https://orcid.org/0000-0001-5677-3692
Figures
Abstract
Background
Anemia in pregnancy has been associated with a number of adverse birth outcomes, such as low birth weight (LBW) or preterm birth (PTB). However, the evidence from primary studies on anemia in pregnancy with LBW and PTB is contentious. Moreover, a systematic review and meta-analysis to summarize these findings have not been conducted for Ethiopia. This study aimed to synthesize the best available evidence and quantify the strength and direction of the association of anemia in Ethiopia.
Methods
This review examined women with singleton pregnancies with low birth weight (LBW) and preterm birth (PTB). We retrieved studies from PubMed, Wiley, Cochrane databases, and Google Scholar from inception to February 2, 2024. The World Health Organization (WHO) defines anemia in pregnancy as a low blood haemoglobin (Hgb) concentration below 11 g/dl or a hematocrit level of < 33%. When the newborn’s weight was below 2500 g, LBW was considered. Preterm birth refers to the birth of a baby before 37 completed weeks of gestation. Meta-analysis was conducted using fixed and random effects models. The degree of heterogeneity, publication bias, and quality of the evidence of studies was assessed.
Results
There were 35 and 8 studies, with 14,319 and 3,265 respondents included in the meta-analysis for LBW and PTB, respectively. Neonates born to women who had normal Hgb levels were less likely to be LBW [pooled odds ratio (POR) = 0.22, 95% CI: (0.17, 0.28); I2 = 80%] (low-quality evidence). Neonates born to women with normal Hgb levels had a lower risk of PTB [POR = 0.22, 95% CI: 0.18, 0.28; I2 = 19%] (very low-quality evidence). The effect size estimate remained significant after sub-group analysis based on study design and province, except in two retrospective cohort studies for LBW.
Citation: Beressa G, Whiting SJ, Kuma MN, Lencha B, Belachew T (2024) Association between anemia in pregnancy with low birth weight and preterm birth in Ethiopia: A systematic review and meta-analysis. PLoS ONE 19(9): e0310329. https://doi.org/10.1371/journal.pone.0310329
Editor: Tebelay Dilnessa, Debre Markos University, ETHIOPIA
Received: March 12, 2024; Accepted: August 28, 2024; Published: September 12, 2024
Copyright: © 2024 Beressa et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors declared that they have no competing interests.
Abbreviations or acronyms: Hgb, Hemoglobin; LBW, Low Birth Weight; PTB, Preterm birth
Introduction
Low birth weight (LBW), preterm birth (PTB), and stillbirth (fetal death at or after 28 gestational weeks) are among other adverse birth outcomes. These are still major public health issues worldwide, particularly in low and middle-income countries (LMICs) [1]. Low birth weight is defined by the World Health Organization (WHO) as a weight at birth of less than 2.5 kg (5.5 lb), irrespective of gestational age. Globally, the prevalence of LBW in 2015 was 14.6%. In 2015, an estimated 20.5 million live births were LBW, with 91% from LMICs, particularly Southern Asia (48%) and SSA (24%) [2].
Low birth weight is closely associated with fetal and neonatal mortality and morbidity, impaired growth and cognitive development, and chronic diseases later in life. Globally, an estimated 13.4 million newborn babies were born preterm (< 37 weeks) in 2020. The most significant gaps in national routine data for preterm births are found in Southern Asia and SSA, which also have the largest estimated preterm birth burden [3]. Ethiopia is one of the LMICs in SSA with high neonatal mortality [4]. In Ethiopia, the incidence of PTB ranges from 4.4 to 25.9% [5–9]. The pooled prevalence of PTB is 10.48% [10].
The WHO defines anemia in pregnancy as a low blood hemoglobin concentration, i.e., below 11 g/dl, or a hematocrit level of less than 33% [11]. Globally, anemia is one of the major public health concerns that affects 32.4 million (38.2%) pregnant women around the world [11, 12]. Worldwide, it has been reported that nearly 510,000 maternal deaths occur per year associated with childbirth or early post-partum. Approximately 20% of maternal deaths are caused by anemia, with the majority of deaths occurring in LMICs [13]. In Africa, prenatal anemia was detected in 48.7% of mothers [14]. Anemia during pregnancy has been reported to cause LBW, PTB, as well as perinatal, neonatal, and maternal mortality [15–21]. However, other studies report no association between maternal anemia with LBW or PTB [6, 22, 23], and, notably, these studies were conducted in SSA.
