Social engagement is associated with sedentary time in older males but not females living in India: analysis of a cross-sectional survey
Bibliographic record
Abstract
Purpose The purpose of this study was to describe the association between sedentary time and social engagement among older adults living in megacities in India. Design/methodology/approach Data from a cross-sectional survey conducted in New Delhi and Chennai were used for analysis. In the total sample ( n = 528), 65% of older adults self-reported engaging in high ( <m:math xmlns:m="http://www.w3.org/1998/Math/MathML" display="inline"><m:mo>≥</m:mo></m:math> 180 min/day) volumes of sedentary time. There were no associations between sedentary time and social engagement in older females. Findings Among older males, those reporting high levels of communicating or visiting with family and friends had lower odds of reporting <m:math xmlns:m="http://www.w3.org/1998/Math/MathML" display="inline"><m:mo>≥</m:mo></m:math> 180 min/day of sedentary time (OR: 0.51, CI: 0.27–0.98) compared to those reporting low levels of this type of social engagement. Older males reporting high levels of participating in a club (OR: 2.27, CI: 1.19–4.3) or participating in religious activities (OR: 1.97, 1.01–3.85) were approximately two times more likely to report <m:math xmlns:m="http://www.w3.org/1998/Math/MathML" display="inline"><m:mo>≥</m:mo></m:math> 180 min/day sedentary time compared to those reporting low levels of these types of social engagement. Originality/value These data suggest that the type of social activity appears to significantly affect self-reported sedentary time among older males, but not females. These findings have implications for interventions aimed at improving active aging among older adults living in megacities in India.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".