in
Ethiopia.

\textbf{Data analysis}

Data that were summarized in Microsoft Excel 16 spreadsheet were
exported to STATA version 15 for statistical analysis. The pooled OR
with 95\%CI of each risk factor was estimated by assuming the true
effect size varies between studies. We presented the pooled results
using a forest plot. We used the forest plot and I
\textsuperscript{2}heterogeneity test to assess the heterogeneity among
the studies\textbf{.} The~\emph{I} \textsuperscript{2}~values of 25\%,
50\%, and 75\% were interpreted as the presence of the low, medium, and
high heterogeneity, \textbf{respectively (Sterne and Egger, 2001; Riley
et al., 2011). In this study, we used a random-effects model for all
risk factors to perform the analysis by considering substantial
variability among the studies (Riley et al., 2011). We explored the}
presence of publication bias through visual inspection of the funnel
plot and statistical significance of Egger's regression test.

\textbf{RESULTS}

\textbf{Study characteristics}

After the systematic article searching in the available databases and
other literature sources, we identified 2238 articles. After removing
244 duplicates, 1994 articles were screened by title and abstract. Then,
full-text screening was conducted for 43 articles. Finally, after the
full-text screening, 27 eligible articles were included in the study
(Abay et al., 2020; Abdella et al., 2015; Adane et al., 2015; Alene et
al., 2019; Arega et al., 2019; Assefa et al., 2017; Babure et al., 2019;
Bedewi et al., 2017; Biru et al., 2020; Deressa et al., 2014; Desissa et
al., 2018; Dessalegn et al., 2016; Fikre et al., 2019; Gobena et al.,
2018; Hamusse et al., 2016; Hirpaet al., 2013; Jaleta et al., 2017;
Mehari et al., 2019; Mekonnen et al., 2015; Mesfin etal., 2018; Mulisa
et al., 2015; Mulu et al., 2015; Seyoum et al., 2014; Tadesse et al.,
2015; Tesfay et al., 2016; Tsega et al., 2017; Welekidan et al., 2020).
We presented the detail using the PRISMA flow diagram \textbf{(Figure
1).} The studies were conducted in different administrative regions
across the country with the most frequent studies were from Addis Ababa
(7 studies) followed by the Amhara region (6 studies), the Oromia region
(5 studies), and the Tigray region (4 studies). However, the studies
were reported from the majority of the regional administrative states.
The studies were based on data collected from TB patients in health care
facilities. The study period for these studies ranges from 2008 (Tadesse
et al., 2015) to 2019 (Welekidan et al., 2020). Based on the study
designs, 15 studies were cross-sectional studies while the remaining 12
studies used a case-control study design. The majority of the studies
included all the age group categories while three studies and two
studies included TB patients above 15 and 18 years of age respectively.
The studies assessed the risk factors/determinates of either MDR-TB (18
studies), RR-TB (3 studies), or any type of drug resistance (6 studies).
The sample size of individual studies ranges from 65 in a study
conducted by Babure et al. (2019) to 1876 in a study done by Arega et
al. (2019) \textbf{(Table 1).}