Nearly one-quarter of Ethiopian women in the reproductive age group are anemic and 29% of them are pregnant [24, 25]. The magnitude of prenatal anemia varies from 7.9 to 56.8% in Ethiopia [26–30]. A meta-analysis carried out in Ethiopia revealed that the pooled prevalence of anemia among pregnant women was 31.66% [31]. Those studies carried out in Ethiopia revealed that there was an association between anemia in pregnancy and LBW or PTB [32–41]. Nevertheless, the evidence from primary studies on anemia in pregnancy with LBW and PTB is equivocal. Therefore, this study aimed to synthesize the best available evidence and quantify the strength and direction of the association between anemia in pregnancy with low birth weight and preterm birth in Ethiopia.
Methods
Study design
This systematic review and meta-analysis were prepared using PRISMA reporting guidelines [42] (S1 Table). The systematic review was conducted following the Joanna Briggs Institute (JBI) methodology for systematic reviews of association evidence [43, 44]. The meta-analysis was prospectively registered in PROSPERO 2020: CRD42020207520 (available at https://www.crd.york.ac.uk/PR). The initial anticipated inception and completion times were updated.
Eligibility criteria
Population.
Studies of women where LBW and PTB data were provided were included in the review to determine the singleton pregnancy relationship with anemia in pregnancy and subsequent LBW and PTB. Multiple births were excluded, as were articles that were not full papers, reviews, qualitative studies, books, conferences, and proceedings, as well as animal studies.
Outcomes of interest
Low birth weight (LBW) and preterm birth (PTB) were the outcome variables. The gestational age (GA) was assessed using LMP and/or early ultrasound [45].
Types of studies
The current review included observational studies (cross-sectional, case-control, retrospective, and prospective cohort studies) that reported an association between anemia or hemoglobin levels in pregnancy and subsequent LBW and PTB. This review considered all studies conducted in health facilities or community-based settings in Ethiopia.
Search strategy
The search strategy aimed to locate both published and unpublished studies at the preprint stage that were written in English. The search was conducted from the inception of scientific databases until February 02, 2024. A three-step search strategy was utilized, with an initial search of PubMed undertaken for the analysis of text words, followed by a search using keywords and index terms across PubMed, Wiley Online Library, Cochrane Library, and Google Scholar, and eventually an examination of all articles retrieved for critical appraisal.
Various Boolean operators and terms were used to develop the search strategies. Specifically, to increase the comprehensiveness of the search results and fit the advanced PubMed database, medical subject headings (MeSH), key terms, and the search strategy were used. The search strategy was tailored to each scientific database to employ the appropriate search terms and available resources (S2 Table).
Study selection
Following the search, all identified citations were collated and uploaded into Endnote version X9 (Thomson Reuters, Philadelphia, PA, USA) software, and duplicates were removed. Two reviewers (GB and MNK) independently screened titles and abstracts against the inclusion criteria for the review. Potentially relevant studies were retrieved in full, and their citation details were imported into the JBI System for the Unified Management, Assessment, and Review of Information (JBI SUMARI) (JBI, Adelaide, Australia), https://www.jbisumari.org/). The full texts of selected citations were assessed in detail against the inclusion criteria by two or more independent reviewers. Reasons for the exclusion of papers in the full text that did not meet the inclusion criteria were recorded. Any disagreements that arose between the reviewers at each stage of the selection process were resolved through discussion, or with an additional reviewer/s. The results of the search and the study inclusion process were reported in full in the final systematic review and presented in the Preferred Reporting Items for Systematic Reviews and Meta-analyses (Fig 1 [46]).
