Study selection
A total of 4931 studies were identified; 3282 from PubMed, 12 from Cochrane Library, 1610 from Google Scholar and 27 from other sources. After duplication removed, 1235 remained. Finally, 301 studies were screened for full-text review and finally, 26 (n=11,239) were selected for the prevalence and/ or associated factors analysis (Fig. 1).
Characteristics of included studies
26 papers were included in this systematic review and meta-analysis [32–36]
10 studies were found in Ethiopia [Alebachew(32), Yirga T.et al./ 2018(33), Gebrehiwot et al/2012(25), G/eyesus et al /2017(5), Gebremedhin et al /2016(6), Getabelew et al. /2017(34), Shitaye D et al/2010(35), Yusuf et al/2008(36), Abate et al/2016(5), Mersha et al. /2019(37) ],
7 in Kenya [Kwame et al/2011(38),MUMBI S. et al /2010(39),Mulongo N et al/2018(40),A.M.R. LAVING et al./ 2003(41),Alison W A et al/2012(42),J LeGeyt et al./ 2016(43),James A. et al./ 2005(44) ], 3 in Sudan [Abdelmoneim E. M et al./ 2014(45),Wafa Babiker et al./ 2018(46),Abd Elrahman et al/2018(47) ], and 6 in Uganda [Petwa(48), K.W. et al./ 2015,J Mugalu et al./ 2006(49),N. A. Mobbs et al/2019(50), Kiwanuka J et al/2013(51),Okaba et al /2018(52), Bua John et al/2015(44) ]. 19 of the studies were done by cross-sectional study design, three studies by case-control study design, whereas four of the studies were conducted through cohort study design respectively. Regarding the year of publication, 4 studies were published between 2000 and 2010, and 22 studies were between 2010 and 2017. The studies included participants, ranging from 62 (32) to 4849 (James A.) (Table 1).
Characteristics and quality status of the studies
Table 1: Distribution of studies on the prevalence and determinants of neonatal sepsis in Ethiopia
Author
|
Study country
|
Study design
|
Sample size
|
Prevalence (%)
|
Quality status
|
1. Alebachew et al/2014(32)
|
Ethiopia
|
cross-sectional
|
306
|
-
|
Low risk
|
2. Yirga T.et al./ 2018(33)
|
Ethiopia
|
case-control
|
231
|
-
|
Low risk
|
3. Gebrehiwot et al/2012(25)
|
Ethiopia
|
cross-sectional
|
181
|
32.10
|
Low risk
|
4. G/eyesus et al /2017 et al.(5)
|
Ethiopia
|
cross-sectional
|
251
|
0.466
|
Low risk
|
5. Gebremedhin et al /2016(6)
|
Ethiopia
|
case-control
|
232
|
|
Low risk
|
6. Getabelew et al. /2017(34)
|
Ethiopia
|
cross-sectional
|
244
|
77.90
|
Low risk
|
7. Shitaye D et al/2010(35)
|
Ethiopia
|
cross-sectional
|
302
|
44.70
|
Low risk
|
8. Yusuf et al/2008(36)
|
Ethiopia
|
cross-sectional
|
578
|
28.70
|
Low risk
|
9. Abate et al/2016(5)
|
Ethiopia
|
cohort
|
1189
|
4.70
|
Low risk
|
10. Mersha et al. /2019(37)
|
Ethiopia
|
cross-sectional
|
275
|
33.80
|
Low risk
|
11. Petwa, K.W. et al./ 2015(48)
|
Uganda
|
cross-sectional
|
258
|
24.00
|
Low risk
|
12. J Mugalu et al./ 2006(49)
|
Uganda
|
cross-sectional
|
290
|
37.90
|
Low risk
|
13. N. A. Mobbs et al/2019(50)
|
Uganda
|
cohort
|
103
|
30.30
|
Low risk
|
14. Kiwanuka J et al/2013(51)
|
Uganda
|
cross-sectional
|
80
|
32.50
|
Low risk
|
15. Okaba et al /2018(52)
|
Uganda
|
cohort
|
325
|
11
|
Low risk
|
16. Kwame et al/2011(38)
|
Kenya
|
case-control
|
100
|
-
|
Low risk
|
17. MUMBI S. et al /2010(39)
|
Kenya
|
cross-sectional
|
104
|
-
|
Low risk
|
18. Mulongo N et al/2018(40)
|
Kenya
|
cross-sectional
|
256
|
13.29
|
Low risk
|