\textbf{Risk factors of drug-resistant tuberculosis}

In the current study, we extracted data to assess the risk factors of
drug-resistant TB in the Ethiopian setting. The risk factors include;
socio-demographic characteristics (age, sex, marital status, residence,
occupation, and family size), behavioral characteristics (smoking
status, alcohol consumption, and khat chewing), and clinical
characteristics (HIV serostatus, DM co-occurrence, contact history,
imprisonment, previous TB treatment, number of TB episodes, and site of
TB infection). We performed a pooled analysis for each variable using a
random effect model by considering substantial variability among the
individual studies. Based on the pooled analysis of the odds ratio,
unemployment (OR; 2.71, 95\% CI; 1.64, 3.78, I\textsuperscript{2};
0.0\%) \textbf{(Figure 2)} , having a history of previous TB (OR; 4.83,
95\% CI; 3.02, 6.64, I\textsuperscript{2}; 69.6\%) \textbf{(Figure 3)} ,
having contact with a known TB patient (OR; 1.72, 95\% CI; 1.05, 2.40,
I\textsuperscript{2}; 73.8\%) \textbf{(Figure 4)} , having contact with
a known MDR-TB patient (OR; 2.54, 95\% CI; 1.46, 3.63,
I\textsuperscript{2}; 0.0\%) \textbf{(Figure 5)} , and having pulmonary
TB (OR; 1.80, 95\% CI; 1.14, 2.45, I\textsuperscript{2};
71.4\%)\textbf{(Figure 6)} were found to be the risk factors associated
with drug-resistant TB in Ethiopia. While, old age individuals (OR;
0.77, 95\% CI; 0.60, 0.95, I\textsuperscript{2}; 47.2\%) \textbf{(Figure
7)}including above 45 years of age (OR; 0.76, 95\% CI; 0.55, 0.97,
I\textsuperscript{2}; 47.6\%) \textbf{(Figure 8)} , and males (OR; 0.86,
95\% CI; 0.76, 0.97, I\textsuperscript{2}; 19.0\%) \textbf{(Figure
9)}had lower risk of DR-TB compared to their counterparts \textbf{(Table
2)} .

However, statistically significant association was not found for the
following variables; urban residence (OR; 0.86, 95\% CI; 0.58, 1.15,
I\textsuperscript{2}; 75.2\%), being single (OR; 1.12, 95\% CI; 0.84,
1.40, I\textsuperscript{2}; 46.0\%), being a house wife (OR; 0.86, 95\%
CI; 0.50, 1.21, I\textsuperscript{2}; 0.0\%), being a farmer (OR; 0.81,
95\% CI; 0.42, 1.19, I\textsuperscript{2}; 48.0\%), being a daily
laborer (OR; 0.97, 95\% CI; 0.16, 1.78, I\textsuperscript{2}; 33.4\%),
family size above three members (OR; 0.87, 95\% CI; 0.61, 1.14,
I\textsuperscript{2}; 0.0\%), alcohol consumption (OR; 0.96, 95\% CI;
0.53, 1.38, I\textsuperscript{2}; 70.01\%), khat chewing (OR; 1.01, 95\%
CI; 0.63, 1.38, I\textsuperscript{2}; 0.0\%), smoking (OR; 0.75, 95\%
CI; 0.34, 1.16, I\textsuperscript{2}; 58.3\%), imprisoned (OR; 1.00,
95\% CI; 0.43, 1.56, I\textsuperscript{2}; 0.0\%), being
\emph{HIV}positive (OR; 1.35, 95\% CI; 0.95, 1.74, I\textsuperscript{2};
73.6\%), having DM (OR; 0.85, 95\% CI; -0.85, 1.93,
I\textsuperscript{2}; 0.0\%), and having two or more number of TB
episodes (OR; 1.03, 95\% CI; -0.03, 2.99, I\textsuperscript{2}; 79.2\%)
\textbf{(Table 2) (Supplementary figure 1)} .

Accordingly, those individuals who were unemployed had 2.71 times the
odds to develop DR-TB compared to the employed ones. Likewise, those
individuals who had a history of previous TB had 4.83 times the odds to
develop DR-TB compared to new TB patients. Similarly, those who had a
contact history with a known TB patient had 1.72 times the odds to
develop DR-TB compared to their counterparts. Also, those who had a
contact history with a known MDR-TB patient had 2.54 times the odds to
develop DR-TB compared to individuals who didn't have a contact history
with a known MDR-TB patient. Besides, individuals with pulmonary TB
had1.80 times the odds to develop DR-TB compared with patients with
extrapulmonary TB. While the risk of DR-TB decreased by 23\% among older
age groups, i.e. individuals who were above 45 years had a 24\%
decreased risk of DR-TB compared to individuals below 45 years of age.
Likewise, the risk of DR-TB decreased by 14\% among males compared to
females \textbf{(Table 2)} .

