Pulmonary Function and Respiratory Symptoms in Railway Workers Exposed to Silica Dust in Southeastern Iran

Pulmonary Function and Respiratory Symptoms in Railway Workers Exposed to Silica Dust in Southeastern Iran | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Pulmonary Function and Respiratory Symptoms in Railway Workers Exposed to Silica Dust in Southeastern Iran Fatemeh Paridokht, Raheleh Hashemi Habybabady, Mahdi Mohammadi, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6741939/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background : Railway maintenance workers are exposed to various pollutants, including silica dust, which can impair pulmonary function. This study aimed to quantify the impact of silica dust exposure on pulmonary function and respiratory symptoms among railway maintenance workers in southeastern Iran. Material and Methods : This case-control study was conducted on 63 sand-cleaning workers from the Zahedan-Fahraj railway line. Demographic variables including age, height, weight, body mass index, marital status, work history, smoking, and COVID-19 history USING demographic questionnaire. Blood pressure were measured using a Sphygmomanometer. Pulmonary function was assessed through spirometry, measuring FEV1, FVC, FEV1/FVC, PEF, and FEF25-75 parameters. All participants completed the American Thoracic Society Respiratory Symptom Questionnaire. Data were analyzed using SPSS version 26. Results : The exposed group showed significantly lower pulmonary function indices, including FEV1, FEV1/FVC, and PEF compared to the non-exposed group ( P 0.05). The mean of FEV1/FVC was significantly higher in the control than the exposed group even after adjusting for possible confounders ( P <0.001). Additionally, all respiratory symptoms including cough, phlegm, wheezing, and breathlessness were significantly higher in the exposed group compared the control group ( P < 0.001). Conclusion : Inhaling silica dust decreased pulmonary function and caused adverse respiratory symptoms in railway workers. This indicates a critical need for interventions to protect railway workers' respiratory health. These findings should inform local health policies aimed at reducing occupational exposures to dust in similar settings. pulmonary function respiratory symptoms spirometry Silica dust exposure railway workers Figures Figure 1 Figure 2 Introduction Railway maintenance workers represent of the occupational groups most frequently exposed to dust. Their responsibilities include the construction, maintenance, inspection, and repair of the railway bed, which is supported by ballast. The disturbance, manipulation, distribution, and spreading of ballast along the railway track during track maintenance operations generates silica dust ( 1 ), which is one of the most common minerals on Earth and a primary component of sand, granite, soil, and glass. Workers in various industries, including foundries, stone cutting, construction, tile making, glazing, sandblasting, and sculpting, are exposed to crystalline silica dust ( 2 , 3 ). Chronic exposure to excessive levels of dust can result in respiratory diseases such as pulmonary fibrosis and reduced respiratory capacity ( 4 – 7 ). According to the National Institute for Occupational Safety and Health (NIOSH), occupational exposure to silica poses a significant health risk to railway maintenance workers. In the United States, approximately 35,000 active railway maintenance workers are affected by silica exposure during maintenance activities ( 1 , 8 ). Over 23 million workers in China were exposed to silica in 2009 ( 9 ). Additionally, more than 2.3 million workers came into contact with silica dust in the United States in 2016 ( 10 ), while this number accounted for more than 2 million workers in Europe in 2007 ( 11 ). Occupational silica exposure is a major health concern in developed and developing countries ( 12 ). The International Agency for Research on Cancer (IARC) has classified crystalline silica as a human carcinogen (Group 1A) ( 13 ). Also, studies have shown that exposure to silica dust can lead to lung cancer ( 14 – 16 ). In 2016, lung cancer caused by silica exposure accounted for approximately 13.8% of all occupational cancer deaths, with a total of 47,999 cases ( 17 ). Silica particles can cause serious lung damage. When inhaled, these particles can travel deep into the lungs, reaching the delicate alveoli and bronchioles. This may lead to inflammation