Dietary glycemic index and glycemic load and their relationship to cardiovascular risk factors in Chinese children
Bibliographic record
Abstract
The purpose of this study was to examine the cross-sectional associations between dietary glycemic index (GI) and glycemic load (GL) and cardiovascular disease (CVD) risk factors in Chinese children. A total of 234 Chinese schoolchildren aged 8-11 years in Guangdong participated in the study. Dietary intake was assessed via a 3-day dietary record. Seven established cardiovascular indicators were analyzed in this study: fasting plasma glucose (FPG), fasting triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), systolic blood pressure, and diastolic blood pressure. Higher dietary GI was significantly associated with higher TG levels (P = 0.037) and lower HDL-C levels (P = 0.005) after adjusting for age, sex, nutritional intake, physical activity, and body mass index z score. LDL-C was found to differ across tertiles of dietary GL. The middle tertile tended to show the highest level of LDL-C. TC, FPG, and blood pressure were independent of both dietary GI and GL. Our findings suggest that higher dietary GI is differentially associated with some CVD risk factors, including lower HDL-C and higher TG, in school-aged children from south China.
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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 | 0.000 | 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) | 0.001 | 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".