\textbf{Publication bias assessment}

Based on the funnel plot and the Egger's regression test publication
bias was detected for older age (P\textless{}0.001), above 45 years age
(P\textless{}0.001), male sex (P=0.0047), being single (P=0.0036), being
farmer (P\textless{}0.0299), urban residence (P\textless{}0.001), HIV
seropositive (P\textless{}0.001), smoking (P\textless{}0.001), alcohol
consumption (P\textless{}0.001), previous TB history
(P\textless{}0.001), having two or more TB episodes (P\textless{}0.001),
and contact with known TB patient (P=0.001). While publication bias was
not detected for age above 40 years (P=0.0608), family size above three
members (P=0.7071), being a daily laborer (P=0.7341), being a house wife
(P=0.3798), unemployed (P=0.8805), imprisoned (P=0.3692), having contact
with known MDR-TB patient (P=0.3425), khat consumption (P=0.2586),
having DM (P=0.3082), and having pulmonary TB (P=0.0622)

\textbf{DISCUSSION}

In the current study, we explored in detail the risk factors associated
with drug-resistant TB in Ethiopia using 27 eligible articles. After
performing a pooled analysis for 18 variables extracted from individual
studies, we found that five variables such that unemployment, having a
history of previous TB, having contact with a known TB patient, having
contact with a known MDR-TB patient, and having pulmonary TB were the
risk factors associated with drug-resistant TB in Ethiopia. However,
older age and male individuals had a lower risk compared to their
counterparts.

The current study revealed that those individuals who were unemployed
had 2.71 times the odds to develop DR-TB compared to the employed ones.
It was also supported in a global pooled estimate performed by Pradipa
et al. (2018). The poor living condition of unemployed individuals that
leads them to pathological changes might be the possible cause
(Przybylski et al., 2014). The present study also revealed that previous
history of TB treatment is a major risk factor associated with DR-TB in
Ethiopia, such that those individuals who had a history of previous TB
treatment had 4.83 times the odds to develop DR-TB compared to their
counterparts. In line with this study, pooled estimates conducted at
different countries across the globe reported a statistically
significant association of previous TB treatment with DR-TB (Pradipta et
al., 2018; Lukoye et al., 2015; Jimma et al., 2017; Faustini et al.,
2006; Zhao et al., 2012). Studies reported that poor treatment adherence
during anti-TB treatment results in the subsequent emergence of drug
resistance (Zhao et al., 2012).

The other risk factor identified based on the pooled estimates in this
study was having contact with a known TB patient whether with an MDR-TB
patient specifically or with a TB patient as a general. Our study
revealed that those individuals who had a contact history with a known
TB patient had 1.72 times the odds to develop DR-TB compared to their
counterparts. The risk becomes higher among individuals who had contact
with an MDR-TB patient. Such that those who had a contact history with a
known MDR-TB patient had 2.54 times the odds to develop DR-TB compared
to individuals who did not have a contact history with a known MDR-TB
patient. Studies from Burkina Faso and Bangladesh also supported it
(Flora et al., 2013; Diande\selectlanguage{ngerman}´ et al., 2009). Screening contacts could
help to early detect DR-TB cases before disseminated across the
population. Besides, the present study revealed that the site of
infection was associated with DR-TB. Based on the pooled estimate in
this study, individuals with pulmonary TB had 1.80 times the odds to
develop DR-TB compared with individuals with extrapulmonary TB. A higher
risk of DR-TB among PTB cases was also reported from India in a study
based on a 13 years retrospective hospital-based analysis (Raveendran et
al., 2015). Another study also supported this (Peto et al., 2009).
Difficulties in detecting EPTB cases with lower bacterial loads might be
the reason. The mycobacterial strains circulating in the country might
be also a reason. For example, a study from China revealed that the
DR-TB is higher among extrapulmonary TB cases compared to pulmonary TB
cases due to the high prevalence of the Beijing strain (Pang et al.,
2019).

