Background: Numerous studies have shown that air pollution is a serious public health threat and risk worldwide. Mongolia is the world leader in outdoor and indoor air pollution, and the morbidity and mortality caused by it are increasing every year. People spend most of their lives indoors, and it is necessary to regularly assess and study indoor air pollution. Aim: To study the concentration of PM2.5 particles in the indoor air of households in Ulaanbaatar and Darkhan cities in relation to some symptoms of respiratory diseases. Materials and Methods: The study was conducted using an analytical cohort design from October 2023 to July 2025, and the 4 districts of the central Ulaanbaatar city and Darkhan cities were included in the study. A total of 240 households were included in the study, including 48 households living in ger and house, 24 households living in apartments, and 48 households living in ger and house, and 24 households living in apartments from Ulaanbaatar city. A direct measurement device (PurpleAir) was installed in the households for 3-4 weeks to measure PM2.5 particles in the indoor air for 24 hours. After measuring PM2.5 particles in the indoor air of the household, data were collected through questionnaires from the participants aged 18-60 who participated in the study and underwent health examinations. The results were processed using STATA-19.0 and R programs. Result: 213-239 households were selected for the study, including households living in 17-26 apartments, 42-58 houses, and 38-50 houses. The 24-hour average concentration of PM2.5 particles in the ambient air of households in Ulaanbaatar city was measured relatively higher in winter and summer than in households in Darkhan city. Among the districts of Ulaanbaatar city, the highest concentration of PM2.5 particles was measured in Songinokhairkhan district, and the lowest concentration was measured in Bayanzurkh district. Considering the cities by heating type, households with stoves are more polluted than households with centralized heating. In Darkhan city, the lowest concentration was measured in apartments (22.78-31.53 μg/m³), houses (44.53-68.17 μg/m³), and the highest concentration was measured in traditional felt houses (houses) (63.20-68.25 μg/m³). In Ulaanbaatar, PM2.5 concentrations were relatively high in all types of housing, including apartments (41.61-58.37 μg/m³), houses (79.22-92.50 μg/m³), and traditional felt dwellings (76.69-86.31 μg/m³). In the summer, PM2.5 concentrations in Darkhan were 3.10-10.03 μg/m³ in apartments, 7.67-14.37 μg/m³ in houses, and 7.98-17.90 μg/m³ in traditional felt dwellings (houses). The concentration of PM2.5 particles in the ambient air of the settlement is statistically significantly associated with shortness of breath, fatigue, weakness, muscle pain, nausea, palpitations, sneezing, runny nose, conjunctivitis, pain in the eye socket, tearing of the eyes, headache, fever, nasal congestion, cough, loss of appetite, sore throat, phlegm, wheezing, and chest pain. Conclusion The 24-hour average concentration of PM2.5 particles in indoor air in households in Ulaanbaatar and Darkhan cities is higher than the Mongolian standard during winter and is statistically significantly associated with some symptoms of respiratory diseases.

Background: Ambient and household air pollution remain leading risk factors for global morbidity and mortality. Exposure to fine particulate matter (PM₂.₅) is associated with increased risks of cardiovascular and respiratory diseases, as well as lung cancer, metabolic and neurological disorders, and immune dysfunction. In urban areas of Mongolia, air pollution reaches critical levels during the winter season. Although improved solid fuels have been introduced in recent years, their impact on both outdoor and indoor air quality remains insufficiently characterized. Aim: To compare outdoor and household air pollution levels in Ulaanbaatar and Darkhan cities. Materials and Methods: Outdoor air pollution data for Ulaanbaatar were obtained from fixed monitoring stations of the National Agency for Meteorology and Environmental Monitoring for the period 2014–2026, with seasonal comparisons performed. For indoor air quality assessment, a longitudinal study was conducted among 240 households (apartments, houses, and traditional gers) in Ulaanbaatar and Darkhan from 2023 to 2026. PM₂.₅ concentrations were measured using real-time sensors (PurpleAir sensor), deployed for 14–21 days per season (winter and summer) in each household, recording data at 10-minute intervals over 24-hour periods. Result: Between 2014 and 2026, the 24-hour mean concentrations in Ulaanbaatar were 60.5 µg/m for PM₂.₅, 117.3 µg/m for PM₁₀, 37.3 µg/m for NO₂, 41.8 µg/m for SO₂, and 27.5 µg/m for O₃. While particulate matter levels showed a decreasing trend following the introduction of improved fuels, SO₂ concentrations increased, and overall pollution levels remained higher than those observed in Darkhan. Indoor PM₂.₅ concentrations were higher in Ulaanbaatar compared to Darkhan (60.7±86.1 vs 48.4±96.7 µg/m). Significant differences were observed by housing type (p<0.0001), with higher concentrations in households using solid fuels (houses and gers) and lower levels in apartments. These findings indicate substantial variability in indoor air pollution by city, housing type, and season, with persistently elevated exposure levels. Conclusion Outdoor air pollutant concentrations in Ulaanbaatar, including particulate matter, NO₂, and SO₂, exceed national standards and WHO guideline values by 1–4 times. Indoor PM₂.₅ pollution is higher in Ulaanbaatar than in Darkhan and varies significantly by housing type and season, indicating a high and heterogeneous exposure burden among urban populations.

