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R E S E A R C H A R T I C L E Open Access
Prevalence of pneumonia and its
associated factors among under-five
children in East Africa: a systematic review
and meta-analysis
Biruk Beletew
*
, Melaku Bimerew, Ayelign Mengesha, Mesfin Wudu and Molla Azmeraw
Abstract
Background: Pneumonia is defined as an acute inflammation of the Lungs’parenchymal structure. It is a major
public health problem and the leading cause of morbidity and mortality in under-five children especially in
developing countries. In 2015, it was estimated that about 102 million cases of pneumonia occurred in under-five
children, of which 0.7 million were end up with death. Different primary studies in Eastern Africa showed the
burden of pneumonia. However, inconsistency among those studies was seen and no review has been conducted
to report the amalgamated magnitude and associated factors. Therefore, this review aimed to estimate the national
prevalence and associated factors of pneumonia in Eastern Africa
Methods: Using PRISMA guideline, we systematically reviewed and meta-analyzed studies that examined the
prevalence and associated factors of pneumonia from PubMed, Cochrane library, and Google Scholar.
Heterogeneity across the studies was evaluated using the Q and the I
2
test. A weighted inverse variance random-
effects model was applied to estimate the national prevalence and the effect size of associated factors. The
subgroup analysis was conducted by country, study design, and year of publication. A funnel plot and Egger’s
regression test were used to see publication bias. Sensitivity analysis was also done to identify the impact of
studies.
Result: A total of 34 studies with 87, 984 participants were used for analysis. The pooled prevalence of pneumonia
in East Africa was 34% (95% CI; 23.80–44.21). Use of wood as fuel source (AOR = 1.53; 95% CI:1.30–1.77; I
2
= 0.0%;P=
0.465), cook food in living room (AOR = 1.47;95% CI:1.16–1.79; I
2
= 0.0%;P= 0.58), caring of a child on mother during
cooking (AOR = 3.26; 95% CI:1.80–4.72; I
2
= 22.5%;P= 0.26), Being unvaccinated (AOR = 2.41; 95% CI:2.00–2.81; I
2
=
51.4%;P= 0.055), Child history of Acute Respiratory Tract Infection (ARTI) (AOR = 2.62; 95% CI:1.68–3.56; I
2
= 11.7%;
P= 0.337) were identified factors of pneumonia.
Conclusion: The prevalence of pneumonia in Eastern Africa remains high. This review will help policy-makers and
program officers to design pneumonia preventive interventions.
Keywords: Pneumonia, Eastern-Africa , Under five children, Indicator Cluster Surveys (MICS) Child Health/
Pneumonia.2017
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* Correspondence: birukkelemb@gmail.com
Department of Nursing, College of Health Sciences, Woldia University,
P.O.Box 400, Woldia, Ethiopia
Beletew et al. BMC Pediatrics (2020) 20:254
https://doi.org/10.1186/s12887-020-02083-z
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Background
Pneumonia is defined as an acute inflammation of the
Lungs’parenchymal structure. It can be classified based
on place of acquisition: as community acquired or hos-
pital acquired; based on its causative agents/ mechanism
as bacterial, viral, fungal, Aspiration, or ventilator-
associated pneumonia; based on the anatomy of the
lungs involved as lobar pneumonia, bronchial pneumo-
nia or acute interstitial pneumonia; and on the basis of
its clinical severity as “no pneumonia”,“pneumonia”or
“severe pneumonia”[1–3].
Under-five children are more vulnerable to pneumonia
and pneumonia remains the leading cause of morbidity
and mortality in those children [4]. According to a glo-
bal estimate made in 2000, approximately 156 million
cases of pneumonia had occurred each year in under-
five children, of which 151 million episodes were in the
developing countries and about 1.2 million of them were
end up in death. South-east Asia and Africa were the
two continents with high magnitude of childhood pneu-
monia, having an estimated of 61 million and 35 million
annual cases of pneumonia in under-five children re-
spectively [5]. The magnitude of under-five pneumonia
was decreased to 120 million (with 0.88 million deaths)
in 2010 and to 102 million (with 0.7 million deaths) in
2015 globally. These decrement was due to decrease in
the magnitude of its key risk factors, increasing socio-
economic development and preventive interventions, im-
proved access to care, and quality of care in hospitals.
Despite this progress, pneumonia is still a major public
health problem for children especially in developing
countries [4].
Globally, many researches had been conducted to
identify risk factors of pneumonia. Despite the inconsist-
ency of findings, low birth weight, malnutrition, indoor
air pollution, parental smoking, being unvaccinated,
overcrowding, lack of separate kitchen, being not on ex-
clusive breast feeding, and maternal education were
identified as factors associated with occurrence of pneu-
monia in under-five children [6–9].
Besides, in East African countries different researchers
had tried to investigate the magnitude of pneumonia in
under-five children and have reported a prevalence
ranges from 5.5% [10] up to 89.8% [11]. They had also
identified risk factors for pneumonia among under-five
children. But, reported finding lack consistency and as
per the investigators knowledge there is no a systematic
review and meta-analysis conducted to address these in-
consistent findings reported from East African countries.
Moreover, assessing the magnitude of pneumonia and
identifying its associated factors for risk based diagnosis
of pneumonia contribute in better interventions and
helps to reduce the higher burden of pneumonia in
under-five children. Hence, this systematic review and
meta-analysis was conducted to assess the magnitude of
pneumonia and its associated factors among under-five
children in East Africa.