The present study also revealed that older individuals had a lower risk
to develop DR-TB. The pooled estimate revealed that individuals who were
above 45 years had a 24\% decreased risk of DR-TB compared to
individuals below 45 years of age. Such that those productive age groups
are at high risk of DR-TB in Ethiopia. Likewise, a pooled estimate in
Jimma et al's. (2017) study based on a systematic review and
meta-analysis conducted in Iran and its neighboring countries revealed
that individuals below 45 years of age had 1.57 times the odds to
develop MDR-TB compared with those individuals above 45 years old.
Higher pooled odds of MDR-TB among individuals below the age of 65 was
also reported from a systematic review performed in Europe (Faustini et
al., 2006). Besides, a study conducted at Northeastern China reported
that those individuals between 28-54 years of age had double odds of
MDR-TB when compared with those 65 years or older (Liu et al., 2013).
The treatment adherence in the productive age group and the working
style of these groups who have a higher contact chance to DR-TB patients
might also contribute. The findings of the present study revealed that
males had a lower risk of DR-TB compared to females. The risk of DR-TB
decreases by 14\% in males compared to females. Likewise, individual
studies also reported a higher risk of DR-TB among females (Lomtadze et
al., 2009; Shivekar et al., 2020). However, the reason behind it should
be explored in detail in future works. In the end, this study was based
on studies published in the English language that might affect the true
estimates. Besides, publication bias was confirmed by the Egger's
regression test for about half of the study variables that might bias
the true estimates.

In conclusion, a previous history of TB treatment is a major risk factor
for acquiring DR-TB in Ethiopia that might be due to poor adherence
during the first-line anti TB treatment. Besides, having contact with a
known TB patient, having contact with a known MDR-TB patient, having
pulmonary TB, and being unemployed were the risk factors of DR-TB in
Ethiopia. Thus, active screening of TB contacts for DR-TB might help to
detect DR-TB cases as early as possible and could help to decrease its
transmission across the population.

\textbf{Abbreviations}

DM: Diabetes Mellitus, DR-TB: Drug-Resistant Tuberculosis, EPTB:
Extrapulmonary Tuberculosis, HIV: Human Immunodeficiency Virus, MDR-TB:
Multi-Drug-Resistant Tuberculosis, OR: Odds Ratio, Pre-XDR-TB:
Pre-Extensively Drug-Resistant Tuberculosis, PRISMA: Preferred Reporting
Items for Systematic Reviews and Meta-analysis, PTB: Pulmonary
Tuberculosis, RR-TB: Rifampicin-Resistant Tuberculosis, TB:
Tuberculosis, XDR-TB: Extensively Drug-Resistant Tuberculosis

\textbf{Acknowledgment}

We acknowledge the authors of the primary studies. Our acknowledgment
also goes to the Ethiopian Public Health Institute for non-financial
supports including access to internet searching.

\textbf{Author contributions}

AA conceptualized, designed, and drafted the manuscript. AA, GD, and ZWB
performed article searching, data extraction, quality assessment, data
analysis and wrote the manuscript. BG reviewed the final manuscript. All
authors read, reviewed, and approved the final manuscript.

\textbf{Funding}

The authors did not receive a specific fund for this work.

\textbf{Availability of data and materials}

All relevant data are available from the corresponding author upon
request.

\textbf{Ethics approval and consent to participate}

Since it is based on published studies, it doesnot require ethical
approval.

\textbf{Consent for publication}

Not applicable.

\textbf{Competing interests}

The authors have declared that they do not have any competing interests.