Background: Substance use remains a critical public health and social concern, closely linked to increased sexual risk behaviors and a heightened vulnerability to sexually transmitted infections (STIs), particularly HIV and syphilis. International and national evidence suggests that individuals who use drugs often experience impaired judgment during intoxication, leading to unprotected intercourse, casual sexual encounters, and multiple sexual partners. In Mongolia, empirical data regarding sexual risk behaviors within this population remain scarce. Therefore, there is a pressing need to determine the prevalence of sexual risk behaviors and identify the specific factors influencing these patterns among drug users. Materials and Methods: This study employed a cross-sectional analytical design involving 181 participants who use drugs. Data were collected via structured questionnaires. Sexual risk behavior was evaluated using two approaches: as a dichotomous categorical variable and as a cumulative sexual risk score. Statistical analysis was performed using frequency distributions, percentages, means, and standard deviations. The associations between variables were tested using the (chi square test, Pearson correlation analysis, and multiple linear regression models. Results: The findings revealed that 12.2% of participants exhibited high-level sexual risk behaviors, with a mean cumulative risk score of 8.13 ±4.40. Engaging in sexual intercourse while under the influence of alcohol, the frequency of intoxicated sex (reported as "often" or "always"), and a history of casual sexual encounters were significantly associated with sexual risk behaviors. Furthermore, gender, cohabitation status, condom use during the first sexual experience, and the frequency of alcohol-involved sexual encounters were statistically significant predictors of the cumulative risk score. A weak positive correlation was observed between the number of sexual partners in the past year and the cumulative sexual risk score, which remained a significant positive predictor in the linear regression model. Conclusion Sexual risk behavior among people who use drugs is more closely associated with behavioral factors—such as alcohol-influenced sexual activity, casual encounters, lack of condom use during sexual debut, and multiple partnership—than with basic socio-demographic characteristics. Consequently, risk reduction interventions should move beyond general awareness. Efforts must prioritize reducing substance- and alcohol-related sexual risks, promoting consistent condom use, and enhancing the accessibility of STI screening and counseling services tailored to this high-risk group.

Background: Drug use is closely associated with sexually transmitted infections, especially syphilis and HIV, through unsafe sexual practices, multiple partners, and high-risk patterns of substance use. Prisoners with a history of drug use represent a particularly vulnerable subgroup. Aim: This study aimed to determine the prevalence of rapid syphilis test positivity and selected associated factors among incarcerated people who use drugs. Materials and Methods: A cross-sectional analytic study was conducted among 105 prisoners. Data were collected using a structured questionnaire and a finger-prick rapid dual test. Descriptive statistics, chi-square tests, and Fisher exact tests were used, with p<0.05 considered statistically significant. Results: The mean age of participants was 29.1±8.4 years; 78.1% were male. A history of STI was reported by 16.2%, STI-related symptoms during the last 12 months by 19.0%, STI testing during the last 12 months by 39.0%, and STI testing while incarcerated by 45.7%. However, 79.0% had received STI-related education or information. Among 81 participants with valid rapid syphilis test results, 27 were positive, giving a prevalence of 33.3%. Syphilis positivity was significantly higher among those using more than one route of drug administration (41.4% vs 13.0%, p=0.018) and among those with a prior STI history (70.0% vs 26.6%, p=0.011). No significant associations were found with sex, age, education, marital status, cohabitation, income, syringe use, recent STI symptoms, casual sex before arrest, or overall sexual risk behavior. Conclusion These findings suggest that targeted syphilis screening, counseling, and linkage to confirmatory testing and treatment should be strengthened among incarcerated people who use drugs, particularly those with multi-route drug use and a previous STI history.

