Associations Between Healthy Behaviors and Persistently Favorable Self-Rated Health in a Longitudinal Population-Based Study in Switzerland
Bibliographic record
Abstract
BACKGROUND: Self-rated health is a subjective yet valuable indicator of overall health status, influenced by various factors including physical, psychological, and socio-economic elements. Self-rated health could be telling and used by primary care physicians to evaluate overall present and predictive health. DESIGN: This study investigates the longitudinal evolution of self-rated health in Switzerland during the COVID-19 pandemic, focusing on the association of persistently favorable self-rated health with various predictors. PARTICIPANTS: This study based on the Specchio cohort, a population-based digital study in Geneva Switzerland, involved participants completing questionnaires from 2021 to 2023. MAIN MEASURES: Self-rated health was assessed alongside factors like physical and mental health, socio-economic status, and lifestyle behaviors. KEY RESULTS: The study included 7006 participants in 2021, and 3888 participants who answered all three follow-ups (2021, 2022, and 2023). At baseline, 34.9% of individuals reported very good, 54.6% reported good, 9.6% reported average, and 1.0% reported poor to very poor self-rated health. Overall, 29.1% had a worsening in their self-rated health between 2021 and 2023. A subset of participants (12.1%) maintained very good self-rated health throughout, demonstrating persistently favorable self-rated health during the COVID-19 pandemic. Positive health behaviors were associated with persistently favorable self-rated health (exercise aOR 1.13 [1.03-1.24]; healthy diet aOR 2.14 [1.70-2.68]; less screen time aOR 1.28 [1.03-1.58]; and better sleep quality aOR 2.48 [2.02-3.04]). Mental health and social support also played significant roles. CONCLUSION: The study underscores the significance of healthy lifestyle choices and social support in maintaining favorable self-rated health, particularly during challenging times like the COVID-19 pandemic. Primary care physicians should focus on promoting these factors, integrating these actions in their routine consultations, and advising patients to undertake in socially engaging activities to improve overall health perceptions and outcomes.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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, 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".