19. A.M.R. LAVING et al./ 2003(41)
|
Kenya
|
cross-sectional
|
84
|
17.90
|
Low risk
|
20. Alison W A et al/2012(42)
|
Kenya
|
cross-sectional
|
4,849
|
23.00
|
Low risk
|
21. J LeGeyt et al./ 2016(43)
|
Kenya
|
Cohort
|
1262
|
23.90
|
Low risk
|
22. James A. et al./ 2005(44)
|
Kenya
|
cross-sectional
|
1783
|
12.80
|
Low risk
|
23. Bua John et al/2015(44)
|
Uganda
|
cross-sectional
|
174
|
21.80
|
Low risk
|
24. Abdelmoneim E. M et al./ 2014(45)
|
Sudan
|
cross-sectional
|
62
|
17.50
|
Low risk
|
25. Wafa Babiker et al./ 2018(46)
|
Sudan
|
cross-sectional
|
119
|
37.80
|
Low risk
|
26. Abdulrahman et al/2018(47)
|
Sudan
|
cross-sectional
|
200
|
62
|
Low risk
|
Quality of studies
The JBI quality appraisal criteria established for cross-sectional, case-control, and cohort studies were used. The studies included in this systematic review and meta-analysis had no considerable risk. Therefore, all the studies were considered [2, 6-7, 33–52] (Table1).
Meta-analysis
Prevalence of neonatal sepsis
21 studies [Abate et al(5), Okaba et al(52) ,James A. ,Bua John(44) , Mulongo N (40),Abdelmoneim E. ,A.M.R. LAVING ,Alison W A (42),J LeGeyt (43),Petwa(48), Yusuf et al(36), N. A. Mobbs (50), Gebrehiwot(25),Kiwanuka J (51), Mersha et al. (37),Wafa ,Babiker ,J Mugalu(49) ,Shitaye D(35) , G/eyesus(5),AbdElrahman, Getabelew(34) ] revealed the prevalence of neonatal sepsis .The prevalence ranges from 4.7% (Abate et al(5)) up to 77.9 % (Getabelew et al (34)). From those studies, the pooled prevalence of neonatal sepsis in East Africa was 29.65 %( 95%CI; 23.36–35.94). We found significant heterogeneity among the studies (I2=98.8%; p<0.001).We analyzed by random-effects model analysis and we did subgroup analysis (Figure 2).
Test of heterogeneity
Subgroup analysis of the prevalence of neonatal sepsis in Eastern Africa
The subgroup analysis was done based on the country, study design, and year of publication. Based on this, the prevalence of neonatal sepsis found to be 38.31 % in Ethiopia, 24.4% in Uganda, 18.28% in Kenya, and 39.26.Based on design 32.63% in cross-sectional studies and 17.08% in cohort studies. Based on the year of publication 23.05% from 2000-2010, 33.01% from 2010-2015 and 31.39 from 2015-2019(Table 2 and Figure 3, 4 and 5).
Variables
|
Characteristics
|
Pooled prevalence (95% CI)
|
I2(P-value)
|
By country
|
Ethiopia
|
38.31(17.43-59.19)
|
99.5%(<0.001)
|
Uganda
|
24.4(14.91-33.90)
|
93.9%(<0.001)
|
Kenya
|
18.28(12.64-23.91)
|
96.9%(<0.001)
|
Sudan
|
39.26(13.31-65.22)
|
96.6%(<0.001)
|
By design
|
Cross-sectional
|
32.63(25.53-39.73)
|
98.4% (<0.001)
|
Cohort
|
17.08(5.22-28.95)
|
98.7%(<0.001)
|
By year of publication
|
2000-2010
|
23.05(12.38-33.73)
|
96.7% (<0.001)
|
2010-2015
|
33.01(20.62-45.40)
|
96.5%(<0.001)
|
2015-2019
|
31.39(19.68-43.10)
|
99.1%(<0.001)
|
Sensitivity analysis
We employed a leave-one-out sensitivity analysis to identify the potential source of heterogeneity in the analysis of the prevalence of neonatal sepsis 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 neonatal sepsis varied between 27.15(21.68–32.61) and 30.94(24.96–36.92) after deletion of a single study.
Abd Elrahman et al/2018(47), Abate et al/2016 (5), Gebremedhin et al /2016 (6), Getabelew et al. /2017(34) had shown an impact on the overall estimation(Figure 6).
