Institutional setting and wealth gradients in cesarean delivery rates: Evidence from six developing countries
Bibliographic record
Abstract
BACKGROUND: The influence of the type of institutional setting on cesarean delivery is well documented. However, the traditional boundaries between public and private providers have become increasingly blurred with the commercialization of the state health sector that allows providers to tailor the quantity and quality of care according to patients' ability to pay. This study examined wealth-related variations in cesarean rates in six lower- and upper-middle income countries: the Dominican Republic, Egypt, Guatemala, Jordan, Pakistan, and the Philippines. METHODS: Demographic and Health Survey data and a hierarchical regression model were used to assess wealth-related variations in cesarean rates in government and private hospitals while controlling for a wide range of women's socioeconomic and risk profiles. RESULTS: The odds of undergoing a cesarean delivery were greater in private facilities than government hospitals by 58% in Jordan, 129% in Guatemala, and 262% and 279% in the Dominican Republic and Egypt, respectively. Additional analysis involving interactions between the type of facility and wealth quintiles indicated that wealthier women were more likely to undergo a cesarean birth in government hospitals than poorer women in all countries but the Dominican Republic and Guatemala. Moreover, in both Egypt and Jordan, differences in cesarean rates between government and private hospitals were smaller for the wealthier strata than for the nonwealthy. CONCLUSIONS: Large wealth-related variations in the mode of delivery across government and private hospitals suggest the need for well-developed guidelines and standards to achieve a more appropriate selection of cases for cesarean delivery.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 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".