Prevalence of Cognitive Impairment and Dementia in Older Adults Living at High Altitude: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
INTRODUCTION: Dementia is a chronic disease with a variable prevalence throughout the world; however, this could be higher at high-altitude populations. We aimed to summarize the prevalence of cognitive impairment and dementia in older adults living at high altitude. METHODS: We searched in PubMed, Medline, Scopus, Web of Science, and Embase and included the studies published from inception to July 20, 2020, with no language restriction, which reported the frequency of cognitive impairment or dementia in older adults living at high-altitude populations. Random-effects meta-analyses were performed to calculate the overall prevalence and 95% confidence intervals (95% CI) of cognitive impairment and dementia. The risk of bias was evaluated using the Newcastle-Ottawa Scale (NOS) adapted for cross-sectional studies. RESULTS: Six studies were included (3,724 participants), and 5 of the 6 included studies were carried out in Latin America. The altitude ranged from 1,783 to 3,847 m, the proportion of women included varied from 38.7 to 65.6%, and the proportion of participants with elementary or illiterate educational level ranged from 71.7 to 97.6%. The overall prevalence of cognitive impairment was 22.0% (95% CI: 8-40, I2: 99%), and the overall prevalence of dementia was 11.0% (95% CI: 6-17, I2: 92%). In a subgroup analysis according to the instrument used to evaluate cognitive impairment, the prevalence of cognitive impairment was 21.0% (95% CI: 5-42, I2: 99%) in the MMSE group while the prevalence was 29.0% (95% CI: 0-78) in the non-MMSE group. CONCLUSIONS: The prevalence of cognitive impairment and dementia in older adults living at high altitude is almost twice the number reported in some world regions.
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.031 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".