Methods
Reporting
The results of this review were reported based on the Pre-
ferred Reporting Items for Systematic Review and Meta-
Analysis statement (PRISMA) guideline (Supplementary
file-PRISMA checklist) and, it is registered in the Prospero
database: (PROSPERO 2019: CRD42019136707) Available
from https://www.crd.york.ac.uk/PROSPERO/#mypros-
peroID = CRD42019136707.
Searching strategy and information sources
We identified studies providing data on the prevalence
of and potential risk factors of pneumonia among
under-five children, with the search focused on Eastern
Africa from PubMed, Cochrane library, and Google
Scholar. The search included MeSH terms and key-
words, combinations, and snowball searching in refer-
ences list of papers found through the data base search
to retrieve additional articles. Articles with incomplete
reported data were handled through contacting corre-
sponding authors. Unpublished studies were retrieved
from the official websites of international and local orga-
nizations and universities. The search was performed by
keywords, medical subject headings (MeSH) terms. We
used the search terms independently and/or in combin-
ation using “OR”or “AND”. The core search terms and
phrases were “under five”,“children”,“child”,“infant”,
and “pneumonia”,“respiratory infection”, causes, risk
factors, determinants, associated factors, predictors and
Eastern Africa. The search strategies were developed
using different Boolean operators. Remarkably, to fit ad-
vanced PubMed database, the following search strategy
was applied: (prevalence OR magnitude OR epidemi-
ology) AND (causes OR determinants OR associated fac-
tors OR predictors OR risk factors) AND (children
[MeSH Terms] OR under five OR child OR childhood)
AND (pneumonia [MeSH Terms] OR respiratory tract
infection) AND Eastern Africa. We also screened at the
reference lists of the remaining papers to identify add-
itional relevant studies to this review.
Study selection / eligibility criteria
Retrieved studies were exported to reference manager
software, Endnote version 8 to remove duplicate studies.
Two investigators (BB and AM) independently screened
the selected studies using their titles and abstracts before
retrieval of full-text papers. We used pre-specified inclu-
sion criteria to further screen the full-text articles.
Disagreements were discussed during a consensus meet-
ing with other reviewers (MW and MB) for the final
Beletew et al. BMC Pediatrics (2020) 20:254 Page 2 of 13
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
selection of studies to be included in the systematic re-
view and meta-analysis.
Inclusion and exclusion criteria
All observational studies (cross-sectional, case-control,
and cohort studies) were included. Those studies had re-
ported the prevalence and/or at least one associated fac-
tors of pneumonia among under-five children and
published in English language from 2000 up to 2019 in
Eastern Africa were considered. A consideration was ex-
tended to unpublished work among children under five
were also considered. Citations without abstract and/or
full-text, anonymous reports, editorials, and qualitative
studies were excluded from the analysis. Furthermore,
researches which did not report our results of interest
were excluded. Regarding inclusion and exclusion cri-
teria of included studies, children below 59 months of
age with mother / care giver visiting out patients depart-
ment during data collection period were included. Se-
verely sick child need life treating intervention and
whose mother / care givers refused were excluded from
the study.
Quality assessment
Duplicate articles were removed using Endnote (version
X8) after combining the Database search results. The
Joanna Briggs Institute (JBI) quality appraisal checklist
was used [12,13].Four independent authors appraised
the quality of the studies. The appraisal was repeated by
exchanging with each other. Thus, one paper was ap-
praised by two Authors. Any disagreement between the
reviewers was solved by taking the mean score of the
two reviewers. Studies were considered as low risk or
good quality when it scored 5 and above for all designs
(cross sectional, case control, and cohort) and were in-
cluded [12,13] whereas the score was 4 and below the
studies considered as high risk or poor quality and was
not included.
Data extraction
The authors developed data extraction form on the excel
sheet which includes author name, year of publication,
study country, study design, sample size, prevalence of
pneumonia, and categories of factors reported. The data
extraction sheet was piloted using 4 papers randomly.
The extraction form was adjusted after piloted the tem-
plate. Two of the authors extracted the data using the
extraction form in collaboration. The third and fourth
authors check the correctness of the data independently.
Any disagreements between reviewers were resolved
through discussions with a third reviewer and fourth re-
viewer if required. The mistyping of data was resolved
through crosschecking with the included papers. If we
got incomplete data, we excluded the study after two
attempts were made to contact the corresponding author
by email.
Outcome measurement
Pneumonia was considered when under five children
with cough and/or difficulty of breathing, have fast
breathing and/or chest indrawing and suggestive X-ray
findings [14,15].
Statistical analysis
After the data was extracted using Microsoft Excel for-
mat we imported the data to STATA version 14.0 statis-
tical software for further analysis. Using the binomial
distribution formula, Standard error was calculated for
each study. We pooled the overall magnitude estimates
of pneumonia by a random effect meta-analysis [16].
The pooled prevalence of pneumonia with 95% CI was
presented using forest plots and Odds ratio (OR) with
95% CI was also presented in forest plot to show the as-
sociated factors of pneumonia. We examined the hetero-
geneity between the studies using Cochrane’s Q statistics
(Chi-square), invers variance (I2) and p-values [17].
In this study, the I
2
statistic value of zero indicates
true homogeneity, whereas the value 25, 50, and 75%
represented low, moderate and high heterogeneity re-
spectively [18,19]. For the data identified as hetero-
geneous, we conducted our analysis by random-effects
model analysis. In addition subgroup analysis was
done by the study country, design, and year of publi-
cation. When statistical pooling is not possible, non-
pooled data was presented in table form. Sensitivity
analysis was employed to see the effect of a single
study on the overall estimation. Publication bias was
checked by funnel plot and more objectively through
Egger’s regression test [20].
