INTRA- AND INTER-HOUSEHOLD DIFFERENCES IN ANTENATAL CARE, DELIVERY PRACTICES AND POSTNATAL CARE BETWEEN LAST NEONATAL DEATHS AND LAST SURVIVING CHILDREN IN A PERI-URBAN AREA OF INDIA
Bibliographic record
Abstract
Nearly a quarter of the world's neonatal deaths take place in India. The state of Uttar Pradesh alone accounts for one-quarter of all neonatal deaths in the country. In this study 892 married women aged less than 50 years living in a peri-urban area of Kanpur city in Uttar Pradesh were interviewed. In all, 109 women reported neonatal deaths. Characteristics of the last neonatal deaths of these 109 women were compared with those of the last surviving children. Also, characteristics of women who had a neonatal death were compared with those of 783 women who had no neonatal death. It was found that as compared with neonatal deaths, the last surviving children of the 109 women had: (a) significantly better antenatal tests during pregnancy, intake of iron/folic acid tablets and higher percentage of tetanus toxoid immunization; (b) safer delivery practices such as a higher percentage of institutional delivery, sterilization of instruments and application of antiseptic after removal of umbilical cord; (c) postnatal care, such as application of antiseptic to the navel and postnatal checkups; and (d) higher maternal age and greater birth spacing. Likewise, better antenatal care and safer delivery practices and postnatal care were observed among the 783 women with no neonatal deaths, when compared with women who had experienced neonatal death. The complexities of inter- and intra-household differences in health care are discussed. The paper concludes that to improve child survival general education and awareness regarding safe delivery should be increased. Continuing cultural stigmas and misconceptions about birth practices before, during and after childbirth should be an important part of the awareness campaigns.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".