The Prevalence of Obesity Among Children With Type 2 Diabetes
Bibliographic record
Abstract
Importance: The childhood obesity epidemic is presumed to drive pediatric type 2 diabetes (T2D); however, the global scale of obesity in children with T2D is unknown. Objectives: To evaluate the global prevalence of obesity in pediatric T2D, examine the association of sex and race with obesity risk, and assess the association of obesity with glycemic control and dyslipidemia. Data Sources: MEDLINE, Embase, CINAHL, Cochrane Library, and Web of Science were searched from database inception to June 16, 2022. Study Selection: Observational studies with at least 10 participants reporting the prevalence of obesity in patients with pediatric T2D were included. Data Extraction and Synthesis: Following the Meta-analysis of Observational Studies in Epidemiology reporting guideline, 2 independent reviewers in teams performed data extraction and risk of bias and level of evidence analyses. The meta-analysis was conducted using a random-effects model. Main Outcomes and Measures: The primary outcomes included the pooled prevalence rates of obesity in children with T2D. The secondary outcomes assessed pooled prevalence rates by sex and race and associations between obesity and glycemic control and dyslipidemia. Results: Of 57 articles included in the systematic review, 53 articles, with 8942 participants, were included in the meta-analysis. The overall prevalence of obesity among pediatric patients with T2D was 75.27% (95% CI, 70.47%-79.78%), and the prevalence of obesity at diabetes diagnosis among 4688 participants was 77.24% (95% CI, 70.55%-83.34%). While male participants had higher odds of obesity than female participants (odds ratio, 2.10; 95% CI, 1.33-3.31), Asian participants had the lowest prevalence of obesity (64.50%; 95% CI, 53.28%-74.99%), and White participants had the highest prevalence of obesity (89.86%; 95% CI, 71.50%-99.74%) compared with other racial groups. High heterogeneity across studies and varying degrees of glycemic control and dyslipidemia were noted. Conclusions and Relevance: The findings of this systematic review and meta-analysis suggest that obesity is not a universal phenotype in children with T2D. Further studies are needed to consider the role of obesity and other mechanisms in diabetes genesis in this population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".