Effects of Low-Intensity Combined Exercise Training on Body Composition, Metabolic Risk Factors and Cognitive Function in Old-Elderly Obese Women

2018 ◽  
Vol 71 ◽  
pp. 551-560
Author(s):  
Tae-Sung Lee ◽  
Nan-Jeong Sim ◽  
Ho-Seong Lee
2010 ◽  
Vol 30 (10) ◽  
pp. 1445-1453 ◽  
Author(s):  
A Gupta ◽  
V Gupta ◽  
AK Singh ◽  
S Tiwari ◽  
S Agrawal ◽  
...  

The present investigations were aimed to identify the possible association between genetic polymorphism in interleukin-6 (IL-6) G-174C gene, which confers susceptibility to metabolic syndrome, and serum level of resistin in North Indian women. The study population comprised 370 unrelated Indian women (192 having abdominal obesity and 178 controls). Polymorphism in genotype (CC+GC) of IL-6 G-174C gene was determined using a combination of polymerase chain reaction (PCR) and sequence-specific primer with restriction fragment length polymorphism (RFLP) technology. Insulin resistance (IR) and serum resistin level were also analyzed along with metabolic risk factors. Of 192 abdominal obese women, 147 (76.56%) were found to have mutant CC+GC ( p = 0.001) genotype and allele frequency ( p = 0.001), which was significantly higher 45 (23.44%) than non-obese and their respective wild type. The mutant genotype (CC+GC) of IL-6 gene was found to be associated significantly with high triglyceride ( p = 0.025) and resistin level ( p < 0.001), when compared with respective wild genotype (GG) in obese women. Non-obese women with no signs of metabolic risk factors were found to have significantly low level of serum resistin and IR in comparison to obese women having genetic polymorphism for IL-6 G-174C gene. Study suggests that IL-6 G-174C gene is one among the susceptibility loci for metabolic syndrome in North Indian women. Genotype for this polymorphism may prove informative for prediction of genetic risk for metabolic syndrome. Further, high level of serum resistin molecules may be targeted to correlate with metabolic syndrome risk factors and could be used as early prediction marker.


2020 ◽  
Vol 17 ◽  
pp. 100171 ◽  
Author(s):  
Marcin Czeczelewski ◽  
Jan Czeczelewski ◽  
Ewa Czeczelewska ◽  
Anna Galczak-Kondraciuk

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