Alzheimer’s Disease and Related Dementia in Indigenous Populations: A Systematic Review of Risk Factors
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: There remains a lack of information and understanding of the prevalence and incidence of Alzheimer's disease and related dementia in Indigenous populations. Little evidence available suggests that Indigenous peoples may have disproportionately high rates of Alzheimer's disease and related dementia (ADRD). OBJECTIVE: Given this information, this study systematically explores what risk factors may be associated with ADRD in Indigenous populations. METHODS: A search of all published literature was conducted in October 2016, March 2018, and July 2019 using Medline, Embase, and PsychINFO. Subject headings explored were inclusive of all terms related to Indigenous persons, dementia, and risk. All relevant words, phrases, and combinations were used. To be included in this systematic review, articles had to display an association of a risk factor and ADRD. Only studies that reported a quantifiable measure of risk, involved human subjects, and were published in English were included. RESULTS: Of 237 articles originally identified through database searches, 45 were duplicates and 179 did not meet a priori inclusion criteria, resulting in 13 studies eligible for inclusion in this systematic review. CONCLUSION: The large number of potentially modifiable risk factors reported relative to non-modifiable risk factors illustrates the importance of socioeconomic context in the pathogenesis of ADRD in Indigenous populations. The tendency to prioritize genetic over social explanations when encountering disproportionately high disease rates in Indigenous populations can distract from modifiable proximal, intermediate, and distal determinants of health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it