Result
Study selection
A total of 6879 studies were identified using electronic
searches (through Databases searching (n= 6867)) and
other sources (n= 12)) that were conducted from 2000
up to 2019. After duplication removed, a total of 3150
articles remained (3729 duplicated). Finally, 200 studies
were screened for full-text review and, 34 articles with
(n= 87,984 patients) were selected for the prevalence
and/ or associated factors analysis (Fig.1).
Characteristics of included studies
Table 1summarizes the characteristics of the 34 in-
cluded studies in the systematic review and meta-
analysis [10,11,21–37,39–52]. 16 studies were found in
Ethiopia [10,22–36], 8 in Kenya [11,37,39–43], 2 in
Uganda [51,52],1 Eritrea [21], 1 in Somali [44],4 Sudan
[45–48],2 Tanzania [49,50].
Beletew et al. BMC Pediatrics (2020) 20:254 Page 3 of 13
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23 studies were cross-sectional, while the others used
either case-control (n= 9) or cohort (n= 2) study design.
Most of the studies 23/34(70.5%) were published be-
tween 2015 and 2019. The studies included participants,
ranging from 40 [45] to 73,778 [44] (Table 1).
Meta-analysis
Prevalence of pneumonia among fewer than five children in
Ethiopia
Most of the studies (n= 23) had reported the prevalence
of pneumonia [10,11,21–25,28,29,33–36,41–47,50–
52]. The prevalence of pneumonia were ranged from
5.5% [10] up to 89.8% [11]. The random-effects model
analysis from those studies revealed that, the pooled
prevalence of pneumonia in East Africa was found to be
34% (95%CI; 23.80–44.21; I
2
= 99.4%; p< 0.001) (Fig.2).
Subgroup analysis of the prevalence of pneumonia in
eastern Africa
The subgroup analysis was done through stratified by
country, study design, and year of publication. Based on
this, the prevalence of pneumonia among under five
children was found to be 29 in Eritrea, 22.62 in Ethiopia,
64.3 in Kenya, 29.71 in Sudan, 22 in Tanzania, and 32.72
in Uganda (Supplementary Fig. 1and Table 2). Based on
the study design, the prevalence of pneumonia was
found to be 32.33 in cross-sectional studies, 55.68% in
cohort studies and 22.6 in case control studies (Supple-
mentary Fig. 2and Table 2). Based on the year of publi-
cation, the prevalence of pneumonia was found to be
33.4 from 2000 to 2015, while it was 34.29 from studies
conducted from 2016 to 2019(Supplementary Fig. 3,
Table 2).
Sensitivity analysis
We employed a leave-one-out sensitivity analysis to
identify the potential source of heterogeneity in the
analysis of the prevalence of pneumonia in Eastern
Africa. The results of this sensitivity analysis showed
that our findings were not dependent on a single
study. Our pooled estimated prevalence of pneumonia
varied between 31.38(22.93–39.83) [11]and
35.3(25.13–45.49) [10] after deletion of a single study
(Supplementary Fig. 4).
Publication Bias
We have also checked publication bias and a funnel plot
showed symmetrical distribution. Egger’s regression test
p-value was 0.63, which indicated the absence of publi-
cation bias (Supplementary Fig. 5).
Factors associated with pneumonia
Out of the total included studies 18 studies [10,22–28,
30–35,37,39,40,43] revealed the factors associated
with pneumonia among under five children in Eastern
Africa (Table 3).
Use of wood as fuel source
Eight studies found significant association between use
of wood as fuel source and pneumonia among under five
Fig. 1 PRISMA flow diagram showed the results of the search and reasons for exclusion
Beletew et al. BMC Pediatrics (2020) 20:254 Page 4 of 13
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
children. Of these the highest risk factor, AOR = 7.41
(95% CI: 2.75, 19.95), Fekadu et al [25] and lowest risk
factor AOR = 1.15(0.47,1.88),Negash et al [22] compared
to those who use non wood items as a source of fuel
(Table 3). Regarding heterogeneity test, Galbraith plot
showed homogeneity and combining the result of eight
studies, the forest plot showed the overall estimate of
AOR of using wood as fuel source was 1.53(95%C I:
1.30, 1.77;I
2
= 0.0%;P= 0.465). I-Squared (I
2
) and P-value
also showed homogeneity (Supplementary Fig. 6).
Regarding publication bias, a funnel plot showed a
symmetrical distribution. During the Egger’s regression
test, the p-value was 0.176, which indicated the absence
of publication bias (Supplementary Fig. 7).
