Hypoadiponectinaemia in South Asian women during pregnancy: evidence of ethnic variation in adiponectin concentration
Bibliographic record
Abstract
AIMS: People of South Asian descent face an increased risk of Type 2 diabetes mellitus (DM) and coronary artery disease (CAD) compared with other ethnic groups. One candidate factor underlying this risk may be adiponectin, as circulating levels of this adipocyte-derived protein are reduced in both Type 2 DM and CAD. In a recent study, we assessed the relationship between adiponectin and gestational diabetes (GDM), a potential model of early events in the natural history of Type 2 DM. Here, we report the impact of ethnicity on plasma adiponectin concentration in that study. METHODS: A cross-sectional study was performed in 180 women undergoing oral glucose tolerance testing in late second or early third trimester to investigate the relationship between adiponectin and glucose tolerance in pregnancy. Based on self-reported ethnicity, participants were stratified into three groups: (i) Caucasian (n = 116), (ii) South Asian (n = 31), and (iii) Asian (n = 28). RESULTS: Median adiponectin concentration was much lower in the South Asian group (9.7 micro g/ml) than in Caucasians (15.8 micro g/ml) or Asians (16.1 micro g/ml) (overall P < 0.0001). With adjustment for age, prepregnancy body mass index, weight gain in pregnancy, previous history of GDM, family history of DM, fasting insulin and glucose intolerance, mean adiponectin remained significantly lower among South Asians compared with either Caucasians (P < 0.0001) or Asians (P = 0.0034). CONCLUSIONS: Women of South Asian descent exhibit significantly reduced plasma concentrations of adiponectin in pregnancy compared with Caucasian and Asian counterparts. This observation raises the possibility of hypoadiponectinaemia as a potential factor contributing to the increased risk of diabetes and cardiovascular disease in South Asians.
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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 | 0.002 |
| 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".