Factors associated with loneliness in immigrant and Canadian-born older adults in Ontario, Canada: a population-based study
Bibliographic record
Abstract
BACKGROUND: While loneliness is common in older adults, some immigrant groups are at higher risk. To inform tailored interventions, we identified factors associated with loneliness among immigrant and Canadian-born older adults living in Ontario, Canada. METHODS: We conducted a cross-sectional analysis of 2008/09 data from the Canadian Community Health Survey (Healthy Aging Cycle) and linked health administrative data for respondents 65 years and older residing in Ontario, Canada. Loneliness was measured using the Three-Item Loneliness Scale, with individuals categorized as 'lonely' if they had an overall score of 4 or greater. For immigrant and Canadian-born older adults, we developed separate multivariable logistic regression models to assess individual, relationship and community-level factors associated with loneliness. RESULTS: In a sample of 968 immigrant and 1703 Canadian-born older adults, we found a high prevalence of loneliness (30.8% and 34.0%, respectively). Shared correlates of loneliness included low positive social interaction and wanting to participate more in social, recreational or group activities. In older immigrants, unique correlates included: widowhood, poor health (i.e., physical, mental and social well-being), less time in Canada, and lower neighborhood-level ethnic diversity and income. Among Canadian-born older adults, unique correlates were: female sex, poor mental health, weak sense of community belonging and living alone. Older immigrant females, compared to older immigrant males, had greater prevalence (39.1% vs. 21.9%) of loneliness. CONCLUSIONS: Although both groups had shared correlates of loneliness, community-level factors were more strongly associated with loneliness in immigrants. These findings enhance our understanding of loneliness and can inform policy and practice tailored to immigrants.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".