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Record W4384008302 · doi:10.1371/journal.pone.0288240

Environmental exposures and adverse pregnancy outcomes in Ethiopia: A systematic review and meta-analysis

2023· review· en· W4384008302 on OpenAlexaboutno aff
Habtamu Demelash, B. Bogale, Abebe Beyene Hailu, Seid Tiku Mereta

Bibliographic record

VenuePLoS ONE · 2023
Typereview
Languageen
FieldEnvironmental Science
TopicEnergy and Environment Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePregnancyEnvironmental healthMeta-analysisLow birth weightCochrane LibraryBirth weightConfidence intervalSystematic reviewPublication biasObservational studyDemographyMEDLINEBiology

Abstract

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BACKGROUND: Maternal exposures to environmental hazards during pregnancy are key determinants of birth outcomes that affect health, cognitive and economic status later in life. In Ethiopia, various epidemiological evidences have suggested associations between environmental exposures such as household air pollution, cigarette smoking, and pesticide exposure and pregnancy outcomes such as low birth weight, preterm birth, and birth defects. OBJECTIVE: This review aimed at generating summarized evidence on the association between maternal exposure to environmental factors (household air pollution, cigarette smoking, and pesticide) and pregnancy outcomes (birth weight, preterm birth, and birth defects) in Ethiopia. METHOD: A systematic literature search was performed using PubMed, Google Scholar, and the Cochrane Library databases. All observational study designs were eligible for inclusion in the review. Quality assessment was conducted using the Newcastle-Ottawa Scale (NOS) quality assessment tools adopted for case-control and cross-sectional studies. The random-effects model was applied in computing the pooled estimates and their corresponding 95% confidence interval (CI). Funnel and Doi plots were used for detecting the potential publication bias. All statistical analyses were performed using comprehensive meta-analysis (CMA 2.0) and MetaXL version 5.3 software. RESULT: The pooled estimates revealed that prenatal biomass fuel use increased the risk of giving a low birth weight baby by twofold (OR = 2.10, 95% CI: 1.33-3.31), and has no separate kitchen increases the risk of having low birth weight baby nearly by two and half times (OR = 2.48, 95% CI: 1.25-4.92). Overall, using biomass fuel as the main energy source for cooking and /or having no separate kitchen from the main house is 2.37 times more likely to give low birth weight babies (OR = 2.37, 95% CI: 1.58-3.53). Active cigarette smoker women were 4 times (OR = 4.11, 95% CI: 2.82-5.89) more prone to have low birth weight babies than nonsmokers; and passive smoker women were 2.6 times (OR = 2.63, 95% CI: 1.09-6.35) more risked to give low birth weight babies. It was also estimated that active cigarette smoker women were nearly 4 times (OR = 3.90, 95% CI: 2.36-6.45) more likely to give preterm birth babies. Pesticide exposure during pregnancy also increases the risk of the birth defect 4 times (OR = 4.44, 95% CI: 2.61-7.57) compared with non-exposed pregnant women. CONCLUSION: Household air pollution from biomass fuel use, active and passive cigarette smoking, and pesticide exposures are significantly associated environmental risk factors for low birth weight, preterm birth, and birth defects in Ethiopia. Therefore, Pregnant and lactating women should be aware of these environmental hazards during pregnancy. Promoting clean energy and improved and efficient stoves at the household level will help to reduce household air pollution-related adverse health effects. TRIAL REGISTRATION: PROSPERO 2022: CRD42022337140.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.816
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.163
GPT teacher head0.294
Teacher spread0.131 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations24
Published2023
Admission routes1
Has abstractyes

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