and tissue damage, which can in turn result in chronic lung diseases ( 15 ). Consequently, workers who inhale silica dust particles are at risk of developing serious silica-related diseases ( 10 ). Occupational exposure to silica dust can also lead to several serious health issues, including Chronic Obstructive Pulmonary Disease (COPD), silicosis, and tuberculosis ( 18 – 23 ). Additionally, silica exposure is associated with other complications, such as kidney and autoimmune diseases ( 10 , 19 ). Epidemiological studies have also shown a link between silica exposure and sarcoidosis ( 24 ). Moreover, numerous studies have demonstrated reduced pulmonary function in workers exposed to silica dust ( 5 , 25 – 27 ). According to studies, more than 548 kilometers of Iran's railway network passes through sandy regions, with approximately 200 kilometers heavily impacted by sand buildup ( 28 ). The Rudshur-Shoreghez block on the Bam-Zahedan line is one of the most critical railway lines in Iran due to severe sand accumulation, requiring 24-hour maintenance ( 29 ). Furthermore, studies have shown that this region experiences strong and persistent winds, excessive dryness, and abundant sand and soil, leading to air pollution ( 30 ). Based on Environmental Protection Agency standards, the permissible level of PM10 (Particulate Matter 10) in the air is a maximum of 150 micrograms per cubic meter, which should not be exceeded more than once per year. However, in Zahedan, the level of suspended particles often exceeds this limit (averaging 189 micrograms per cubic meter), especially in the summer, with the seasonal winds known as the “120-day wind” in the northern areas and monsoon systems in the southern areas ( 31 ). Previous studies have indicated that the dust in this region contains crystalline silica, constituting 30–40% of the total composition ( 32 ). Given that silica is present in rocks, sand, and soil, any activity that generates respirable-sized particles can lead to silica exposure ( 33 , 34 ). This situation, combined with the region's climatic conditions and the nature of the sand-cleaning workers’ activities in this line—where workers clear tracks of soil and sand amid stormy conditions– results in severe exposure to silica-containing dust and sand. Additionally, studies have shown that the airborne dust in the Sistan and Baluchestan region reduces the lung capacity of workers ( 35 ). Pulmonary function tests, particularly spirometry, play a key role in diagnosing respiratory diseases, especially asthma and COPD. Spirometry measures the volume of air exhaled during a forced complete exhalation following a maximal inhalation. Key parameters reported include Forced Vital Capacity (FVC), Forced Expiratory Volume in One Second (FEV1), and their ratios. These results are graphically represented, which can serve as a diagnostic tool ( 36 , 37 ). Evaluating the pulmonary function of workers exposed to crystalline silica dust, Sohrabi et al. (2022) demonstrated significant reductions in all pulmonary function parameters in the exposed group compared to the non-exposed group, with the FEV 1 parameter showing the greatest decrease ( 38 ). Other studies have also shown significant reductions in spirometry indices and pulmonary function among individuals occupationally exposed to silica dust compared to non-exposed individuals ( 5 , 39 ). No research has yet been conducted on Zahedan-Fahraj railway workers, despite the health risks associated with respiratory exposure to silica, and given the exposure of maintenance workers on this railway line to silica and sand dust as observed by the authors of this study. Therefore, This study aimed to quantify the impact of silica dust exposure on pulmonary function and respiratory symptoms among railway maintenance workers in southeastern Iran. Material and methods Study design and participants The current case-control study was conducted among sand-cleaning workers at the Zahedan-Fahraj railway line in the year 2024. A census sampling approach was employed. As there are 74 sand maintenance workers at this railway, the sample size was set at 74. Also, 74 individuals were selected as controls, comprising those with no past and current dust exposure. The decision to include all available sandblasting workers in the study was driven by the limited number of workers in this specific occupation at the study site, ensuring comprehensive representation of the target population. As a