PRISMA 2020 flow diagram of association between anemia in pregnancy with low birth weight and preterm birth in Ethiopia, from inception to February 2, 2024.
Missing data handling
We handled missing data by carefully considering the types of missing data and conducting sensitivity analyses.
Assessment of methodological quality
Two independent reviewers critically appraised eligible studies at the study level using standardized critical appraisal instruments for cross-sectional studies, case-control studies, and cohort studies [44, 47] (S3 Table) and quality assessment (QA) (Tables 1–4 in S3 Table). Studies that did not meet a certain quality threshold were excluded, and reasons for their exclusion were provided in the (S4 Table). Any discord that arose between the reviewers was resolved through discussion or with a third reviewer. Studies were considered low-risk when they scored 50% or above on the quality of assessment indicators [48].
Data extraction
Two independent reviewers (GB and MNK) extracted data from papers included in the review using the standardized data extraction tool for association available in JBI SUMARI software (available at https://www.jbisumari.org/) and the JBI manual for evidence synthesis [47]. The data extraction included specific details about the study: region, study type, sample size, outcomes measured, and main results for cross-sectional studies; for case-control studies: province or region, context, participant characteristics, sample size, exposures or variables measured, and main results; whereas for cohort studies: study, region, study type, participants, sample size, outcome assessed, and main results (Table 1). Any disagreements that arose between the reviewers were resolved through discussion or with a third reviewer.
Data synthesis and analysis
Where possible, quantitative data were pooled in a statistical meta-analysis using Review Manager (RevMan) version 5.3 and STATA software version 14. A DerSimonian and Laird’s random and fixed effects model [49, 50] using the Mantel-Haenszel method was used to evaluate the significance of the results for LBW and PTB. The effect size was expressed as an odds ratio (OR) along with 95% confidence intervals (CI) around the summary estimate for dichotomous outcomes (LBW and PTB). Heterogeneity was assessed statistically using Tau2, the standard chi-squared (Cochran Q test), and Higgins I2 (I squared) tests. The conservative significance threshold of a p-value of < 0.1 for the Cochrane’s Q test was used to determine heterogeneity [51]. The I2 test statistics of 25%, 50%, and 75% were declared as low, moderate, and high heterogeneity, respectively [52–55]. Higgins’ I2 test statistic describes the percentage of variability in point estimates that is due to heterogeneity rather than sampling error [54]. Evidence of publication bias was also assessed visually by inspecting the funnel plot [56, 57] and more objectively using Harbord’s test at a 5% level of significance [50, 58]. A p-value of < 0.05 was used to declare statistical significance. The Duval and Tweedie nonparametric trim and fill analysis [59] was not performed to deal with publication bias, as there was no evidence of a risk of publication bias among the included studies. The Stata commands ’metabias’ and ’metaninf’ were used to deal with publication bias and sensitivity analysis, respectively. We prudently carried out subgroup analysis based on study design (cross-sectional, case-control, retrospective, and prospective cohort) and regions.
Sensitivity analyses using the leave-one-out approach were used to assess the robustness of the study results [60]. The findings of the meta-analysis were displayed on a forest plot. The quality of evidence for studies was assessed using the Grading of recommendation, assessment, development, and evaluation (GRADE) pro guideline development tool (GDT) software version 3.6.1 developed by the (GRADE) working group [61]. The GRADE system rates the quality of evidence as varying from high, moderate, low, and very low in five domains: risk of bias (RoB), inconsistency, indirectness, imprecision, and publication bias [62, 63].
