Adiposity and glucose intolerance exacerbate components of metabolic syndrome in children consuming sugar‐sweetened beverages: <scp>QUALITY</scp> cohort study
Bibliographic record
Abstract
Summary What is already known about this subject The increase in sugar‐sweetened beverage (SSB) consumption over the last generation is temporally associated with epidemic levels of childhood obesity. There is increasing evidence linking added sugar consumption to the development of metabolic syndrome and type 2 diabetes. What this study adds Higher SSB consumption is associated with elevated systolic blood pressure and greater insulin resistance among overweight/obese children whereas these associations are not evident among normal‐weight children. In youth with impaired glucose tolerance, higher SSB consumption is strongly associated with greater adiposity. Background Sugar‐sweetened beverage (SSB) consumption is linked to weight gain and metabolic syndrome (MetS) components in children, but whether these associations are modified by excess weight and glucose tolerance status in children is not known. Objective The objective of this study was to examine the cross‐sectional associations between SSB intake and MetS components among children above and below the 85th body mass index (BMI) percentile and those with and without impaired glucose tolerance (IGT). Methods Data were from the QUébec Adiposity and Lifestyle InvesTigation in Youth study (2005–2008). Caucasian children aged 8–10 years (n = 632) were recruited from 1040 primary schools in Québec, Canada. SSB consumption was assessed by three 24‐h dietary recalls, body fat mass by dual‐energy absorptiometry, physical activity by 7‐d accelerometer. Multivariate linear regressions were used, with age, sex, fat mass index and physical activity as covariates, including waist circumference (WC), systolic blood pressure (SBP), concentrations of triglyceride and high‐density lipoprotein cholesterol and homeostasis model assessment of insulin resistance (HOMA‐IR) as outcome variables. Results Among overweight children, a 100‐mL higher SSB consumption was associated with a 0.1‐unit higher HOMA‐IR (P = 0.009) and a 1.1‐mm Hg higher SBP (P = 0.001). In children with IGT, a 100‐mL higher SSB consumption was associated with a 1.4‐mm Hg higher SBP and a 4.0‐cm higher WC (P < 0.001). These associations were not observed among children <85th BMI percentile. Conclusions Our results suggest that the association between higher SSB consumption and MetS components is more evident in overweight/obese and glucose‐intolerant children.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".