A comparison of practices, distributions and determinants of birth attendance in two divisions with highest and lowest skilled delivery attendance in Bangladesh
Bibliographic record
Abstract
BACKGROUND: Delivery by skilled birth attendants (SBAs) is strongly recommended to reduce maternal and neonatal mortality. The percentage of births attended by SBAs is low in Bangladesh (42% in 2014), though this rate varies widely by divisions, with the highest 58% in Khulna and only 27% in Sylhet. Comparing and critically analyzing the practices, distributions and determinants of delivery attendance in two divisions with the highest and lowest SBA attendance could help to understand the differences and to employ the findings of the high-performing division to the low-performing division. METHODS: The 7th Bangladesh Demographic and Health Survey (BDHS 2014) data were analyzed. After reporting the types of delivery attendants, logistic regression analyses were applied to calculate the odds ratios of determinants of deliveries attended by SBAs. RESULTS: SBAs attended 225 (58.6%) and 128 (27.4%) deliveries in Khulna and Sylhet, respectively. Khulna had higher birth attendance by qualified doctors (42.5%, n = 163) than Sylhet (15.8%, n = 74). Sylhet had higher attendance by traditional attendants (60.8%, n = 285) than Khulna (33.7%, n = 129). In both regions, attendance by community skilled birth attendants (CSBAs) was very low (< 1%). Khulna had higher percentages of women with higher education level, husbands' higher education, antenatal care (ANC) visits by SBAs, and higher wealth quintiles than Sylhet. In multivariable analyses, higher education level (adjusted odds ratio (AOR): 8.4; 95% confidence interval (CI): 1.9-36.7), ANC visits (AOR: 3.6; 95% CI: 2.0-6.5), family planning workers' visit (AOR: 3.0; 95% CI: 1.6-5.4), and belonging to richer (AOR: 2.6; 95% CI: 1.4-5.1) or richest (AOR: 3.8; 95% CI: 1.9-7.6) household wealth quintiles had significant positive associations with deliveries by SBAs in Sylhet. Similarly, ANC visits (AOR: 2.5; 95% CI: 1.4-4.6) and higher wealth quintile (AOR: 4.7; 95% CI: 1.9-11.5) were positive predictors in Khulna. CONCLUSIONS: The higher proportion of educated women and their husbands, wealth status and ANC visits were associated with higher SBA utilization in Khulna compared to Sylhet. Improvement of socioeconomic status, increasing birth attendant awareness programs, providing ANC services, and family-planning workers' visits could increase the proportion of SBA-attended deliveries in Sylhet Division. CSBA program should be re-evaluated for both divisions.
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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 | 0.000 |
| 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) | 0.002 | 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".