Adiponectin and the Incidence of Type 2 Diabetes in Hispanics and African Americans
Bibliographic record
Abstract
OBJECTIVE: A recent meta-analysis of 13 prospective studies reported that higher levels of adiponectin were significantly associated with lower risk of type 2 diabetes. Most previous studies, however, were limited in their ability to adjust for appropriate confounding variables. Our objective, therefore, was to study this association after adjustment for directly measured adiposity and insulin sensitivity, expressed as the insulin sensitivity index (S(I)). RESEARCH DESIGN AND METHODS: The study included 1,096 Hispanic and African American participants free of diabetes at baseline (2000-2002) who returned for follow-up after 5 years. S(I) was determined from frequently sampled intravenous glucose tolerance tests with minimal model analysis. Visceral adipose tissue (VAT) area was determined by computed tomography. Diabetes and impaired fasting glucose (IFG) were defined using American Diabetes Association criteria. Multivariate generalized estimating equation logistic regression models were used to account for correlations within families. RESULTS: A total of 82 subjects met criteria for incident diabetes. After adjustment for age, sex, ethnicity, and smoking, adiponectin was significantly inversely associated with diabetes (odds ratio [OR] 0.54 per 1 SD difference [95% CI 0.38-0.76]). The association remained significant after additional adjustment in individual models for BMI, homeostasis model assessment of insulin resistance, or VAT (all P < 0.05). However, adiponectin was no longer associated in separate models adjusted for S(I) or IFG (OR 0.81 [0.56-1.16] and 0.75 [0.53-1.06], respectively). CONCLUSIONS: Adiponectin was inversely associated with incident diabetes after adjustment for conventional anthropometric and metabolic variables or VAT. Adjustment for detailed measures of S(I) attenuated this relationship, however, suggesting that the link between adiponectin and diabetes may operate at least in part through insulin resistance.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".