Out-of-pocket costs and time spent attending antenatal care services: a case study of pregnant women in selected rural communities in Zinder, Niger
Bibliographic record
Abstract
BACKGROUND: Despite an official policy of exemption from health care costs, pregnant women in Niger still face some out-of-pocket costs (OPC) in addition to time costs when they attend antenatal care (ANC) services. We aimed to: 1) assess the OPC for pregnant woman attending ANC, 2) estimate the time spent to attend ANC and the opportunity cost of that time, and 3) assess how OPC and time spent to attend ANC affected ANC attendance. METHODS: Data were obtained from a quasi-experimental descriptive study carried out in the region of Zinder, Niger, which compared pre- and post-intervention cohorts of pregnant women (n = 1736 women who reported attending ANC during their current pregnancy). An ANC attendance score was developed to describe the timing of ANC attendance in regard to the WHO recommendation of attending 4 ANC sessions. OPC and time spent were evaluated separately for associations with ANC attendance using Spearman correlations. RESULTS: The mean (±SD) age of pregnant women was 25.0 ± 6.4 yr, 19.0% were ≤ 19 yr and 99.7% were in their second or third trimester of gestation at the time of the interview. Among those who were > 13 weeks and > 27 weeks of gestation, 4.0 and 74.4% had attended ANC during their first and second trimesters, respectively. The median (1st quartile (Q1), 3rd quartile (Q3)) ANC score was 0 (- 1, 0), reflecting that the majority of women failed to follow the WHO recommendation. More than half of the women (72.5%) experienced OPC related to ANC. The majority of women (> 80%) reported spending ~ 3 h for an ANC visit, including travel and waiting time. Time spent to attend ANC was not associated with ANC attendance score. Women who experienced OPC, and those who received iron folic acid (IFA) or long-lasting insecticide-treated bednets during an ANC visit, were more likely to have a higher ANC attendance score compared to those who did not. CONCLUSION: OPC and time spent were not identified as barriers to ANC visits, and IFA and long-lasting insecticide-treated bednets distribution could be used to motivate pregnant women to attend ANC. TRIAL REGISTRATION: The NiMaNu project was registered at www.clinicaltrials.gov as NCT01832688 . Registered 16 April 2013.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".