Psychosocial adversity and allostatic load burden in midlife and older ages.
Bibliographic record
Abstract
OBJECTIVE: To investigate the individual and cumulative impact of childhood and adulthood adversity on allostatic load (AL) burden. METHOD: Retrospective cross-sectional study design involving 4,165 participants from the first wave of The Irish Longitudinal study on Ageing (TILDA). AL was operationalized using 12 biomarkers across four physiological systems (cardiovascular, metabolic, renal, and immune). Measures of psychosocial adversity included poverty, abuse, loss, and illness. Negative binomial regression models estimated the relationship of individual adversities and a cumulative count of adversities with AL burden, controlling for age and sex. Multivariable models adjusted additionally for a range of other sociodemographic and lifestyle factors. RESULTS: Childhood poverty, childhood physical abuse, and having a spouse/partner/child experience a life-threatening illness/accident were associated with 10% (95% CI [1.04, 1,16]), 10% (95% CI [1.01, 1.18]), and 6% (95% CI [1.01, 1.11]) greater AL burden, respectively. Cumulative adversity was associated with 3% (95% CI [1.01, 1.04]) higher AL burden. Adjusting for sociodemographic and lifestyle covariates rendered the association of childhood poverty (IRR= 1.04, 95% CI [.98, 1.09]; p = .190) and childhood physical abuse (IRR= 1.07, 95% CI [.99, 1.15]; p = .081) with AL burden nonsignificant, while the association of having an ill spouse/partner/child on AL persisted (IRR= 1.06, 95% CI [1.01, 1.11]; p = .021). CONCLUSIONS: This study provided limited support for the idea that psychosocial stress leads to higher AL, with just three out of 11 adversities associated with AL. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 teacher head, 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".