Maternal interventions to decrease stillbirths and neonatal mortality in Tanzania: evidence from the 2017-18 cross-sectional Tanzania verbal and social autopsy study
Bibliographic record
Abstract
BACKGROUND: Reduction of Tanzania's neonatal mortality rate has lagged behind that for all under-fives, and perinatal mortality has remained stagnant over the past two decades. We conducted a national verbal and social autopsy (VASA) study to estimate the causes and social determinants of stillbirths and neonatal deaths with the aim of identifying relevant health care and social interventions. METHODS: A VASA interview was conducted of all stillbirths and neonatal deaths in the prior 5 years identified by the 2015-16 Tanzania Demographic and Health Survey. We evaluated associations of maternal complications with antepartum and intrapartum stillbirth and leading causes of neonatal death; conducted descriptive analyses of antenatal (ANC) and delivery care and mothers' careseeking for complications; and developed logistic regression models to examine factors associated with delivery place and mode. RESULTS: There were 204 stillbirths, with 185 able to be classified as antepartum (88 [47.5%]) or intrapartum (97 [52.5%]), and 228 neonatal deaths. Women with an intrapartum stillbirth were 6.5% (adjusted odds ratio (aOR) = 1.065, 95% confidence interval (CI) 1.002, 1.132) more likely to have a C-section for every additional hour before delivery after reaching the birth attendant. Antepartum hemorrhage (APH), maternal anemia, and premature rupture of membranes (PROM) were significantly positively associated with early neonatal mortality due to preterm delivery, intrapartum-related events and serious infection, respectively. While half to two-thirds of mothers made four or more ANC visits (ANC4+), a third or fewer received quality ANC (Q-ANC). Women with a complication were more likely to deliver at hospital only if they received Q-ANC (neonates: aOR = 4.5, 95% CI 1.6, 12.3) or ANC4+ (stillbirths: aOR = 11.8, 95% CI 3.6, 38.0). Nevertheless, urban residence was the strongest predictor of hospital delivery. CONCLUSIONS: While Q-ANC and ANC4 + boosted hospital delivery among women with a complication, attendance was low and the quality of care is critical. Quality improvement efforts in urban and rural areas should focus on early detection and management of APH, maternal anemia, PROM, and prolonged labor, and on newborn resuscitation.
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".