Publication bias
A funnel plot showed asymmetrical distribution .Egger’s regression test p-value was 0.010, which indicated the presence of publication bias.
Prevalence of neonatal sepsis
The estimated overall prevalence of neonatal sepsis is presented in a forest plot (Fig. 4). The overall prevalence of LBW was 29.65% (95% CI; 23.36–35.94; I2= 98.8%) (Figure 7).
Factors associated with neonatal sepsis
In Eastern Africa context neonatal sepsis is associated with socio-economic, obstetric and maternal behavior, infant, and environmental-related factors (Table 3).
Table 3: Factors associated with neonatal sepsis
Factors
|
Odds ratio (AOR)
|
Author
|
Year
|
Place of birth
|
4.20
|
Alebachew et al.
|
2014
|
4.36
|
Yirga et al.
|
2018
|
6.36
|
G/eyesus et al.
|
2017
|
19.00
|
Gebremedhin et al.
|
2016
|
6.00
|
Getabelew et al.
|
2017
|
Maternal history of UTI
|
2.9
|
Alebachew et al.
|
2014
|
10.8
|
Yirga et al.
|
2018
|
7.06
|
G/eyesus et al.
|
2017
|
15.04
|
Gebremedhin et al.
|
2016
|
6.45
|
Getabelew et al.
|
2017
|
6.28
|
Okaba et al.
|
2018
|
3.37
|
Bua John et al.
|
2015
|
1.65
|
J Mugalu et al.
|
2006
|
1.12
|
Mersha et al.
|
2019
|
Gestational age(preterm)
|
6.44
|
Alebachew et al.
|
2014
|
3.49
|
Yirga et al.
|
2018
|
10.60
|
G/eyesus et al.
|
2017
|
38.60
|
Gebremedhin et al.
|
2016
|
7.38
|
Getabelew et al.
|
2017
|
2.92
|
Yusuf et al.
|
2008
|
1.49
|
Abate et al.
|
2016
|
4.66
|
J LeGeyt et al.
|
2016
|
7.22
|
Mulongo N et al
|
2018
|
6.45
|
A.M.R. LAVING et al.
|
2003
|
Prolonged labor
|
6.95
|
Alebachew et al.
|
2014
|
11.92
|
Yirga et al.
|
2018
|
1.29
|
G/eyesus et al.
|
2017
|
1.41
|
J Mugalu et al.
|
2006
|
2.53
|
Getabelew et al.
|
2017
|
12.4
|
Okaba et al.
|
2018
|
PROM
|
5.20
|
A.M.R. LAVING et al.
|
2003
|
10.37
|
Yirga et al.
|
2018
|
11.80
|
G/eyesus et al.
|
2017
|
27.10
|
Gebremedhin et al.
|
2016
|
1.28
|
Getabelew et al.
|
2017
|
1.85
|
Mersha et al.
|
2019
|
1.56
|
J Mugalu et al.
|
2006
|
4.74
|
Okaba et al.
|
2018
|
6.7
|
MUMBI S. et al.
|
2010
|
8.28
|
Mulongo N et al.
|
2018
|
Place of birth
Five studies (Alebachew et al (32), Yirga (33), Gebremedhin(6)) found a significant association between home delivery and neonatal sepsis. Alebachew et al revealed that the odds of neonatal sepsis was higher among newborns who delivered at home (AOR=4.2, 95% CI: 1.93, 8.97) compared to those who delivered at the health institution. Yirga et al revealed that neonates who delivered at home were 4.36 times at risk of being neonatal sepsis compared to those who delivered at the health institution. G/eyesus et al(5) revealed that neonates who delivered at home were 6.36 times at risk of being neonatal sepsis compared to those who delivered at the health institution. Gebremedhin et al(6) found that the odds of neonatal sepsis was higher among newborns who delivered at home (AOR=19, 95% CI: 1.74, 4.41) compared to those who delivered at the health institution. Getabelew et al revealed that neonates who delivered at home were 6 times at risk of being neonatal sepsis compared to those who delivered at the health institution. Four studies (Mersha et al., J Mugalu, Okaba, et al, Bua John et al) found no significant association between place of birth and neonatal sepsis.
Test of heterogeneity place of birth
Galbraith plot showed homogeneity and combining the result of nine studies the forest plot showed the overall estimate of AOR of home delivery was 2.67( 95%C I: 1.15-4.00;I2= 0.0%;P=0.996).I-Squared (I2)and P-value also showed homogeneity.
