Global and regional trends in the nutritional status of young people: a critical and neglected age group
Bibliographic record
Abstract
Adolescence and emerging adulthood form a critical time period for the achievement of optimal health and nutrition across all stages of the life course. We undertook a review of published literature and global data repositories for information on nutrition levels, trends, and patterns among young people aged 10-24 years from January 1, 2016 to September 20, 2016. We describe patterns for both males and females at the global level and for geographic regions for the period covering 1990-2015. The results of this study paint a less than ideal picture of current young people's nutrition, suggesting dual burdens of underweight and high body-mass index in many countries and variable improvements in micronutrient deficiencies across geographical regions. Poor diet diversity and lack of nutrient-dense food, high risk for metabolic syndrome, and sedentary lifestyles also characterize this population. The need for objective, comparable, and high-quality data is also recognized for further study in this area. As the global community works toward supporting and scaling up health gains in the sustainable development goal era, realizing the critical role of young people is essential. Investing in young people's nutrition is critical to making strides in improving the overall health and well-being of all populations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".