IntroductionAround for the last 70 years, an annual average temperature in Mongolian territory has been increasedby 2.14°Ñ which is 3 times more rapid than the global average warming rate. Also, the number of heatwave days have been increased [1, 2].Heat wave day’s leads to heat related morbidity and mortality. Espesially, stroke [3-5], cardiovascular [3-13] and respiratory [3, 5, 10, 12] mortalities are prevelant. Cardiovascular mortality has been determinedas a leading cause of mortality in our population while it takes the 3rd place [14] as a cardiovascularmorbidity.As the city of Ulaanbaatar houses 46% of Mongolian population, heat effects on health in the area andits trend need to be assessed, analyzed and identifi ed.PurposeTo identify heat risk days to health of the population of Ulaanbaatar city between the years of 1985through 2015Materials and MethodUnder the requirements set to sample, heat risk days with temperatures above 21.10C or 700F refl ectedon weather forecasts broadcasted from 1985 through 2015 by the Information And Research InstituteOf Meteorology, Hydrology And Environment, Mongolia have been selected. The afore mentioneddata have been translated into the heat index of National Weather Service of USA and processed andconcluded [15] according to the special formula and tables.ResultsIt is shown that heat risk days for the health of population of the Ulaanbaatar city had been 201 from1985 through 1995, 385 from 1996 through 2005 and 373 from 2006 through 2015. The average heatrisk days per given year varied in numbers from 4 through 56 and trended to increase. The largest heatwave days in number happened in the year of 2010 which is 56.According to health impacts of heat risk days, we had 0-47 Cautions, 0-17 Extreme Cautions and 2Dangers in the each of 1999 and 2005 and 1 in 2007 whilst no Extreme Danger has not been recordedyet.Conclusions:1. The number of heat risk days in the area of Ulaanbaatar tends to increase2. The number of Caution and Extreme caution days of Ulaanbaatar is observed to increase. Increaseof “Danger” tagged days, happening of “Extreme” tagged days and heat intense will depend onclimate change.

This abstract is a brief summary of results of studies on climate change related potential health risks.Climate change is a phenomenon, which is resulted by a direct and indirect human-induced change inthe earth’s atmospheric composition during its natural course of variation.The main source of climate change is greenhouse gas emission in the atmosphere which is associatedwith human-related activities.One of the climate change’s effect is elevated atmospheric temperature or global warming which directlyaffects human health. There has been a direct link between a raise in the ambient temperature andcardiovascular morbidity cases sought medical assistances and increased cardiovascular mortality ratedetected. It is found to be that elderly; children and outdoor workers are susceptible to heat-stress duringhigh heats and heat waves. Also, media that, in terms of locations, tropical and sub-tropical countries arefound to be vulnerable to heat effects has pointed it out.Cardiovascular, respiratory and cerebrovascular diseases are commonly reported as the underlyingcause of death, because persons with these preexisting diseases are more susceptible to death duringheat waves and high temperature.Hypertensive, ischemic heart disease and stroke are prevalent contributors to cardiovascular mortality.Cardiovascular morbidity lines up in the 3rd place among the most common causes of the world humanmortality.Identifi cation of vulnerable groups during climate change is the most effective public health action whichis equally being critical in prevention. Therefore, initiate a public alert procedure on extreme heat eventssuch as high ambient temperature and consecutive heat wave days, as well as preventive measurestargeted on vulnerable groups are considered to be effective.

Introduction. The metabolic syndrome is related to increased risk of developing cardiovascular disease andtype 2 diabetes. Adiponectin is an adipose tissue-specific collagen-like factor, which is abundant in plasma, anda decrease of adiponectin is associated with obesity and type-2 diabetes.Goal. This study aimed to determine the ADIPOQ gene -11377 polymorphism in association with plasmaadiponectin level and risk factors of metabolic syndrome.Materials and Methods. We investigated adiponectin gene -11377C>G polymorphism in 156 subjects withmetabolic syndrome and 142 healthy control subjects. The -11377C>G polymorphic locus was amplified using theforward primer 5’-ACTTGCCCTGCCTCTGTCTG-3’ and the reverse primer, 5-CCTGGAGAACTGGAAGCTG-3’.A p value <0.05 was considered statistically significant.Results. Adiponectin level positively correlated with age, but correlated negatively with TG, waist circumference,waist hip ratio, diastolic blood pressure, weight and BMI (p < 0.05). With genotype CG and GG (6.57±3.09ng/ml) of -11377C>G had lower levels of serum adiponectin than those with the genotype CC (7.38±3.68ng/ml) butno significant difference in people with MS (p=0.157). Therefore with genotype CG and GG (168.56±113.31mg/dl) of -11377C>G had higher levels of serum triglycerides than those with the genotype CC (132.94±74.78mg/dl) significant difference in people with MS (OR=1.006, p=0.015). With CG and GG (75.04±12.49mg/dl) of-11377C>G had significantly higher glucose level compared to with the genotype CC (68.85±11.76mg/dl) inwithout MS (OR=1.071, p=0.017).Сonclusions.1. ADIPOQ gene -11377>G polymorphism of the adiponectin gene was found not to be related to adiponectinlevel (p=0.157).2. -11377C>G polymorphism was related to the metabolic syndrome susceptibility, and this polymorphismimpacted on circulating triglyceride and glucose concentrations.

