Sex differences in insulin action and body fat distribution in overweight and obese middle-aged and older men and women
Bibliographic record
Abstract
Controversy exists as to whether there are differences in insulin action between older men and women, and what factors contribute to these differences. This study tests the hypothesis that sex differences in regional fat distribution contribute to a disparity in insulin sensitivity in older men vs. older women. Healthy, older (50-71 years), sedentary men (n = 28) and women (n = 29) were recruited to participate in the study. Body fat, fat-free mass (FFM), and visceral (VAT) and subcutaneous abdominal (SAT) adipose tissue areas were measured by DXA and computed tomography (CT). For measurements of insulin-stimulated glucose disposal (M), insulin was infused at a constant rate of 240 pmol.m(-2).min(-1), and M was calculated between the 90th and 120th min of the hyperinsulinemic-euglycemic clamp. The men weighed 16% more and had 16% higher waist and 4% lower hip circumferences than women (p < 0.05 for all). Total fat mass and SAT were 21% and 33% lower and FFM was 49% higher in men than in women, whereas waist-to-hip ratio (WHR) and VAT:SAT ratio were 21% and 56% higher in men than in women (p < 0.05 for all). Although insulin concentrations during the glucose clamp were higher in men, M was 47% lower in men vs. women (21.7 +/- 1.1 vs. 46.7 +/- 3.1 micromol.L(-1).kg FFM(-1).min(-1), p < 0.05). The sex-related differences in M persisted after controlling for insulin concentrations during the glucose clamp, for waist, WHR, and VAT:SAT. Older men are more insulin resistant than women, despite lower body fat and subcutaneous abdominal fat. This difference in insulin sensitivity is not explained by abdominal fat distribution, therefore other metabolic factors contribute to the sex differences in insulin sensitivity.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".