Evidence map›Paper›PMID 38178972›Full record

ArticleAdvances in hematology2023

Anemia Prevalence and Risk Factors in Two of Ethiopia's Most Anemic Regions among Women: A Cross-Sectional Study.

Gebru Gebremeskel Gebrerufael, Bsrat Tesfay Hagos

Open access · goldAbstract read
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Article in Advances in hematology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.7field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 6 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 2 institutions in 1 country.

Gebru Gebremeskel GebrerufaelDepartment of Statistics, College of Natural and Computational Science, Adigrat University, Adigrat, Ethiopia.ORCID https://orcid.org/0000-0003-2795-8529
Bsrat Tesfay HagosDepartment of Statistics, College of Natural and Computational Science, Mekelle University, Mekelle, Ethiopia.
Adigrat University · ETMekelle University · ET

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: In Sub-Saharan African (SSA) nations, including Ethiopia, anemia is a significant public health issue. Ethiopia has continued to bear the enormous burden of anemia infections. Over time, the prevalence of anemia has significantly increased in Ethiopia. In addition, there is a paucity of literature and regional variations in the pace of increment expansion. Therefore, the primary goal of this study was to evaluate the prevalence of anemia and risk factors among women in Ethiopia's two most anemic regions. Methods: 2,519 women participated in a community-based cross-sectional study from January 18 to June 27, 2016. In order to determine the causes of anemia in women in two of Ethiopia's most anemic regions, an ordinal logistic regression model was taken into consideration. The applicability of the proportional odds test was evaluated using the chi-square test of the parallelism assumption. A Results: The overall prevalence rate of anemia was 56.8% (95% CI (54.8%-58.7%)). The chi-square test of the parallelism assumption indicated that the odds ratios were constant across all cut-off points of women's anemia levels at a 5% significance level ( Conclusions: Finally, the anemia burden was dangerously greater than the national average. The region, usage of contraceptives, being pregnant at the time, ANC follow-up, toilet facilities, parity, and marital status all had a substantial impact on anemia. Therefore, to lessen the prevalence of anemia in certain parts of Ethiopia, public health initiatives that improve maternal health service utilization are required, such as ANC follow-up to minimize parity.

Identifiers

PMID38178972
PMCPMC10766469
OpenAlexW4390338944

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.