Race, Visceral Adipose Tissue, Plasma Lipids, and Lipoprotein Lipase Activity in Men and Women
Bibliographic record
Abstract
Abdominal obesity is associated with numerous metabolic alterations, such as hypertriglyceridemia and low levels of high density lipoprotein (HDL) cholesterol. However, compared with abdominally obese white individuals, abdominally obese black individuals have been characterized by higher plasma HDL cholesterol levels, suggesting that the impact of abdominal fat accumulation on the lipoprotein-lipid profile may differ among ethnic groups. Therefore, we have compared the associations between body fatness, visceral adipose tissue (AT) accumulation, and metabolic risk variables in a sample of 247 white men and 240 white women versus a sample of 93 black men and 143 black women. Although no difference in mean total body fatness was found between the 2 race groups, white men had higher levels of visceral AT than did black men (P<0.001). Despite the fact that black women had a greater body fat content than did white women, black women had levels of visceral AT that were similar to those of white women, suggesting a lower susceptibility to visceral obesity in black women. This lower accumulation of visceral AT in blacks was accompanied by significantly reduced apolipoprotein B concentrations and ratios of total cholesterol to HDL cholesterol as well as higher plasma HDL cholesterol levels (P<0.05) compared with those values in whites. Irrespective of sex, higher postheparin plasma hepatic lipase (HL) and lower lipoprotein lipase (LPL) activities were found in whites, resulting in an HL/LPL ratio that was twice as high in whites as in blacks (P<0.005). Although differences in lipoprotein-lipid levels were noted between whites and blacks, results from multiple regression analyses revealed that after control for morphometric and metabolic variables of the study (body fat mass, visceral AT, LPL, HL, and age), ethnicity had, per se, only a minor contribution to the variance in plasma lipoprotein levels. Thus, our results suggest that the higher plasma HDL cholesterol levels and the generally more cardioprotective plasma lipoprotein profile found in abdominally obese black versus white individuals are explained, at least to a certain extent, by a lower visceral AT deposition and a higher plasma LPL activity in black individuals.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".