Insecticide-treated net utilization and associated factors among pregnant women in Ethiopia: a systematic review and meta-analysis
Bibliographic record
Abstract
Background Malaria is a major public health problem in many developing countries, particularly in sub-Saharan Africa. The pregnant woman, fetus, and newborn infant are all at risk from malaria during pregnancy. Hence, insecticide-treated bed net (ITN) use is the most effective and advisable method for preventing malaria during pregnancy. Studies on the prevalence of ITN utilization among pregnant women in Ethiopia are inconsistently reported and highly varied. Therefore, this systematic review and meta-analysis aimed to estimate the pooled prevalence of ITN utilization and associated factors among pregnant women in Ethiopia. Methods A comprehensive search of databases such as PubMed, CINAHL, Web of Science, SCOPUS, Science Direct, Google, and Google Scholar was performed to find studies conducted in Ethiopia. All original observational studies that reported the prevalence of ITN utilization were identified and screened. The Newcastle-Ottawa scale tool was used to assess the quality of the studies. Data were extracted in Microsoft Excel 2010 format and analyzed using STATA Version 14. A random-effect meta-analysis model was utilized to estimate the pooled prevalence of ITN utilization. The statistical heterogeneity was checked using the I 2 test and subgroup analysis. The publication bias was assessed using funnel plots and Egger's regression test. The size of the pooled effect of the factors influencing the use of ITNs was estimated using an odds ratio (OR) with a 95% confidence interval (CI), and a P -value <0.05 was considered statistically significant. Results Twenty-nine cross-sectional studies with 13,957 study participants were included in this meta-analysis. The overall pooled prevalence of ITN utilization among pregnant women in Ethiopia was 51% (95% CI: 43–60). A statistically significant heterogeneity was observed across studies ( I 2 = 99.09%; P < 0.001). Being literate [OR = 2.93 (95% CI: 2.14–4.01)], rural residence [OR = 1.76 (95% CI: 1.37–2.26)], and having knowledge of ITN [OR = 4.13 (95% CI: 1.57–10.81)] were factors significantly associated with ITN utilization among pregnant women. Conclusion The utilization of ITNs among pregnant women was substantially lower than the national target, alarmingly highlighting the need for urgent and effective interventions. Maternal education status, place of residence, and knowledge of ITNs were independent predictors of ITN utilization. Health policymakers and programmers should design and implement the most effective strategies to scale up the utilization of ITNs by pregnant women and reduce malaria-related morbidity during pregnancy. Systematic Review Registration CRD42022304432.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.014 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".