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\textbf{Table 1:} Characteristics of individual studies on the
determinants of drug-resistant tuberculosis in Ethiopia, included in
this systematic review and meta-analysis.\selectlanguage{english}
\begin{longtable}[]{@{}lllllllll@{}}
\toprule
\textbf{Author, Year} & \textbf{Regional state covered} & \textbf{Study
setting} & \textbf{Study design} & \textbf{Study period} & \textbf{Study
age-group} & \textbf{Type of drug resistance TB} & \textbf{Cases} &
\textbf{Controls}\tabularnewline
\midrule
\endhead
Abay et al., 2020 & Tigray & Adigrat General Hospital & Cross-sectional
& January 2015, to December 2018 & All & RR-TB & 132 &
1314\tabularnewline
Abdella et al., 2015 & Southwest Ethiopia & Southwest Ethiopia &
Cross-sectional & March 2012 and April 2013 & All & Any drug resistance
& 41 & 29\tabularnewline
Adane et al., 2015 & Amhara & Debre Markos and Mota District hospitals &
Cross-sectional & May 2011 and January 2012 & All & Any drug resistance
& 18 & 71\tabularnewline
Alene et al., 2019 & Amhara & Gondar University Hospital & Case-control
& September 2010 to August 2015 & All & MDR & 242 & 210\tabularnewline
Arega et al., 2019 & Addis Ababa & Three referral hospitals and regional
laboratory & Cross-sectional & March 2015 to October 2017 & All & RR-TB
& 186 & 1690\tabularnewline
Assefa et al., 2017 & Addis Ababa & St Peter, and ALERT hospitals &
Case-control & April 1, 2013 to June 30, 2013 & All & MDR & 229 &
48`\tabularnewline
Babure et al., 2019 & Oromia & Nekemte Hosp & Case-control & September
1st 2016 to August 30th 2017 & All & MDR & 21 & 44\tabularnewline
Bedewi et al., 2017 & Central Ethiopia & Health facilities in Central
Ethiopia & Cross-sectional & October 2012 and September 2013 &
\textgreater{}18 years & Any drug resistance & 66 & 213\tabularnewline
Biru et al., 2020 & SNNP & Yirgalem and Butajira Hospitals &
Case-control & November 2016 to January 2017 & \textgreater{}15 years &
Any drug resistance & 84 & 243\tabularnewline
Deressa et al., 2014 & Addis Ababa & 10 health facilities & Case-control
& January to February 2013 & \textgreater{}18 years & MDR & 96 &
288\tabularnewline
Desissa et al., 2018 & Oromia & Bishoftu \& Adama Hospitals &
Case-control & February 1, 2016, to April 29, 2016 & All & MDR & 73 &
146\tabularnewline
Dessalegn et al., 2016 & Addis Ababa & St Peter Hosp & Case control & -
& All & MDR & 103 & 103\tabularnewline
Fikre et al., 2019 & SNNP & Six hospitals & Case-control & March 2016 to
March 2018 & All & MDR & 102 & 102\tabularnewline
Gobena et al., 2018 & Oromia & Shenen Gibe Hospital & Case-control &
August 2016 to April 2017 & All & MDR & 59 & 73\tabularnewline
Hamusse et al., 2016 & Oromia & Hitossa District of Arsi Zone &
Cross-sectional & 1 July 2013 and 30 June 2014 & [?]15 years & Any drug
resistance & 23 & 83\tabularnewline
Hirpa et al., 2013 & Addis Ababa & St. Peter Hospital and five health
centers & Case-control & 1 November 2011 to February 30, 2012 & All &
MDR & 134 & 134\tabularnewline
Jaleta et al., 2017 & Amhara & Gondar Hospital & Cross-sectional &
January 2013 to August 2015 & All & RR-TB & 71 & 377\tabularnewline
Mehari et al., 2018 & Tigray & Health facilities in all zones & Cross
sectional & 2015-2016 & All & MDR & 37 & 37\tabularnewline
Mekonnen et al., 2015 & Amhara & Metema \& west armachiho & Cross
sectional & February 01 and June 25, 2014 & All & MDR & 7 &
117\tabularnewline
Mesfin et al., 2018 & Addis Ababa & Different health facilities &
Cross-sectional & June 2015 to December 2016 & All & MDR & 89 &
137\tabularnewline
Mulisa et al., 2015 & Oromia & Different health facilities &
Case-control & October 1, 2013 to March 30, 2014 & \textgreater{}18
years & MDR & 88 & 177\tabularnewline
Mulu et al., 2015 & Amhara & Gondar University specialized and Borumeda
Hospital & Case-control & May 2013 to January 2014 & All & MDR & 153 &
153\tabularnewline
Seyoum et al., 2014 & Eastern Ethiopia & Five health facilities in Dire
Dawa, Harar, and Jigjiga & Cross-sectional & October 2011 and May 2013 &
All & Any drug resistance & 82 & 275\tabularnewline
Tadesse et al., 2015 & Addis Ababa & 26 public health centers &
Cross-sectional & 1 Jan 2008 to Dec 30, 2011 & All & MDR & 113 &
326\tabularnewline
Tesfay et al., 2016 & Tigray & Tigray regional TB Lboratory &
Cross-sectional & January 2013 and August 2014 & All & MDR & 143 &
119\tabularnewline
Tsega et al., 2017 & Amhara & Debre Markos Hosp & Cross-sectional &
September 1, 2015 to March 10, 2017 & All & MDR & 48 &
355\tabularnewline
Welekidan et al., 2020 & Tigray & Six hospitals in Tigray &
Cross-sectional & July 2018 and August 2019 & All & MDR & 38 &
189\tabularnewline
\bottomrule
\end{longtable}

