Deciphering the Association Between Hypothalamus‐Pituitary‐Adrenal Axis Activity and Obesity: A Meta‐Analysis
Bibliographic record
Abstract
OBJECTIVE: Both the cortisol awakening response (CAR; corresponding to the state measurement) and hair cortisol concentration (HCC; corresponding to the trait measurement) are considered reliable markers of hypothalamus-pituitary-adrenal axis activity. Because cortisol has long been associated with adiposity, this systematic review and meta-analysis aims to summarize and compare the literature around CAR and HCC and their association with obesity or fat distribution indices. METHODS: The PubMed, Web of Science (Web of Science Core Collection and Medline), EBSCO Information Services, Embase, and PsycNET databases were searched, and full-text articles investigating the association between CAR or HCC and markers of adiposity in humans were included. Meta-analyses were then performed to compare studies associating CAR or HCC with BMI (a marker of general adiposity) and waist circumference (a marker of fat distribution). RESULTS: The results of this review highlight inconsistencies in cortisol sampling and CAR computation, which makes comparisons between studies difficult. It was found that adiposity indices are not associated with CAR but that they correlate significantly and positively with HCC. The subgroup analysis hinted to possible age differences in the magnitude of the association between HCC and BMI. CONCLUSIONS: Trait rather than state measurement of the hypothalamus-pituitary-adrenal axis activity is associated with increased general and abdominal adiposity in humans.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.019 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".