Sex-specific associations of fat mass and muscle mass with cardiovascular disease risk factors in adults with type 2 diabetes living with overweight and obesity: secondary analysis of the Look AHEAD trial
Bibliographic record
Abstract
Abstract Background Distinguishable sex differences exist in fat mass and muscle mass. High fat mass and low muscle mass are independently associated with cardiovascular disease (CVD) risk factors in people living with type 2 diabetes; however, it is unknown if the association between fat mass and CVD risk is modified by muscle mass, or vice versa. This study examined the sex-specific interplay between fat mass and muscle mass on CVD risk factors in adults with type 2 diabetes living with overweight and obesity. Methods Dual-energy X-ray absorptiometry (DXA) measures were used to compute fat mass index (FMI) and appendicular muscle mass index (ASMI), and participants were separated into high-fat mass vs. low-fat mass and high-muscle mass vs. low-muscle mass. A two-way analysis of covariance (ANCOVA: high-FMI vs. low-FMI by high-ASMI vs. low-ASMI) was performed on CVD risk factors (i.e., hemoglobin A1C [A1C]; high-density lipoprotein cholesterol; low-density lipoprotein cholesterol; triglycerides; systolic and diastolic blood pressure; cardiorespiratory fitness, depression and health related-quality of life [HR-QoL]) at baseline and following a 1-year intensive lifestyle intervention (ILI) for females and males separately, with a primary focus on the fat mass by muscle mass interaction effects. Results Data from 1,369 participants (62.7% females) who completed baseline DXA were analyzed. In females, there was a fat mass by muscle mass interaction effect on A1C (p = 0.016) at baseline. Post-hoc analysis showed that, in the low-FMI group, A1C was significantly higher in low-ASMI when compared to high-ASMI (60.3 ± 14.1 vs. 55.5 ± 13.5 mmol/mol, p = 0.023). In the high-FMI group, there was no difference between high-ASMI and low-ASMI (56.4 ± 12.5 vs. 56.5 ± 12.8 mmol/mol, p = 0.610). In males, only high-FMI was associated with higher A1C when compared to low-FMI (57.1 ± 14.4 vs. 54.2 ± 12.0 mmol/mol, p = 0.008) at baseline. Following ILI, there were significant fat mass by muscle mass interaction effects on changes in the mental component of HR-QoL in males. Conclusion Considering that A1C predicts future CVD, strategies to lower A1C may be especially important in females with low fat and low muscle mass living with type 2 diabetes. Our results highlight the complicated and sex-specific contribution of fat mass and muscle mass to CVD risk factors.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".