Life expectancy, death, and disability in Haiti, 1990-2017: a systematic analysis from the Global Burden of Disease Study 2017
Bibliographic record
Abstract
OBJECTIVE: To investigate the magnitude and distribution of the main causes of death, disability, and risk factors in Haiti. METHODS: We conducted an ecological analysis, using data estimated from the Global Burden of Disease Study 2017 for the period 1990-2017, to present life expectancy (LE), healthy life expectancy (HALE) at under 1-year-old, cause-specific deaths, years of life lost (YLLs), years lived with disability (YLDs), disability adjusted life-years (DALYs), and risk factors associated with DALYs. RESULTS: LE and HALE increased substantially in Haiti. People may hope to live longer in 2017, but in poor health. The Caribbean countries had significantly lower YLLs rates than Haiti for ischemic heart disease, stroke, lower respiratory infections, and diarrheal diseases. Road injuries were the leading cause of DALYs for people aged 5-14 years. Road injuries and HIV/AIDS were the leading causes of DALYs for men and women aged 15-49 years, respectively. Ischemic heart disease was the main cause of DALYs for people older than 50 years. Maternal and child malnutrition were the leading risk factors for DALYs in both sexes. CONCLUSION: Haiti faces a double burden of disease. Infectious diseases continue to be an issue, while non-communicable diseases have become a significant burden of disease. More attention must also be focused on the increase in worrying public health issues such as road injuries, exposure to forces of nature and HIV/AIDS in specific age groups. To address the burden of disease, sustained actions are needed to promote better health in Haiti and countries with similar challenges.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".