Sleep duration, lifestyles and chronic diseases: a cross-sectional population-based study
Bibliographic record
Abstract
BACKGROUND Adequate sleep is essential for health. Both, short and long sleep durations are associated to worse quality of life and poor health outcomes. Portugal represents a specific population model, since according to European statistics it has high rates of chronic diseases like depression, hypertension, diabetes and stroke; and low quality of life as well as low index of physical activity, while in parallel it has some other good health indicators such as: low age-standardized mortality for both genders, nutrition in terms of energy and fruit consumption, smoking and alcohol, obesity and overweight prevalence. The aim of this study was to characterize health and chronic diseases, lifestyles and quality of life in subjects with short and long sleep duration. Methods A population-based cross-sectional evaluation of the third wave of follow-up of the EpiDoC Cohort was carried between 2015-2016. A sample of 5,436 adults ≥18 years, representative of the national population, self-reported their daily total sleep time. Associations between short sleep duration (SSD ≤5h), long sleep duration (LSD≥9h) and independent variables were determined. Results The prevalence for SSD was high (20.7%) and the LSD (5.9%) was low. Being older, with lower education, retired and unemployed were associated to SSD and LSD (p<0.01). Being obese was associated to SSD as well as hypertension, gastrointestinal disease and hypercholesterolemia (p<0.01). SSD and LSD, were associated with diabetes (p<0.01 and p=0.03) and depression (p<0.01 and p=0.02) respectively. Cardiovascular disease (p<0.01) was associated to LSD. Multimorbidity (p<0.01) was associated to SSD. Worse quality of life and bad physical function were associated to SSD and LSD, as well as being hospitalized in the previous 12 months (p<0.01). Conclusions Socio-demographic, physical activity and chronic diseases were associated to reduction and extension of sleep duration. There was no association between rheumatic diseases and cancer with sleep duration, as found in other studies. This study emphasizes the burden of self-reported SSD for Portugal, its consequences to health and the need to increase sleep awareness campaigns enhancing the importance of sleep in health. Furthermore, it emphasizes that chronic diseases risks are dependent on multiple parameters which varying in different countries or regions, imply the need of regional studies and interventions.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".