Background: The first confirmed case of COVID-19 in Mongolia was reported on November 11, 2020. In response, the government imposed a nationwide lockdown, which significantly impacted the population’s mental health. Heightened levels of stress, anxiety, loneliness, and depression during the pandemic altered individuals’ psychological stability and behavior. Personality traits—defined as relatively stable patterns of emotion, cognition, and behavior—play a key role in stress responses and emotional regulation under pressure. Emerging evidence suggests that these psychological factors may influence the immune system’s responsiveness, including vaccine-induced antibody production. Aim: To evaluate the association between post-vaccination antibody responses and personality types following two doses of COVID-19 vaccines. Materials and Methods: A total of 738 participants who received two doses of COVID-19 vaccines (AstraZeneca ChAdOx1, n=29; Pfizer-BioNTech, n=119; Sinopharm BBIBP, n=590) and had no prior SARS-CoV-2 infection were enrolled. Serum samples were collected 21–28 days after the second dose, and SARS-CoV-2 RBD (S) IgG antibodies were measured using ELISA (Proteintech Inc., USA). Personality types were assessed using a 56-item temperament questionnaire developed by A. Belov, categorizing individuals into classical temperament types (choleric, phlegmatic, sanguine, melancholic). Logistic regression and ROC analysis were used to examine associations between personality types and antibody response. Results: The presence of an antibody response was significantly higher among individuals with a melancholic temperament, and significantly lower among those with a phlegmatic temperament. Furthermore, antibody titers were higher in participants with melancholic and sanguine temperaments and lower in those with a phlegmatic type. Conclusions 1. During the early period following the second dose of COVID-19 vaccination, the antibody response was higher in individuals with a pure melancholic temperament, while it was lower in those with a phlegmatic temperament. 2. After the second dose of the Sinopharm BBIBP COVID-19 vaccine, antibody titers were higher in individuals with pure melancholic and sanguine temperaments, and lower in those with a phlegmatic temperament.

Background: An estimated 99% of the global population lives in environments where PM2.5 levels exceed the WHO air quality guideline of 15 μg/m³. In 2018, air pollution contributed to approximately 4.2 million deaths worldwide. In Mongolia, air pollution—particularly in urban centers like Ulaanbaatar, worsens significantly during the winter season, posing a serious public health and local concern. Therefore, it is compulsory to compare the outdoor air quality in Ulaanbaatar, the capital and Darkhan city. Aim: To assess and compare the outdoor PM2.5 concentrations in Ulaanbaatar and Darkhan during the winter season. Materials and Methods: This study was conducted in Ulaanbaatar and Darkhan from December 10, 2024, to February 19, 2025. A total of 60 PurpleAir Classic+ sensors (30 per city) were installed to assess PM2.5 concentrations at 2-minute intervals. We analyzed collected data using R software. The 24-hour average PM2.5 concentrations were compared with both the Mongolian National Air Quality Standard (MNS4585:2016) and the WHO air quality guidelines (2021). Results: The 24-hour average PM2.5 concentration in Ulaanbaatar was 112.3±62.2 μg/m³, which was significantly higher than that in Darkhan (79.2±25.6 μg/m³; p<0.05). In Ulaanbaatar, the monthly averages were 119.9±67.7 μg/m³ (Decem ber), 113.5±60.8 μg/m³ (January), and 95.0±51.9 μg/m³ (February) respectively (p<0.05). In contrast, Darkhan city’s monthly average PM2.5 remained relatively close across the months: 79.1±22.2 μg/m³ (December), 78.7±28.6 μg/m³ (January), and 84.6±30.0 μg/m³ (February), with no statistical significance (p>0.05). During the study period, the 24-hour average PM2.5 concentrations exceeded the MNS4585:2016 (50 μg/m³) in 69.8% of days in Ulaanbaatar and 64.6% in Darkhan. WHO’s guideline of 15 μg/m³ was exceeded 93.4% of the time in both cities. Conclusion Darkhan city has lower PM2.5 concentrations compared to Ulaanbaatar, both cities significantly exceeded MNS4585:2016 standard and the WHO air quality guidelines (2021) during the winter months.

