Relationship between life satisfaction and preventable hospitalisations: a population-based cohort study in Ontario, Canada
Bibliographic record
Abstract
OBJECTIVE: To examine if low life satisfaction is associated with an increased risk of being hospitalised for an ambulatory care sensitive condition (ACSC), in comparison to high life satisfaction DESIGN AND SETTING: Population-based cohort study of adults from Ontario, Canada. Baseline data were captured through the Canadian Community Health Survey (CCHS) and linked to health administrative data for follow-up information. PARTICIPANTS: 129 467 men and women between the ages 18 and 74. MAIN OUTCOME MEASURES: Time to avoidable hospitalisations defined by ACSCs. RESULTS: Life satisfaction was measured at baseline through the CCHS and follow-up information on ACSC hospitalisations were captured by linking participant respondents to hospitalisation records covered under a single payer health system. Within the study time frame (maximum of 14 years), 3037 individuals were hospitalised. Older men in the lowest household income quintile were more likely to be hospitalised with an ACSC. After controlling for age, sex, socioeconomic status (SES) and other behavioural factors, low life satisfaction at baseline had a strong relationship with future hospitalisations for ACSCs (HR 2.71; 95% CI 1.87 to 3.93). The hazards were highest for those who jointly had the lowest levels of life satisfaction and low household income (HR 3.80; 95% CI 2.13 to 6.73). Results did not meaningful change after running a competing risk survival analysis. CONCLUSIONS: This study demonstrates that poor life satisfaction is associated with hospitalisations for ACSCs after adjustment for several confounders. Furthermore, the magnitude of this relationship was greater for those who were more socioeconomically disadvantaged. This study adds to the existing literature on the impact of life satisfaction on health system outcomes by documenting its impact on avoidable hospitalisations in a universal health system.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".