A Longitudinal Analysis of the Mortality Spectrum of Children under 5 Years from 1990 to 2015 in Hubei Province of China
Bibliographic record
Abstract
OBJECTIVES: This research analyzed trends of the mortality spectrum resulted from dynamics of the health care service for children under 5 years.METHODS: It was sampled 23 surveillance sites to establish a population-based surveillance network for children under 5 years by implementing a multistage randomized, stratified and cluster sampling since 1990 in Hubei province of China.RESULTS: Among children under 5 years, the mortality rates of pneumonia, birth asphyxia, preterm birth/low birth weight and accidental asphyxia declined from 12.9, 6.6, 4.3 and 3.5 in 1990 to 0.9, 0.7, 1.1 and 0.7 per 1,000 live births in 2015 respectively, and manifested a distinguished milestone at which pneumonia and birth asphyxia had been replaced by preterm birth/low birth weight after 2005 (P<0.05). The death proportions of pneumonia and birth asphyxia decreased from 22.2% and 11.4% in 1990 to 10.3% and 7.7% in 2015, while the death proportions of preterm birth/low birth weight and accidental asphyxia increased from 7.4% and 6.0 % in 1990 to 12.9% and 8.6% in 2015 accordingly. The proportions of clinical diagnosis, emergence treatment and death place at the county/district hospitals increased from 9.0%, 27.4% and 28.7% in 1990 to 75.5%, 67.7% and 60.4% in 2015, and had the significant differences between 1990 and 2015 in Hubei province (P<0.01).CONCLUSIONS: It was suggested that the trends of the mortality spectrum were mainly due to the improvement of the health care service for children under 5 years in Hubei province.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".