Cognitive trends in an urban Indian elderly community: Glycated hemoglobin and geriatric depression play a bigger role than age
Bibliographic record
Abstract
Abstract Objectives To explore the cognitive profile in urban Indian older adults and observe the prevalence of cognitive impairment associated with age, glycated hemoglobin (HbA1c) levels, vitamin B12, and other psychosocial factors Methods Urban community dwelling older adults (55-85years, n=123) underwent a detailed demographic and cognitive assessment comprising of tests from different cognitive domains – memory, executive function, visuospatial abilities, and verbal fluency. Serum samples were collected from a subset of participants (n=60) to determine HbA1c and vitamin B12 levels. Results Performance in all cognitive domains declined with age. The decline became prominent around age 70. HbA1c correlated inversely with processing speed and executive function. Vitamin B12 did not correlate with performance on any cognitive test. Geriatric depression correlated inversely with visuospatial abilities. Surprisingly, stepwise multiple regression revealed that HbA1c and geriatric depression contributed to 28% variance on Montreal Cognitive Assessment whereas participant age did not contribute significantly. Mild Cognitive Impairment (MCI) was observed in 17% of participants. Participants classified as MCI had higher levels of HbA1c and geriatric depression, and lower performance in all cognitive domains compared to non-MCI participants. Conclusion Although cognitive performance declined with age, HbA1c and geriatric depression played a greater role than age in predicting cognitive decline. This study highlights the prevalence of metabolism linked changes in cognition in community dwelling Indian older adults.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".