Childhood Misfortune as a Threat to Successful Aging: Avoiding Disease
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to examine whether childhood misfortune reduces the likelihood of being disease free in adulthood. DESIGN AND METHODS: This article used a sample of 3,000+ American adults, aged 25-74, who were first interviewed in 1995 and reinterviewed in 2005. Logistic regression was used to estimate the odds of avoiding disease at the first wave and remaining disease free a decade later. RESULTS: Consistent with a life course view of successful aging, higher levels of childhood misfortune (e.g., abuse, financial strain) are associated with a lower probability of disease avoidance. This pattern was observed across a large set of chronic conditions and in multivariate analyses spanning both waves of the study. IMPLICATIONS: Childhood misfortune has approximately equal consequences for adult disease avoidance as does the combined effect of moderate lifetime smoking and obesity. Efforts to alleviate adverse experiences for children may have long-term benefits for successful aging.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".