Educational Mobility, the Pace of Biological Aging, and Lifespan in the Framingham Heart Study
Bibliographic record
Abstract
Abstract Importance People who complete more education live longer lives with better health. New evidence suggests that these benefits operate through a slowed pace of biological aging. If so, measurements of the pace biological aging could offer intermediate endpoints for studies of how interventions to promote education will impact healthy longevity. Objective To test the hypothesis that upward educational mobility contributes to a slower pace of biological aging and increased longevity. Design Prospective cohort study. Setting We analyzed data from three generations of participants in the Framingham Heart Study: the Original cohort, enrolled beginning in 1948, the Offspring cohort, enrolled beginning in 1971, and the Gen3 cohort, enrolled beginning in 2002. Follow-up is on-going. Data analysis was conducted during 2022-2023 using data obtained from dbGaP (phs000007.v33). Participants We constructed a three-generation database to quantify intergenerational educational mobility. We linked mobility data with blood DNA methylation data collected from the Offspring cohort in (2005-2008) (n=1,652) and the Gen3 cohort in 2009-2011 (n=1,449). These n=3,101 participants formed our analysis sample. Exposure We measured educational mobility by comparing participants’ educational outcomes with those of their parents. Outcomes We measured the pace of biological aging from whole-blood DNA-methylation data using the DunedinPACE epigenetic clock. For comparison purposes, we repeated analysis using four other epigenetic clocks. Survival follow-up was conducted through 2019. Results Participants who were upwardly mobile in educational terms tended to have slower DunedinPACE in later life (r=-0.18, 95% CI [-0.23,-0.13], p<0.001). This pattern of association was similar across generations and held in within-family sibling comparisons. 402 Offspring-cohort participants died over the follow-up period. Upward educational mobility was associated with lower mortality risk (HR=0.89, 95% CI [0.81,0.98] p=0.014). Slower DunedinPACE accounted for roughly half of this association. Conclusions and Relevance Our findings support the hypothesis that interventions to promote educational attainment will slow the pace of biological aging and promote longevity. Epigenetic clocks, like DunedinPACE, have potential as near-term outcome measures of intervention effects on healthy aging. Experimental evidence is needed to confirm findings.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".