1.Respiratory Symptoms Associated with Household Indoor PM2.5 Exposure
Ulziimaa D ; ; Ulziikhutag B ; Ser-Od Kh ; Shatar Sh ; Myagmarchuluun S ; Enkhjargal G ; Gantuya D ; Munkh-Erdene L ; Khurelbaatar N ; Damdindorj B ; Davaalkham D
Mongolian Journal of Health Sciences 2026;91(1):116-123
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.
2.Assessment of impairments in body functions and body structures among individuals with work capacity loss due to occupational diseases
Sansartsetseg Ts ; Achiimaa S ; Shinebileg B ; Myagmarchuluun S ; Gantugs Yu
Mongolian Journal of Health Sciences 2026;96(6):72-79
Background:
The International Classification of Functioning, Disability and Health (ICF) provides a comprehensive framework for assessing body functions, body structures, activity limitations, participation restrictions, and environmental factors. The combined use of the International Classification of Diseases (ICD) and the ICF can contribute to more comprehensive and person-centered approaches to rehabilitation planning, disability assessment, and compensation systems for work capacity loss.
Aim:
To assess individuals with occupational diseases and work capacity loss using the ICF framework and to evaluate impairments in body functions and impairments of body structures.
Materials and Methods:
A cross-sectional analytical study was conducted among individuals with work capacity loss due to occupational diseases. Data were collected using two sections of the ICF Checklist Version 2.1a, Clinician Form, focusing on body functions (b) and body structures (s). Statistical analyses were performed using IBM SPSS-26.0.
Result:
A total of 180 participants were included in the study, of whom 80.6% (n=145) were male and 19.4% (n=35) were female, with a mean age of 60.5±10.7 years. The mean duration of employment under hazardous occupational conditions was 19.5±5.2 years. Respiratory system disorders were 57.2% (n=103), and nervous system disorders were 20.0% (n=36). The internal consistency of the ICF assessment was high for the body functions impairment domain (Cronbach’s α=0.904) and acceptable for the body structures impairment domain (α=0.788). Sensory functions and pain impairments (b2) differed significantly across all occupational disease groups (p<0.001), while impairments of the structures of the nervous system (s1) also showed a statistically significant difference (p=0.015). Multivariable logistic regression analysis showed that an increase in the percentage of work capacity loss was significantly associated with body function impairment (OR=1.065; 95% CI: 1.003–1.131; p=0.030), while increasing age was significantly associated with impairments of body structures (OR=1.112; 95% CI: 1.013–1.234; p=0.042).
Conclusion
1. The body functions and body structures domains of the ICF Checklist Version 2.1a, Clinician Form, demonstrated adequate internal consistency, indicating that the ICF may be applicable for assessing individuals with occupational diseases.
2. Sensory function and pain impairments were common among individuals with occupational diseases. Furthermore, a higher percentage of work capacity loss was associated with greater body function impairment, while increasing age was associated with a higher risk of body structure impairment.
3.Comparative study of outdoor and indoor air pollution in Ulaanbaatar and Darkhan cities
Davaalkham D ; ; Ulziikhutag B ; Batzorig B ; ; Ser-Od Kh ; ; Nyamsuren B ; ; Yerkebulan M ; ; Enkhjargal G ; ; Shatar Sh ; ; Myagmarchuluun S ; ; Gantuya D ; ; Ulziimaa D ; ; Buyantushig B ; ; Jargalsaikhan G ; ; Anujin M ; Maralmaa E ; Khurelbaatar N ; ; Damdindorj B ;
Mongolian Journal of Health Sciences 2026;93(3):107-113
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.
4.Environmental factors affecting access to rehabilitation services in occupational diseases
Sansartsetseg Ts ; Achiimaa S ; Shinebileg B ; Ulzii-Orshikh R ; Gantugs Yu ; Myagmarchuluun S
Mongolian Journal of Health Sciences 2026;95(5):116-122
Background:
The World Health Organization (WHO) recommends using both the ICD and ICF frameworks in combination when assessing work disability. The ICF evaluates patients in terms of body functions, disability, and health-related functioning. Integrating ICD and ICF classifications is essential for accurate disability assessment, effective rehabilitation planning, and compensation processes.