Results
Description of studies
The database search yielded a total of 6,605 records (Fig 1). After the removal of duplicates, 1,547 potentially relevant papers were retained for further review. After screening titles and abstracts, 45 papers were retained for full-paper examination. Of these, six full-text papers were excluded as they did not meet the inclusion criteria (i.e., two papers were excluded because they did not relate to outcome variables; four papers due to inadequate information on exposure variables; and two papers because of the low quality of the studies). A total of 45 papers were retained for methodological quality assessment and were critically appraised by the independent reviewers (S3 Table) and QA-Tables 1–4 in S3 Table. Subsequently, two papers [64, 65] were excluded after critical appraisal. Finally, thirty-five and eight studies contained 14,319 and 3,265 study subjects whose pregnancies were analysed for LBW and PTB, respectively, that were retained for meta-analysis (Fig 1). The included studies in the meta-analyses were eighteen cross-sectional studies [32–35, 37–40, 66–75], thirteen case-control studies [41, 76–87], two retrospective cohort studies [88, 89], and two prospective cohort studies [90, 91] that reported LBW. Many studies that described LBW were from Ethiopian regions: twelve Amhara studies [32–34, 38, 40, 69, 70, 72, 75, 78, 79, 81], ten Southern Nations, Nationalities, and Peoples’ Region (SNNPR) studies [37, 41, 66, 68, 71, 77, 83, 86, 88, 89], four Addis Ababa studies [35, 76, 82, 87], four Oromia studies [80, 84, 90, 91], three Tigray studies [39, 67, 85], one Harari study [74], and one Benishangul-Gumuz study [73]. Four cross-sectional studies [38, 68, 92, 93], two case-control studies [36, 85], and two prospective cohort studies [90, 94] were analysed for PTB, and there were two studies [36, 38] from Amhara, one study [68] from SNNPR, one study [90] from Oromia, three studies [85, 92, 94] from Tigray, and one study [93] from the Somali region, Ethiopia, and all reported PTB (Table 1).
Methodological quality analysis
We endeavoured to include studies that fulfilled a high methodological quality standard by requiring that they meet at least 50% of the particular requirements for each study design checklist out of 100. Based on the results of the JBI-MAStARI assessment tool critical appraisal, the methodological quality of the included studies had a low RoB. However, two prospective cohort studies were excluded because of poor methodological quality.
For cross-sectional studies, some authors did not provide clear inclusion and exclusion criteria before the recruitment of study subjects [34, 39, 68, 72, 73]. The authors did not also describe the method of measuring exposures [39]. Besides, the authors did not use standard criteria for the measurement of the condition [68]. Moreover, the authors did not measure the outcome validly and reliably [33, 39, 68, 69, 93] (S3 Table) and QA-Table 1 in S3 Table.
For cases and controls, when the authors did not assess the exposure in a standard, valid, and reliable way or did not assess the outcomes in a standard, valid, and reliable way, the study was excluded [83] (S3 Table) and QA-Table 2 in S3 Table.
For cohort studies, some authors did not state strategies to address incomplete follow-up [94] (S3 Table) and QA-Table 3 in S3 Table. Nevertheless, two prospective cohort studies [64, 65] were excluded from the meta-analysis as they did not meet the minimal inclusion criteria. The studies were deemed to have insufficient information concerning the exposure of interest. Moreover, the reasons for the failure to follow up were not described and explored clearly. Furthermore, strategies to address incomplete follow-up were not delineated (S3 Table) and QA-Table 4 in S3 Table.
Meta-analysis
Relationship between anemia in pregnancy and low birth weight
The meta-analysis results of 35 studies revealed that neonates born to women who had normal Hgb levels were less likely to have LBW [Pooled odds ratio (POR) = 0.22, 95% CI: (0.17 to 0.28)]. The I2 statistic revealed that there was statistical evidence of heterogeneity among studies, and the heterogeneity was statistically significant (I2 = 80%, P < 0.00001) (Fig 2).
Publication bias assessment
The risk of publication bias was assessed using a visual inspection of funnel plots. The funnel plots appeared substantially asymmetrical (i.e., tilted to the left side) (S1 Fig). However, Harbord’s test (P-value = 0.06) revealed that there was no statistical evidence of publication bias.
Subgroup analysis for low birth weight
Subgroup analysis based on study design.
The present subgroup analysis of 18 cross-sectional studies indicated that the odds of neonates born to women who had normal Hgb levels were [POR = 0.20, 95% CI: (0.16 to 0.25)] less likely to have LBW. The I2 test of a meta-analysis of eighteen cross-sectional studies indicated that there was heterogeneity among studies, and the heterogeneity was statistically significant (I2 = 48%, P = 0.01).