We employed a leave-one-out sensitivity analysis to
identify the potential source of heterogeneity in the ana-
lysis of the pooled estimate of using wood as fuel source
as a risk factor of pneumonia in Eastern Africa. The re-
sults of this sensitivity analysis showed that our findings
were not dependent on a single study. Our pooled esti-
mate of using wood as fuel source varied between
1.409(95% CI, 1.122–1.696) and 1.664 (95% CI, 1.321–
Table 1 Distribution of studies on the prevalence and determinants of pneumonia among under five children in East Africa, 2000–2019
Author/Reference Year Country Study design Sample size Prevalence (%) Quality score
Shah et al [21] 2012 Eritrea Cross-sectional 1502 29 5/8
Negash et al [22] 2019 Ethiopia Cohort 362 21.5 9/11
Abaye et al [23] 2019 Ethiopia Cross-sectional 477 18.4 6/8
Lema et al [24] 2019 Ethiopia Cross-sectional 344 17.7 7/8
Fekadu et al [25] 2014 Ethiopia Cross-sectional 286 16.1 7/8
Dadi et al [26] 2014 Ethiopia Case control 356 7/8
Geleta et al [27] 2016 Ethiopia case control 382 8/8
Shibre et al [10] 2015 Ethiopia Cross-sectional 458 5.5 6/8
Tegenu et al [28] 2018 Ethiopia Cross-sectional 306 28.1 5/8
Abuka et al [29] 2017 Ethiopia Cross-sectional 206 33.5 7/8
Workineh et al [30] 2017 Ethiopia Case control 558 7/10
Markos et al [31] 2019 Ethiopia Case control 435 7/10
Gedefaw et al [32] 2015 Ethiopia Case control 244 8/10
Tadesse et al [33] 2015 Ethiopia Cross-sectional 150 26.7 8/8
Adhanom et al [34] 2019 Ethiopia Cross-sectional 252 43.7 5/8
Lenda et al [35] 2018 Ethiopia Cross-sectional 458 17.6 8/8
Deribew et al [36] 2007 Ethiopia case control 168 22.6 9/10
MANYA et al [37] 2005 Kenya case control 188 7/10
Keter et al [38] 2015 Kenya Cross-sectional 422 67.1 6/8
Onyango et al [39] 2012 Kenya case control 206 7/10
Muthumbi et al [40] 2017 Kenya Cross-sectional 1483 7/8
Ndungu et al [41] 2018 Kenya Cross-sectional 323 74.3 6/8
Walekhwa et al [42] 2019 Kenya Cross-sectional 206 20.39 7/8
Sikolia et al [43] 2002 Kenya Cross-sectional 300 69.7 6/8
Ásbjörnsdóttir et al [11] 2012 Kenya Cohort 365 89.8 10/11
Kinyoki et al [44] 2017 Somalia Cross-sectional 73,778 17 6/8
Gritly et al [45] 2018 Sudan Cross-sectional 40 65 7/8
Salih et al [46] 2014 Sudan Cross-sectional 195 10.32 5/8
Gabbad et al [47] 2014 Sudan Cross-sectional 282 20.2 7/8
Deng et al [48] 2019 Sudan case control 108 8/10
Ndosa et al [49] 2015 Tanzania Cross-sectional 12.3 5/8
Lugangira et al [50] 2017 Tanzania Cross-sectional 1130 22 8/8
Lindstrand et al [51] 2018 Uganda Cross-sectional 1723 56 6/8
Tuhebwe et al [52] 2014 Uganda Cross-sectional 278 9.4 7/8
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2.008) after deletion of a single study (Supplementary
Fig. 8).
Cooking food in living room
Six studies found significant association between cook-
ing food at living room and pneumonia among under
five children. Of these the highest risk factors, AOR =
3.27(1.4, 7.9) Tegenu et al [28] and lowest risk factor
AOR = 1.35(0.3,0.99) Sikolia et al [43] compared to those
who cook food at kitchen (Table 3). Regarding hetero-
geneity test for cooking food at in living room, Galbraith
plot showed homogeneity and combining the result of
six studies the forest plot showed the overall estimate of
AOR of cooking food in living room was 1.47(95%CI:
1.16–1.79;I
2
= 0.0%;P= 0.58).I-Squared (I
2
) and P-value
also showed homogeneity (Supplementary Fig. 9). Re-
garding publication of bias for cooking food at home,
the funnel plot analysis showed asymmetrical distribu-
tion. During the Egger’s regression test, the p-value was
0.026, which indicated the presence of publication bias
(Supplementary Fig. 10). Trim and fill analysis was done,
and 3 study were added and the total number of studies
Fig. 2 Forest plot showing the pooled prevalence of pneumonia among under-five children in Eastern Africa from 2000 up to 2019
Table 2 Subgroup analysis of the prevalence of pneumonia in Eastern Africa by country, design and year of publication
Variables Characteristics Pooled prevalence (95% CI) I
2
(P-value)
By country Eritrea 29.00(26.71–31.29) –
Ethiopia 22.62(16.37–28.87) 96%(< 0.001)
Kenya 64.31(42.70–85.92) 99.1%(< 0.001)
Sudan 29.71(11.83–47.60) 96.1%(< 0.001)
Tanzania 22.00(19.58–24.42) –
Uganda 32.72(12.95–78.38) 99.8%(< 0.001)
By design Cross-sectional 32.33(23.22–41.44) 99.2% (< 0.001)
Cohort 55.68(−11.27–122.60) 99.8%(< 0.001)
Case control 22.60(16.28–28.92) –
By year of publication 2000–2015 33.40(11.54–55.25) 99.6% (< 0.001)
2016–2019 34.29(23.05–44.21) 99.2%(< 0.001)
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Table 3 Factors associated with pneumonia in East Africa
Variables Odds ratio(95%CI) Author (reference) Year Pooled AOR(95%CI) I
2
(P-value)
