| Literature DB >> 35564842 |
Minyahil Tadesse Boltena1, Ziad El-Khatib2,3, Abraham Sahilemichael Kebede4, Benedict Oppong Asamoah5, Appiah Seth Christopher Yaw6, Kassim Kamara7, Phénix Constant Assogba8, Andualem Tadesse Boltena5, Hawult Taye Adane1, Elifaged Hailemeskel1,9, Mulatu Biru1,10.
Abstract
Malaria and helminthic co-infection during pregnancy causes fetomaternal haemorrhage and foetal growth retardation. This study determined the pooled burden of pregnancy malaria and helminthic co-infection in sub-Saharan Africa. CINAHL, EMBASE, Google Scholar, Scopus, PubMed, and Web of Science databases were used to retrieve data from the literature, without restricting language and publication year. The Joanna Briggs Institute's critical appraisal tool for prevalence studies was used for quality assessment. STATA Version 14.0 was used to conduct the meta-analysis. The I2 statistics and Egger's test were used to test heterogeneity and publication bias. The random-effects model was used to estimate the pooled prevalence at a 95% confidence interval (CI). The review protocol has been registered in PROSPERO, with the number CRD42019144812. In total, 24 studies (n = 14,087 participants) were identified in this study. The pooled analysis revealed that 20% of pregnant women were co-infected by malaria and helminths in sub-Saharan Africa. The pooled prevalence of malaria and helminths were 33% and 35%, respectively. The most prevalent helminths were Hookworm (48%), Ascaris lumbricoides (37%), and Trichuris trichiura (15%). Significantly higher malaria and helminthic co-infection during pregnancy were observed. Health systems in sub-Saharan Africa must implement home-grown innovative solutions to underpin context-specific policies for the early initiation of effective intermittent preventive therapy.Entities:
Keywords: co-infection; comorbidity; helminthic infections; pregnancy malaria; sub-Saharan Africa
Mesh:
Year: 2022 PMID: 35564842 PMCID: PMC9101176 DOI: 10.3390/ijerph19095444
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 4.614
Figure 1Flow diagram of the included studies. Moher, D. et al. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Medicine, 2009, 6(7).
Quality assessment of the eligible studies.
| Included Studies for Meta-Analysis | Study Level Bias Score | ||
|---|---|---|---|
| S. No | Author, Publication year | Total No. Yes (Y) | Percentage of Yes (Y) |
| 1 | Hillier et al., 2008 | 9 | 100.00% |
| 2 | Getachew et al., 2013 | 8 | 89.00% |
| 3 | Joseph et al., 2017 | 9 | 100.00% |
| 4 | Wanyonyi et al., 2018 | 8 | 89.00% |
| 5 | Teklemariam A., 2018 | 8 | 89.00% |
| 6 | Egwunyenga et al., 2001 | 8 | 89.00% |
| 7 | Adegnika et al., 2010 | 9 | 100.00% |
| 8 | Nelly et al., 2009 | 9 | 100.00% |
| 9 | Shapiro et al., 2004 | 9 | 100.00% |
| 10 | Thigpen et al., 2011 | 9 | 100.00% |
| 11 | Olusola Ojurongbe | 8 | 89.00% |
| 12 | Olarewaju et al., 2016 | 9 | 100.00% |
| 13 | Polycarp Uche Agu et al., 2013 | 9 | 100.00% |
| 14 | Ndyomugyenyi et al., 2008 | 8 | 89.00% |
| 15 | Anchang-Kimbi et al., 2017 | 8 | 89.00% |
| 16 | Umeh et al., 2018 | 8 | 89.00% |
| 17 | Nnah and Kasso, 2018 | 8 | 89.00% |
| 18 | Akinbo et al., 2017 | 7 | 78.00% |
| 19 | Ekejindu et al., 2011 | 9 | 100.00% |
| 20 | Ifeanyi., 2014 | 9 | 100.00% |
| 21 | Fairley, 2014 | 9 | 100.00% |
| 22 | Fuseini et al., 2010 | 7 | 78.00% |
| 23 | Masai, Rael Jepkogei, 2016 | 8 | 89.00% |
| 24 | Honkpehedji et al., 2017 | 8 | 89.00% |
| Average bias score (%Yes) | 93.00% | ||
Subtotal Yes (Y) 93%. Subtotal No (N) 6.5%. Subtotal Unclear (U) 0%. Overall risk of bias assessment score was 93%. Remark: The risk of bias for each eligible study was calculated from the domain of nice criteria.
