Factors associated with skilled attendants at birth among married adolescent girls in Nigeria: evidence from the Multiple Indicator Cluster Survey, 2016/2017
Bibliographic record
Abstract
BACKGROUND: This study examines the factors associated with skilled birth attendants at delivery among married adolescent girls in Nigeria. METHODS: The study was a secondary data analysis of the fifth round of the Multiple Indicator Cluster Survey conducted between September 2016 and January 2017. Married adolescent girls aged 15-19 y who had live births in the last 2 y preceding the survey were included in the analysis. We performed univariate and multivariate logistic regression analyses with a skilled birth attendant (doctor, nurse or midwife) at delivery as the outcome variable and sociodemographic, male partner- and maternal health-related factors as explanatory variables. RESULTS: Of the 789 married adolescent girls, 387 (27% [95% CI=22.8-30.7]) had a skilled birth attendant at delivery. In the adjusted model, adolescent girls who were aged ≥18 y (ref: <18 y), primiparous (ref: multiparous), had antenatal care (ANC) provided by skilled healthcare providers (ref: no ANC), belonged to at least the poor and middle wealth index quintiles (ref: poorest), and resided in the south west zone (ref: north central), independently had a significantly higher likelihood of having a skilled birth attendant at delivery. CONCLUSIONS: Interventions that will reduce pregnancy in younger adolescent girls, poverty, and increase ANC provided by skilled attendants, are likely to improve deliveries assisted by skilled birth attendants among married adolescent girls in Nigeria.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".