Resistin is an adipocyte-secreted cytokine recently discovered and has been proposed as a link between obesity and diabetes. Many resistin gene polymorphisms were described and their implication in obesity and metabolic syndrome (MetS) was controversial. Our aim was to study the relationship between four resistin polymorphisms (420C/G, 44G/A, 62G/A, and 394C/G), MetS parameters, and the risk of obesity in Tunisian volunteers. We recruited 169 nonobese (sex ratio=0.594; mean age=43.25±13.12 years; mean body mass index [BMI]=24.73±3.50 kg/m(2)) and 160 obese subjects (sex ratio=0.221; mean age=48.41±10.92 years; mean BMI=36.6±4.8 kg/m(2)). Genotyping was performed using polymerase chain reaction-restriction fragment length polymorphism. Anthropometric parameters, lipid levels, glycemia, and insulinemia were measured. BMI was calculated and insulin resistance was evaluated with the homeostasis model assessment insulin resistance (HOMA-IR). Statistical analyses were performed by SPSS 17.0. The 420C/G seems to contribute to obesity. In fact adjusted odds ratio (OR) of obesity associated to mutated genotypes was 2.17 and 95% confidence interval was 1.28-3.68 (p=0.004). Mutated genotypes at 420C/G were associated with higher waist circumference and BMI. In addition, 44G/A polymorphism was associated with increased total cholesterol and low-density lipoprotein-cholesterol levels. The other genotypes showed no association with MetS parameters. Concerning association between single-nucleotide polymorphisms and MetS risk, only mutated genotypes at 44G/A increase the risk of MetS after adjustment to confounding parameters (OR=1.93, p=0.023). In conclusion, resistin gene polymorphisms 420C/G and 44G/A were associated with obesity and MetS parameters in Tunisian volunteers.
One of the current concerns of our planet is the degradation of the ecosystem which seems to be ascribable with the climate changes and which is likely to cause strong negative externalities which threaten the wellness of the populations as well of the countries developed as in the countries in the process of development. This research aims to study the effect of corruption on pollution and per capita income of 21 countries from the MENA region over the period 1996-2013, through the use of a dynamic panel data model. The main statements issued from this empirical test stipulate a positive direct impact of corruption on per capita emissions and a negative indirect effect of corruption on per capita income. Our results support also the Environmental Kuznets Curve hypothesis for carbon dioxide. The environmental quality deteriorates at early stages of economic growth and subsequently improves at a later stage.
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