Assessment of cognition in obese young adults
Bibliographic record
Abstract
Background: Obesity is abnormal or excessive accumulation of fat that has adverse effects on health.Obese individuals are at risk of several life threatening diseases and complications such as Type-2 Diabetes Mellitus, Hypertension, Metabolic syndrome, Cardiovascular diseases, Stroke, Cancers, and Psychosocial disorders.Apart from these, it also leads to neurological disorders like impairment in cognition, motor skills and higher executive functions.Aim: To assess the cognition in young adult obese males.Materials and methods: 80 male participants of which 40 obese males and 40 normal weight healthy subjects in the age group of 18 to 35 years were recruited from the Non Communicable Disease Outpatient Department, Body Mass Index(BMI),Waist Circumference(WC) and Waist Hip Ratio(WHR) were the obesity indices used to assess the obesity.Montréal Cognitive Assessment Score (MoCA score) was used to assess the cognition.Results: The data was analysed using Statistical Package for Social Sciences(SPSS) version 20.The study group were with the mean age of 34.02 + 3.20 yrs, mean BMI of 32.06 +3.47,mean WHR of 0.86 + 0.08, mean WC of 98.37 +5.35 and mean MoCA score of 26.09+0.49.Among the study group 28% of the participants had cognitive impairment with the score between 23-25.Negative correlation was observed between the obesity indices and MoCA score, among which BMI had better negative correlation with the MoCA score.Conclusion: Cognition was impaired in obese individuals and it was inversely related to the obesity indices.This shows that they are at the risk for early onset of dementia.Hence, early diagnosis and appropriate interventions may prevent severe impairment in cognition in obese individuals.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".