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Record W4396606422 · doi:10.1371/journal.pone.0302560

Why does the number of antenatal care visits in Ethiopia remain low?: A Bayesian multilevel approach

2024· article· en· W4396606422 on OpenAlexaff
Daniel Atlaw, Tesfaye Getachew Charkos, Jeylan Kasim, Vijay Kumar Chatu

Bibliographic record

VenuePLoS ONE · 2024
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsCentre for Global Health Research
Fundersnot available
KeywordsMedicineDemographyPregnancyPediatricsEnvironmental health

Abstract

fetched live from OpenAlex

INTRODUCTION: Antenatal care (ANC) visit is a proxy for maternal and neonatal health. The ANC is a key indicator of access and utilization of health care for pregnant women. Recently, eight times ANC visits have been recommended during the pregnancy period. However, nearly 57% of women received less than four ANC visits in Ethiopia. Therefore, the objective of this study is to identify factors associated withthe number of ANC visits in Ethiopia. METHODS: A community-based cross-sectional study design was conducted from March 21 to June 28/2019. Data were collected using interviewer-administered questionnaires from reproductive age groups. A stratified cluster sampling was used to select enumeration areas, households, and women from selected households. A Bayesian multilevel negative binomial model was applied for the analysis of this study. There is an intra-class correlation (ICC) = 23.42% and 25.51% for the null and final model, respectively. Data were analyzed using the STATA version 17.0. The adjusted incidence risk ratio (IRR) with 95% credible intervals (CrI) was used to declare the association. RESULT: A total of 3915 pregnant women were included in this study. The mean(SD) age of the participants was 28.7 (.11) years. Nearly one-fourth (26.5%) of pregnant women did not have ANC visits, and 3% had eight-time ANC visits in Ethiopia. In the adjusted model, the age of the women 25-28 years (IRR:1.13; 95% CrI: 1.11, 1.16), 29-33 years (IRR: 1.15; 95% CrI: 1.15, 1.16), ≥34 years (IRR:1.14; 95% CrI: 1.12, 1.17), being a primary school (IRR: 1.22, 95% CrI: 1.21, 1.22), secondary school and above (IRR: 1.26, 95% CrI: 1.26, 1.26), delivered in health facility (IRR: 1.93; 95% CrI: 1.92, 1.93), delivered with cesarian section (IRR: 1.18; 95% CrI: 1.18, 1.19), multiple (twin) pregnancy (IRR: 1.11; 95% CrI: 1.10, 1.12), richest (IRR:1.23; 95% CrI: 1.23, 1.24), rich family (IRR: 1.34, 95% CrI: 1.30, 1.37), middle income (IRR: 1.29, 95% CrI: 1.28, 1.31), and poor family (IRR = 1.28, 95% CrI:1.28, 1.29) were shown to have significant association with higher number of ANC vists, while, households with total family size of ≥ 5 (IRR: 0.92; 95% CrI: 0.91, 0.92), and being a rural resident (IRR: 0.92, 95% CrI: 0.92, 0.94) were shown to have a significant association with the lower number of ANC visits. CONCLUSION: Overall, 26.5% of pregnant women do not have ANC visits during their pregnancy, and 3% of women have eight-time ANC visits. This result is much lower as compared to WHO's recommendation, which states that all pregnant women should have at least eight ANC visits. In this study, the ages of the women 25-28, 29-33, and ≥34 years, being a primary school, secondary school, and above, delivered in a health facility, delivered with caesarian section, multiple pregnancies, rich, middle and poor wealth index, were significantly associated with the higher number of ANC visits, while households with large family size and rural residence were significantly associated with a lower number of ANC visits in Ethiopia.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score0.148

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0030.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.274
Teacher spread0.253 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations3
Published2024
Admission routes1
Has abstractyes

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