Aim:
To investigate environmental factors influencing rehabilitation services among patients with work-related diseases who have experienced loss of work capacity, using the International Classification of Functioning, Disability and Health (ICF) framework.
Materials and Methods:
This analytical cross-sectional study was conducted at the Department of Occupational Medicine of the Occupational Health Center. Data were collected from 150 patients with occupational diseases resulting in work disability. The ICF assessment tool developed by WHO was utilized. A total of 150 indicators across four main domains were assessed: 27 items on general information and health-related issues; 31 items on body functions (Group 1a); 16 items on body structures (Group 1b); 48 items on activities and participation (Group 2); and 32 items on environmental factors (Group 3). Statistical analysis was performed using SPSS version 26.0 Descriptive statistics, including frequencies, percentages, means, and standard deviations, were calculated.
Results:
A total of 150 patients with work disability due to occupational diseases were included in the study. The mean age was 60.5±10.9 years, with males comprising 80% (n=120) and females 20% (n=30). The reliability of the ICF questionnaire was acceptable across all domains (Cronbach’s alpha > 0.7). Respiratory occupational diseases accounted for the largest proportion 58.7% ( n=88), followed by neurological conditions 19.3% (n=29) and surgical conditions 8.7% (n=13). Environmental factors affecting rehabilitation, support from health professionals (e360) showed moderate facilitation (2.0±1.0). In contrast, climate (e225) (-2.7±0.6), education services (e585) (-3.4±0.8), and employment services (e590) (-3.5±0.7) were identified as substantial barriers. Environmental factors were significantly associated with age and duration since diagnosis of occupational disease (p<0.05).
Conclusions
1. The integrated application of the International Classification of Diseases (ICD) and the International Classification of Functioning, Disability and Health (ICF) allow for a more comprehensive evaluation of work-related disability. This approach moves beyond a purely diagnosis-based assessment to incorporate functional status and environmental determinants. 2. The findings highlight its significant value in optimizing rehabilitation service planning, identifying key barriers, and ultimately improving both the accessibility and effectiveness of rehabilitation services.
5.Study results of PM1 and PM10 particulate matter concentrations in Ulaanbaatar city’s household environments using low-cost sensors.
Ulziimaa D ; Jargalsaikhan G ; Ser-Od Kh ; Enkhjargal G ; Myagmarchuluun S ; Gantuya D ; Munkh-Erdene L ; Damdindorj B ; Khurelbaatar N ; Davaalkham D
Mongolian Journal of Health Sciences 2025;88(4):88-91
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.
6.Indoor Particulate Matter Concentration in Households of Darkhan City
Nyamdorj J ; Bolor M ; Maralmaa E ; Yerkyebulan M ; Ser-Od Kh ; Myagmarchuluun S ; Shatar Sh ; Gantuya D ; Gregory C. Gray ; Junfeng Zhang ; Ulziimaa D ; Damdindorj B ; Khurelbaatar N ; Davaalkham D
Mongolian Journal of Health Sciences 2025;85(1):25-29
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.
7.Comparative analysis of household indoor PM2.5 concentrations and prevalence of hypertension between cities
Anujin M ; Myagmarchuluun S ; Erkebulan M ; Ser-Od Kh ; Shatar Sh ; Gantuyаa D ; Enkhjargal G ; Munkh-Erdene L ; Gregory C. Gray ; Jungfeng Zhang ; Damdindorj B ; Ulziimaa D ; Davaalkham D
Mongolian Journal of Health Sciences 2025;89(5):5-10
Background:
According to the World Health Organization (WHO), 6.7 million people die annually due to air pollution
caused by solid fuel use, with the majority of deaths resulting from respiratory diseases and cardiovascular conditions. In
Mongolia, air pollution ranks as the fourth leading risk factor contributing to mortality, following hypertension, diabetes,
and other major health risks. Although there have been numerous studies on outdoor air pollution in Mongolia, research
linking indoor air pollution at the household level with the health status of residents remains limited.
Aim:
To compare indoor PM2.5 concentrations in households of Ulaanbaatar and Darkhan and examine their association
with hypertension during the winter season.
