Life-Course Socioeconomic Position and Hippocampal Atrophy in a Prospective Cohort of Older Adults
Bibliographic record
Abstract
OBJECTIVE: Low socioeconomic position (SEP) has been linked to an increased risk of dementia and cognitive decline. However, little is known about the association between SEP and morphologic brain changes in older age. This study examines the relationships between indicators of life-course SEP with both hippocampal volume (HcV) and HcV loss in a population-based cohort of 1328 older adults aged 65 to 80 years. METHODS: Multivariable linear regression models were used to estimate the associations of SEP with baseline HcV and the annual rate of HcV atrophy according to three life-course conceptual models: the sensitive/critical periods model (which explored SEP in specific periods: in childhood [using parental education], early adulthood [based on participants' education], and midlife [based on participants' socioprofessional group]); the accumulation-of-risk model (life-course cumulative SEP), and the social mobility model (life-course SEP trajectories). RESULTS: Participants with lower midlife SEP had smaller HcV (-0.08 cm; 95% confidence interval, -0.15 to -0.01) and 0.17% (95% confidence interval, 0.04%-0.30%) faster hippocampal atrophy than participants with higher midlife SEP. Childhood and early adulthood SEPs were not related to hippocampal measures. The accumulation-of-risk and the social mobility models revealed that the accumulation of socioeconomic disadvantage and declining socioeconomic trajectories were related to faster hippocampal atrophy. CONCLUSIONS: In this cohort of older adults, lower socioprofessional attainment in midlife and disadvantageous life-course socioeconomic position were associated with faster hippocampal atrophy, a cerebral change linked to cognitive disorders. Results support the hypothesized links between socioenvironmental exposures related to stress and/or cognitive enrichment and brain/cognitive reserve capacities.
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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".