Use of wood as fuel source 1.15(0.47,1.88) Negash et al [22] 2019 1.53(1.30, 1.77) 0.0% (0.465)
2.1 (0.58,6.98) Lema et al [24] 2019
7.41 (2.75,19.95) Fekadu et al [25] 2014
1.49 (0.32,6.36) Shibre et al [10] 2015
3.41(1.5,7.7) Tegenu et al [28] 2018
2.92 (0.78,10.84) Abuka et al [29] 2017
1.78(0.28,1.09) Onyango et al [39] 2012
1.42(0.28,0.92) Sikolia et al [43] 2002
Cook food in living room 2.12(0.76, 5.92) Lema et al [24] 2019 1.47(1.16–1.79) 0.0% (0.58)
1.5(1.42, 5.4) Dadi et al [26] 2014
2.1(1.2, 3.7) Geleta et al [27] 2016
3.27(1.4,7.9) Tegenu et al [28] 2018
2.16(1.17,3.99 Lenda et al [35] 2018
1.35(0.3,0.99) Sikolia et al [43] 2002
Caring of a child on mother during cooking 11.76(4.6,30.08) Lema et al [24] 2019 3.26(1.80–4.72) 22.5% (0.26)
5.38(2.13,9.65) Fekadu et al [25] 2014
1.7(1.317,7.362) Dadi et al [26] 2014
2.55(1.33,6.5) Tegenu et al [28] 2018
1.37(0.24,7.83) Abuka et al [29] 2017
7.37(2.55,21.32) Tadesse et al [33] 2015
6.2(3.25,11.83) Lenda et al [35] 2018
Being unvaccinated 2.6(0.8, 8.1) Negash et al [22] 2019 2.41(2.00–2.81) 51.4% (0.055)
1.6(0.9,2.9) Geleta et al [27] 2016
4.62(2.64,11) Tegenu et al [28] 2018
1.68(0.16,2.42) Abuka et al [29] 2017
2.77(0.19,0.54) Workineh et al [30] 2017
2.67(0.15,0.92) MANYA et al [37] 2005
1.68(0.16,2.42) Onyango et al [39] 2012
Non-exclusive breast feeding 1.51(0.88,2.58) Negash et al [22] 2019 2.47(1.79, 3.16) 65.0% (0.01)
6(3.33,10.8) Abaye et al [23] 2019
2.49(0.05,3.7) Lema et al [24] 2019
2(1.58, 7.98) Dadi et al [26] 2014
3.3(2,5.4) Geleta et al [27] 2016
2.37(0.16,1.08) Shibre et al [10] 2015
3.3(1.27,8.3) Tegenu et al [28] 2018
4.2(1.07,16.6) Abuka et al [29] 2017
1.64(0.36,0.93) Workineh et al [30] 2017
6.10(2.5,14.93) Markos et al [31] 2019
8.33(2.6.3,10.50) Gedefaw et al [32] 2015
Child history of Acute Respiratory Tract infection (ARTI) 1.56(0.79,3.06) Negash AA et al [22] 2019 2.62 (1.68, 3.56) 11.7% (0.337)
1.36(0.26,7.21) Abaye et al [23] 2019
4.26(1.56,11.59) Lema et al [24] 2019
3.04(1.2,7.77) Dadi et al [26] 2014
5.2(3.1,8.9) Geleta et al [27] 2016
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become 9. The pooled estimate of AOR of preterm be-
comes 1.406 (Supplementary Fig. 11). We employed a
leave-one-out sensitivity analysis to identify the potential
source of heterogeneity in the analysis of the pooled esti-
mate of cooking food in living room as a risk factor of
pneumonia in Eastern Africa. The results of this sensitiv-
ity analysis showed that our findings were not dependent
on a single study. Our pooled estimate of cooking food
in living room varied between 1.428(95%CI, 1.102–
1.755) and 2.09(95%CI, 1.314–2.875) after deletion of a
single study (Supplementary Fig. 12).
Caring of the child on mothers during cooking
Seven studies found significant association between put-
ting a child at the back during cooking and pneumonia
among under five children. Of these the highest risk fac-
tors, AOR = 11.76(4.6, 30.08) Lema et al [24] and lowest
risk factor AOR = 1.37(0.24,7.83) Abuka et al [29] com-
pared to those who didn’t put their baby at their back
(Table 3). Regarding heterogeneity test, Galbraith plot
showed homogeneity and combining the result of seven
studies the forest plot showed the overall estimate of
AOR of pneumonia was 3.26(95%CI: 1.80–4.72;I
2
=
22.5%;P= 0.258).I-Squared (I
2
) and P-value also showed
homogeneity (Supplementary Fig. 13). Regarding test of
publication bias a funnel plot showed a symmetrical dis-
tribution. Egger’s regression test p-value was 0.074,
which indicated the presence of publication bias
(Supplementary Fig. 14). We employed a leave-one-out
sensitivity analysis to identify the potential source of het-
erogeneity in the analysis of the pooled estimate of put-
ting a child at the back during cooking as a risk factor of
pneumonia in Eastern Africa. The results of this sensitiv-
ity analysis showed that our findings were not dependent
on a single study. Our pooled estimate of putting a child
at the back during cooking varied between 2.87(95% CI,
1.329–4.426) and 3.59(95% CI, 1.828–5.355) after dele-
tion of a single study (Supplementary Fig. 16).
Being unvaccinated
Seven studies found significant association between be-
ing unvaccinated and pneumonia among under five chil-
dren. Of these the highest risk factors, AOR = 4.62(2.64,
11) Tegenu et al [28] and lowest risk factor AOR =
1.6(0.9,2.9) Geleta et al [27] compared to those who have
been vaccinated (Table 3). Regarding heterogeneity test,
Galbraith plot showed homogeneity and combining the
result of seven studies, the forest plot showed the overall
estimate of AOR of not being vaccinated was 2.41(95%C
I: 2.00–2.81;I
2
= 51.4%;P= 0.055).I-Squared (I
2
) and P-
value also showed homogeneity (Supplementary Fig. 17).
