Background: Metabolic dysfunction–associated steatotic liver disease (MASLD) is a major cause of chronic liver disease and is increasingly linked to cardiovascular disease (CVD), the leading cause of mortality globally. Aim: To evaluate individuals participating in early screening using the Hepatic Steatosis Index (HSI) and examine its association with CVD risk levels. Materials and Methods: This population-based retrospective cross-sectional study included 47,542 adults aged 40–70 years who participated in a national screening program between 2023 and 2025. Hepatic steatosis was assessed using the Hepatic Steatosis Index (HSI) and categorized as <30 (no steatosis), 30–36 (indeterminate), and >36 (steatosis). Ten-year CVD risk was estimated using laboratory-based WHO cardiovascular disease risk charts for Central Asia. Associations were evaluated using logistic regression and expressed as odds ratios (ORs) with 95% confidence intervals (CIs). Result: The mean age of participants was 53.18±8.17 years, and 67.1% (31,886) were women. The prevalence of HSI <30, 30–36, and >36 was 8.9% (4,219), 32.1% (15,271), and 59.0% (28,052), respectively. The distribution of low-, moderate-, and high-risk CVD groups was 48.6% (23,115), 41.3% (19,637), and 10.1% (4,790), respectively. The proportion of individuals with high CVD risk was 5.5% in the HSI <30 group and 10.1% in the HSI >36 group. Compared with the reference group, the odds of high CVD risk were increased in the HSI 30–36 group (OR=1.333; 95% CI: 1.152–1.542) and the HSI >36 group (OR=2.401; 95% CI: 2.094–2.753). These associations remained statistically significant after adjustment for age, sex, systolic blood pressure, waist circumference, physical inactivity, and smoking. Conclusion The prevalence of hepatic steatosis in the study population was 59.0%. Individuals with hepatic steatosis had a 1.2-fold higher risk of cardiovascular disease compared with those without steatosis.

Background: In Mongolia, the prevalence of non-communicable diseases and their intermediate risk factors has continuously increased in recent years. From results of early detection and prevalence studies of non-communicable diseases in Mongolia, studies linking intermediate risk factors to insulin resistance are scarce. Aim: To identify the prevalence of insulin resistance among the population and study its connection with intermediate risk factors of non-communicable diseases. Materials and Methods: This study was approved by the MNUMS Ethics Committee on February 23, 2024 (2024/3- 02), and was conducted based on the data of participants who took part in the “Population-based Preventive and Early Detection Screening of Infectious and Non-Infectious Diseases” organized by the Mongolian government from 2022 to 2023. Insulin resistance was identified using the triglyceride-glucose index (TyG), calculated by the formula Ln [fasting triglycerides (mg/dL) × fasting glucose (mg/dL) / 2]. “Ln” refers to the natural logarithm, based on Euler’s number, approximately 2.71828. TyG levels were classified into low risk (<8.5), medium risk (8.5-9.0), and high risk (>9.0). Defined intermediate risk factors for non-communicable diseases according to stages of hypertension and diabetes. Results: The mean age of participants was 44.3±15.2 years, with 39.2% (n=49,270) male and 41.4% (n=49,749) residing in urban areas. Among the participants, 59.1% had overweight or obesity, 23.6% had diabetes or impaired fasting glucose, 61.4% had hypertension, and 19.7% had elevated triglycerides. Analyzing by levels of insulin resistance risk, 62.8% of the population had low risk, 22.5% medium risk, and 14.7% high risk. Comparing systolic blood pressure across levels of insulin resistance risk showed that even without central obesity or diabetes, as the level of insulin resistance increased, the level of systolic blood pressure also increased (low risk group: 117.0±11.7, medium risk group: 121.1±10.9, high risk group: 123.5±16.2 mmHg). Regression analysis of the risk of hypertension by insulin resistance risk level showed that the risk increased with higher levels of insulin resistance (medium risk group OR=1.35, p<0.0001; high risk group OR=1.63, p<0.0001). Conclusion 22.5% of the population is at medium risk and 14.7% at high risk of insulin resistance. The increase in hypertension risk with higher insulin resistance levels is statistically significant, independent of central obesity and diabetes stages.

Background: Obesity and metabolic disorders are significant contributors to hypertension and cardiovascular disease (CVD). While body mass index (BMI) and waist circumference are known to be associated with systolic blood pressure (SBP), the interplay between adiposity, glucose levels, triglycerides, and SBP is not fully understood. This study aims to investigate the relationships between BMI, waist circumference, glucose, triglycerides, and SBP in a large population-based cohort. Methods: A cross-sectional analysis was conducted on [insert total number] participants with complete data on BMI, waist circumference, blood pressure, glucose, and triglycerides. Descriptive statistics, ANOVA, Pearson correlations, mediation analysis, and multiple regression were used to explore the associations between variables. The moderation effect of glucose on the BMI-SBP relationship was examined using an interaction term in the regression model. Results: The mean age of the study population was 44.3 ± 15.2 years. The mean BMI was 26.7 ± 4.9 kg/m², and 22.7% of participants were classified as obese. Central obesity, measured by waist circumference, was prevalent in 55.9% of the population. BMI, waist circumference, glucose, and triglycerides were significantly associated with SBP (p < 0.0001). Mediation analysis showed that waist circumference partially mediated the effect of BMI on SBP. The interaction term for BMI and glucose was significant (β = 0.32, p < 0.05), indicating that glucose levels moderated the relationship between BMI and SBP, with higher glucose levels amplifying the hypertensive effect of BMI. Conclusion This study highlights the complex interplay between BMI, waist circumference, glucose, triglycerides, and SBP. Waist circumference partially mediates the effect of BMI on SBP, and glucose levels moderate this relationship, amplifying the impact of obesity on blood pressure.

Introduction: During this pandemic, overcrowding in classroom caused by a lack of educational facilities and poor indoor air quality are the main causes of respiratory diseases among children and adolescents. Therefore, it is essential to measure and assess the indoor air quality where children spend extended periods of time such as school. Materials and methods: This study covered four schools with old buildings and four schools with new buildings in Bayanzurkh, Sukhbaatar, Khan-Uul, Chingeltei district of Ulaanbaatar. We collected PM10 and PM2.5, carbon dioxide, air temperature, humidity, and microbiological count from chosen classrooms and compared to the MNS4585:2016 standard. SPSS-24 was used to do statistical analysis on the information gathered during the evaluation. Results and Discussion: The 24-hour average PM2.5 concentration was 64.3 (95% CI: 64.1-64.5) mcg/m3, which was 4.3 times higher than the WHO guideline value and 1.3 times higher than the MNS4585:2016 standard. The 24-hour average PM10 concentration was 85.3 (95 % CI: 85.1-85.6) mcg/m3, which is 1.9 times higher than WHO guideline value. In older school buildings, the 24-hour average PM2.5 concentration was 5.6 times higher than the WHO guideline value and 1.7 times higher than the MNS4585:2016; the average PM10 concentration was 2.8 times higher than the WHO guideline value and 1.3 times higher than the MNS4585:2016. The air temperature and carbon dioxide concentration in classroom was met the MNS4585: 2016. The average relative humidity of all schools is 24.2±6.5%, which is 14-16% lower than the MNS4585: 2016. Conclusion The indoor air quality of the school in new and old buildings was similar poor, therefore a variety of steps are needed to improve it.