Is plasma vitamin C an appropriate biomarker of vitamin C intake? A systematic review and meta-analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: As the primary source of dietary vitamin C is fruit and to some extent vegetables, the plasma level of vitamin C has been considered a good surrogate or predictor of vitamin C intake by fruit and vegetable consumption. The purpose of this systematic review was to investigate the relationship between dietary vitamin C intakes measured by different dietary methods and plasma levels of vitamin C. METHOD: We searched the literature up to May 2006 through the OVID interface: MEDLINE (from 1960) and EMBASE (from 1988). We also reviewed the reference lists in the articles, reviews, and textbooks retrieved. A total of 26 studies were selected and their results were combined using meta-analytic techniques with random-effect model approach. RESULTS: The overall result of this study showed a positive correlation coefficient between Food Frequency Questionnaire (FFQ) and biomarker (r = 0.35 for "both" genders, 0.39 for females, and 0.46 for males). Also the correlation between Dietary Recalls (DR)/diary and biomarker was 0.46 for "both" genders, 0.44 for females, and 0.36 for males. An overall correlation of 0.39 was found when using the weight record method. Adjusting for energy intake improved the observed correlation for FFQ from 0.31 to 0.41. In addition, we compared the correlation for smokers and non-smokers for both genders (FFQ: for non-smoker r = 0.45, adjusted for smoking r = 0.33). CONCLUSION: Our findings show that FFQ and DR/diary have a moderate relationship with plasma vitamin C. The correlation may be affected/influenced by the presence of external factors such as vitamin bioavailability, absorption condition, stress and food processing and storage time, or by error in reporting vitamin C intake.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 it