Rural development and shifts in household dietary practices from 1999 to 2010 in the Tapajós River region, Brazilian Amazon: empirical evidence from dietary surveys
Bibliographic record
Abstract
BACKGROUND: Research on changing dietary practices is rare in lower and middle income countries, and understanding the impact of global economic processes on population health and nutrition is important, especially of rural communities. We analyzed the diet of 22 families in Brasília Legal, a riverside community in the Tapajós River region of the Brazilian Amazon, using nonparametric tests to compare dietary surveys taken in 1999 and 2010. RESULTS: Data from the two surveys show that food obtained through commercial supply chains became more frequent in household diets, corresponding to significant increases in daily consumption of food items rich in energy, protein, and sugar. At the same time, there was a decline in traditional Amazonian food intake. CONCLUSIONS: Comparing these results with household socio-economic characteristics and drawing on open-ended interviews, we consider the multiple influences that economic development processes may have had on local diets. The introduction of new income sources and employment opportunities, infrastructural and transportation expansion, as well as environmental change appear to have influenced the observed dietary shifts. Such shifts are likely to have important implications for the nutritional status of communities in the Amazon, highlighting concerning trade-offs between current development trajectories and human health. Public policies and health education programs must urgently consider the interactions between sustainable development priorities in order to address emerging health risks in this rapidly changing region.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".