| Literature DB >> 12423554 |
Radka Lichnovská1, Simona Gwozdziewiczová, Jirí Hrebícek.
Abstract
BACKGROUND: The increase in the prevalence of insulin resistance-related metabolic syndrome, a disorder that greatly increases the risk of diabetes, heart attack and stroke, is alarming. One of the most frequent and early symptoms of metabolic syndrome is hypertriglyceridemia. We examined the gender differences between various metabolic factors related to insulin resistance in elderly non-diabetic men and postmenopausal women of comparable age suffering from hypertriglyceridemia, and compared them with healthy subjects of equal age.Entities:
Year: 2002 PMID: 12423554 PMCID: PMC140144 DOI: 10.1186/1475-2840-1-4
Source DB: PubMed Journal: Cardiovasc Diabetol ISSN: 1475-2840 Impact factor: 9.951
Main characteristics that served in selection of groups of patients under study
| WOMEN | ||||||
| 60.3 ± 11.0 | 58.6 ± 10.4 | 0.69 | 56.9 ± 13.0 | 62.0 ± 7.36 | 0.15 | |
| 5.07 ± 1.06 | 6.62 ± 0.82 | 5.15 ± 0.70 | 6.92 ± 1.01 | |||
| 1.11 ± 0.44 | 3.52 ± 1.38 | 1.42 ± 0.47 * | 2.72 ± 0.92* | |||
| 1.43 ± 0.39 | 0.96 ± 0.24 | 1.50 ± 0.21 | 1.21 ± 0.21*** | |||
| 3.08 ± 0.83 | 4.38 ± 1.06 | 3.21 ± 0.71 | 4.74 ± 1.02 | |||
Statistical significance between control and hyperlipemic groups was tested using the unpaired Student's T-test in the case of normal distribution of compared data sets, and using Kolmogorov-Smirnov's test when at least in one of the data sets compared the normal distribution was excluded (marked with KS). The significant p values are denoted by thick underlined numbers. With asterisks statistically significant differences between controls and hypelipemic patients of different gender are denoted (*, **, *** = p < 0,05, 0,01 and 0,001, respectively).
Detailed characteristics of the subjects under study
| 25.91 ± 3.58 | 28.51 ± 2.60 | 25.36 ± 3.72 | 26.73 ± 3.59 | 0.24 | ||
| 1.685 ± 0.771 | 3.137 ± 1.419 | 1.717 ± 0.893 | 2.694 ± 1.011 | |||
| 0,3596 ± 0,0263 | 0,3266 ± 0,0185 | 0,3603 ± 0,0281 | 0,3332 ± 0,0192 | |||
| 270.5 ± 65.4 | 379.9 ± 84.2 | 236.1 ± 67.0 | 270.8 ± 58.9*** | 0.13 | ||
| 5.31 ± 0.53 | 6.11 ± 0.95 | 5.26 ± 0.42 | 5.85 ± 0.70 | |||
| 6.96 ± 2.80 | 11.43 ± 4.50 | 7.33 ± 3.80 | 10.27 ± 3.52 | |||
| 2.68 ± 1.15 | 5.51 ± 2.75 | 2.51 ± 1.76 | 4.49 ± 3.11 | |||
| 0.66 ± 0.31 | 1.11 ± 0.39 | 0.75 ± 0.35 | 0.92 ± 0.34 | 0.22KS | ||
| 3.07 ± 3.38 | 6.21 ± 3.78 | 16.06 ± 13*** | 17.79 ± 5.9** | 0.17KS | ||
| 14.2 ± 4.15 | 11.52 ± 2.77 | 0.063KS | 11.65 ± 6.80 | 12.73 ± 9.15 | 0.43KS | |
| 3.86 ± 2.47 | 4.53 ± 1.97 | 0.46 | 3.09 ± 1.80 | 3.79 ± 2.00 | 0.41KS | |
| 13.08 ± 6.75 | 19.63 ± 16.9 | 0.57KS | 12.28 ± 6.38 | 16.35 ± 16.8 | 0.99KS | |
BMI = body mass index, HOMA IR and QUICKI = homeostatic indexes of insulin resistance (see Methods), TNFα = tumor necrosis factor α, hFABP = heart fraction of fatty acid binding protein, ACL-IgG = IgG anticardiolipin. Other designations are the same as in Table 1.
