Factors associated with late seeking of prenatal care in the district of Lugela-Zambézia, Mozambique
Bibliographic record
Abstract
Abstract Objectives: to analyze the factors associated with late prenatal care attendance by pregnant women at the Lugela health center in the first quarter of 2023. Methods: cross-sectional survey conducted with 205 pregnant women. Data were collected using a structured questionnaire, supplemented with information from the pregnant woman’s prenatal records. R software version 4.2.0 was used to perform inferential statistical analyses, calculating odds ratios (ORs) and constructing a logistic regression model. Categorical variables were analyzed descriptively and tested for associations with late prenatal care attendance. Multivariate logistic regression considered a significance level of 5%, with early prenatal care attendance as the dependent variable. Results: 69.3% (n=142) of the pregnant women interviewed considered prenatal care initiation late. Late prenatal care seeking was significantly associated with education (p=0.034, OR=0.228, 95%CI= −2.915 to −0.046), age (p=0.040, OR=0.506, 95%CI= −1.369 to 0.006), and pregnancy planning (p=0.009, OR=0.451, 95%CI= −1.485 to −0.106). Conclusion: the factors associated with late prenatal care seeking were essentially obstetric, socioeconomic, and sociodemographic, highlighting the need for strategies targeted at more vulnerable groups.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".