Descriptive summary of the eligible studies.
| S. No | Author, Year of Publication | Year Study Conducted | Country | Study Design | Sample Size | Trimester | Parity | Test Approach for Malaria Diagnosis | Test Approach for Helminthiases | Prevalence of | Prevalence of | Prevalence of Any Malaria Infection | Prevalence of Malaria Associated Anemia | Overall | Overall Prevalence of Malaria-Helminthiases Co-infection |
|
|
|
| |||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1st | 2nd | 3rd | Primigravida | Multigravida | ||||||||||||||||||
| 1 | Hillier et al., 2008 | 2003–2005 | Uganda | Cross-sectional | 2507 | Microscopy | Kato-Katz thick smear | 268 (11%) | 268 (11%) | 1693 (68%) | 1112 (45%) | 58 (2%) | 226 (9%) | 458 (18%) | ||||||||
| 2 | Getachew et al., 2013 | 2011 | Ethiopia | Cross-sectional | 388 | 156 | 167 | 95 | 133 | 285 | Microscopy | McMaster concentration technique | 45 (11.6%) | 159 (41%) | 30 (7.7%) | 114 (29%) | 58 (15%) | 13 (3.4%) | ||||
| 3 | Joseph, R. et al., 2017 | 2015 | Nigeria | Cross-sectional | 252 | 63 | 169 | Microscopy | Formalin-ether concentration techniques+ wet mount | 51 (20.2%) | 54 (21.4%) | 16 (6.3%) | ||||||||||
| 4 | Wanyonyi et al., 2018 | 2016–2017 | Kenya | Cross-sectional | 750 | Microscopy | Kato-Katz thick smear | 21.60% | 367 (48.9%) | 24.70% | 6.8% | |||||||||||
| 5 | Teklemariam A., 2018 | 2016 | Ethiopia | Cross-sectional | 460 | Microscopy | Formalin-ether concentration techniques | 27 (5.9%) | 55 (12%) | 84 (18.3%) | 198 (43%) | 46 (10%) | 54 (11.7%) | 77 (16.7%) | ||||||||
| 6 | Egwunyenga et al.,2001 | 1997–1998 | Nigeria | Cross-sectional | 2104 | Microscopy | Formalin-ether concentration techniques | 762 (36.2%) | 816 (38.8%) | 394 (48.3%) | 116 (5.5%) | 156 (7.4%) | 57 (2.7%) | 28 (1.3%) | ||||||||
| 7 | Adegnika et al., 2010 | 2003–2004 | Gabon | Cross-sectional | 388 | 111 | 277 | Microscopy | Kato-Katz thick smear | 98 (25%) | 216 (64%) | 15% | 34 (8.8%) | 112 (28.9%) | 83 (21.4%) | |||||||
| 8 | Nelly J et al., 2009 | 2006 | Ghana | Cross-sectional | 746 | 390 | 324 | 26 | 255 | 521 | Malaria Antigen CELISA assay | Kato-Katz thick smear | 271 (36.3%) | 36.30% | 192 (25.7%) | 124 (16.6%) | 59 (7.5%) | 92 (12.3%) | 42 (5.6%) | |||
| 9 | Shapiro et al., 2004 | 2003 | Uganda | Cross-sectional | 856 | Microscopy | Kato-Katz thick smear | 217 (49.9% | 217 (49.9%) | 405 (47.3%) | 118 (54.8%) | 275 (32.1%) | 149 (17.4%) | 70 (8.1%) | ||||||||
| 10 | Thigpen et al., 2011 | 2002–2004 | Malawi | Cross-sectional | 848 | 412 | 436 | Microscopy | Kato-katz thick smear | 667 (37.6%) | 667 (37.6%) | 691 (81.5%) | 143 (16.8%) | 81 (9.7%) | 122 (14.4%) | 21 (2.5%) | ||||||
| 11 | Olusola Ojurongbe | 2018 | Nigeria | Cross-sectional | 200 | 90 | 178 | 25 | Microscopy | Formalin-ether concentration techniques | 29.5% (59/200) | 12% (24/200) | 5% (10/200) | 2.0% (4/200) | 10.0% (20/200) | |||||||
| 12 | Olarewaju AB et al., 2016 | 2015 | Nigeria | Cross-sectional | 300 | 32 | 116 | 152 | 185 | 115 | Microscopy | Kato-Katz techniques | 14 (4.6) | 12 (4.0) | 73.1% (219) | 11 (3.6) | 15 (5.0) | 12 (4.0) | ||||
