SENSE OF PURPOSE IN LIFE AND ALLOSTATIC BURDEN IN TWO LONGITUDINAL COHORTS
Bibliographic record
Abstract
Abstract Sense of purpose in life has been linked with better physical health, longevity, and reduced risk for disability and dementia, but the mechanisms linking purposefulness with diverse health outcomes is unclear. Chronic activation and dysregulation of neural, immune, and other bodily systems, known as allostatic load, may contribute to these underlying mechanisms. Specifically, sense of purpose may promote better physiological regulation in response to stressors and health challenges, leading to lower allostatic burden and disease risk over time. Data from the nationally representative US Health and Retirement Study (HRS) and English Longitudinal Study on Ageing (ELSA) (Total N=5846; Mean Age=67.24, SD=10.68, 59.08% female) were used to examine associations between sense of purpose and repeated assessments of allostatic load across 8 and 12 years of follow-up. Allostatic load scores were constructed from 12 blood-based and anthropometric biomarkers of cardiovascular, metabolic, immune, and lung function, with higher scores representing higher allostatic burden. Population-weighted multilevel models revealed that sense of purpose in life was associated with lower overall levels of allostatic load in HRS (b = -0.22, 95% CI: -0.27,-0.17) and in ELSA (b = -0.19, 95% CI: -0.35,-0.03). Sense of purpose in life did not predict rate of change in allostatic load in either sample. Associations with sense of purpose were highest among cardiovascular and immune biomarkers, suggesting that preservation of these bodily systems may underlie associations between purposefulness and reduced risk for chronic health conditions. Discussion will focus on biological and behavioral pathways connecting sense of purpose in life 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".