Nutrition status in adult Chilean population: economic, ethnic and sex inequalities in a post-transitional country
Bibliographic record
Abstract
OBJECTIVE: To assess the relationship between malnutrition, socioeconomic status (SES) and ethnicity in Chilean adult population. DESIGN: Nationally representative survey (ENS) conducted in 2016-2017. Sociodemographic information, weight, height and hemoglobin (Hb) were measured (2003 ENS). Excess weight was defined as BMI ≥25 kg/m2. Undernutrition included underweight (BMI <18·5 kg/m2), short stature (height <1·49 m in women and <1·62 m in men) or anaemia (Hb <12 g/l). Education and household income level were used as indicators of SES; ethnicity was self-reported. We applied linear combinations of estimators to compare the prevalence of excess weight and undernutrition by SES and ethnicity. SETTING: Chile. PARTICIPANTS: In total, 5082 adults ≥20 years (64 % women) and 1739 women ≥20 years for anaemia analyses. RESULTS: Overall, >75 % of women and men had excess weight. Low SES women either by income or education had higher excess weight ((82·0 (77·1, 86·1) v. 65·0 (54·8, 74·1)) by income; (85·3 (80·6, 89·0) v. 68·2 (61·6, 74·1) %) by education) and short stature (20-49 years; 31(17·9, 48·2) v. 5·2 (2·2,11·4) by education); obesity was also more frequent among indigenous women (20-49 years; 55·8 (44·4, 66·6) v. 37·2 (32·7, 42·0) %) than non-indigenous women. In men, excess weight did not significantly differ by SES or ethnicity, but short stature concentrated in low SES (20-49 years; 47·6 (24·6, 71·6) v. 4·5 (2·1, 9·5) by education) and indigenous men (21·5 (11·9, 5·5, 11·9) v. 8·2 (5·5, 11·9)) (P < 0·05 for all). CONCLUSIONS: In Chile, malnutrition is disproportionately concentrated among women of low SES and indigenous origin; these inequalities should be considered when implementing prevention policies.
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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 | 0.000 | 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 | 0.001 |
| 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".