Life-Course Socioeconomic Position and Mild Cognitive Impairment in Midlife: Evidence from the 1958 British Birth Cohort
Bibliographic record
Abstract
BACKGROUND: Dementia has been the leading cause of death in the UK since 2015. Increasing evidence supports an association between socioeconomic position (SEP) and dementia onset in later life. However, limited studies have examined how life-course SEP influences the development of mild cognitive impairment (MCI), an intermediate state potentially preceding dementia. Therefore, the present study aims to examine the relationship between life-course SEP and MCI amongst adults aged 50 years in Great Britain. METHODS: We employed data from the National Child Development Study (NCDS), also known as the 1958 British Birth Cohort, to determine the associations between SEP and MCI in 6590 participants. We categorised life-course measures of SEP as stable high/low or moving upward/downward over the life course. We assessed MCI at age 50 using one standard deviation below the averaged combined scores from all cognitive tests available. We then used binary logistic regression to estimate the longitudinal associations between life-course SEP and MCI. RESULTS: Relative to those of a high SEP across the life course, participants who moved upward, downward, or remained at a low SEP were significantly associated with 25% (95% CI 1.02-1.54, p = 0.035), 70% (95% CI 1.27-2.27, p < 0.001), and 85% (95% CI 1.50-2.29, p < 0.001), respectively, higher odds of MCI, independent of all selected covariates. CONCLUSIONS: Lower life-course SEP was associated with significantly higher odds of MCI onset in middle life within the NCDS cohort. Public health policies targeting cognitive impairment should encompass a life-course approach to reduce socioeconomic inequalities.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".