Association of DXA-derived Fat Mass Indices and Anthropometry with Blood Lipid Profile in Postmenopausal Women
Bibliographic record
Abstract
PURPOSE: Our purpose was to determine whether dual energy X-ray absorptiometry (DXA)-derived fat mass indices or standard anthropometry was better for predicting blood lipid profile in postmenopausal women. METHODS: Subjects were 437 postmenopausal women (age 58.1±6.4y). Fat mass was assessed at total body, trunk and abdomen (i.e. upper L1 to lower L4 and costal ridges) using DXA. Anthropometric measurements included body mass index (BMI), and waist girth. Blood samples were analyzed for total cholesterol, triglycerides, HDL and LDL. RESULTS: BMI (kg/m2), waist girth and DXA-determined fat mass indices were significantly correlated with HDL, LDL, total cholesterol to HDL ratio, and LDL to HDL ratio. Among the indices assessed, DXA-derived, abdominal fat was the most predictive of the blood lipid measures, showing highest correlation coefficient estimates with triglycerides (r= 0.44, p<0.001), HDL-cholesterol (r=−0.44, p<0.001), LDL-cholesterol (r=0.14, p=0.05), total cholesterol to HDL ratio (r=0.45, p<0.001) and LDL to HDL ratio (r=0.34, p<0.001). After abdominal fat, waist girth had the next highest correlation with blood lipids. The results of regression analyses revealed that abdominal fat and waist girth can explain 20% and 16.5% of variation in total cholesterol to HDL ratio respectively. In sub analyses based on BMI groups, abdominal fat was the superior fat mass index for predicting blood lipid profile only in normal and overweight subjects. Among all indices, only waist girth had a significant correlation with total cholesterol to HDL ratio (r=0.21, p=0.03) in obese subjects. CONCLUSION: Among all DXA body composition or anthropometric measures, DXA-derived abdominal fat mass provides the most useful information regarding the risk of cardiovascular diseases through its relationship with blood lipid profile in non-obese postmenopausal women. Waist girth was the next strongest predictor of blood lipid status and is therefore a good measure in obese and non-obese postmenopausal women. Supported by the Canadian Institutes of Health Research, and the Heart and Stroke Foundation of Saskatchewan
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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".