Similarly, there were 13 case-control studies in which there was a relationship between anemia in pregnancy and LBW [POR = 0.26, 95% CI: (0.15 to 0.47)]. The I2 test of a meta-analysis revealed that there was high heterogeneity, and the heterogeneity was statistically significant (I2 = 90%, P < 0.00001).
Likewise, there were two prospective cohort studies in which there was a relationship between anemia in pregnancy and LBW [POR = 0.11, 95% CI: (0.07 to 0.19)]. The I2 test of a meta-analysis revealed that there was no heterogeneity, and the heterogeneity was not statistically significant (I2 = 0%, P = 0.69). Nevertheless, there were two retrospective cohort studies in which there was no relationship between anemia during pregnancy and LBW [POR = 0.57, 95% CI: (0.20 to 1.66)], I2 = 80% (P = 0.02).
The overall effect estimates of the meta-analysis indicated that the odds of infants born to women who had normal Hgb levels were less likely to have LBW [(POR = 0.23, 95% CI: (0.18 to 0.29)]. The I2 test statistic of the overall effect estimates of the eighteen cross-sectional studies, thirteen case-control studies, two retrospective cohort studies [88, 89], and two prospective cohort studies [90] indicated that there was statistical evidence of heterogeneity among studies and the heterogeneity was statistically significant (I2 = 81%, P < 0.00001) (S2 Fig).
Subgroup analysis based on study province
The subgroup analysis of the current twelve studies revealed that infants born to women who had normal Hgb levels were less likely to be LBW [POR = 0.26, 95% CI: (0.18 to 0.37)], (I2 = 71%, P < 0.0001) in Amhara, [POR = 0.22, 95% CI: (0.12 to 0.43)], (I2 = 92%, P < 0.00001) in SNNPR region, [POR = 0.32, 95% CI: (0.18 to 0.56)], (I2 = 54%, P = 0.09) in Addis Ababa city, [POR = 0.19, 95% CI: (0.10 to 0.38)], (I2 = 70%, P = 0.02) in Oromia, [AOR = 0.13, 95% CI: (0.07 to 0.23)], I2 = 46% (P = 0.16) in Tigray, [POR = 0.29, 95% CI: (0.18 to 0.47)] in Harari region, and [POR = 0.13, 95% CI: (0.07 to 0.25)] in Benishangul-Gumuz region. The overall effect sizes of the included studies by regions were [POR = 0.23, 95% CI: (0.18 to 0.29)], I² = 81% (P < 0.00001) (S3 Fig).
Relationship between anemia in pregnancy and preterm birth
The present meta-analysis findings of eight studies indicated that the odds of neonates born to women who had normal Hgb levels were less likely to have PTB [POR = 0.22, 95% CI: (0.18, 0.28)]. The I2 test indicated that there was low heterogeneity among studies, and the heterogeneity was statistically significant (I2 = 19%, P = 0.28) (Fig 3).
Subgroup analysis based on study design
The sub-group analysis employing the fixed effect model of four cross-sectional studies revealed that the neonates born to women who had normal Hgb levels were less likely to have PTB [POR = 0.21, 95% CI: (0.16 to 0.27)]. The I2 test indicated that there was low heterogeneity among studies, and the heterogeneity was statistically significant (I2 = 39%, P = 0.18). Similarly, a sub-group analysis of two case-control studies indicated that the neonates born to women who had normal Hgb levels were less likely to have PTB [POR = 0.20, 95% CI: (0.14 to 0.29)]. Nonetheless, the I2 test indicated that there was no heterogeneity among studies, and that the heterogeneity was not statistically significant (I2 = 0%, P = 0.76).
A sub-group analysis of two prospective cohort studies revealed that the neonates born to women who had normal Hgb levels were less likely to have PTB [POR = 0.28, 95% CI: (0.18 to 0.43)]. The I2 test indicated that there was high heterogeneity among studies, and the heterogeneity was not statistically significant (I2 = 19%, P = 0.14). The overall effect sizes of the four cross-sectional, two case-control, and two prospective cohorts of the included studies were [POR = 0.22, 95% CI: (0.18 to 0.26)]. The I2 test indicated that there was low heterogeneity among studies, and the heterogeneity was not statistically significant (I2 = 19%, P = 0.28) (S4 Fig).
