Stress-Related Socioeconomic Factors and Risk of Alzheimer's Disease: A Literature Review
Bibliographic record
Abstract
Introduction: Recent studies have proposed an association between chronic stress and an increased risk of Alzheimer’s Disease (AD) and other dementias. AD pathology has been linked to elevated amyloid β (Aβ) production and formation of Aβ plaques. A key indicator of chronic stress is high cortisol levels, which have also been shown to amplify amyloid β production, thus making chronic stress a risk factor for AD. A number of risk factors for chronic stress development, including socioeconomic variables have also been suggested as potential risk factors for AD. However, the link between socioeconomic factors, chronic stress and AD incidence remains unclear. This review examines how education, income levels and occupation status may influence the relationship between chronic stress and AD risk. Methods: We reviewed the literature examining the relationship between occupation, education, and income with stress and AD risk. We performed a thorough search of PubMed, Medline, Web of Science and PsycInfo using predefined keywords, prioritizing prospective cohort studies that primarily examined AD, but also included articles on vascular dementia. Results: Job strain and increased mental demands at work are associated with increased AD risk. Low income is associated with multiple comorbidities, which is further associated with adverse AD. Additionally, higher education is correlated with decreased AD risk, but independently of the relationship between psychological stress and AD. Discussion: Literature suggests that chronic stress is related to AD risk, but this relationship is complicated when considering stress-related factors including occupation, education and income. Our review demonstrates that further research must be conducted on this topic to elucidate the correlation between socioeconomic factors, chronic stress and AD risk. Conclusion: This study will contribute to our understanding of how occupation, education level and income impact AD risk and advocate for methods in closing the health disparity through socioeconomic disparity.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| 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".