The Association Between Metabolic Syndrome and Serum Concentrations of Micronutrients, Inflammation, and Oxidative Stress Outside of the Clinical Reference Ranges: A Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: Clinical reference ranges are often used to assess nutritional status, but whether having lower or higher than the current clinical reference range for micronutrients, inflammation, and oxidative stress is related to metabolic syndrome (MetS) is not known. Our objectives are to estimate the odds of having MetS outside of established clinical references, and to identify any effect modifications by sex have for these relationships. METHODS: Data from the 2005 to 2006 National Health and Nutrition Examination Survey were used (≥20 years; N = 2049) with MetS defined utilizing the harmonized criteria from the Joint Interim Statement. The odds of having MetS in individuals with lower or higher than the clinical reference range for the serum concentrations of micronutrient antioxidants, inflammation, and oxidative stress were estimated following adjustments for age, sex, ethnicity, education, income, smoking, alcohol intake, recreational physical activity, and BMI. RESULTS: Having lower than the clinical reference range for carotenoids and vitamin C [odds ratios (95% confidence interval): 1.37 (1.05-1.78) and 1.39 (1.01-1.90), respectively] was associated with significantly greater odds of MetS. By contrast, having higher than the clinical reference range for vitamins A and E, uric acid, and γ-glutamyl transferase (GGT) [2.10 (1.50-2.92), 2.36 (1.78-3.13), 2.65 (1.54-4.57), and 2.08 (1.61-2.69), respectively] was associated with higher odds of MetS, whereas higher levels of vitamins B12 were protective [0.64 (0.42-0.98]. Sex moderated these relationships for carotenoids, vitamin A, C, E, uric acid, C-reactive protein, and GGT. CONCLUSIONS: Lower carotenoids and vitamin C and higher vitamins A and E, uric acid, and oxidative stress were associated with a greater likelihood of MetS, whereas higher vitamin B12 was protective. Further research is necessary to replicate these findings in a prospective setting to confirm the importance of the overall and sex-specific 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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".