Subgroup analysis based on study province
The sub-group analysis of the fixed effect model studies revealed that the neonates born to women who had normal Hgb levels were less likely to have PTB [POR = 0.19, 95% CI: (0.13, 0.28)], (I2 = 0%, P = 66) in Amhara, [POR = 0.29, 95% CI: (0.16 to 0.52)] in SNNPR region, and [POR = 0.26, 95% CI: (0.19 to 0.37)], (I2 = 44%, P = 0.17) in Tigray region, whereas the overall effect sizes of the included studies by regions were [POR = 0.22, 95% CI: (0.18 to 0.26)], I² = 19%; (P = 0.28) (S5 Fig).
Sensitivity analysis of the included studies for anemia in pregnancy with low birth weight and preterm birth of neonates, Ethiopia
To assess the robustness of the study results, we meticulously performed sensitivity analyses using the leave-one-out approach. Nonetheless, there was no change in the overall (pooled) effect estimate (S6 and S7 Figs).
Quality of evidence
The quality of the evidence in the included studies for LBW and PTB was rated as low and very low, respectively. The major reasons for downgrading the quality of evidence might be RoB and high heterogeneity among included studies, as well as the relatively smaller sample size (Table 2).
Discussion
Our review identified that newborns born to women with anemia during pregnancy had a higher risk of LBW and PTB. The present finding that neonates born to women who had normal Hgb levels were 78% less likely to have LBW is in agreement with other systematic reviews and meta-analyses carried out in other countries [19, 21, 95–99] and [100]. However, several published meta-analyses showed either no effect of maternal anemia during pregnancy on LBW [101] or that high maternal Hgb was not significantly associated with LBW [21]. The possible reasons for differences in results could be because of variation in the socio-demographic characteristics of study subjects.
The present sub-group analyses of 18 cross-sectional studies revealed that the odds of neonates born to women who had normal Hgb levels were 80% less likely to be LBW. Likewise, the subgroup analysis of 13 case-control studies indicated that the odds of neonates born to women who had normal Hgb levels were 74% less likely to be LBW. This is in agreement with other studies [19] and [95]. However, the sub-group meta-analysis results of two retrospective cohort studies indicated that there was no relationship between normal Hgb during pregnancy and LBW, which is different from a meta-analysis [19]. The possible explanation might be because of the low power to detect the association using this design.
The overall effect estimates of the meta-analysis based on study designs indicated that the odds of infants born to women who had normal Hgb levels were 78% less likely to be LBW. The I2 statistic test of the overall effect estimates of the 18 cross-sectional, 13 case-control, two retrospective, and two prospective cohort studies indicated that there was statistical evidence of heterogeneity among studies and that the heterogeneity was statistically significant. The high heterogeneity among included studies could be attributed to differences in study subjects’ characteristics such as health, socioeconomic status, and nutritional status [102, 103].
The current systematic review and meta-analysis identified eight studies in which the odds of neonates born to women who had normal Hgb levels were 78% less likely to be PTB. This study’s findings agreed with those of other studies [95, 96, 101]. Likewise, the present result supports the WHO anemia policy brief [104]. The possible explanation might be because of the variety of study settings with low access to quality health care and the time difference between the reviews, in which the current review also included recent studies among study subjects. Moreover, this finding agreed with other meta-analyses [100] conducted in LMICs, which revealed that anemic women are associated with increased odds of giving PTB. This could be because anemia impairs oxygen transportation, resulting in placental insufficiency, which will ultimately result in PTB. However, the current study’s result is not in agreement with a meta-analysis carried out on HICs [20]. This is not unexpected, as in these countries there is likely to be good access to quality health care.
