Contribution of beef to key nutrient intakes in American adults: an updated analysis with NHANES 2011-2018
Bibliographic record
Abstract
Beef represents an important source of high-quality dietary protein and several micronutrients including iron, zinc, and B vitamins. Consumption of lean meat including lean beef is recommended by the Dietary Guidelines for Americans 2020-2025 as part of overall healthy diet. Given beef intake has been declining, the objective of this study was to provide updated evaluation of the nutritional contribution of beef types. Twenty-four-hour dietary recall data from adults age 19+ years (n = 19,766) participating in the National Health and Nutrition Examination Survey 2011-2018 was used to assess intakes. On the day of recall, 49.3%, 40.2%, 26.3%, and 15.3% adults consumed total beef, lean fresh beef, ground beef, and processed beef, respectively, with mean intakes of 45.6, 36.6, 21.3, and 6.23 g/day, respectively. Intake of total beef contributed to daily intakes of energy (5.4%), protein (14%), vitamin B 12 (20%), zinc (21%), choline (11%), niacin (9.4%), vitamin B 6 (8.3%), iron (7.6%), phosphorus (6.8%), potassium (5.6%), and magnesium (3%). Lean fresh beef contributed most to the daily intakes of energy and nutrients followed by ground and processed beef. Beef intake also contributed to daily intakes of fat (8.7%), saturated fat (11%), and sodium (2.9%) and lean fresh beef contributed less intakes of fat and saturated fat than ground and processed beef. Beef and particularly lean fresh beef were efficient sources of nutrients and provided more nutrients per 100 kcal than the total diet. In conclusion, based on nutrient contribution, these findings provide evidence to support inclusion of beef (especially lean fresh beef) in dietary recommendations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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".