Prevalence and predictors of anemia among pregnant women in Ethiopia: Systematic review and meta-analysis

Background In Ethiopia limited information is available regarding the prevalence and predictors of anemia in pregnancy. This systematic review and meta-analysis estimated the pooled prevalence of anemia among pregnant women in Ethiopia and also identified its predictors. Materials and methods The published primary studies were searched in the following electronic databases; PubMed/Medline, Google scholars, AJOL, and EMBASE. All primary studies published from 01/01/2010 to 30/05/2020 and written in English language were included without restriction on study setting and design. Critical appraisal of all available articles was done and extracted data was analyzed using STATA software version 14. The pooled prevalence of anemia was presented using a forest plot. The I2 statistical test for heterogeneity, and the Egger’s and Begg’s tests for publication bias were used. The relative risk was used to assess the association of predictor variables with anemia. Result After screening 274 articles, sixty studies were included in the analysis. The pooled prevalence of anemia among pregnant women was 26.4(95% CI: 23.1, 29.6). Sub-group analysis showed higher pooled prevalence from community-based studies than institutional-based studies. Factors that were protective against maternal anemia included urban residence, formal education and smaller family size. Short birth interval and not having antenatal care (ANC) are associated with a higher risk of maternal anemia. Women with low dietary diversity [RR: 2.61(95% CI, 1.85, 3.68)], mid-upper arm circumference (MUAC) less than 23 cm [RR: 2.35(95% CI, 1.53, 3.68)] and those not taking iron-folic acid [RR: 1.53(95% CI: 1.30, 1.81)] also had a higher risk of anemia. Conclusion Almost one in four pregnant women in Ethiopia had anemia. Being literate, living in urban areas with small family size and adequate birth spacing, as well as good dietary diversity are associated with a lower risk of anemia in pregnancy. Registration number (ID: CRD42020211054).

Details of the individuals, organizations, groups, companies or other legal entities who have funded or sponsored the review.
no fund for the review Grant number (s) State the funder, grant or award number and the date of award

* Conflicts of interest.
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Collaborators.
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* Review question.
State the review question(s) clearly and precisely. It may be appropriate to break very broad questions down into a series of related more specific questions. Questions may be framed or refined using PI(E)COS or similar where relevant.
what is the prevalence of anemia among pregnant women in Ethiopia what are the predictors of anemia among pregnant women in Ethiopia

* Searches.
State the sources that will be searched (e.g. Medline). Give the search dates, and any restrictions (e.g. language or publication date). Do NOT enter the full search strategy (it may be provided as a link or attachment below.) The articles for this systematic review and meta-analysis will be searched by electronic databases such as PubMed/MEDLINE, google scholars, HINARI, ScienceDirect, AJOL, and EMBASE. Further tracing of studies will be done by direct contact with the corresponding author of the existing article through email. The original research articles that reported the prevalence and predictors of anemia among pregnant women in different regions of Ethiopia and published until October 30, 2020, will be included. All accessible full-text articles written in the English language will be eligible with no restriction to study design.

URL to search strategy.
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Or provide a URL or link to the strategy. Do NOT provide links to your search results. https://www.crd.york.ac.uk/PROSPEROFILES/211054_STRATEGY_20200925.pdf Do not make this file publicly available until the review is complete

* Condition or domain being studied.
Give a short description of the disease, condition or healthcare domain being studied in your systematic review.
Anemia is a condition of a reduced number of circulating RBCs or insufficiency of the oxygen-carrying capacity of RBC to meet physiologic needs. Hemoglobin concentration is the most common hematological assessment method used to define anemia. World health organization (WHO) defined anemia for pregnant women as a hemoglobin concentration less than 110gm/l at sea level.
https://www.crd.york.ac.uk/prospero/#recordDetails 4/9 The prevalence of anemia among pregnant women in low and middle-income countries is 38.9% to 48.7%. The Ethiopian Demographic Health Survey 2016 (EDHS) showed the prevalence of anemia among pregnant women was 41%. Anemia during pregnancy is an important predictor of poor pregnancy outcomes such as low birth weight (LBW), prematurity, and stillbirth. It is also associated with maternal morbidities such as abortions, antepartum hemorrhage, postpartum hemorrhage, preeclampsia, and prolonged labor.
Multiple factors contribute to the occurrence of anemia during pregnancy in addition to physiologic changes. Dietary patterns such as meal frequency and low dietary diversity score and nutritional status of women during pregnancy may be an important predictor of anemia. Other factors associated with anemia are low socioeconomic status, malaria, helminthic infection, small birth interval and late initiation of ANC follow up. All the factors work in the interaction with one another.

* Participants/population.
Specify the participants or populations being studied in the review. The preferred format includes details of both inclusion and exclusion criteria.
Inclusion criteria All pregnant women included in the original studies irrespective of gestational age will be the population of the current review. Exclusion criteria Women whose information collected after delivery will be excluded.

