Early-Neonatal, Late-Neonatal, Postneonatal, and Child Mortality Rates Across India, 1993-2021
Bibliographic record
Abstract
Importance: The global success of the child survival agenda depends on how rapidly mortality at early ages after birth declines in India, and changes need to be monitored to evaluate the status. Objective: To understand the disaggregated patterns of decrease in early-life mortality across states and union territories (UTs) of India. Design, Setting, and Participants: Repeated cross-sectional data from the 5 rounds of the National Family Health Survey conducted in 1992-1993, 1998-1999, 2005-2006, 2015-2016, and 2019-2021 were used in a representative population-based study. The study was based on data of children born in the past 5 years with complete information on date of birth and age at death. The analysis was conducted in February 2024. Exposure: Time and geographic units. Main Outcomes and Measures: Mortality rates were computed for 4 early-life periods: early-neonatal (first 7 days), late-neonatal (8-28 days), postneonatal (29 days to 11 months), and child (12-59 months). For early and late neonatal periods, the rates are expressed as deaths per 1000 live births, for postneonatal, as deaths per 1000 children aged at least 29 days and for child, deaths per 1000 children aged at least 1 year. These are collectively mentioned as deaths per 1000 for all mortalities. The relative burden of each of the age-specific mortalities to total mortality in children younger than 5 years was also computed. Results: The final analytical sample included 33 667 (1993), 29 549 (1999), 23 020 (2006), 82 294 (2016), and 64 242 (2021) children who died before their fifth birthday in the past 5 years of each survey. Mortality rates were lowest for the late-neonatal and child periods; early-neonatal was the highest in 2021. Child mortality experienced the most substantial decrease between 1993 and 2021, from 33.5 to 6.9 deaths per 1000, accompanied by a substantial reduction in interstate inequalities. While early-neonatal (from 33.5 to 20.3 deaths per 1000), late-neonatal (from 14.1 to 4.1 deaths per 1000), and postneonatal (from 31.0 to 10.8 deaths per 1000) mortality also decreased, interstate inequalities remained notable. The mortality burden shifted over time and is now concentrated during the early-neonatal (48.3% of total deaths in children younger than 5 years) and postneonatal (25.6%) periods. A stagnation or worsening for certain states and UTs was observed from 2016 to 2021 for early-neonatal, late-neonatal, and postneonatal mortality. If this pattern continues, these states and UTs will not meet the United Nations Sustainable Development Goal targets related to child survival. Conclusions and Relevance: In this repeated cross-sectional study of 5 time periods, the decrease in mortality during early-neonatal and postneonatal phases of mortality was relatively slower, with notable variations across states and UTs. The findings suggest that policies pertaining to early-neonatal and postneonatal mortalities need to be prioritized and targeting of policies and interventions needs to be context-specific.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".