Publication bias place of birth
A funnel plot showed an asymmetrical distribution. Egger's regression test p-value was 0.003, which indicated the presence of publication bias.
Trim and fill analysis place of birth
Trim and fill analysis was done and 4 studies were added and the total number of studies become 13 .the pooled estimate of AOR of home delivery becomes 2.36(Figure 8).
The pooled effect of place of birth
Publication bias for the place of birth
The Beggs test shows there is publication bias regarding place of birth(Figure 9)
Trim and fill analysis place of birth
After adding 4 studies during trim and fill the effect size of place of birth changed from 2.57 to2,36(Figure 10).
Maternal history of UTI
Seven studies (Alebachew(32), Yirga(33), G/eyesus et al(5), Gebremedhin(6), Getabelew et al(34), Okaba et al(52) and Bua John et al(44) found a significant association between maternal history of and neonatal sepsis.
Alebachew et al revealed that the odds of neonatal sepsis was higher among neonates whose mother have a history of UTI(AOR=2.9,95% CI: 1.48, 5.52) compared to those whose mother has no history of UTI. Yirga et al revealed that neonates whose mother have a history of UTI were 10.8 times at risk of being neonatal sepsis (95% CI: 3.44, 33.97) compared to those who delivered at the health institution. G/eyesus et al revealed that neonates whose mothers have a history of UTI were 7.06 times at risk of being neonatal sepsis compared to those whose mother has no history of UTI. Gebremedhin et al (6)found that the odds of neonatal sepsis was higher among neonates whose mother have a history of UTI (AOR=15.04, 95% CI: 1.65, 3.38) compared to those whose mother has no history of UTI. Getabelew et al revealed that neonates whose mothers have a history of UTI were 6.45 times at risk of being neonatal sepsis compared to those whose mother has no history of UTI. Okaba et al revealed that the odds of neonatal sepsis was higher among neonates whose mother have a history of UTI (AOR=6.28, 95% CI: 1.62, 7.38) compared to those whose mother has no history of UTI. Bua John et al revealed that the odds of neonatal sepsis was higher among neonates whose mother have a history of UTI (AOR=3.37,95% CI: 1.23, 9.22) compared to those whose mother has no history of UTI. Four studies (J Mugalu, Mersha, et al.) found no significant association between maternal history of UTI and neonatal sepsis.
Test of heterogeneity for the maternal history of UTI
Galbraith plot showed moderate heterogeneity and the forest plot showed the overall estimate of AOR of a place of birth was 2.083( 95%C I: 0.24-3.93;I2= 69.1%;P=0.001). I-Squared (I2) and P-value also showed substantial heterogeneity. Main meta-analysis was done with random effect models(Figure 11).
The pooled estimate of UTI
Publication bias maternal history of UTI
A funnel plot showed a symmetrical distribution. Egger's regression test p-value was 0.928, which indicated the absence of publication bias(Figure 12).
Eight studies (Alebachew(32), Yirga(33), G/eyesus et al(5), Gebremedhin, Getabelew et al(34), Yusuf et al(36), Abate et al(5) ,J LeGeyt et al. (43))found significant association between gestational age and neonatal sepsis. Alebachew et al revealed that preterm neonates were 6.44 times at risk of being neonatal sepsis compared to term neonates. Yirga et al revealed that preterm neonates were 3.49 times at risk of being neonatal sepsis (95% CI: 1.14, 10.67) compared to term neonates. G/eyesus et al revealed that preterm neonates were 10.6 times at risk of being neonatal sepsis compared to term neonates. Gebremedhin et al found that the odds of neonatal sepsis was higher among preterm neonates (AOR=38.6, 95% CI: 1.96, 9.51) compared to term neonates. Getabelew et al revealed that preterm neonates were 7.38 times at risk of being neonatal sepsis compared to term neonates. Yusuf et al revealed that the odds of neonatal sepsis was higher among preterm neonates (AOR=2.92, 95% CI: 1.97, 4.31) compared to term neonates. Abate et al revealed that preterm neonates were 1.49 times at risk of being neonatal sepsis compared to term neonates. J LeGeyt et al. found that the odds of neonatal sepsis was higher among preterm neonates (AOR=4.66, 95% CI: 0.65,0.98)compared to term neonates. Two studies (Mulongo N et al, A.M.R. LAVING et al., found no significant association between gestational age and neonatal sepsis.
