Prediabetes: An emerging public health concern in adolescents
Bibliographic record
Abstract
OBJECTIVES: To identify the presence of risk factors for type 2 diabetes (ethnicity, body mass index, blood glucose tolerance and blood pressure) and to determine the prevalence of prediabetes and type 2 diabetes in Canadian adolescents attending two multicultural urban high schools. METHODS: A total of 266 multicultural urban high school students who live in a mid-sized Western Canadian city, aged 14-21, were screened for risk factors of prediabetes and type 2 diabetes in March-April 2018. Data with respect to demographics, family history of diabetes, anthropometrics, blood pressure and haemoglobin A1c (HbA1c) were collected. Data analysis was done using descriptive and inferential statistics in addition to chi-square analyses. RESULTS: Based on body mass index, 38% of the adolescents were classified as either overweight or obese. Overweight rates for females (69.8%) were double than males (30.2%); however, males (52.2%) were more likely to obese than the females (47.8%). Based on HbA1c levels, 29.3% were at high risk to develop either diabetes or prediabetes and 2.6% were classified in the prediabetes range. Prehypertension/hypertension rates of 47% in the sample increased to 51% in those adolescents with elevated HbA1c; the majority of these prehypertensive/hypertensive participants were male. CONCLUSION: High rates of overweight/obesity and prehypertension/hypertension were found in the adolescents studied and indicated the presence of prediabetes and an increased risk to develop type 2 diabetes and associated complications. Obesity and hypertension are major risk factors for developing type 2 diabetes, resulting in earlier exposure to metabolic consequences and, ultimately, long-term complications. Thus, timely research is needed to identify age-appropriate strategies that address risks and to develop recommendations for routine screening of adolescents for prediabetes.
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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 | 0.001 |
| 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".