Social isolation and mortality among Canadian seniors
Bibliographic record
Abstract
BACKGROUND: Subjective and objective measures of isolation have been associated with increased risk of mortality in many studies, and some have found differential effects. DATA AND METHODS: Canadian Community Health Survey-Healthy Aging data (2008/2009) linked to the Canadian Vital Statistics-Death Database were used to estimate the prevalence of social isolation measured objectively (low social participation) and subjectively (feelings of loneliness and weak sense of community belonging). Associations with death during the 8 to 9 year follow-up period were examined with multivariate Cox proportional hazards models controlling for sociodemographic and health-related characteristics. Structural equation models (SEM) examined direct paths with survival time and indirect effects through health status controlling for covariates that were significant in the Cox models. Analyses were stratified by sex. RESULTS: An estimated 525,000 people (12%) aged 65 or older felt socially isolated and over 1 million (1,018,000) (24%) reported low participation. In multivariate Cox models, low participation was significantly associated with death for men and women even when the potential confounding effects of subjective isolation, socio-demographic characteristics, health status, and health behaviours were considered. Subjective isolation was not associated with death in final multivariate models for men or women. SEM revealed significant associations between low participation and survival time for men and women. In addition to the direct effects, there were significant indirect effects mediated by health status. There were no direct effects of subjective isolation on survival for men or women, only indirect effects mediated through health status. DISCUSSION: Subjective and objective isolation differed in their association with mortality.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".