Trends in Prevalence of Insulin Resistance Among Nondiabetic/Nonprediabetic Adolescents, 1999–2020
Bibliographic record
Abstract
Purpose: Insulin resistance (IR)/hyperinsulinemia in young individuals is associated with the subsequent development of diabetes and cardiovascular disease. To assess trends in the prevalence of IR/hyperinsulinemia among nondiabetic/nonprediabetic adolescents in the US from 1999 to 2020. Methods: A total of 6111 adolescents without diabetes and prediabetes were included from ten cycles of National Health and Nutrition Examination Survey (NHANES) between 1999–2000 and 2017–2020. Hyperinsulinemia or IR was defined as fasting insulin or homeostasis model assessment of insulin resistance [HOMA‐IR] above the 75th percentile in all participants who underwent blood tests on fasting insulin, glucose, and hemoglobin A1c. Trends in prevalence rates were estimated using joinpoint regressions with heteroscedastic and uncorrelated errors. Results: The overall weighted median fasting insulin level, prevalence of hyperinsulinemia, and IR were 9.9 μU/ml [95% confidence interval (CI): 9.6, 10.1], 17.2% (95% CI: 15.7, 18.6), and 16.4% (95% CI: 15.2, 17.9), respectively. The estimated prevalence of hyperinsulinemia and HOMA‐IR increased significantly from 15.2% (95% CI: 12.1, 18.9) and 14.0% (95% CI: 11.1, 17.8) in 1999–2000% to 21.5% (95% CI: 17.1, 26.3) and 20.4% (95% CI: 16.4, 25.6) in 2017–2020, respectively, with a 3.35% (95% CI: 1.74, 4.99) and 3.41% (95% CI: 1.72, 5.12) relative increase per 2‐year survey cycle, respectively ( p for trend <0.05). Substantial increases were observed in the subgroups of girls, Hispanic, non‐Hispanic white, and overweight adolescents. Conclusions: The prevalence of hyperinsulinemia/IR increased substantially among US nondiabetic/nonprediabetic adolescents over the last two decades. Early detection and effective interventions are in dire need to reverse the rising tide.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".