Carotenoids as biomarkers of fruit and vegetable intake in men and women
Bibliographic record
Abstract
High fruit and vegetable (FAV) intake is associated with a lower prevalence of chronic diseases. Identifying the ideal number of FAV servings needed to reduce chronic disease risk is, however, difficult because of biases inherent to common self-report dietary assessment tools. The aim of our study was to examine the associations between daily FAV intake and plasma carotenoid concentrations in men and women enrolled in a series of fully controlled dietary interventions. We compiled and analysed data from a group of 155 men and 109 women who participated in six fully controlled dietary interventions and compared post-intervention fasting plasma carotenoid (α-carotene, β-carotene, β-cryptoxanthin, lutein, lycopene, zeaxanthin) concentrations with regard to the daily FAV servings consumed by the participants. We found that plasma β-cryptoxanthin, lutein and zeaxanthin concentrations were positively associated with daily FAV servings (P≤0·005). However, daily FAV intake was negatively associated with plasma α-carotene (P<0·0005) and lycopene (P<0·0001) concentrations, whereas no association was noted with plasma β-carotene. When men and women were analysed separately, we found that for any given number of FAV servings consumed women had higher circulating lutein concentrations compared with men (P<0·01). Significant sex×FAV (P<0·0001) and sex×dietary β-cryptoxanthin (P<0·0005) interactions were also noted favouring higher plasma β-cryptoxanthin concentrations in women than in men for a given FAV consumption. Results from these fully controlled dietary feeding studies indicate that plasma β-cryptoxanthin and lutein concentrations can be used as robust biomarkers of FAV consumption. They also suggest the existence of sex differences influencing circulating β-cryptoxanthin and lutein concentrations following FAV consumption.
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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 | 0.000 |
| 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".