28 The effect of screen time on cardiometabolic risk in young children: A longitudinal cohort study
Bibliographic record
Abstract
Young children in Canada do not meet the current screen time recommendations (< 1 hour for children 3 to 4 years; < 2 hours for children 5 years and older). While increased screen time is associated with physical and psychological health consequences in children, very little is known regarding the association with cardiometabolic risk (CMR) in young children. This study defined screen time as the use of TV, DVD/video, computer/laptop, video games, and handheld devices (e.g., cell phone, iPad Touch, iPad, etc.) on a typical weekday and a weekend day. The primary objective of this study was to examine the association between screen time and total CMR score [sum of age- and sex-standardized z-scores of systolic blood pressure (SBP), glucose, triglycerides, high-density lipoprotein (HDL) cholesterol, and waist circumference (WC) / square root of 5]. The secondary objectives were to examine associations between screen time and individual CMR factors including waist-to-height ratio and non-high-density lipoprotein (non-HDL) cholesterol. A longitudinal cohort study was conducted with young children 3-to-6-years (n = 1,706). Children with repeated measures of both screen time and CMR were included in the study. Generalized estimating equation (GEE) multivariate linear regressions were conducted to evaluate the associations. Among those aged 3-to-4-years, the proportion of children meeting the screen time guidelines was 10.8%, with 61.9% of those being females, and 56.3% males. In children over the age of 5, 37.7% met the screen time guideline, with no differences by sex. No statistically significant associations were found between screen time and total CMR nor the individual factors of glucose, SBP, triglycerides, WC, and waist-to-height ratio (p > 0.05), after adjusting for confounders. A small and statistically significant association between screen time and non-HDL cholesterol was reported (B = 8.80x10-3; 95% CI: 1.61x10-3, 1.59x10-2; p = 0.02). Studies are needed to understand how exposure to screens at a very young age impacts CMR beyond early childhood. The significant association ascertained between screen time and non-HDL cholesterol should be examined further over time, and may contribute to the development of appropriate health promotion interventions to examine how decreasing screen time can decrease the risk of non-HDL cholesterol among young children as they age.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".