Prevalence of overweight, obesity and underweight among 5-year-old children in Saint Lucia by three methods of classification and a comparison with historical rates
Bibliographic record
Abstract
BACKGROUND: The study aimed to determine if child obesity rates have risen in the Caribbean nation of Saint Lucia, as found globally, and whether under-nutrition coexists, as in other developing nations. The average adult in Saint Lucia is overweight, thus considerable child obesity might be expected, but there are no current data. METHODS: Heights and weights were obtained from a sample (n= 425) of the 2001 birth cohort of Saint Lucian children measured during the nation-wide 2006/2007 Prior to School Entry Five-Year Assessment. Prevalence of overweight, obesity and underweight were estimated by Centers for Disease Control (CDC), Cole et al. and new World Health Organization (WHO) methods. Previously reported 1976 estimates, including children ≤60 months of age only, based on National Centre for Health Statistics curves, were adjusted to new WHO equivalents using an algorithm developed by Yang and de Onis, and compared with rates in our subsample of children ≤60 months of age (n= 99). RESULTS: Regardless of classification method, overweight and obesity rates were high: 14.4% and 9.2% (WHO); 11.3% and 12.0% (CDC); and 9.9% and 7.1% (Cole et al.), respectively. Underweight estimates also varied: 4.7% (WHO); 11.3% (CDC) and 6.6% (Cole et al.). Obesity in our young subsample (15.2%; WHO) was more than 3 times the adjusted 1976 rate (4.3%). CONCLUSIONS: Obesity among Saint Lucian pre-schoolers has tripled in 30 years. Our findings also suggest that this country, like many undergoing a 'nutrition transition', faces the dual challenge of over-nutrition and under-nutrition. Routine monitoring of overweight and underweight is needed in Saint Lucia, as is the implementation and evaluation of programmes to address these problems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".