Oxytocin varies across the life course in a sex-specific way in a human subsistence population
Bibliographic record
Abstract
Oxytocin, a hormone linked to reproduction and health, may mediate life-history trade-offs across the human life course. Yet, how oxytocin naturally varies with age remains poorly understood. Here, working with the Tsimane, forager-horticulturalists of lowland Bolivia, we collected the largest sample of oxytocin measurements to date (n = 1,242 samples, n = 405 individuals, age = 2 to 84 y, 51% female), and i) examined how oxytocin varies throughout the life course in females and males, and ii) investigated potential drivers of age- and sex-specific variation. Our sample provides rare insight into the relationship between oxytocin and age in a context where energy is limited and trade-offs between reproduction and somatic maintenance are more salient. We found that oxytocin follows a nonlinear sex-specific trajectory throughout the life course. In females, oxytocin levels were high during the reproductive years and declined in the early to midforties, a pattern largely explained by breastfeeding and, to a lesser extent, childcare and good self-rated health. In males, oxytocin was low in early adulthood but high in old age, and although higher oxytocin was linked to good self-rated health, this did not explain the rise in oxytocin in later life. These findings suggest that oxytocin is instrumental for reproduction and caregiving in females and may also be associated with health in both males and females. Together, our work highlights oxytocin's broader biological significance across the human life course, suggesting that it may play a pivotal role in coordinating age- and sex-specific trade-offs involving reproduction and health.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".