Determinants of health status and the influence of primary health care services in Latin America, 1990–98
Bibliographic record
Abstract
Primary health care (PHC) services have been advocated as a means by which less developed countries may improve the health of their populations even in the face of poverty, low levels of literacy, poor nutrition and other factors that negatively influence health status. Using aggregated data from the World Bank and UNICEF this study examined which factors, both within the health care system and outside of it, are associated with under-5 mortality rates in 22 countries of Latin America and the Caribbean during the 1990s. In a multivariate analysis using generalized estimating equations for repeated measures, five factors were found to be independent predictors of lower under-5 mortality rates (U5MRs). These were vaccination levels, female literacy, the use of oral rehydration therapy, access to safe water and GNP per capita. When the magnitude of these associations were assessed, higher levels of GNP per capita was found to be very weakly associated with lower U5MRs, compared with female literacy and vaccination rates. These findings suggest that government policies which focus only on promoting economic growth, while not making important investments in PHC services, female education and access to safe water are unlikely to see large improvements in health status.
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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 | 0.006 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".