Does obesity affect cognitive functions in middle-aged adulthood? A comparative study in Sri Lanka
Bibliographic record
Abstract
Abstract Background Cognition is the collection of an intellectual process, such as perception, thinking, reasoning and remembering for goal-directed behaviors. Recent studies have shown that obesity associated with poor cognitive functions (CFs). However, this association is not known in the Sri Lankan context. The objective was to determine the association of cognitive function and obesity among middle-aged adults in Colombo district, Sri LankaMethods A comparative cross-sectional study was conducted among 166 middle-aged adults aged 50-60 years in a selected MOH division in Colombo District, Sri Lanka. Generalized and central obesity were determined using the WHO cutoff of Body Mass Index (BMI) and Waist Hip Ratio (WHR) values. CFs were assessed using validated Montreal Cognitive Assessment (MoCA) and Mini Mental State Examination (MMSE) tools.Results The study sample consisted 83 subjects of each obese and normal weight categories while 50% were females. Obese middle-aged adults showed significantly lower CF scores in both MoCA and MMSE compared to the normal-weight adults. In addition, lower MMSE scores were significantly associated with high WHR values. Education level of the obese people was a significant predictor of the cognitive functions.Conclusion Obese middle-aged adults had poor cognition compared with their normal-weight subjects. Therefore, remedial actions need to be taken to overcome adulthood obesity for better neuropsychological functions in the brain.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.002 | 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".