Regarding publication bias, a funnel plot showed a sym-
metrical distribution. During the Egger’s regression test,
the p-value was 0.177, which indicated the absence of
publication bias (Supplementary Fig. 18). We employed
a leave-one-out sensitivity analysis to identify the poten-
tial source of heterogeneity in the analysis of the pooled
estimate of being unvaccinated as a risk factor of pneu-
monia in Eastern Africa. The results of this sensitivity
analysis showed that our findings were not dependent
on a single study. Our pooled estimate of being unvac-
cinated varied between 2.4(95%CI, 2.07–2.72) and
2.71(95%CI, 2.55–2.86) after deletion of a single study
(Supplementary Fig. 19).
Non-exclusive breast feeding
Eleven studies found significant association between
non-exclusive breast feeding and pneumonia among
under five children. Of these the highest risk factors,
AOR = 8.33(2.6.3,10.50) Gedefaw et al [32] and lowest
risk factor AOR = 1.51(0.88,2.58) Negash et al [22] com-
pared to those who breast feed exclusively (Table 3). Re-
garding heterogeneity test, Galbraith plot showed
heterogeneity and combining the result of eleven studies,
the forest plot showed the overall estimate of AOR of
non-exclusive breast feeding was 2.47(95%C I: 1.79, 3.16;
I
2
= 65.0%;P= 0.01).I-Squared (I
2
)andP-value also
showed heterogeneity (Supplementary Fig. 20). Regard-
ing publication bias, a funnel plot showed an asymmet-
rical distribution. During the Egger’s regression test, the
p-value was 0.016, which indicated the presence of pub-
lication bias (Supplementary Fig. 21). Due to presence of
publication bias trim and fill analysis was done and 5
studies were added, and the total number of studies
becomes 16. The pooled estimate of AOR of non-
exclusive breast feeding was found to be 2.05
(Supplementary Fig. 22). We employed a leave-one-out
sensitivity analysis to identify the potential source of het-
erogeneity in the analysis of the pooled estimate of being
non-exclusive breast feeding as a risk factor of pneumo-
nia in Eastern Africa. The results of this sensitivity ana-
lysis showed that our findings were not dependent on a
Table 3 Factors associated with pneumonia in East Africa (Continued)
Variables Odds ratio(95%CI) Author (reference) Year Pooled AOR(95%CI) I
2
(P-value)
4.03(2, 8) Tegenu et al [28] 2018
2.75(1.3,5.81) Lenda et al [35] 2018
2.71(1.12,6.52) Onyango et al [39] 2012
17.13(5.01,60.26) Muthumbi et al [40] 2017
Beletew et al. BMC Pediatrics (2020) 20:254 Page 8 of 13
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
single study. Our pooled estimate of being for non-
exclusive breast feeding is found to be between
1.757(95%CI, 1.49–2.01) and 1.936(95%CI, 1.70–2.17)
after deletion of a single study (Supplementary Fig. 23).
History acuter respiratory tract infection (ARTI)
History ARTI was considered when a child has history
of ARTI with in the 2 weeks before being diagnosed for
pneumonia. Nine studies found significant association
between history ARTI and pneumonia among under five
children. Of these the highest risk factors, AOR =
17.13(5.01,60.26) Muthumbi et al [40] and lowest risk
factor AOR = 1.36(0.26,7.21) Abaye et al [23] compared
to those who use non wood item as a source of fuel
(Table 3). Regarding heterogeneity test, Galbraith plot
showed homogeneity and combining the result of nine
studies, the forest plot showed the overall estimate of
AOR of history ARTI was considered was 2.62(95%C I:
1.68, 3.56;I
2
= 11.7%;P= 0.337).I-Squared (I
2
) and P-value
also showed homogeneity (Supplementary Fig. 24). Re-
garding publication bias, a funnel plot showed an asym-
metrical distribution. During the Egger’s regression test,
the p-value was 0.024, which indicated the presence of
publication bias (Supplementary Fig. 25). Due to pres-
ence of publication bias trim and fill analysis was done
and 5 studies were added, and the total number of stud-
ies becomes 14. The pooled estimate of AOR of history
of ARTI was found to be 1.958(Supplementary Fig. 26).
We employed a leave-one-out sensitivity analysis to
identify the potential source of heterogeneity in the ana-
lysis of the pooled estimate of being history of ARTI as a
risk factor of pneumonia in Eastern Africa. The results
of this sensitivity analysis showed that our findings were
not dependent on a single study. Our pooled estimate of
having history of ARTI ranges between 2.195(95%CI,
1.36–3.02) and 3.28(95%CI, 2.153–4.417) after deletion
of a single study (Supplementary Fig. 27).
Discussion
This systematic review and meta-analysis was conducted
to assess the magnitude of pneumonia and its associated
factors among under-five children in East Africa. Thirty-
four studies were included for the final analysis. Twenty-
two studies had reported the prevalence of pneumonia
and the pooled prevalence of pneumonia in under-five
children was found to be 34% with 95% CI of (23.8–
44.21%). This result was higher than a study con-
ducted in Dibrugarh, India which had reported the
prevalence of pneumonia in under-five children to be
16.34% [9]. This might be due to socioeconomic and
seasonal discrepancies as countries in East Africa are
less developed than India. A study conducted in
Nigeria had revealed the prevalence of pneumonia in
under-five children to be 31.6% which was
consistence with the findings of this systematic review
[53]. This consistency might be due to similarities in
socio-economic status as Nigeria is an African coun-
try probably having comparable socio-economic status
with east African countries. In addition the discrep-
ancy might be due to difference in case definition of
pneumonia.
