Physical Activity and the Home Environment of Pre-School-Aged Children in Urban Bangladesh
Bibliographic record
Abstract
Physical activity (PA) is a key determinant of health and development, yet few studies have examined PA levels and risk factors for low PA among young children in low- and middle-income countries. This study aimed to describe the PA and sedentary (SED) behavior levels of preschool-aged children in Dhaka, Bangladesh, and to estimate the associations between potential risk factors in the home built environment and moderate to vigorous PA (MVPA). In a sample of preschool-aged children (n = 65) in Dhaka, PA and SED behavior were measured for 7 days using ActiGraph GT3X-BT accelerometers. Characteristics of the home built environment, socioeconomic factors, and anthropometry were also measured. Linear mixed-effects models were used to estimate multivariable-adjusted associations between characteristics of the home environment and MVPA. Preschool-aged children spent a mean (±standard deviation) 421 ± 48 and 82 ± 23 min per day sedentary and in MVPA, respectively. There were no statistically significant associations between factors in the home built environment (indoor area, presence of an open stairwell, and presence of gross motor activity facilitating items) and MVPA. These findings suggest that the studied characteristics of the home built environment may not significantly influence the MVPA observed among preschool-aged children in Dhaka. Future research should focus on other structural and behavioral factors that facilitate PA among young children in dense urban settings.
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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 | 0.000 | 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 | 0.001 | 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) | 0.002 | 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".