Risk Factors for Non-Communicable Diseases at Baseline and Their Short-Term Changes in a Workplace Cohort in Singapore
Bibliographic record
Abstract
We aimed to examine the behavioural and clinical risk factors for non-communicable diseases (NCDs) at baseline and their changes over 12 months in a workplace cohort in Singapore. A total of 464 full-time employees (age ≥ 21 years) were recruited from a variety of occupational settings, including offices, control rooms, and workshops. Of these, 424 (91.4%) were followed-up at three months and 334 (72.0%) were followed up at 12 months. Standardized questionnaires were used to collect data on health behaviours and clinical measurements were performed by trained staff using standard instruments and protocols. Age-adjusted changes in risk factors over time were examined using generalized estimating equations or linear mixed-effects models where appropriate. The mean age of the participants at baseline was 39.0 (SD: 11.4) years and 79.5% were men. Nearly a quarter (24.4%) were current smokers, slightly more than half (53.5%) were alcohol drinkers, two-thirds (66%) were consuming <5 servings of fruit and vegetables per day, and 23.1% were physically inactive. More than two-thirds (67%) were overweight or obese and 34.5% had central obesity. The mean follow-up was 8.6 months. After adjusting for age, over 12 months, there was a significant increase in the proportion consuming <5 servings of fruit and vegetables per day by 33% (p = 0.030), who were physically inactive by 64% (p < 0.001), and of overweight or obese people by 15% (p = 0.018). The burden of several key NCD risk factors at baseline was high and some worsened within a short period of time in this working population. There is a need for more targeted strategies for behaviour change towards a healthy lifestyle as part of the ongoing health and wellness programs at workplaces in Singapore.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".