Calorie and Nutrient Intake in Obese Women With Low-Income
Bibliographic record
Abstract
Background: Central obesity is a growing pandemic in developing countries. The aim of this study was to assess the energy intake and nutritional characteristics of low-income obese women. Methods: A total of 103 obese women, age 46 ± 11 years, 89% nonwhite, monthly income up to US $678.00, 77.0% with BMI ≥ 30 kg/m 2 , and 100.0% with waist circumference > 80.0 cm (106.3 ± 14.2 cm), followed at the Obesity Clinic of the Bahiana School of Medicine, at Salvador, Bahia, Brazil, were studied. Nutritional data was collected by direct interview and by a 24 hour recall on two non-consecutive days. Results: A total of 24 h median energy intake was 1,462 kcal, with a daily median carbohydrate intake of 212.6 g (62.1% within the 55.0-75.0% of the recommended total daily energy intake), with 34.6 g of lipids (> 30%) in 20.4%, and within the daily recommended requirements of 5-30% in 63.1%), 66.7 g of protein (above the 10-15% daily recommended intake in 62.1%), and a low fiber intake ( 7.0% the total recommended intake in 81.6%). In addition, a low intake of Vitamin E (91.2%), D (100%), A (67.96%) and calcium (97.08%), plus excessive sodium intake (29.1%) was also documented. Conclusion: The obesity of these low-income females was associated with a low median daily total energy intake, mildly elevated protein, elevated saturated fat acids, and low fiber intake. The inadequacies of food consumption are also reflected in a low intake of micronutrients, specially vitamins E and D. The low socioeconomic level of these subjects certainly represents the major factor for these findings.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".