Materials and Methods:
The study was conducted during November and December 2023, and January 2024, involving
240 households in Ulaanbaatar and Darkhan. Indoor PM2.5 concentrations were measured using Purple Air real-time
sensors continuously for 24 hours over approximately one month. After measuring indoor air pollution, individuals aged
18–60 years living in the selected households were recruited based on specific inclusion criteria. Blood pressure was
measured three times and the average value was recorded. Information on respiratory illnesses was collected through
structured questionnaires. Statistical analysis was performed using STATA version 19.0.
Results:
A total of 241 households participated in the study, with 116 from Ulaanbaatar and 125 from Darkhan. Of the
participants, 46.5% were male and 53.5% were female. In terms of housing type, 96 households (39.8%) lived in gers,
97 (40.2%) lived in stove-heated houses, and 48 (19.9%) lived in apartments. Among all participants, 66.0% (n=159) had
hypertension and 34.0% (n=79) had normal blood pressure. Among participants aged over 40, 69.9–88.5% had hypertension, which is statistically significantly higher compared to younger individuals (p=0.0001). By body mass index, 75.3%
(n=72) of overweight individuals and 78.4% (n=58) of obese participants had hypertension, showing a statistically significant difference compared to participants with normal weight (p=0.0001). The 24-hour average concentration of indoor
PM2.5 was measured using the Purple Air device, and the levels in gers and stove-heated houses exceeded the limit set
by the MNS 4585:2025 standard (37.5 µg/m³)
Conclusion
This study identified a relationship between environmental factors, such as air pollution and housing type,
and the prevalence of hypertension. The indoor PM2.5 concentration in gers and stove-heated houses was above the standard limit, indicating a negative impact on the health of those residents. Furthermore, the high prevalence of hypertension
among participants over the age of 40 and those who are overweight suggests a possible link to lifestyle and environmental conditions.
8.Comparative Analysis of Outdoor Particulate Matter Concentrations in Ulaanbaatar Using Direct Measurements and Fixed Monitoring Station Data
Ulziikhutag B ; Enkhjargal G ; Buyantushig B ; Nyamsuren B ; Shatar Sh ; Gantuya D ; Myagmarchuluun S ; Gregory Gray ; Junfeng Zhang ; Ulziimaa D ; Damdindorj B ; Davaalkham D
Mongolian Journal of Health Sciences 2025;89(5):112-117
Backgroun:
Air pollution is a major global public health concern that poses serious risks to human health regardless of
a country’s level of economic or technological development. According to the World Health Organization (WHO, 2021),
nine out of ten people worldwide breathe polluted air, and air pollution is responsible for the deaths of approximately
800 people every hour and 13 people every minute. Prolonged exposure to polluted air has been linked to a wide range
of chronic illnesses, including chronic obstructive pulmonary disease (COPD), lung and bronchial cancers, asthma, and
stroke. In Mongolia, air pollution reaches its highest levels during the winter months, particularly in Ulaanbaatar, where
the majority of the country’s population resides. A study conducted by Enkhjargal G. (2012) reported that the concentrations
of PM10 and PM2.5 in Ulaanbaatar were 7–8 times higher than the WHO recommended guidelines. In response
to such challenges, many countries have increasingly adopted low-cost, direct measurement devices such as PurpleAir
to monitor air quality. These devices are valued for their accessibility, network connectivity, and potential role in smart
city pollution management systems. Despite their global application, there remains a lack of research in Mongolia on the
use of PurpleAir sensors to measure PM2.5 concentrations and compare the results with official monitoring station data.
Addressing this gap is essential for improving local air quality monitoring capacity and informing effective public health
and environmental policies.
Aim:
Determination of PM2.5 particulate matter pollution in the outdoor environment of Ulaanbaatar city using a direct
measurement device (Purple Air).
Materials and Methods:
A cross-sectional study design was employed. Direct measurement devices (Purple Air) were
installed in selected districts of central Ulaanbaatar between December 2024 and February 2025, measuring PM2.5 concentrations
at two-minute intervals over 24-hour periods. All data were statistically processed and analyzed using the
SPSS-26 software package.
