Different Associations of Diabetes With β-Cell Dysfunction and Insulin Resistance Among Obese and Nonobese Chinese Women With Prior Gestational Diabetes Mellitus
Bibliographic record
Abstract
OBJECTIVE: To examine the relative contributions of β-cell dysfunction and insulin resistance to postpartum diabetes risk among obese and nonobese women with prior gestational diabetes mellitus (GDM). RESEARCH DESIGN AND METHODS: We performed a cross-sectional survey 1-5 years after 1,263 women who had GDM gave birth. Polytomous logistic regression models were used to assess the associations of β-cell dysfunction (the lower quartile of HOMA-%β), insulin resistance (the upper quartile of HOMA-IR), decreased insulin sensitivity (the lower quartile of HOMA-%S), and different categories of BMI with prediabetes and diabetes risk. RESULTS: β-Cell dysfunction, insulin resistance, and decreased insulin sensitivity all were significantly associated with hyperglycemic status across normal weight, overweight, and obese groups, and the patterns of insulin resistance and decreased insulin sensitivity were similar. BMI was inversely associated with β-cell dysfunction and positively associated with insulin resistance across normal glucose, prediabetes, and diabetes categories. Compared with women with normal glucose and weight, obese women with normal glucose had increased β-cell secretory function (odds ratio [OR] 0.09 [95% CI 0.02-0.37]) and insulin resistance (OR 17.4 [95% CI 9.47-31.9]). Normal weight diabetic women displayed the most β-cell dysfunction (OR 13.6 [95% CI 4.06-45.3]), whereas obese diabetic women displayed the highest insulin resistance (OR 45.8 [95% CI 18.5-113]). CONCLUSIONS: For women with prior GDM, β-cell dysfunction had more pronounced contribution to postpartum diabetes among nonobese subjects, whereas insulin resistance contributed more to postpartum hyperglycemia among obese subjects.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".