\textbf{Table 2:} The summary of the pooled estimates of the OR per
associated risk factors of drug-resistant tuberculosis in Ethiopia.\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
Variable & Odds ratio & Odds ratio & Odds ratio & Odds
ratio\tabularnewline
\midrule
\endhead
& Number of studies & Estimate, 95\% CI & Heterogeneity &
Heterogeneity\tabularnewline
& & & I\textsuperscript{2} & P-value\tabularnewline
Older age & 23 & 0.77 (0.60, 0.95) & 47.2\% & 0.007\tabularnewline
Age \textgreater{} 40 years & 4 & 0.83 (0.54, 1.13) & 34.2\% &
0.207\tabularnewline
Age \textgreater{} 45 years & 19 & 0.76 (0.55, 0.97) & 47.6\% &
0.011\tabularnewline
Being male & 24 & 0.86 (0.76, 0.97) & 19.0\% & 0.202\tabularnewline
Urban residence & 17 & 0.86 (0.58, 1.15) & 75.2\% &
\textless{}0.001\tabularnewline
Single & 11 & 1.12 (0.84, 1.40) & 46.0\% & 0.047\tabularnewline
Being a house wife & 7 & 0.86 (0.50, 1.21) & 0.0\% &
\textless{}0.875\tabularnewline
Being a farmer & 8 & 0.81 (0.42, 1.19) & 48.0\% & 0.061\tabularnewline
Being a daily laborer & 4 & 0.97 (0.16, 1.78) & 33.4\% &
0.212\tabularnewline
Unemployed & 4 & 2.71 (1.64, 3.78) & 0.0\% & 0.556\tabularnewline
Family size \textgreater{} 3 members & 6 & 0.87 (0.61, 1.14) & 0.0\% &
0.760\tabularnewline
Alcohol consumption & 12 & 0.96 (0.53, 1.38) & 70.01\% &
\textless{}0.001\tabularnewline
Khat chewing & 6 & 1.01 (0.63, 1.38) & 0.0\% & 0.440\tabularnewline
Smoker & 11 & 0.75 (0.34, 1.16) & 58.3\% & 0.08\tabularnewline
Imprisonment & 8 & 1.00 (0.43, 1.56) & 0.0\% & 0.954\tabularnewline
Being HIV positive & 21 & 1.35 (0.95, 1.74) & 73.6\% &
\textless{}0.001\tabularnewline
Have DM & 4 & 0.85 (-0.22, 1.93) & 0.0\% & 0.838\tabularnewline
MDR-TB contact & 4 & 2.54 (1.46, 3,63) & 0.0\% & 0.621\tabularnewline
TB contact & 11 & 1.72 (1.05, 2.40) & 73.8\% &
\textless{}0.001\tabularnewline
History of previous TB treatment & 20 & 4.83 (3.02, 6.64) & 69.6\% &
\textless{}0.001\tabularnewline
History of two or more TB episodes & 7 & 1.03 (-0.03, 2.99) & 79.2\% &
\textless{}0.001\tabularnewline
Having pulmonary TB & 8 & 1.80 (1.14, 2.45) & 0.0\% &
0.487\tabularnewline
\bottomrule
\end{longtable}

\textbf{Hosted file}

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