Nutritional Factors, Physical Health and Immigrant Status Are Associated with Anxiety Disorders among Middle-Aged and Older Adults: Findings from Baseline Data of The Canadian Longitudinal Study on Aging (CLSA)
Bibliographic record
Abstract
The main purpose of this study was to compare the lifetime prevalence of anxiety disorders among foreign-born and Canadian-born adults in middle and later life. Using baseline data of the Canadian Longitudinal Study on Aging (2010-2015), multivariable binary logistic regression was conducted to investigate anxiety diagnosis and immigrant status, while controlling for socio-economic, health-related, and nutrition covariates. Of 26,991 participants (49.3% men, 82.5% Canadian born, 58.5% aged 45-65 years), the overall prevalence of self-reported physician diagnosis of anxiety disorders was 8.5%, with immigrants being lower than Canadian-born respondents (6.4% vs. 9.3%, p < 0.001). After accounting for all covariates, the adjusted odds ratio (aOR) for anxiety disorders was lower among immigrants (aOR = 0.77, 95% CI: 0.67-0.88) compared to those who were Canadian born. Identified risk factors included: younger age (aORs = 1.79-3.52), being a woman (aOR = 1.25, 95% CI: 1.07-1.46), single status (aOR = 1.27, 95% CI: 1.09-1.48), lower income (aORs = 1.28-2.68), multi-morbidities (aORs = 2.73-5.13), chronic pain (aOR = 1.31, 95% CI: 1.18-1.44), lifetime smoking ≥ 100 cigarettes (aOR = 1.35, 95% CI: 1.23-1.48), BMI < 18.5 (aOR = 1.87, 95% CI: 1.20-2.92), body fat ≥ 26% (aORs = 1.28-1.79), fruit and vegetable intake (< 3/day; aORs = 1.24-1.26), and pastry consumption (> 1/day; aOR = 1.55, 95% CI: 1.12-1.15) (p < 0.05). Targeting socio-economic and nutritional risk factors may reduce the burden of anxiety disorders in middle and late adulthood.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | medium |
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".