Background: According to the World Health Organization (WHO), 99 percent of the world’s population is exposed to air that exceeds WHO recommendations, with low- and middle-income countries being the most affected. The main causes of indoor air pollution include human activities such as fuel burning, cooking, cleaning, and smoking; housing characteristics such as walls, floors, ceilings, and furniture; ventilation; and outdoor air pollution. Aim : To assess PM1 and PM10 concentrations in 120 selected households in Ulaanbaatar. Materials and Methods : Indoor PM1 and PM10 concentrations were measured using Purple Air real-time sensors in randomly selected Ulaanbaatar households between October 2023 and January 2024. Supplementary data on factors affecting the PM2.5 concentration were collected via questionnaires. Each measurement was taken in 10-minute intervals, yielding 51,309 data for analysis. Results : PM1 concentrations were measured at 55.5±53.2 μg/m³ in gers, 54.9 ± 46.7 μg/m³ in houses, and 31.6±40.1 μg//m³ in apartments (p<0.001) and measuring PM10 concentrations were 110.6±108.6 μg/m³ in gers, 110.6±96.7 μg/m³ in houses, and 62.2±83.0 μg/m³ in apartments (p<0.001) When considering the concentration of PM1, PM10 by heating type, PM1 was 55.3±50.1 μg/m³ and PM10 was 110.6±103.0 μg/m³ in households with stoves and furnaces, and PM1 was 31.6±40.1 μg/m³ and PM10 was 62.2±83.0 μg/m³ in households connected to the central heating system (p<0.001). Regarding the months of measurement, the highest concentration was observed in December 2023, at 77.1±94.1 μg/m³. The highest concentrations for both PM₁ and PM₁₀ were recorded in January 2024, at PM₁: 64.8±55.1 μg/m³, PM₁₀: 131.4±116.0 μg/m³. Conclusion 1. Indoor PM10 concentrations in residential environments in Ulaanbaatar city were within the MNS4585:2016 Air Quality Standard, however, it was exceeded the WHO air quality guidelines, indicating an excessive risk of increasing morbidity and mortality among the population. 2. Indoor PM1 and PM10 concentrations in residential environments in Ulaanbaatar varies depending on location, type of housing, type of heating, and month of measurement.

Background: The development of a country is often measured by the state of human development, especially maternal and child health indicators. In Mongolia, public health policies targeting the prevention of non-communicable diseases related to lifestyle and physical development among adolescents are critically needed. However, there is a lack of regional studies on adolescent health, particularly in rural areas. Aim: To study certain physical development indicators among adolescents in Bulgan province. Materials and Methods: This analytical study was conducted in 2022 involving 781 twelve-year-old children. Data were collected from parents and processed using Stata 17.0. Percentages were calculated for qualitative data, and Chi-square and Fisher’s exact tests were used for statistical analysis. Where statistically significant, multinomial logistic regression analysis was applied to identify risk factors affecting physical development. Results: 52.88% of the participants were boys,92.45% lived in traditional or private hous12.04% of the children showed growth retardation. 49.68% were overweight.70.94% were classified as overweight or obese based on their Body Mass Index (BMI).Weak muscle strength (1.66%), flexibility (2.05%), endurance (1.66%), and agility (1.92%) were observed. Boys were more likely to experience height retardation but had stronger muscle strength.Girls showed a higher prevalence of being overweight.Children living in the provincial center had higher height and BMI, while those in soum centers demonstrated statistically significant strength in muscle power, flexibility, and endurance. Conclusion 1. Among the study participants, 70.94% of children were overweight or obese. 2. 1.66% of the study participants had weak muscle strength, 2.05% had weak flexibility, 1.66% had weak endurance, and 1.92% had weak speed and agility. 3. The use of mobile phones, parental involvement, inactivity, lack of sports, and lack of horse riding have negative effects on physical development.

