Supplementary Material for: Effects of Sex and Physical Activity Level on Serum Biomarker-Based Physiological Dysregulation: The Impact to Predict Frailty and Mortality in the Quebec NuAge Cohort
Bibliographic record
Abstract
Background: Age-related changes in biological processes such as physiological dysregulation (the progressive loss of homeostatic capacity) vary considerably among older adults and may influence health profiles in late life. These differences could be related, at least in part, to the impact of intrinsic and extrinsic factors such as sex and physical activity level (PAL). Objectives: The objectives of this study were (1) to assess the magnitude and rate of changes in physiological dysregulation in men and women according to PAL and (2) to determine whether/how sex and PAL mediate the apparent influence of physiological dysregulation on health outcomes (frailty and mortality). Methods: We used data on 1,754 community-dwelling older adults (age = 74.4 ± 4.2 years; women = 52.4%) of the Quebec NuAge cohort study. Physiological dysregulation was calculated based on Mahalanobis distance of 31 biomarkers regrouped into 5 systems: oxygen transport, liver/kidney function, leukopoiesis, micronutrients, and lipids. Results: As expected, mean physiological dysregulation significantly increased with age while PAL decreased. For the same age and PAL, men showed higher levels of physiological dysregulation globally in 3 systems: oxygen transport, liver/kidney function, and leukopoiesis. Men also showed faster global physiological dysregulation in the liver/kidney and leukopoiesis systems. Overall, high PAL was associated with lower level and slower rate of change of physiological dysregulation. Finally, while mortality and frailty risk significantly increased with physiological dysregulation, there was no evidence for differences in these effects between sexes and PAL. Conclusion: Our results showed that both sex and PAL have a significant effect on physiological dysregulation levels and rates of change. Also, although a higher PAL was associated with lower level and slower rate of change of physiological dysregulation, there was no evidence that PAL attenuates the effect of physiological dysregulation on subsequent declines in health at the end of life. Substantial work remains to understand how modifiable behaviors impact the relationship between physiological dysregulation, frailty, and mortality in men and women.
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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 | 0.001 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.495 | 0.058 |
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".