This finding is higher than other studies done in
Austria (4.1%) [54], in Mali (6.7%) [55], and in
Bangladesh (21.3%) [56]. This variation might be due to
socio-economic and socio-demographic vitiations, the
variation in the study setting, seasonal variation,
unreachability and provision of Vitamin A supplementa-
tion and immunization, lack of confirmatory laboratories
and imaging investigations.
This systematic review and meta-analysis had also re-
vealed using woods as a source of fuel, cooking foods liv-
ing rooms, holding children on back while cooking
foods, being unvaccinated, history of being not on exclu-
sive breast feeding, history of upper respiratory tract in-
fection and parental smoking as a significant risk factors
for increased prevalence of pneumonia among under-
five children in East Africa.
Higher odds of pneumonia were observed in under-
five children whose family uses wood as a source of fuel.
This result was in line with studies conducted in India
[57], and Sri Lanka [58]; and with systematic reviews
conducted in Low and Middle income countries [59],
and Africa, China and Latin America [60]. It was also
consistent with a global review conducted by Jackson
et al. [61]. The association between using wood as a
source of fuel and pneumonia in under-five children
might be due to the fact that using woods as a source of
fuel results in release of wood smokes containing major
air pollutants like carbon monoxide and particulate mat-
ters which causes indoor air pollution [62]. Indoor air
pollution and inhaling wood smoke in turn impairs the
function of pulmonary alveolar macrophages and epithe-
lial cells which will increase the likelihood of pulmonary
infections including pneumonia [62,63].
According to this systematic review and meta-analysis,
cooking foods in living rooms was found to be signifi-
cantly associated with occurrence of pneumonia in
under-five children as higher odds of pneumonia was ex-
hibited among children living in families who cooks food
at living rooms than children living in families who
cooks food in kitchen. Holding children on back while
cooking foods was another factor found to be signifi-
cantly associated with pneumonia. This association
might be due to the reason that cooking foods in living
rooms will cause indoor air pollution and holding a child
on back while cooking foods can increase the probability
of inhaling smokes and food vapors (steams) which in
turn will increase the risk of acquiring pneumonia by
Beletew et al. BMC Pediatrics (2020) 20:254 Page 9 of 13
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
altering the structure and function of the respiratory
tract [58,63].
In this systematic review children with history of
Acute Respiratory Tract Infections (ARTIs) were found
to be at increased risk to acquire pneumonia; as the odds
of pneumonia among children who had history of ARTIs
was higher than children without history of ARTIs. The
reason behind this association might be due to the fact
that ARTIs will alter the structure and function of the
respiratory tract and can cause Lower Respiratory Infec-
tions (LRTIs) including pneumonia in two ways—by in-
creasing invasion of the Lower respiratory tract (LRT)
with other microorganisms which cause secondary infec-
tions or by progressive invasion of LRT with the same
microorganism causing the ARTIs (Primary infections)
[64].
The risk of acquiring pneumonia in unvaccinated chil-
dren was found to be higher than vaccinated children.
This result was similar with studies conducted in Brazil
[65], Bellary [7], and India [66]. A systematic review con-
ducted by Jackson et al. [61] was also in line with this re-
sult. Similarly, children who were not on exclusive
breast feeding were at higher risk to develop pneumo-
nia than children who were on exclusive breast feed-
ing for the first 6 months of age. This result was
consistent with different studies conducted across the
world [7,61,67,68]. The reason behind this associ-
ation might be due to low or weak immunity. Because
exclusive breast feeding and vaccination are strategies
used to increase the immunity of children and pre-
vent childhood infections. So, children who were not
on Exclusive breast feeding and/ or unvaccinated will
have weak immunity and increased probability of ac-
quiring infections including pneumonia [69].
Strength and limitations
This study has several strengths: First, we used a pre-
specified protocol for search strategy and data abstrac-
tion and used internationally accepted tools for a critical
appraisal system for quality assessment of individual
studies. Second, we employed subgroup and sensitivity
analysis based on study country, study design, and publi-
cation year to identify the small study effect and the risk
of heterogeneity. Nevertheless, this review had some lim-
itations: There may be publication bias because not all
grey literature was included and language biases since all
included studies are published in English.
Conclusion and recommendation
The prevalence of pneumonia among under-five chil-
dren in Eastern Africa remains high. Use of wood as fuel
source, cooking food in living room, caring of a child on
mother during cooking, being unvaccinated, on-
exclusive breast feeding,child history of ARTI, and
parental smoking were independent potential predictors
of under-five pneumonia in Eastern Africa. Hence, ap-
propriate intervention on potential determinates such as
health education on exclusive breastfeeding, place of
food cooking, increase vaccination coverage and early
control of respiratory tract infection was recommended
to prevent those risk factors.
Supplementary information
Supplementary information accompanies this paper at https://doi.org/10.
1186/s12887-020-02083-z.
