Sociodemographic predictors of the association between self-reported sleep duration and depression
Bibliographic record
Abstract
A growing interest has been recently reported in exploring sleep duration within psychology context in particular to its relation to some mental chronic diseases such as depression. The aim of this study is to investigate the association between self-reported sleep hours as an outcome and self-perceived depression among Emirati adults, after adjusting for sociodemographic factors such as age, gender, marital status, and employment status. We performed a cross-sectional analysis using 11,455 participants baseline data of the UAE Healthy Future Study (UAEHFS). Univariate and multivariate logistic regression models were performed with self-reported sleep hours as an outcome. The predictors were the self-reported depression by measuring the PHQ-8 score, sociodemographic factors (age, gender, marital status, and employment status) Odds ratios with 95% confidence intervals (CI) were reported. In a sensitivity analysis, a multivariate imputation by chained equations (MICE) procedure was applied with classification and Regression Trees (CART) to impute missing values. Overall, 11,455 participants were included in the final analysis of this study. Participants' median age was 32.0 years (Interquartile-Range: 24.0, 39.0). There were 6,217 (54.3%) males included in this study. In total, 4,488 (63.6%) of the participants reported sleep duration of more than 7 hours. Statistically significant negative association was observed between the total PHQ-8 score as a measure for depression and binarized self-reported sleep, OR = 0.961 (95% CI: 0.948, 0.974). For one unit increase in age and BMI, the odds ratio of reporting shorter sleep was 0.979 (95% CI: 0.969, 0.990) and 0.987 (95% CI: 0.977, 0.998), respectively. The study findings indicate a correlation between self-reported depression and an increased probability of individuals reporting shorter self-perceived sleep durations especially when considering the sociodemographic factors as predictors. There was a variation in the effect of depression on sleep duration among different study groups. In particular, the association between reported sleep duration and reported depression, students and unemployed individuals have reported longer sleep hours as compared to employed participants. Also, married individuals reported a higher percentage of longer sleep duration as compared to single and unmarried ones when examined reported depression as a predictor to sleep duration. However, there was no gender differences in self-perceived sleep duration when associated with reported depression.
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 | 0.001 | 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 | 0.000 | 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".