Cross-sectional study of ethnic differences in physical fitness among children of South Asian, black African–Caribbean and white European origin: the Child Heart and Health Study in England (CHASE)
Bibliographic record
Abstract
OBJECTIVE: Little is known about levels of physical fitness in children from different ethnic groups in the UK. We therefore studied physical fitness in UK children (aged 9-10 years) of South Asian, black African-Caribbean and white European origin. DESIGN: Cross-sectional study. SETTING: Primary schools in the UK. PARTICIPANTS: 1625 children (aged 9-10 years) of South Asian, black African-Caribbean and white European origin in the UK studied between 2006 and 2007. OUTCOME MEASURES: A step test assessed submaximal physical fitness from which estimated VO2 max was derived. Ethnic differences in estimated VO2 max were estimated using multilevel linear regression allowing for clustering at school level and adjusting for age, sex and month as fixed effects. RESULTS: The study response rate was 63%. In adjusted analyses, boys had higher levels of estimated VO2 max than girls (mean difference 3.06 mL O2/min/kg, 95% CI 2.66 to 3.47, p<0.0001). Levels of estimated VO2 max were lower in South Asians than those in white Europeans (mean difference -0.79 mL O2/min/kg, 95% CI -1.41 to -0.18, p=0.01); levels of estimated VO2 max in black African-Caribbeans were higher than those in white Europeans (mean difference 0.60 mL O2/min/kg, 95% CI 0.02 to 1.17, p=0.04); these patterns were similar in boys and girls. The lower estimated VO2 max in South Asians, compared to white Europeans, was consistent among Indian, Pakistani and Bangladeshi children and was attenuated by 78% after adjustment for objectively measured physical activity (average daily steps). CONCLUSIONS: South Asian children have lower levels of physical fitness than white Europeans and black African-Caribbeans in the UK. This ethnic difference in physical fitness is at least partly explained by ethnic differences in physical activity.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".