Relationship between sense of community belonging and self-rated health across life stages
Bibliographic record
Abstract
BACKGROUND: Health interventions aimed at facilitating connectedness among seniors have recently gained traction, seeing as social connectedness is increasingly being recognized as an important determinant of health. However, research examining the association between connectedness and health across all age groups is limited, and few studies have focused on community belonging as a tangible aspect of social connectedness. Using a population-based Canadian cohort, this study aims to investigate (1) the associations between community belonging with self-rated general health and self-rated mental health, and (2) how these associations differ across life stages. METHODS: Data from six cycles of a national population health survey (Canadian Community Health Survey) from 2003 to 2014 were combined. Multinomial logistic regressions were run for both outcomes on the overall study sample, as well as within three age strata: (1) 18-39, (2) 40-59, and (3) ≥ 60 years old. RESULTS: Weaker community belonging exhibited an association with both poorer general and mental health, though a stronger association was observed with mental health. These associations were observed across all three age strata. In the fully adjusted model, among those reporting a very weak sense of community belonging, the odds of reporting the poorest versus best level of health were 3.21 (95% CI: 3.11, 3.31) times higher for general health, and 4.95 (95% CI: 4.75, 5.16) times higher for mental health, compared to those reporting a very strong sense of community belonging. The largest effects among those reporting very weak community belonging were observed among those aged between 40 and 59 years old. CONCLUSION: This study contributed to the evidence base supporting life stage differences in the relationship between community belonging and self-perceived health. This is a starting point to identifying how age-graded differences in unmet social needs relate to population health interventions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".