Ramadan-Induced Lifestyle Changes: Effects on Sleep and Physical Activity in Nonfasting Individuals With Type 1 Diabetes
Bibliographic record
Abstract
OBJECTIVES: In this study, we aimed to identify sleep patterns, physical fitness, and barriers to physical activity (PA) during Ramadan observance in a cohort of nonfasting individuals with type 1 diabetes (T1D). METHODS: Sixty-one nonfasting individuals with T1D, age 28.34±9.43 years (ranging from 15 to 54 years), completed questionnaires before and during Ramadan. The questionnaires included 3 assessment instruments: the Barriers to Physical Activity in Type 1 Diabetes (BAPAD1), the Pittsburgh Sleep Quality Index (PSQI), and the International Physical Activity Questionnaire. RESULTS: During Ramadan, there was no significant change in BAPAD1 scores compared to before Ramadan (p=0.378). The primary barriers encompassed hypoglycemia risk, work schedules, diabetes control, and fatigue. Moreover, subjective sleep quality deteriorated during Ramadan compared to the pre-Ramadan period (p<0.001). Sleep duration decreased by 58 minutes (p<0.01) and was associated with later bedtimes and more awakenings. There was a notable decrease in PA levels (p=0.042), particularly for vigorous activities (p=0.017), whereas sedentary time showed a significant increase (p=0.008). CONCLUSIONS: Ramadan observance did not affect barriers to PA in individuals with T1D despite alteration of sleep patterns and PA levels. Lifestyle alterations associated with Ramadan observance significantly impact individuals with T1D who are not fasting, resulting in reduced PA, shortened sleep duration, and increased sedentary time.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".