Figure 1Schematic presentation of 95% confidence limits of insulin resistance indexes HOMA IR and QUICKI in groups of control and hyperlipemic women and men. = Controls (women) = Controls(men) = Hyperlipemic women = Hyperlipemic men
Spearman's correlations between HOMA IR and various metabolic factors studied
| Sk = 0,248 | Sk = 0,515 | Sk = 0,006 | Sk = 0,428 | Sk = -0,119 | Sk = -0,405 | |||
| p = 0,49 | p = 0,13 | p = 0,85 | p = 0,29 | p = 0,778 | p = 0,319 | |||
| Sk = 0,354 | Sk = 0,157 | Sk = 0,393 | Sk = 0,296 | Sk = 0,134 | ||||
| p = 0,13 | p = 0,51 | p = 0,13 | p = 0,459 | p = 0,325 | p = 0.660 | |||
| Sk = 0,358 | Sk = -0,278 | Sk = -0,180 | Sk = -0,057 | Sk = -0,235 | Sk = 0,173 | Sk = 0,014 | ||
| p = 0,12 | P = 0,24 | p = 0,45 | p = 0,99 | p = 0,317 | p = 0,466 | p = 0,952 | ||
| Sk = 0,308 | Sk = 0,334 | Sk = -0,111 | Sk = 0,079 | Sk = 0,224 | ||||
| p = 0,19 | p = 0,15 | p = 0,85 | p = 0,740 | p = 0.342 | ||||
Sk = Spearman's correlation index. Significant values (p < 0,05) are denoted with thick numbers.
Multiple regression analysis of data from men and women (controls and tests).
| -0,27 | -1,07 | 0,11 | -0,06 | 0,19 | 0,29 | 2,74 | -1,95 | 0,31 | 0,02 | 0,05 | |||
| 0,91 | 0,04 | 0,55 | 0,79 | 0,03 | 0,11 | 0,09 | 0,87 | 0,19 | |||||
| -0,75 | -1,68 | -0,07 | 0,19 | 2,62 | -1,83 | 0,34 | 0,05 | ||||||
| 0,73 | 0,03 | 0,68 | 0,016 | 0,09 | 0,04 | 0,16 | |||||||
| -0,84 | -1,52 | 0,19 | 4,11 | -1,98 | 0,38 | ||||||||
| 0,69 | 0,015 | ||||||||||||
| -2,54 | 0,18 | 0,17 | 6,09 | -2,86 | |||||||||
| 0,25 | |||||||||||||
| 0,20 | 0,17 | -0,04 | -1,46 | -0,07 | 0,27 | 0,78 | 0,05 | 0,05 | -0,95 | 0,41 | |||
| 0,94 | 0,055 | 0,62 | 0,09 | 0,70 | 0,62 | 0,17 | 0,14 | ||||||
| 0,14 | 0,16 | -0,04 | -1,29 | 0,27 | 2,32 | 0,05 | 1,15 | 0,45 | |||||
| 0,95 | 0,054 | 0,58 | 0,08 | 0,04 | 0,07 | ||||||||
| -0,84 | 0,18 | -1052 | 0,36 | 0,06 | 0,61 | ||||||||
| 0,69 | 0,31 | ||||||||||||
| -2,55 | 0,19 | 0,17 | 0,79 | 0,68 | |||||||||
| 0,25 | |||||||||||||
| 0,54 | 0,09 | 0,13 | -1,07 | -0,03 | 1,90 | 0,01 | 0,03 | -1,14 | 0,46 | ||||
| 0,81 | 0,31 | 0,10 | 0,19 | 0,85 | 0,18 | 0,73 | 0,077 | ||||||
| 0,52 | 0,09 | 0,13 | -0,99 | 2,18 | 0,04 | -1,14 | 0,47 | ||||||
| 0,81 | 0,30 | 0,08 | 0,14 | 0,06 | 0,07 | ||||||||
| 2,62 | 0,18 | -0,80 | 0,13 | 0,05 | 0,64 | ||||||||
| 0,007 | 0,22 | 0,68 | |||||||||||
| 1,59 | 0,20 | 0,79 | 0,68 | ||||||||||
| 0,0001 | |||||||||||||
| 2,48 | 0,17 | -0,04 | -0,05 | 0,004 | 0,29 | 0,46 | 0,04 | 0,05 | 0,17 | 0,002 | |||
| 0,07 | 0,57 | 0,70 | 0,82 | 0,38 | 0,82 | ||||||||
| 2,49 | 0,18 | -0,04 | -0,04 | 0,29 | 0,52 | 0,04 | 0,04 | 0,17 | |||||
| 0,06 | 0,56 | 0,72 | 0,25 | ||||||||||
| 2,27 | 0,18 | -0,04 | 0,28 | 1,25 | 0,04 | 0,04 | |||||||
| 0,04 | 0,58 | 0,0012 | |||||||||||
| 1,59 | 0,20 | 1,36 | 0,05 | 0,26 | |||||||||
| 0,0001 | 0,0001 | ||||||||||||
HOMA IR was taken as dependent variable, various combinations of metabolic factors studied as independent variables. Par. = parameter (slope, regression coefficient). T = 0 = p-value in testing the regression coefficient being zero. Interc = intercept. R = coefficient of determination (expressing the percentage of determination of dependent variable by independent variables). A step-down regression model was used to disclose dominant independent variables (see Statistics). R2 of dominant independent variables and statistically significant regression coefficients are denoted by thick numbers.