Maternal Tetanus Toxoid Vaccination in Benin: Evidence from the Demographic and Health Survey
Bibliographic record
Abstract
Tetanus toxoid vaccination is critical for improving maternal and child health. Yet, the prevalence and correlates of maternal tetanus toxoid vaccination coverage remain largely underexplored in Benin where infant and child mortality rates are high. Using the 2017−18 Benin Demographic and Health Survey, we apply logistic regression analysis to address this void in the literature. We find that overall maternal vaccination coverage is 69%. A range of demographic, health care, and socioeconomic factors are associated with maternal tetanus toxoid vaccination coverage. Women aged 20−34 (OR = 0.84, p < 0.05) and 35−49 (OR = 0.63, p < 0.01) are less likely to receive tetanus toxoid vaccination in comparison to those aged 15−19. Health care factors are also significantly associated with maternal tetanus toxoid vaccination, indicating that women who deliver at home (OR = 0.20, p < 0.001) and visit antenatal care fewer than eight times (OR = 0.62, p < 0.001) are less likely to receive tetanus toxoid vaccination than their counterparts who deliver in a health facility and visit antenatal care eight times or more. We also find that women with secondary (OR = 0.54, p < 0.05), primary (OR = 0.47, p < 0.01), and no education (OR = 0.47, p < 0.01) are less likely to receive tetanus toxoid vaccination compared to their counterparts with higher education. Based on these findings, we discuss several implications for policymakers.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".