Background: Lumbar disc herniation (LDH) is one of the leading causes of lower back pain and disability, significantly impacting public health and socio-economic well-being. International studies have shown that paraspinal muscle size and structure correlate with age, body mass index (BMI), and spinal disorders. However, comprehensive MRI-based research investigating the correlation between LDH and specific morphometric parameters in Mongolia remains limited. Aim: To evaluate lumbar disc herniation using magnetic resonance imaging (MRI) and compare paraspinal muscle volume and subcutaneous fat thickness. Materials and Methods: An observational retrospective study design was conducted between June 2024 and June 2025 at Asraltmed and Orgil hospitals, enrolling 300 cases selected from 2,840 lumbar spine MRI scans based on inclusion and exclusion criteria. Demographic data (age, sex, BMI) were collected alongside MRI metrics. LDH type, size, location, and severity were evaluated using axial, sagittal, and coronal views across T1WI, T2WI, and STIR/T2FS sequences. Paraspinal muscle cross-sectional area (Multifidus, Erector spinae, Psoas) was measured on axial T1WI and T2WI sequences, while subcutaneous fat thickness was measured on sagittal T2WI sequences. LDH parameters were evaluated in relation to paraspinal muscle measurements, subcutaneous fat thickness, and BMI. Disc degeneration was classified using the Pfirrmann grading system, and statistical analysis was performed using IBM SPSS 25.0. Result: The mean age of participants was 45.6±12.3 years. Higher BMI (r=0.41) and increased subcutaneous fat thickness (r=0.46) showed a significant positive correlation with LDH severity (p<0.001). Conversely, paraspinal muscle cross-sectional area (CSA) was negatively correlated with LDH severity (r=0.49, p<0.001). Multivariate regression analysis revealed that age, sex, BMI, subcutaneous fat thickness, and paraspinal muscle CSA were statistically significantly associated with LDH (p<0.01). Subgroup analysis by sex demonstrated similar correlations between paraspinal muscle size, subcutaneous fat thickness, and LDH severity in both male and female groups. Conclusion Lumbar disc herniation severity is associated with increased BMI and subcutaneous fat thickness, as well as decreased paraspinal muscle mass. Normalized muscle parameters reduce sex-related discrepancies and establish an effective MRI-based risk assessment approach.

Purpose: Kidney function assessment method is improving gradually. New biomarkers are studied and started using in clinical practice, such as beta 2 microglobulin. Beta 2 microglobulin is improving diagnostic and prognosis in CKD patients. We aimed to assess convenience usage of B2MG alone and B2MG based eGFR in Mongolian patients. Materials and method: We included 116 patients diagnosed with CKD and 55 donors whom with normal kidney function. We collected participant's blood sample by venipuncture in plain vacutainer. Creatinine, urea, cystatin C, B2MG were tested by Roche Cobas C311 equipment in serum. eGFR was calculated by online calculation from NKF. B2MG based eGFR was calculated by eGFR=133*B2M^-0.852 Result: Assessment of kidney biomarkers and eGFR was significantly correlated in both groups. Measured serum creatinine was 3.37 mg/dl in CKD patients and 0.87 mg/dl in donors. Serum urea was 97.6 mg/dl, 31.1 mg/dl, cystatin C 3.05 mg/L, 1.49mg/L and beta 2 microglobulin 10.65 mg/L, 2.43 mg/L respectively. Estimated GFR was 21.5-28.4 ml/min/1.73m2 in CKD patients and 47.7-103.9 ml/min/1.73m2 in donors. Assessing kidney function by biomarkers (r=0.720-0.918, p<0.05), and eGFR (r=0.495-0.996, p<0.05) were significantly correlated in both groups. Conclusion B2MG can be used in clinical practice in Mongolia. B2MG is optional with creatinine, urea, cystatin C for assessing and improving kidney function.

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 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.