Diurnal cortisol trajectories from mid-pregnancy to one year after birth
Bibliographic record
Abstract
BACKGROUND: The hypothalamic-pituitary-adrenal (HPA) axis is involved in the regulation of pregnancy and postpartum recovery. Diurnal cortisol indices, specifically cortisol awakening response (CAR), area under the curve (AUCg), and slope, are ways to study HPA axis activity. Whether these indices show within-person changes during the perinatal period is not clear, nor do we know how maternal sociodemographic, health, or prenatal medical conditions are associated with within-person diurnal cortisol index trajectories. The purpose of this study is to investigate within-person changes in three diurnal cortisol indices from mid-pregnancy to one year postpartum, and test whether sociodemographic, pregnancy, or health factors moderate these changes. METHODS: A sample of 172 pregnant women provided saliva samples at six time points from mid-pregnancy to one year after birth. At each time point, they provided samples on two days (wake, 30 + wake, noon, pm). The samples were assayed for cortisol. CAR, slope and AUCg indices were calculated. Piecewise growth curve models tested for within-person changes during pregnancy and postpartum on each index with sociodemographic, pregnancy and health variables included in the models. RESULTS: Within-person trajectories were observed only for AUCg during pregnancy, linear: b = -0.51, p = .012; quadratic: b = -0.45, p = .009, such that AUCg increased from mid to late pregnancy. No significant within-person changes in CAR or slope were observed in pregnancy or after birth. Hispanic women demonstrated increasing CAR in the postpartum year, whereas the opposite was observed for non-Hispanic women. Longer gestation was associated with increasing AUCg after birth. CONCLUSION: AUCg increased from mid-to-late pregnancy, consistent with prior research. Maternal ethnicity and gestational length moderated diurnal cortisol index trajectories during the postpartum period only.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".