Social epidemiology of cardiometabolic risk factors in early adolescents
Bibliographic record
Abstract
Background: To estimate associations between sociodemographic factors and cardiometabolic risk factors among a demographically diverse sample of U.S. adolescents aged 10-14 years. Methods: This study analyzed data from the Adolescent Brain Cognitive Development (ABCD) Study (N = 1412), Years 2 and 3 (2018-2021). Cardiometabolic risk factors including hemoglobin A1c and cholesterol (total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and non-HDL-C) were assessed. Multivariable linear regression models were conducted to estimate the associations between sociodemographic factors (age, sex, race and ethnicity, household income, and parental education) and cardiometabolic risk factors (hemoglobin A1c, TC, HDL-C, and non-HDL-C). Results: The average hemoglobin A1c level was 5.2 % (±0.4 %), the average TC level was 156.6 (±28.9) mg/dL, and the average HDL-C level was 56.0 (±12.9) mg/dL. Out of our sample, 0.5 % had diabetes (hemoglobin A1c ≥ 6.5 %), 7.6 % had high TC (≥200 mg/dL), and 7.4 % had low HDL-C (<40 mg/dL). Older age was associated with lower TC, HDL-C, and non-HDL-C levels. Male sex was associated with higher hemoglobin A1c (beta coefficient [B] 0.04; 95 % confidence interval [CI], 0.00, 0.08; p = 0.037) and lower TC (B -3.14; 95 % CI, -6.17, -0.11; p = 0.042) compared to female sex. Black and Native American race and ethnicity were associated with higher hemoglobin A1c compared to White race. Higher household income was associated with higher TC and HDL-C. Conclusion: This study of a diverse population of early adolescents identified sociodemographic differences in hemoglobin A1c and cholesterol levels that can inform clinical and public health interventions.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".