Patterns of Mortality in the Elderly in Chi Linh, Hai Duong, Vietnam, Period 2004–2012
Bibliographic record
Abstract
Objective: This paper examines the trends of mortality in the elderly people in Chi Linh during period 2004–2012 and identifies a number of factors related to mortality in the elderly. Design: The longitudinal study method is used. The analyzed data is extracted from database of theDemographic—Epidemiologic Surveillance System (DESS) of Chililab. The data is collected from 7 communes/town of Chi Linh district, Hai Duong province during 2004–2012 with all elderly people. Descriptive statistical analysis and survival analysis using Kaplan Meier survival estimates and Cox regression models were used. The indirect standardization was used to compare between the mortality rate of the elderly in Chi Linh and the rates of those in some reference groups. Results: Mortality rate in elderly tend to decrease over the period 2004–2012. In all the time, mortality rate in elderly men is higher than that in the elderly women. Specific mortality rates by age groups have increased in both males and females. The increase Age specific mortality rates in males is higher than females. Indirect standardized mortality data for the elderly in 2009 in Chi Linh, Vietnam, Canada, the United States of America (USA) showed that elderly mortality rate in Chililab in 2009 was lower than that in elderly of Vietnam (standardized mortality ratio—SMR of elderly in Chililab is only by 75% in comparison with elderly of Vietnam), and also lower than that in elderly people in the US, and Canada. Cox regression analysis (multivariate models) show that with every 1 year older, the risk of death in elderly men increased by 9% and 12% increase in elderly female, for both men and women general risk increased by 10% (p < 0.05). Elderly with higher education levels, elderly with better family economic conditions; elderly living with wife/ husband have lower mortality risk than the other counterparts. Conclusions: The research results suggest some recommendations: Strengthening health care programs for elderly people with low education levels, poor economic conditions, and celibacy groups (the vulnerable groups).
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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".