Amino Acid Intake and Conformance with the Dietary Reference Intakes in the United States: Analysis of the National Health and Nutrition Examination Survey, 2001–2018
Bibliographic record
Abstract
The lack of complete amino acid composition data in food composition databases has made determining population-wide amino acid intake difficult. This cross-sectional study characterizes habitual intakes of each amino acid and adherence to dietary requirements for each essential amino acid (EAA) by age, gender, and race/ethnicity in the US population. Food and Nutrient Database for Dietary Studies ingredient codes with missing amino acid composition data were matched to similar ingredients with available data, so that amino acid composition could be determined for virtually 100% of foods reported in What We Eat in America, the dietary intake assessment component of NHANES. Amino acid intakes during 2-y cycles of NHANES 2001–2018 (n = 84,629; ≥ 2 y) were calculated as relative [mg/kg of ideal body weight (IBW)/d] and absolute (g/d) intakes. Data from NHANES 2011–2018 were used to determine the percentage of the population consuming less than the Dietary Reference Intakes for each EAA by age, sex, and race/ethnicity. Relative intakes of EAAs were greatest in those 2–3 y (females: 1552 ± 9 and males: 1659 ± 9 mg/kg IBW/d) and lowest in those ≥80 y (females: 446 ± 2 and males: 461 ± 3 mg/kg IBW/d). Absolute intakes of EAAs were greatest in those 31–50 y (females: 31.4 ± 0.1 and males: 45.5 ± 0.1 g/d) and lowest in those 2–3 y (females: 22.4 ± 0.1 and males: 26.0 ± 0.1 g/d). In individuals 2–18 y and ≥19 y, relative intakes of EAAs were lowest in the NHB population (860 ± 16 and 505 ± 5 mg/kg IBW/d, respectively) and highest in the Asian population (994 ± 35 and 580 ± 7 mg/kg IBW/d, respectively). Less than 1% of individuals ≥19 y were not meeting the Estimated Average Requirements for each EAA. Individual amino acid intakes in the US population exceed recommended minimum population requirements. Future studies can use the method described here to quantify habitual amino acid intake and examine relationships with health and disease. Institute for the Advancement of Food and Nutrition Sciences (IAFNS) Protein Committee, US Army Medical Research and Development Command, and the Department of Defense Center Alliance for Nutrition and Dietary Supplements Research.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".