Epidemiological and nutritional transition in low- and middle-income countries
Bibliographic record
Abstract
Abstract Issue/problem In the last decades, the number of deaths from non-communicable diseases in developing countries has risen to those observed in developed countries. Description of the problem Nutritional research in developing countries has primarily focused on under-nutrition, particularly among vulnerable population subgroups such as women and children. However, while economic growth has a significant social impact at population level, there is suggestive evidence of an ongoing nutritional transition leading to concurrent under- and over-nutrition in the population. Results The ongoing nutritional transition in these settings has been mostly linked to the rapid process of urbanisation and westernization. Data from several developing countries suggest that improvements in developmental indicators is accompanied by higher availability of highly processed poorly nutritious foods. Regarding socioeconomic factors, results demonstrated that better education and better living standards were associated with higher odds of overweight/obesity after adjusting for confounders, including urban vs. rural setting. This is likely a consequence of the ongoing nutritional and epidemiological transition occurring in these settings. In fact, developing countries have not yet reached the same phase of nutritional transition as an economically affluent country, and while high-calorie diets comprising fast-food are the more economically affordable option in the latter, such diets are still reserved for the more affluent individuals in some developing countries, where economic growth has only just begun to allow affluent individuals to afford fast-food. Conclusions Understanding the underlying ecological and socioeconomic roots of both extremes of the nutritional status is vital to design successful public health interventions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".