* Intervention(s), exposure(s).
Give full and clear descriptions or definitions of the interventions or the exposures to be reviewed. The preferred format includes details of both inclusion and exclusion criteria.
Exposures(predictor variables) Sociodemographic histories such as advanced age, rural residence, no formal education, unemployment, and household size Obstetric and medical history such as low birth interval, being the third trimester, multigravida, no ANC uptake, malaria infection, helminthic infection, and HIV infection Nutrition status of women i.e MUAC below standard, not taking iron foliate, less frequency of meal per day than usual, and low dietary diversity. Other exposure variables will be included as they arise during the review, with justifications for their inclusion

* Comparator(s)/control.
Where relevant, give details of the alternatives against which the intervention/exposure will be compared (e.g. another intervention or a non-exposed control group). The preferred format includes details of both inclusion and exclusion criteria.
Comparative/ control groups for the current review will be women with better socioeconomic status i.e urban residence, having a formal education, getting employed than their counterparts. Women with the gestational age of first and second trimester, primigravida, women taking ANC service, women with no malaria, helminthic, and HIV infections will be also the control group. Moreover, pregnant women with normal MUAC measurement, took iron folate supplementation, women taking a frequent meal, and having high dietary diversity is considered in this group.

* Types of study to be included.
Give details of the study designs (e.g. RCT) that are eligible for inclusion in the review. The preferred format includes both inclusion and exclusion criteria. If there are no restrictions on the types of study, this should be stated. no restriction to study design

Context.
Give summary details of the setting or other relevant characteristics, which help define the inclusion or exclusion criteria.
The setting of the included primary study can be either community based or health facilities

* Main outcome(s).
Give the pre-specified main (most important) outcomes of the review, including details of how the outcome is defined and measured and when these measurement are made, if these are part of the review inclusion criteria.
https://www.crd.york.ac.uk/prospero/#recordDetails 5/9 Prevalence of anemia among pregnant women -anemia is defined as a hemoglobin concentration less than 110g/l at sea level.
predictors of anemia -predictors considered for the current review will be socio-demographic factors, obstetric and medical factors, nutritional status, and dietary pattern.

* Measures of effect
To show the association between predictor variables and outcome variables i.e anemia, odds ratio (OR) with a 95% confidence interval will be used.

* Additional outcome(s).
List the pre-specified additional outcomes of the review, with a similar level of detail to that required for main outcomes. Where there are no additional outcomes please state 'None' or 'Not applicable' as appropriate to the review none * Measures of effect none

* Data extraction (selection and coding).
Describe how studies will be selected for inclusion. State what data will be extracted or obtained. State how this will be done and recorded.
After fully addressing all the available articles, the duplicate will be removed using endnote. Then the title and abstract of all the studies will be reviewed. The full-text review will be done for relevant articles. Finally, articles with variables of interest will be included in the review.
The two authors will independently extract all necessary data by using Microsoft excel data extraction format. The data extraction format includes the author's name, year of publication, study design, sample size, and prevalence of anemia. The format will also include the prevalence of anemia among women with and without exposure. After completing data extraction, it will be checked for consistency and completeness. Then, the extracted data will be checked again by the three authors, and disagreement will be solved by tracing back to the original articles. Finally, incomplete data will be traced by direct contact with the principal author using an email address.

* Risk of bias (quality) assessment.
State which characteristics of the studies will be assessed and/or any formal risk of bias/quality assessment tools that will be used.
Quality of all the study will be assessed by critical appraisal using the Joanna Briggs Institute Meta-Analysis of Statistics Assessment and Review Instrument (JBI-MAStARI). This critical appraisal tool addresses the methodology of the study. It includes sample representativeness, sample adequacy, appropriate recruitment of participants, sufficient description of participants, use of standard measurement and its reliability, appropriate statistical analysis done with sufficient coverage of identified sample size, appropriate statistical analysis used, and subgroup or confounding variables identified. All the components of quality assessment will be discussed among the review team. The quality assessment of all articles will be done by two investigators independently. Any disagreement between them will be resolved by the negotiation of the third member of the review team. Studies with a score greater than or equal to 6 out of 10 will be considered as high quality and those studies with less than 6 out of 10 considered as low quality. Those studies with high quality will be included in the meta-analysis.

* Strategy for data synthesis.
Describe the methods you plan to use to synthesise data. This must not be generic text but should be specific to your review and describe how the proposed approach will be applied to your data.
If meta-analysis is planned, describe the models to be used, methods to explore statistical heterogeneity, and software package to be used.
Extracted data from Microsoft will be transported to STATA software version 14 for analysis. The general character of original articles such as the first author name, year of publication, study area, study setting, study design, and sample size will be presented using a table. The prevalence and its standard error of each original article will be considered to calculate the pooled prevalence of anemia. The pooled prevalence will be presented using a forest plot. The heterogeneity among the prevalence of anemia in the studies will be tested by the I² statistical test and a p-value less than 0.05 will be used to declare it. If there is https://www.crd.york.ac.uk/prospero/#recordDetails 6/9 significant heterogeneity between the studies, a random effect meta-analysis model will be used. Moreover, a meta-regression model will be used to detect possible sources of heterogeneity. The potential publication bias will be assessed by using Egger's correlation test at a 5% significance level.

* Analysis of subgroups or subsets.
State any planned investigation of 'subgroups'. Be clear and specific about which type of study or participant will be included in each group or covariate investigated. State the planned analytic approach.
To reduce the random variation between point estimates of the primary study, subgroup analysis will be done based on different regions of the country.

* Type and method of review.
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Type of review
Health area of the review

Language.
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There is an English language summary.

* Country.
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Other registration details.
Name any other organisation where the systematic review title or protocol is registered (e.g. Campbell, or The Joanna Briggs Institute) together with any unique identification number assigned by them.
If extracted data will be stored and made available through a repository such as the Systematic Review Data Repository (SRDR), details and a link should be included here. If none, leave blank.

Reference and/or URL for published protocol.
If the protocol for this review is published provide details (authors, title and journal details, preferably in Vancouver format) No I do not make this file publicly available until the review is complete