Trends in energy and nutrient supply in Ethiopia: a perspective from FAO food balance sheets
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Ethiopia is the second-most populous country in Africa. Although most people still live in rural areas, the urban population is increasing. Generally, urbanisation is associated with a nutrition transition and an increase in risk factors for non-communicable diseases (NCDs). The objective of this study was to determine how the nutritional composition of the Ethiopian food supply has changed over the last 50 years and whether there is evidence of a nutrition transition. METHODS: Food balance sheets for Ethiopia from 1961 to 2011 were downloaded from the FAOSTAT database and daily per capita supply for 17 commodity groupings was calculated. After appropriate coding, per capita energy and nutrient supplies were determined. RESULTS: Per capita energy supply was 1710 kcal/d in 1961, fell to 1403 kcal/d by 1973, and increased to 2111 kcal/d in 2011. Carbohydrate was by far the greatest energy source throughout the period, ranging from 72% of energy in 1968 to 79% in 1998; however, this was mostly provided by complex carbohydrates as the contribution of sugars to energy only varied between 4.7% in 1994 and 6.7% in 2011. Energy from fat was low, ranging from 14% of energy in 1970 to 10% in 1998. Energy from protein ranged from 14% in 1962 to 11% in 1994. Per capita supplies of calcium, vitamin A, C, D, folate and other B-vitamins were insufficient and there was a low supply of animal foods. CONCLUSIONS: The Ethiopian food supply is still remarkably high in complex carbohydrates and low in sugars, fat, protein, and micronutrients. There is little evidence yet of changes that are usually associated with a nutrition transition.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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 it