The associations of life course adversity on cognitive function and decline in the United States’ representative US Health and Retirement Study
Bibliographic record
Abstract
BACKGROUND: As the proportion of the US population aged 65 and over increases from 16.8% in 2020 to an estimated 22.8% by 2050, understanding how experiences over the life course shape trajectories of healthy aging becomes increasingly important. Maintenance of cognitive function is a key facet of healthy aging and may determine an individual's ability to remain autonomous in later adulthood. Additionally, the growing social and economic burden of cognitive impairment makes it a vital public health concern and highlights the need to understand its risk factors. METHOD: We used 12 waves of data (1998-2020) from the Health and Retirement Study, a nationally representative longitudinal cohort of US adults over the age of 50 (n = 8,503). Cognitive function was assessed via a modified Telephone Interview for Cognitive Status. Life course adversity was derived from self-reported childhood and adulthood economic and psychosocial exposures. Nonlinear mixed-effects models evaluated associations between adversity and cognitive function, testing critical period, accumulation, and interaction hypotheses. Models were adjusted for race/ethnicity, sex, education, marital status, smoking, chronic conditions, alcohol use, and physical activity. RESULTS: Greater childhood adversity was independently associated with lower baseline cognitive function (β = -0.74; 95% CI, -0.91 to -0.57; p < .001), consistent with a critical period effect. Adulthood adversity alone was not significantly associated with baseline cognition or decline. However, interaction models revealed that the adverse effect of adulthood adversity on cognitive decline was amplified among individuals with high childhood adversity (3-way interaction: β = -0.014; 95% CI, -0.020 to -0.009; p < .001), suggesting compounding effects across the life span. CONCLUSION: Childhood adversity exerts a persistent influence on later-life cognitive function. Adulthood adversity further accelerates decline, but primarily among those with early-life disadvantage. These findings support both critical period and interaction models of life course risk and highlight the need for early preventive efforts and targeted interventions for high-risk populations.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".