Screen-based sedentary behaviour and adiposity among school children: Results from International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE) - Kenya
Bibliographic record
Abstract
BACKGROUND: High levels of sedentary behaviours have been independently associated with several negative health indicators, including obesity. Screen time (ST) is often used as a contributing measure of sedentary time. It is recommended that children spend no more than 2 hours on recreational sedentary screen-based activities daily. We describe screen-based sedentary time of urban school children and examine the associations between body mass index (BMI) and percent Body Fat (%BF) with ST levels. METHODS: Data were collected from 563 children aged 9 to 11 years attending 29 non-boarding primary schools in Nairobi, Kenya, as part of the International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE). Data were analysed to test for associations between ST and sex, type of school attended (public verses private), Socioeconomic status, adiposity, and access to electronic devices. We also assessed participants' ST on school and weekend days. RESULTS: Of the participants recruited, 15.5% had high ST levels, 67.9% spent no more than 2 hours in recreational screen activities on school days while 74.2% did not meet the guidelines on weekend days. Participants sex was associated with daily ST (t = 3.5, p<0.001), ST on the weekend (t = 3.9, p <0.001) and total ST per week (t = 3.5, p<0.001) with males having higher ST than females. ST was associated with type of school for daily ST (t = 3.6, p <0.001), ST on the weekend (t = 4.5, p<0.001) and total ST per week (t = 3.6, p<0.001) where private schools pupils had higher ST. ST was not associated with BMI. ST was not associated with %BF except on weekend days (p = 0.038) where those classified as overfat/obese (fat) had higher ST. CONCLUSIONS: A large proportion of children spend more time than recommended on screen activities particularly on weekend days. Strategies to improve healthy living should focus on the reduction of sedentary ST for school-aged children.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".