Introduction: The metabolic syndrome (MS) is characterized by central obesity, hypertriglyceridemia,low high-density lipoprotein (HDL), increase blood pressure and raise fasting plasma glucose. ThePGC-1α gene is located on chromosome 4 p.15.1 in humans and encodes a protein containing 798amino acids. The protein encoded by this gene is a transcriptional coactivator that regulates thegenes involved in energy metabolism. PPARγ, a coactivator molecule recently identified based on itsability to interact with PPARγ, is involved in many important metabolic processes, including adaptivethermogenesis, mitochondrial biogenesis and fatty acid β–oxidation.Goal: To study the frequency of PGC-1α Gly482Ser polymorphism in people with MS in relation to therisk factors of the MS.Materials and methods: The study population comprised 302 unrelated Mongolian subjects (158 withmetabolic syndrome and 144 controls). The genotypes for polymorphism of candidate gene related toMS were determined using a RFLP analysis of the MspI digest of the PCR product.Result: From the control group, 33.4% (48) had GG, 47.2% (68) had GS and 19.4% (28) had SSgenotypes. 51.9% (82) of people with MS had GG, 35.4% (56) had GS and 12.7% (20) had SSgenotypes. The prevalence of G allele in people with MS was 69.6%, which is much higher than healthygroup. Comparing PGC-1α Gly482Ser GG, GS and SS genotypes with systolic arterial blood pressurerevealed statistically significant difference which was higher among subjects with GG genotype. Theblood pressure of people with MS and carrying GG genotype of PGC-1α Gly482Ser polymorphismwas significantly increased 2.35 times than people without MS.Conclusions:1. 69.6 percentages of the people with MS had G allele and 2.2 times more than those withoutmetabolic syndrome.2. We determined that the odds ratio for the high blood pressure and it was 2.35 times higher inpeople with GG allele of Gly482Ser carriers than GS and SS alleles carriers (OR = 2.35, p =0.012).

INTRODUCTION: The PGC-1 gene is located on chromosome 4 p.15.1 in humans and encodes a protein containing 798 amino acids. As PGC-1a regulates multiple aspects of energy metabolism, it is not surprising that PGC-1a has been found to be deregulated in several pathological conditions. Might be associated with type 2 diabetes because PGC-1, besides being a coactivator of PPAR a and b, has a critical role in glucose uptake and adaptive thermogenesis. Addition, a common polymorphism of the PGC-1 gene Gly482Ser, which apparently reduces PGC-1 activity, has been linked to increased risk of type 2 diabetes. Association has also been reported between the Gly482Ser substitution and insulin resistance in Japanese subjects. Similar reduction of PGC-1 expression was also observed in the adipose tissue of insulin-resistant and morbidly obese individuals. Previous studies have reported significant association between the Gly482Ser missense mutation of the PGC-1 gene and reduced insulin sensitivity in obese subjects. This association resulted independent from all other known modulators of insulin resistance, and suggests a primary role for the PGC-1 gene on the genetic susceptibility to insulin resistance in obesity.GOAL: To study the presence of PGC-1 gene Gly482Ser polymorphism in people with Metabolic syndrome and study the relation to serum insulin level and insulin resistance.MATERIALS AND METHODS: The study population comprised 302 unrelated Mongolian subjects (158 with metabolic syndrome and 144 controls). MS was determined by IDF (International Diabetes Federation) criteria. The genotypes for polymorphism of candidate gene related to MS were determined using a RFLP analysis of the MspI digest of the PCR product. We determined serum insulin by ELISA, using Eucardio Company’s kit and insulin resistance was defined by the HOMA-IR formula.RESULT: 33.4% (48) of control group had GG, 47.2% (68) had GS and 19.4% (28) had SS genotypes of PGC-1 gene. 51.9% (82) of people with MS had GG, 35.4% (56) had GS and 12.7% (20) had SS genotypes. The prevalence of G allele in people with MS was 69.6%, which is much higher than healthy group. Insulin and HOMA-IR of MS group were higher than compared to healthy group (p<0.05). HOMA-IR was lower in people with GS genotype comparing to GG and SS in people with metabolic syndrome. CONCLUTIONS: 1. People with MS had higher levels of serum insulin (p<0.013) and insulin resistance (p<0.004) in compare to healthy people. 2. 69.6 percentages of the people with MS had G allele, which was 2.2 times more than those without metabolic syndrome.3. People with MS who carry SS genotype had higher levels of serum insulin (p=0.02) and insulin resistance (p=0.008) than people without MS. Insulin resistance was significantly correlated (r=0.302, p<0.001) with hypertension in people with G allele.