Test of heterogeneity gestational age
Galbraith plot showed moderate heterogeneity and the forest plot showed the overall estimate of AOR of the place of birth was 1.56 (95% CI: 1.04-2.08; I2= 27.8%; P=0.000). I-Squared (I2)and P-value also showed moderate heterogeneity.
Publication bias gestational age
A funnel plot showed an asymmetrical distribution. Egger's regression test p-value was 0.000, which indicated the presence of publication bias.
Trim and fill analysis gestational age
Trim and fill analysis was done and 2 studies were added and the total number of studies become 12 .the pooled estimate of AOR of preterm becomes 4.69(Figure 13).
Preterm pooled estimate
Publication bias preterm
Begg’s test shows there is publication bias among studies regarding gestational age of respondents (Figure 14).
Trim and fill
After trim and fill analysis two studies were added and the pooled effect size changed from 1.56 to 4.69 (Figure 15).
Prolonged labor
Four studies (Alebachew(32), Yirga(33), Getabelew et al(34), Okaba et al(52) found a significant association between prolonged labor and neonatal sepsis. Alebachew et al revealed that mothers of neonates who have a history of prolonged labor were 6.95 times at risk of being neonatal sepsis compared to those who have no history of prolonged labor. Yirga et al shown that mothers of neonates who have a history of prolonged labor were 11.92 times at risk of being neonatal sepsis compared to those who have no history of prolonged labor. Getabelew et al revealed that mothers of neonates who have a history of prolonged labor were 2.53 times at risk of being neonatal sepsis compared to those who have no history of prolonged labor. Okaba et al shown that mothers of neonates who have a history of prolonged labor were 12.4 times at risk of being neonatal sepsis compared to those who have no history of prolonged labor. Two studies (G/eyesus et al, J Mugalu )found no significant association between prolonged labor and neonatal sepsis.
Test of heterogeneity prolonged labor
Galbraith plot showed moderate heterogeneity and the forest plot showed the overall estimate of AOR of the place of birth was 3.23 (95% CI: -0.04-6.51; I2= 62.7%; P=0.020) .I-Squared (I2) and P-value also showed substantial heterogeneity (Figure 16).
Publication bias
Publication bias prolonged labor
A funnel plot showed a symmetrical distribution. Egger's regression test p-value was 0.770, which indicated the absence of publication bias (Figure 17).
PROM
Seven studies ( Yirga(33), G/eyesus et al(5), Gebremedhin(6), Okaba, et al, MUMBI S. et al(39), Mulongo N et al, A.M.R. LAVING et al.)found a significant association between PROM and neonatal sepsis. Yirga et al revealed that mothers of neonates who have history of PROM were 10.37 times at risk of being neonatal sepsis (95% CI: 2.3,46.5) compared to those who have no history of PROM.G/eyesus et al indicated that mothers of neonates who have history of PROM were 11.8 times at risk of being neonatal sepsis compared to those who have no history of PROM. Gebremedhin et al found that mothers of neonates who have a history of PROM were 27.1 times at risk of being neonatal sepsis (95% CI: 2.01, 6.39) compared to those who have no history of PROM. Okaba et al revealed that mothers of neonates who have a history of PROM were 4.74 times at risk of being neonatal sepsis compared to those who have no history of PROM. MUMBI S. et al indicated that mothers of neonates who have a history of PROM were 6.7 times at risk of being neonatal sepsis compared to those who have no history of PROM. Mulongo N et al, revealed that mothers of neonates who have history of PROM were 8.28 times at risk of being neonatal sepsis compared to those who have no history of PROM.A.M.R. LAVING et al. indicated that mothers of neonates who have history of PROM were 5.2 times at risk of being neonatal sepsis compared to those who have no history of PROM. Three studies (Getabelew, Shitaye D, et al,Mersha et al. , J Mugalu ) found no significant association between PROM and neonatal sepsis.
Test of heterogeneity PROM
Galbraith plot showed moderate heterogeneity and the forest plot showed the overall estimate of AOR of a place of birth was 1.95 (95% CI: 0.53-3.37; I2= 43.2%; P=0.062).I-Squared (I2)and P-value also showed moderate heterogeneity(Figure 18).
Publication bias
Publication bias PROM
A funnel plot showed an asymmetrical distribution. Egger's regression test p-value was 0.030, which indicated the presence of publication bias (Figure 19).
Trim and fill PROM
Trim and fill analysis PROM
Trim and fill analysis was done and 4 studies were added and the total number of studies become 15 .The pooled estimate of AOR of preterm becomes 5.86 (Figure 20).