Environmental Influences on Life Satisfaction and Depressive Symptoms Among Older Adults With Multimorbidity: Path Analysis Through Loneliness in the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: More older adults with multimorbidity are aging in place than ever before. Knowing how the environment affects their mental well-being could enhance the efficacy of age-friendly interventions for multimorbidity resilience. With reference to the Transdisciplinary Neighborhood Health Framework, we construct and examine a priori models of environmental influences on life satisfaction and depressive symptoms. RESEARCH DESIGN AND METHODS: Baseline and follow-up data (after 3 years) were drawn from the Canadian Longitudinal Study on Aging to identify a subsample (n = 14,301) of participants aged at least 65 years with at least 2 chronic diseases. Path analysis examined sociobehavioral attributes (i.e., social support, social participation, walking) and loneliness as primary and secondary mediators, controlling for age, sex, education, and outcomes during baseline. RESULTS: Good model fit was found (TFI = 1.00; CFI = 1.00; RMSEA < 0.001; SRMR < 0.001). The total effects of housing quality (rtotal = 0.08, -0.07) and neighborhood cohesion (rtotal = 0.03, -0.06) were weak but statistically significant in the expected direction. The mediators explained 21%-31% of the total effects of housing quality and 67%-100% of the total effects of neighborhood cohesion. Loneliness mediated 27%-29% of these environmental influences on mental well-being, whereas walking mediated a mere 0.4%-0.9% of the total effects. Walking did not explain the relationship between housing quality and mental well-being. DISCUSSION AND IMPLICATIONS: Data supported a priori pathways from environment to mental well-being through sociobehavioral attributes and loneliness. If these pathways from neighborhood cohesion to life satisfaction reflect causal effects, community-based age-friendly interventions should focus on enhancing neighborhood cohesion to mitigate loneliness among multimorbid older adults for their mental well-being.
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 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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".