result, the same number of control participants was selected for comparison. The exclusion criteria included any patients with a history of asthma, COPD, tuberculosis, acute and chronic respiratory infections, abdominal or chest surgery, cardiovascular diseases, diabetes, and hypertension. Individuals previously working at other occupations were also excluded. Inclusion criteria required at least one year of work experience. All the participants gave informed consent to participate in the study and publication of data. All participants signed written consent to participate in the study voluntarily. The participants of the present study provided written informed consent for the publication of their personal or clinical information along with any images that may identify them. This study was conducted in accordance with the ethical standards of the Helsinki Declaration (1964, amended most recently in 2013), as developed by the World Medical Association. Our study adhered to the Declaration of Helsinki. The study protocol was reviewed and approved by the Ethics Committee of Zahedan University of Medical Sciences with the approval code: [IR.ZAUMS.REC.1403.294]. Clinical trial number: not applicable. Data collection To gather data, the researcher conducted on-site observations of sandblasting workers after securing managerial approval for the project. Participants were initially presented with informed consent documents. Following their agreement, the researcher administered demographic and respiratory symptoms questionnaire face-to-face. Subsequently, participants’ blood pressure was measured and recorded using a digital device. Finally, the participants received practical training on the FVC spirometry test. Once they learned how to perform the test correctly, they were provided with the device to conduct it themselves. Demographic information Demographic information, including gender, age, weight, height, body mass index, work experience, education level, marital status, smoking history was collected from both groups. Participants who smoked one or more cigarettes per day or who had smoked cigarettes within the past month were considered smokers. Those who had smoked 100 cigarettes in their lifetime but had quit at the time of the study (at least for 30 days) were classified as ex-smokers while those who had never smoked were considered non-smokers ( 40 ). Respiratory symptoms questionnaire The ATS (American Thoracic Society) questionnaire was used to assess individuals’ respiratory status in terms of symptoms such as cough, phlegm, wheezing, and shortness of breath, while also considering their smoking habits, work history, and medical history. Cough, phlegm, and wheezing were categorized into four levels of severity: no symptoms, mild (lasting less than three months), frequent (occurring for three consecutive months), and chronic (lasting more than two years). Shortness of breath was categorized into 5 grades according to the Modified Medical Research Council Dyspnea Scale: Grade 0 (Not troubled with breathlessness, except during strenuous exercise); Grade1 (Troubled by shortness of breath when hurrying or walking up a slight hill); Grade 2 (Walks slower than people of the same age due to breathlessness or has to stop for breath when walking at their own pace on a level surface); Grade 3 (Stops for breath after walking about 100 m or after a few minutes on a level surface); and Grade 4 (Too breathless to leave the house or breathless when dressing or undressing) ( 41 ). The information obtained from this questionnaire was used to determine the prevalence of respiratory symptoms between the two groups. The Persian version of this questionnaire has also been used in other studies ( 26 , 42 , 43 ). The ATS questionnaire (American Thoracic Society) has been published elsewhere ( 35 ). Pulmonary function test Pulmonary Function Tests (PFTs) were performed according to the guidelines of the American Thoracic Society (ATS) ( 44 ). A calibrated spirometer (Spirobank II advanced; MIR Medical International Research, Rome, Italy) was used for the tests, ensuring an accuracy of 3% and a flow of 5%. In order to evaluate pulmonary function, the parameters of forced vital volume (the maximum amount of air that can be exhaled when blowing out as fast as possible)( 45 ), forced expiratory volume in the first second, FEV1/FVC ratios, Peak Expiratory Flow (PEF), the maximal flow that can be exhaled when blowing out as fast as possible( 