| 13 | Polycarp Uche Agu et al., 2013 | 2013 | Nigeria | Cross-sectional | 226 | 65 | 113 | 47 | Microscopy | Kato-Katz techniques | 119 | 90 (40%) | 60 (26.5%) | 14 (6.2%) | ||||||||
| 14 | R. Ndyomugyenyi et al., 2008 | 2007 | Uganda | Cross-sectional | 802 | Microscopy | Kato-Katz techniques | 281 (35%) | 219 (16%) | 554 (69%) | 4 (0.5%) | 38 (4.74%) | 31 (3.87%) | |||||||||
| 15 | Judith K. Anchang-Kimbi et al., 2017 | 2014 | Cameroon | Cross-sectional | 205 | 10 (4%) | 125 (50%) | 115 (46%) | Microscopy | Kato-Katz techniques | 98 (39.2%) | 38 (15.2%) | 117 (46.8%) | |||||||||
| 16 | Umeh et al., 2018 | 2017 | Nigeria | Cross-sectional | 300 | Microscopy | Kato-Katz techniques | 45 (15.0%) | 9 (3%) | 19 (6.3%) | ||||||||||||
| 17 | E. W. Nnah and T. Kasso 2018 | 2016 | Nigeria | Cross-sectional | 192 | Microscopy | Kato-Katz techniques | 47 (24.5%) | 32 (16.7%) | 1 (0.5%) | 6 (3.1%) | 144 (75%) | ||||||||||
| 18 | Akinbo et al., 2017 | 2014 | Nigeria | Cross-sectional | 402 | Microscopy | Kato-Katz techniques | 100 (24.9%) | 73 (18.2%) | 173 (43.14%) | 12 (3%) | 36 (9%) | 10 (2.5%) | |||||||||
| 19 | Ekejindu IM et al., 2011 | 2015 | Nigeria | Cross-sectional | 100 | Microscopy | Kato-Katz techniques | 81 (81%) | 17 (13%) | 17 (17%) | ||||||||||||
| 20 | Obeagu E. Ifeanyi., 2014 | 2012 | Nigeria | Cross-sectional | 87 | Microscopy | Kato-Katz techniques | 44 (51%) | 11 (13%) | 16 (18%) | ||||||||||||
| 21 | Jessica K. Fairley., 2014 | 2005 | Kenya | Cross-sectional | 696 | Microscopy | Kato-Katz techniques | 297 (42.7%) | 205 (29.5%) | 219 (31.5%) | 41 (5.9%) | |||||||||||
| 22 | Fuseini et al., 2010 | 2005 | Ghana | Cross-sectional | 300 | Microscopy | Kato-Katz techniques | 174 (58%) | 69 (23%) | 21 (7%) | 2 (0.7%) | 37 (12.3%) | ||||||||||
| 23 | Masai, Rael Jepkogei, 2016 | 2015 | Kenya | Cross-sectional | 300 | Microscopy | Kato-Katz techniques | 24 (8%) | 39 (13%) | 45 (15%) | 90 (30%) | 3 (1%) | ||||||||||
| 24 | Y. J. Honkpehedji et al., 2017 | 2015 | Gabon | Cross-sectional | 678 | Microscopy | Kato-Katz techniques | 221 (33%) | 259 (38%) | 468 (69%) | ||||||||||||
Figure 2Funnel plot with pseudo 95% confidence limit of individual study estimates attributed with prevalence of malaria and helminthic co-infection among pregnant women in sub-Saharan Africa.
Figure 3Forest plot for the overall and country—specific pooled prevalence of malaria among pregnant women in sub—Saharan Africa.
Figure 4Forest plot for the overall and country-specific pooled prevalence of helminthic infection among pregnant women in sub-Saharan Africa.
Figure 5The proportion of Hookworm estimated from the overall helminthic infection among pregnant women in sub-Saharan Africa.
Figure 6The proportion of Ascaris lumbricoides estimated from the overall helminthic infection among pregnant women in sub-Saharan Africa.
Figure 7The proportion of Trichuris trichiura estimated from the overall helminthic infection among pregnant women in sub-Saharan Africa.
Figure 8The overall pooled estimate and country-specific prevalence of malaria and helminthic co-infection among pregnant women in sub-Saharan Africa.