Serum phosphate is related to adiposity in healthy adults
Bibliographic record
Abstract
BACKGROUND: Inorganic phosphate is a crucial component of cellular energy metabolism. We have identified an inverse relationship between serum phosphate concentration and fat mass in a cohort of healthy men. This study reports those data and determines whether this association is present in two female populations. METHODS: Cross-sectional data from three independent cohorts, consisting of healthy adult males (Male Cohort, n = 323) and healthy postmenopausal women (Female Cohort 1, n = 185; and Female Cohort 2, n = 1471), are reported. Associations between serum phosphate and weight, body mass index (BMI), fat mass and bone mineral density (BMD) were assessed. In a fourth cohort of postmenopausal women (FGF23 Cohort, n = 20), associations between fibroblast growth factor 23 (FGF23), weight and BMI were assessed. RESULTS: Serum phosphate correlated inversely with weight, BMI and fat mass across all three cohorts (r = -0·13 to -0·31, P < 0·0001-0·02). Associations were diminished after adjustment for PTH, but remained significant. In the FGF23 Cohort, FGF23 was positively correlated with weight (r = 0·60, P = 0·007) and BMI (r = 0·49, P = 0·03). Phosphate was inversely associated with BMD in Female Cohorts 1 and 2 (r = -0·08 to -0·29, P < 0·0001-0·02). This relationship was attenuated, but remained significant at most sites, following adjustment for age, fat mass, renal function and 25-hydroxyvitamin D. CONCLUSIONS: Serum phosphate is inversely associated with measures of adiposity in both women and men, largely independently of PTH. FGF23 might mediate these associations. This relationship may be an unrecognized confounder in some of the correlates of serum phosphate already described.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".