Effects of a closed office environment on the risk of Sick Building Syndrome in a medical city in Riyadh, Saudi Arabia: Findings from a cross-sectional study
Bibliographic record
Abstract
Background: Sick Building Syndrome (SBS) is a state of discomfort and irritation in several body systems which affects employees in a closed office work environment. It has a 30% reported prevalence worldwide. This study aimed to determine the prevalence of Sick Building Syndrome and its associated symptoms. In addition, it also aimed to investigate the association between closed offices environment and the risk of Sick Building Syndrome as well as identifying its associated risk factors and its correlation to in the Medical City in Riyadh, Saudi Arabia. Methods: This cross-sectional study was conducted using a self-constructed questionnaire for data collection among office workers in four different during the year 2018. Convenient random sampling was then used to select study subjects for the study. Results: A total of 373 subjects participated in the study. SBS prevalence among office workers was found to be 20%. The study found that being female (OR 2.80; [95%CI: 1.61-4.84]), higher stress level (OR 2.885; [95%CI: 1.001-8.32]), allergies (OR 2.25; 95%CI: 1.32-3.85]), temperature fluctuations (OR 1.84; [95%CI 1.04-3.26]), noises (OR 1.83; [95%CI: 1.09-3.06]), and a cumulative exposure level to office conditions (OR 2.48; [95%CI: 1.47-4.16 ]) increased the likelihood of SBS. Four out of six SBS symptoms were reported in more than a quarter of the employees, while five symptoms were significantly associated with building types. Age and the number of years working in the same building or office were found to be protective factors (OR 0.64, OR 0.69, OR 0.75) respectively. Conclusion: The high prevalence of SBS among office workers should attract attention to the existence of sick buildings in Saudi Arabia. Awareness and preventive measures should be adopted by the responsible entities of these sick buildings to reduce the health effects of SBS among office workers.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".