Trends in perinatal mortality and its determinants in Ethiopia using longitudinal data from the demographic surveillance system (2009–2016)
Bibliographic record
Abstract
In Ethiopia, the reduction in perinatal mortality rates is still falling short of national and global targets set for 2030. Additionally, accurate recording is challenging, as many births occur at home. This study aimed to assess the trends and determinants of perinatal mortality using population-based longitudinal data from 2009 to 2016 across three Health and Demographic Surveillance Systems (HDSS) in Ethiopia: Gelgel-Gibe, Dabat, and Kilite-Awlaelo. Data on vital events and pregnancies were continuously collected at these HDSS sites. The study utilized follow-up data from prospective linked pregnancy and birth cohorts from January 2009 to December 31, 2016. Perinatal mortality was defined as deaths occurring from 28 weeks of gestation until six days after birth, measured per 1000 live births. Relevant health, demographic, and socioeconomic data were included in the analysis. Poisson regression was employed to assess factors associated with perinatal mortality. Out of 38,691 pregnancies that led to births, there were 1214 perinatal deaths (456 stillbirths and 758 early neonatal deaths), resulting in a perinatal mortality rate of 31 deaths per 1000 total births. The early neonatal death rate was higher, at 19.6 deaths per 1000 total births, compared to the stillbirth rate of 11.8 per 1000 total births. The perinatal mortality rate declined from 40.6 in 2009 to 29.1 per 1000 total births in 2016, reflecting an average annual rate reduction of 2.4%. Determinants of perinatal mortality included being a male newborn, multiple births, first-time pregnancies (primi-gravidity), lack of antenatal care visits, absence of delivery services, and residing in tropical zones. The primary causes of death were asphyxia, sepsis, and preterm birth. Overall, perinatal mortality rates were high in the three HDSS sites, with slow reductions over time and significant variations between them. Addressing the issue of stillbirths and improving the availability and quality of emergency obstetric care are crucial. Continuous home visits in rural communities to prevent stillbirths and newborn deaths, are also essential.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".