Allostatic Load Following Short-Term Intervention: Cognition in Older Hypertensive Adults
Bibliographic record
Abstract
Abstract Allostatic load (AL), a measure of cumulative effect of prolonged stressors across physiological systems, is consistently associated with adverse health outcomes. Greater AL is correlated with functional decline in aging, but effects of behavioral interventions, such as Tai Chi (TC), on AL in older adults in a short-term is unknown. To investigate the effects of TC practice on AL and cognitive function and an AL-cognition relationship, older adults (60-95 years) with hypertension were recruited and randomly assigned to 12-week TC or Healthy Aging Practice-centered Education (HAP-E) classes. The AL index (ALI) included: SBP and DBP; urinary epinephrine and norepinephrine; plasma inflammatory biomarkers (CRP, IL-6); metabolic biomarkers (HDL, total cholesterol, triglycerides, HbA1c); and BMI. The Montreal Cognitive Assessment (MoCA) was administered to assess cognitive function. Generalized linear mixed-effects models, adjusted for age, race, education, and intervention attendance, was used. Pre- and post-intervention ALI did not change significantly in TC (2.61 (1.48) to 2.76 (1.62)) or HAP-E (2.84 (1.61) to 2.66 (1.86)). High ALI was associated with lower MoCA scores, indicating poorer cognitive performance (IRR=0.96; 95% CI: 0.93-0.98; p=0.002) across the time points. Of note, the MoCA scores did not significantly change across time (25.4 (3.2) to 26.0 (3.0)). 12-week TC or HAP-E interventions did not lead to a significant change in ALI or cognitive performance in our population. However, our findings show greater AL theoretically attributed to chronic stress is associated with cognitive functioning in older adults consistently over about 4 months.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".