Indigenous individuals present distinct modifiable risk factors of dementia than white individuals: an ELSI‐Brazil study
Bibliographic record
Abstract
Abstract Background Risk factors for dementia have distinct frequency and impact according to racial origins. Our aim was to identify differences of modifiable risk factors of dementia related to Indigenous and White individuals, estimate their Population Attributable Fraction (PAF) and highlight the differences between races. Methods An epidemiological cohort named ELSI‐Brazil was used to estimate the prevalence of 10 modifiable risk factors for dementia among 2 races ‐ White and Indigenous. he ELSI‐Brazil cohort consists of 9412 individuals (63.55+‐10.14 years of age). This cohort comprises individuals at/ or above 50 years of age from across the country. Complex sampling warrants nationwide representativity for diseases with low prevalence. Races were self‐reported according to the Brazilian Census. Sample weighting was used to estimate the prevalence and PAF of each risk factor in each race. Results Among 3810 individuals included, 220 were Indigenous individuals. The Indigenous were younger (mean age 62.6 [±9.6] years) and less educated (mean 4.3 [±4.0] years) than the White (mean age 64 years [±10.2], mean education years 6.2 [±4.4]). Both were composed by most females. The most important weighted PAF were hearing loss for both races (Indigenous 16.7%; White 15.2%). The most prevalent risk factor for both were less education, which were higher in Indigenous individuals (69.5%) than in White individuals (55.1%). By contrast, social isolation was less prevalent in Indigenous (1.5%) than White (5.1%). Overall adjusted PAF was lower in Indigneous (38.9%), compared to White (49,2%). Conclusion White and Indigenous presented different prevalence of risk factors, though they had hearing loss as the most impacting risk factor for dementia. However, it seemed that Ocidental risk factors didn’t produce the same effect in indigenous individuals as in white individuals. Thus, indigenous individuals presented a distinct profile of risk factors of dementia than individuals from other self‐reported races.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".