Results:
The average concentration of PM2.5 particles in the air of Ulaanbaatar city in winter is 66.68 μg/m3. Compared
to the districts, the highest concentration was determined in SKHD (118.58±90.22 μg/m3), while the lowest concentration
was determined in KHUD (42.37±43.51 μg/m3). Compared to the days of the week, the highest concentrations were measured
on Monday (76.68±71.98 μg/m³), Saturday (77.50±71.63 μg/m³), and Sunday (80.34±74.45 μg/m³). The highest
concentration of PM2.5 particles occurred from 6 pm to 1 am, and the lowest concentration was measured during the day
(between 2 pm and 4 pm). The highest concentration of PM2.5 was measured in December (74.22±73.45 μg/m3), while
the lowest concentration was measured in February (50.25±57.44 μg/m3).
Conclusion
The concentration of PM2.5 in the air of Ulaanbaatar city is 1.7 times higher than the general standard and
technical requirements of Mongolia in winter, and the highest concentration is in the SKHD. The highest concentration of
PM2.5 occurs more often in December and at night than in the winter months.
9.Comparative Analysis of Outdoor Particulate Matter Concentrations in Ulaanbaatar Using Direct Measurements and Fixed Monitoring Station Data
Maralmaa E ; ; Yerkyebulan M ; Ser-Od Kh ; Shatar Sh ; Gantuya D ; Munkh-Erdene L ; Enkhjargal G ; Myagmarchuluun S ; Gregory Gray ; Junfeng Zhang ; Ulziimaa D ; Damdindorj B ; Davaalkham D ; ; Darambazar G
Mongolian Journal of Health Sciences 2025;89(5):105-111
Background:
Particulate matter with an aerodynamic diameter of 2.5 micrometers or smaller (PM2.5) penetrates
deep into the alveoli through the respiratory tract and is characterized by its ability to induce oxidative stress, systemic
inflammation, and vascular inflammation. Mongolia ranks among the countries with the highest levels of air pollution. In
Ulaanbaatar, where more than half of the country’s population resides, wintertime PM2.5 concentrations often exceed 200
μg/m³, which is about eight times higher than the World Health Organization (WHO) guideline value. A study involving
1,200 adults in Ulaanbaatar showed that quality of life deteriorated sharply during periods of high air pollution, with
effects more pronounced among individuals who already had impaired respiratory function.
Aim:
To examine the relationship between indoor household PM2.5 concentrations and lung function indicators among
adults in Ulaanbaatar and Darkhan.
Materials and Methods:
This analytical cross-sectional study recruited adult participants from Ulaanbaatar and Darkhan
through targeted sampling. Household air quality was measured using PurpleAir sensors, which were installed in
participants’ homes for one month. After exposure measurement, lung function was assessed via spirometry. Statistical
analyses were conducted using SPSS version 25.0.
Results:
A total of 236 participants were included: 114 (48.3%) from Ulaanbaatar and 122 (51.7%) from Darkhan. The
sample consisted of 111 men (47.0%) and 125 women (53.0%). The mean indoor PM2.5 concentration was 66.24 μg/m³
(SD 44.87 μg/m³), ranging from a minimum of 7.79 μg/m³ to a maximum of 264.55 μg/m³. Stratification by housing type
showed the highest PM2.5 levels in gers (82.34 μg/m³), followed by detached houses (67.34 μg/m³), while apartments
had the lowest concentrations (32.24 μg/m³). Correlation analysis revealed statistically significant negative associations
between PM2.5 levels and measures of expiratory function, including the FEV1/FVC ratio, peak expiratory flow (PEF),
and mid-expiratory flow (FEF25–75). Reduced forced vital capacity (FVC) was observed in 9.4% of participants, reduced
forced expiratory volume in one second (FEV1) in 15.3%, and a decreased FEV1/FVC ratio in 3.8%.
Conclusion
Indoor household PM2.5 concentrations were highest in gers, and expiratory flow-related lung function
parameters showed significant negative associations with particulate exposure. This suggests that indoor PM2.5 primarily
affects airflow limitation rather than overall lung volumes in this population.
Result Analysis
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