Socio-demographic and maternal predictors of adherence to 24-hour movement guidelines in Singaporean children
Bibliographic record
Abstract
Abstract Purpose Integrated 24-Hour Movement Guidelines provide specific recommendations on screen viewing (SV), moderate-to-vigorous physical activity (MVPA) and sleep to improve health of children and youth. However, few studies have examined whether these guidelines are met in young children, particularly in Asia. We evaluated adherence to integrated and individual guidelines and its predictors in 5.5-year-old Singaporean children. Methods Growing Up in Singapore towards Healthy Outcomes (GUSTO) is a mother-offspring birth cohort study. At age 5.5 years, child SV was reported by parents. Movement behaviours (MBs) were measured continuously using wrist-worn accelerometers over 7 consecutive days and nights. For accelerometer data including ≥3 days with ≥16 h/day we estimated mean (±SD) daily MVPA, SV and nighttime sleep duration across the week. Adherence to integrated (Canadian/Australian) guidelines was defined as meeting all individual guidelines: ≥60 min of MVPA/day, ≤2 h of screen time/day, and 9–11 h of sleep/night. Socio-demographic and maternal predictors collected at pregnancy enrolment and at 26–28 weeks’ gestation were examined by multivariable logistic regression. Results Of 864 children followed up age 5.5 years, 547 (63.3%) had both valid ActiGraph and questionnaire data (51.7% boys and 58.3% Chinese ethnicity). Children averaged 101.9 (± 88.7) min/day SV, 67.3 (± 23.7) min/day MVPA and 480.6 (± 57.2) min/night sleep. Few children met integrated guidelines. Specifically, the proportions of children who met none, SV, MVPA, sleep and integrated guidelines were 11.2, 70.2, 59.6, 13.7 and 5.5%, respectively. Multivariable analysis showed that maternal activity and television (TV) viewing were associated with meeting integrated guidelines (insufficiently vs. highly active (OR [95% CI]): 0.11 [0.01, 0.95]; 2–3 vs. ≥ 3 h TV: 3.52 [1.02, 12.22]). Examining higher adherence to individual guidelines, Chinese ethnicity, younger maternal age and lower maternal TV and sleep time were associated with greater SV; male sex, Malay ethnicity, higher birth order and higher maternal activity level were associated with greater MVPA; and older maternal age was associated with adherence to sleep guideline. Conclusions Beyond individual behaviours, consideration of the full spectrum of MBs may be important to improve children’s health. However, few Singaporean children adhere to integrated 24-h movement guidelines. Maternal behaviours as early as during pregnancy could be important targets for future interventions aiming to promote these MBs in children.
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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 | 0.000 |
| 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) | 0.179 | 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".