Additional file 1. PRISMA 2009 Checklist
Additional file 2 Supplementary Figure 1. Forest plot showing
subgroup analysis (by country) of pooled prevalence of pneumonia
among under-five children in Ethiopia from2002 up to 2019. Supple-
mentary Figure 2. Forest plot showing subgroup analysis (by study de-
sign) of pooled prevalence of pneumonia among under-five children in
Ethiopia from2002 up to 2019. Supplementary Figure 3. Forest plot
showing subgroup analysis (by country) of pooled prevalence of pneu-
monia among under-five children in Ethiopia from2002 up to 2019. Sup-
plementary Figure 4. sensitivity of pooled prevalence of pneumonia
among under-five children in Ethiopia from2002 up to 2019. Supple-
mentary Figure 5. publication bias of pooled prevalence of pneumonia
among under-five children in Ethiopia from2002 up to 2019. Supple-
mentary Figure 6. Forest plot showing of pooled estimate of AOR for
using wood as fuel source as a predictor of pneumonia among under-
five children in Ethiopia from2002 up to 2019. Supplementary Figure
7. publication bias of pooled estimate of AOR for using wood as fuel
source as a predictor of pneumonia among under-five children in
Ethiopia from2002 up to 2019. Supplementary Figure 8. sensitivity ana-
lysis of pooled estimate of AOR for using wood as fuel source as a pre-
dictor of pneumonia among under-five children in Ethiopia from2002 up
to 2019. Supplementary Figure 9: Forest plot showing the pooled esti-
mate of AOR for cooking food at home as a predictor of pneumonia
among under-five children in Ethiopia from2002 up to 2019.Supplemen-
tary Figure 10. publication bias for pooled estimate of AOR for cooking
food at home as a predictor of pneumonia among under-five children in
Ethiopia from2002 up to 2019. Supplementary Figure 11. Trim and fill
analysis for pooled estimate of AOR for cooking food at home as a pre-
dictor of pneumonia among under-five children in Ethiopia from2002 up
to 2019. Supplementary Figure 12. Sensitivity analysis for pooled esti-
mate of AOR for cooking food at home as a predictor of pneumonia
among under-five children in Ethiopia from2002 up to 2019. Supple-
mentary Figure 13. Forest plot showing estimate of AOR for caring of
the child on mothers during cooking as a predictor of pneumonia
among under-five children in Ethiopia from2002 up to 2019. Supple-
mentary Figure 14. publication bias for estimate of AOR for caring of
the child on mothers during cooking as a predictor of pneumonia
among under-five children in Ethiopia from2002 up to 2019. Supple-
mentary Figure 15. trim and fill analysis for estimate of AOR for caring
of the child on mothers during cooking as a predictor of pneumonia
among under-five children in Ethiopia from2002 up to 2019. Supple-
mentary Figure 16. sensitivity analysis for estimate of AOR for caring of
the child on mothers during cooking as a predictor of pneumonia
among under-five children in Ethiopia from2002 up to 2019. Supple-
mentary Figure 17. Forest plot showing the pooled estimate of AOR
for being unvaccinated as a predictor of pneumonia among under-five
children in Ethiopia from2002 up to 2019. Supplementary Figure 18.
publication bias for pooled estimate of AOR for being unvaccinated as a
predictor of pneumonia among under-five children in Ethiopia from2002
up to 2019. Supplementary Figure 19. sensitivity analysis for pooled es-
timate of AOR for being unvaccinated as a predictor of pneumonia
among under-five children in Ethiopia from2002 up to 2019. Supple-
mentary Figure 20. Forest plot showing the pooled estimate of AOR
for non-exclusive breast feeding as a predictor of pneumonia among
under-five children in Ethiopia from 2002 up to 2019. Supplementary
Beletew et al. BMC Pediatrics (2020) 20:254 Page 10 of 13
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Figure 21. publication bias for the pooled estimate of AOR for non-
exclusive breast feeding as a predictor of pneumonia among under-five
children in Ethiopia from 2002 up to 2019. Supplementary Figure 22.
Trim and fill analysis for the pooled estimate of AOR for non-exclusive
breast feeding as a predictor of pneumonia among under-five children in
Ethiopia from 2002 up to 2019. Supplementary Figure 23. Sensitivity
analysis for the pooled estimate of AOR for non-exclusive breast feeding
as a predictor of pneumonia among under-five children in Ethiopia from
2002 up to 2019. Supplementary Figure 24. Forest plot showing the
pooled estimate of AOR for history of ARTI as a predictor of pneumonia
among under-five children in Ethiopia from 2002 up to 2019. Supple-
mentary Figure 25. Publication bias for the pooled estimate of AOR for
history of ARTI as a predictor of pneumonia among under-five children in
Ethiopia from 2002 up to 2019. Supplementary Figure 26. Trim and fill
analysis for the pooled estimate of AOR for history of ARTI as a predictor
of pneumonia among under-five children in Ethiopia from 2002 up to
2019. Supplementary Figure 27. sensitivity analysis for the pooled esti-
mate of AOR for history of ARTI as a predictor of pneumonia among
under-five children in Ethiopia from 2002 up to 2019
Additional file 3 Table S1. Search strategy used for one of the
databases
Additional file 4 Table S2. Quality appraisal result of included studies
in East Africa, from 2002 to 2019. Using Joanna Briggs Institute (JBI)
quality appraisal checklist
Additional file 5 Table S3. Adjusted confounders and main findings
extracted from included studies in East Africa
Abbreviations
CI: Confidence Interval; OR: Odds Ratio; U5M: Under Five Mortalities;
WHO: World Health Organization; DHS: Demographic and Health Surveys;
EDHS: Ethiopian Demographic and Health Survey; AOR: Adjusted odds ratio;
ARTI: Acute Respiratory Tract Infections
Acknowledgments
We would like to thank the primary authors of the included studies.
Authors’contributions
BB, MB, MA, AM and MW: developed the study design and protocol,
literature review, selection of studies, quality assessment, data extraction,
statistical analysis, interpretation of the data and developing the initial drafts
of the manuscript and prepared the final draft of the manuscript. All authors
read and approved the final manuscript.
Funding
No funding was obtained for this study.
Availability of data and materials
The datasets analyzed during the current study are available from the
corresponding author upon reasonable request.
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
We have confirmed that we have no competing interests.
Received: 5 February 2020 Accepted: 13 April 2020
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