Intersections of sex and neighborhood disadvantage on Alzheimer's disease pathology
Bibliographic record
Abstract
BACKGROUND: Differences in Alzheimer's disease (AD) biomarkers have been reported by sex, but their intersection with neighborhood disadvantage is not understood. METHOD: C-PiB SUVR. Our vascular (V) measure was lobar unhealthy white matter connectivity (UWMC), a novel measure indicating the proportion of white matter connections affected by white matter hyperintensities (WMH). Neurodegeneration (N) was measured via cortical thickness from an AD-specific meta-region. Intersectional effects of sex and ADI on AV(N) were examined on the multiplicative and additive scale via robust and log-binomial regressions, respectively. RESULT: The sample included N = 196 participants (age 62 years; female sex 67%; Black racialization 49%; education 14 years; APOE4+ 32%; cognitively impaired 27%; Table 1). In robust regressions, female participants had greater frontal UWMC (β=0.07, SE=0.02, p <0.01) and amyloid (β=0.03, SE=0.01, p = 0.02) but lower parietal (β=-0.03, SE=0.01, p = 0.04) and occipital UWMC (β=-0.05, SE=0.02, p <0.01) versus male participants. High ADI participants had greater frontal (β=0.05, SE=0.02, p = 0.01) and temporal UWMC (β=0.03, SE=0.02, p = 0.05) versus low ADI participants (Table 2). Intersectional effects were found such that high ADI female participants had the greatest temporal UWMC on the additive scale (relative excess risk due to interaction = 0.68, 95% CI=[0.12,1.25]), and low ADI men had the greatest amyloid on the multiplicative scale (p-interaction = 0.03). Sex-stratified regressions indicated that high ADI was associated with greater temporal UWMC in female participants (β=0.05, SE=0.02, p = 0.01), but not male participants (β=-0.003, SE=0.03, p = 0.92; Figure 1a) and low ADI was associated with greater amyloid in male participants (β=-0.06, SE=0.02, p = 0.02) but not female participants (β=0.01, SE=0.02, p = 0.74; Figure 1b). Results examining WMH instead of UWMC were similar. CONCLUSION: We confirmed differences in AV(N) by sex and ADI. Intersectional effects were found such that women with high ADI had the greatest temporal UWMC and men with low ADI had the greatest amyloid. Understanding the role of neighborhood disadvantage on V is important for future interventions, especially for women.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.004 | 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".