Background: The first case of COVID-19 was reported in our country on November 11, 2020. As of 2023, a total of 869,385 cases and 2,128 deaths have been recorded nationwide. The World Health Organization (WHO) has recommended that countries use 15 vaccines from 11 manufacturers listed for emergency use. The WHO has advised low-income member states to prioritize vaccinating healthcare workers and other high-risk populations vulnerable to severe illness and death from COVID-19. The main goal of the coronavirus vaccination program is to prevent infection, complications, and death among priority target groups, such as healthcare workers and other populations at high risk of severe illness. The effectiveness of the vaccination is measured by its ability to reduce the risk of illness, hospitalization, and death from COVID-19-related complications among vaccinated individuals. While extensive research is being conducted globally to develop, evaluate, and assess the effectiveness and outcomes of COVID-19 vaccines, there has been limited research focused on these outcomes within our country. This gap highlights the need for and serves as the basis of the present study. Аim: To assess the risk of infection, hospitalization, and associated risk factors among healthcare workers vaccinated against COVID-19, and to examine the factors that influence these risks. Materials and Methods: A This follow-up study was conducted over an 80-week period—at weeks 12, 24, and 48—from February 23, 2021, to December 31, 2022. The study involved healthcare workers from Ulaanbaatar city and the aimags of Bayankhongor, Orkhon, Bulgan, Dundgovi, Darkhan-Uul, and Dornod. The study was conducted over a period of 1.5 years (80 weeks) following the administration of the first two doses of the COVID-19 vaccine. Data were collected from participants at three time points: before vaccination, after the second dose, and after each booster dose. A structured questionnaire comprising 7 sections and 49 questions was used for data collection, and the results were analyzed using SPSS version 26.0. Results: Of the total respondents, 574 (60%) worked in direct contact with infected individuals in the 'red zone,' while 370 (40%) worked in the 'yellow zone.' Additionally, 250 participants (27.1%) were healthcare workers from Ulaanbaatar city, and 674 (72.9%) were from rural areas. In our observational study, the risk of new infections among healthcare workers increased over time, rising from 38.4% at week 24 to 59.6% by week 80. Hospitalizations also increased during the follow-up period: 24 cases (2.6%) were recorded at week 12, 160 (17.3%) at week 24, 202 (21.9%) at week 48, and 204 (22.1%) by week 80. Among frontline workers in rural areas, those in Bayankhongor and Orkhon aimags exhibited a lower risk of infection compared to their counterparts in other aimags. Conclusion In our follow up study, an increase in the duration since primary immunization was associated with a higher risk of new infection among workers, rising from 38.4% at 24 weeks to 59.6% at 80 weeks post-vaccination. Administration of additional (booster) immunizations was associated with a reduced risk of subsequent infection. COVID-19 vaccination was associated with a reduced risk of complications necessitating hospitalization. Employment in rural settings and designated red zones was identified as a risk factor for incident infections, hospitalizations, and reinfections.

Background: A 2018 study on the global burden of disease, accidents, and risk factors reported that 1.6 million peo ple died in 2017 due to household air pollution. Poor indoor air quality has been highlighted as a contributing factor to respiratory diseases, cardiovascular conditions, and exacerbation of asthma and allergies. A 2019 study estimated that long-term exposure to fine particulate matter (PM2.5) with a diameter of 2.5 micrometers or less reduces average life expectancy by 1.8 years, with more severe effects in highly polluted regions. Additionally, a study by Miller et al. (2007) found that prolonged exposure to PM2.5 increases the risk of cardiovascular diseases, particularly among women. Direct measurement devices are highly effective in determining indoor PM2.5 concentrations, identifying sources of pollution, tracking pollutant dispersion, and monitoring temporal variations. Studies suggest that direct measurement is an accurate, cost-effective method that provides detailed data suitable for local conditions. Aim: To investigate the indoor air quality of houses and apartments in Darkhan city during the winter season using the Purple Air monitoring device. Materials and Methods: A cross-sectional study was conducted with a targeted sample of 128 households in Darkhan city. The study examined factors such as stove type, type of coal used, annual and daily coal consumption, frequency of heating, and chimney sealing conditions. To collect data, the Purple Air monitoring device was installed in each house hold for a month, after which it was retrieved. During retrieval, participants completed a questionnaire. The questionnaire consisted of 55 questions across 7 pages at the time of device installation and 25 questions across 3 pages at the time of device retrieval. The collected data was analyzed using SPSS 25.0. Results: A total of 128 households in Darkhan city participated in the study. The average duration of residence in the current home was 9.5 years, with no statistically significant variation. The distribution of housing types was as follows: traditional Mongolian gers (40.6%), houses (39.1%), and apartments (20.3%). The 24-hour average PM2.5 concentration was highest in gers (70.9 μg/m³), followed by houses (46.8 μg/m³) and apartments (22.8 μg/m³), with a statistically significant difference (p=0.0001). PM2.5 levels were most variable in gers, followed by houses and then apartments. House holds using central heating (apartments) had an average 24-hour PM2.5 concentration of 22.8 μg/m³, whereas households using stoves (gers and houses) had a significantly higher concentration of 59.4 μg/m³ (p=0.0001). However, there was no statistically significant difference between traditional and improved stoves. Among study participants, 21.4% reported that someone in their household smoked indoors. Additionally, 86.5% regularly burned incense, candles, or herbs, while 99.2% did not use an air purifier. Conclusion The indoor particulate matter concentration in houses and gers in Darkhan was 59.4μг/m3. Variations in stove types, poor chimney sealing limited space, and frequent gaps and cracks contribute to increased spread of indoor air pollutants.