The mechanisms underlying the link between low maternal haemoglobin and birth outcomes are complex and multifactorial, and may include nutritional deficiencies (e.g., iron, vitamin A, folic acid, or vitamin B12 deficiency), infectious causes (e.g., malaria, schistosomiasis, hookworm infection, HIV), hemoglobinopathies (sickle cell anaemia, thalassemia), and inflammation [105]. Iron deficiency has been linked to up to 75% of all kinds of anaemia during pregnancy [105]. Iron deficiency is caused by inadequate food intake combined with increased systemic demand, poor absorption, or blood loss. Iron deficiency varies by geography, with a higher frequency in low-income nations. Iron needs and absorption vary throughout pregnancy, with lower requirements in the first trimester and a roughly three-fold rise in the third trimester due to increased maternal red blood cell mass expansion, placental demand, and foetal development [106]. Iron deficiency anemia (IDA) is related to reduced oxygen supply to the tissues, weariness, an increased risk of infection, and heart failure in severe cases [107]. Iron deficiency is caused by inadequate food intake combined with increased systemic demand, poor absorption, or blood loss. Iron deficiency varies by geography, with a higher frequency in low-income countries.
Iron needs and absorption vary throughout pregnancy, with lower requirements in the first trimester and a roughly three-fold rise in the third trimester due to increased maternal red blood cell mass expansion, placental demand, and foetal development [106]. IDA is related to reduced oxygen supply to the tissues, weariness, an increased risk of infection, and heart failure in severe cases [107]. IDA in children is linked to poor prenatal outcomes such as LBW and PTB. Although iron insufficiency has been generally linked to dietary factors (e.g., low iron intake or poor iron absorption), numerous non-nutritional causes should be considered as well. Inflammation (due to viral causes or low-grade inflammation exhibited in overweight or obese individuals) may potentially affect iron absorption and metabolism by increasing hepcidin levels, resulting in anemia of inflammation despite adequate iron reserves [106].
Strengths and limitations of the review
The strengths of this review were its comprehensive search strategy and having at least two reviewers participate in each step of the review process. The heterogeneity and publication bias, as well as the quality of evidence for each outcome, were assessed. This systematic review and meta-analysis were based on studies carried out in Ethiopia, but a limitation is that no data was found in the three provinces. We found high heterogeneity within the included studies. Further, the search strategy was limited to studies published in the English language and could be subject to reporting bias. As the included studies were observational (cross-sectional, case-control, and cohort study designs), the outcome of interest might be affected by other confounding variables, such as sample size, dwelling, and study year, so the findings could not establish cause-and-effect relationships. Not all studies accounted for altitude when assessing hemoglobin levels. Some measurements for Hgb level were taken after delivery, and this may not be indicative of anemia in pregnancy and LBW and PTB.
Conclusion
Neonates born to women who had normal hemoglobin (Hgb) levels were less likely to be LBW or PTB. The quality of evidence for studies was rated low to very low. Our findings highlight the importance of locally appropriate, priority interventions to improve maternal Hgb status during pregnancy to reduce the risk of LBW and PTB. Investing in maternal Hgb status is also a key strategy to diminish LBW and PTB. Therefore, to prevent maternal anemia, pregnant women are counselled to get ferrous folate supplements and iron-rich diets. Moreover, deworming pregnant women in the third trimester is crucial for the prevention and control of anemia.
Recommendations for practice and research
It is imperative to identify which interventions are promoted to address maternal anemia, LBW, and PTB. Low-quality evidence indicates optimal nutrition intervention during which enhancing Hgb levels during pregnancy is effective in decreasing LBW. Very low-quality evidence reveals that investing in maternal Hgb status would be more effective in decreasing PTB. Interpretation should be given due attention because of methodological quality and high heterogeneity (high variations between and within studies). Further research, such as randomized control trials, is needed to establish strong evidence or ensure effective evidence-based food and nutrition policy.
Acknowledgments
We express our gratitude to Dr. Zachary Munn and Dr. Timothy Barker, Directors of the Evidence Synthesis Center, Joanna Briggs Institute (JBI), the University of Adelaide, Australia, who enabled us to conduct this review.
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