45 ), and forced expiratory flow at 25–75% of expiratory volume (FEF 25–75%) were evaluated. The spirometer calculated predicted pulmonary function parameters based on age, height, weight, sex, smoking and race. Each participant was advised to refrain from eating and drinking alcohol, smoking, and heavy exercise two hours before the test, and to wear comfortable clothes (tight clothing can restrict chest movements). Additionally, suitable exercises were provided to all participants, their weight and height were measured while standing, and BMI was calculated. The researchers taught each participant individually how to perform the spirometry test. Then, they were asked to rest for about 5 minutes and then prepare themselves for the test by using a nose clip. The test was repeated three times for each participant, and the maximum value from the consecutive tests was recorded. Participants who did not complete the maneuvers successfully after three attempts were excluded from the study. Statistical analysis Mean and standard deviation were used to describe quantitative variables, while frequency and percentage were employed for qualitative variables. The Shapiro-Wilk test was conducted to check the normality assumption of quantitative variables. To compare pulmonary function parameters in two groups, a t-test was utilized for two independent samples; however, if the normal assumption was not met, Mann-Whitney test was applied instead. The Chi-square test was used to compare the frequency of respiratory symptoms in the two groups. A classical regression model was used to control for confounding factors in the comparison of pulmonary parameters in two groups, while a logistic regression model was used to account for the effect of confounding factors in the comparison of the frequency of symptoms in the two groups. Analyses were performed using SPSS version 26. Results A total of 63 railway workers and 66 controls participated in this study. Four participants were excluded from the study due to recent cardiovascular surgery, and seven individuals declined to participate in the study. The mean age of individuals was 41.71 ± 7.31 in the exposed group and 33.52 ± 10.55 years in the unexposed (control) group (P < 0.001). Single individuals comprised 63.6% of the control group, while all railway workers in the other group were single (P < 0.001). In terms of education, 50% of the unexposed group had a university degree, compared to 15.8% in the exposed group (P < 0.001). Regarding weight, most participants were either normal or overweight, and BMI was not significantly different between the two groups (P = 0.756). The mean work experience was 12.79 ± 3.94 in the exposed group and 10.24 ± 8.03 years in the unexposed group (P = 0.025). Cigarette smoking was reported by 14.3% and 27.3% in the exposed and unexposed groups, respectively (P = 0.070). Furthermore, there was no significant difference in tobacco use (P = 0.164) and COVID-19 history (P = 0.508) between the two groups. Exposure to dust occurred for only 9.1% of the control group, but all railway workers were exposed to dust (P < 0.001) (Table 1 ). The mean of systolic and diastolic blood pressure was 12.29 ± 1.30 in the exposed group and 11.54 ± 1.44 in the unexposed group (P = 0.003). However, the mean of diastolic blood pressure was not significantly different between the two groups (P = 0.231). Table 1 Frequency distribution of demographic factors in the exposed and unexposed groups Exposed (n = 63) Unexposed (n = 66) N (%) N (%) Age (year) < 0.001* 35 51 (81.0) 27 (40.9) Marital status < 0.001* Single 0 (0.0) 42 (63.6) Married 63 (100.0) 24 (36.4) BMI 0.756 Underweight 1 (1.6) 3 (4.5) Normal 29 (46.0) 27 (40.9) Overweight 23 (36.5) 26 (39.4) Obese 10 (15.9) 10 (15.2) Work experience (year) < 0.001* 20 1 (1.6) 8 (12.3) Education < 0.001 Primary/Secondary school 36 (57.1) 2 (3.0) High school & Diploma 17 (27.0) 31 (47.0) Associate degree 6 (9.5) 14 (21.2) BSc or higher degree 4 (6.3) 19 (28.8) Cigarette smoking 0.070 No 54 (85.7) 48 (72.7) Yes 9 (14.3) 18 (27.3) Non-cigarette tobacco use 0.164 No 61 (96.8) 60 (90.9) Yes 2 (3.2) 6 (9.1) COVID-19 0.508 No 38 (60.3) 36 (54.5) Yes 25 (39.7) 30 (45.5) *p-value < 0.05 Railway workers were more likely to be affected by COVID-19 symptoms and side effects. Specifically, there was a significant difference between the exposed and unexposed groups in terms of shortness of breath (P = 0.042), wheezing (P = 0.004), and using spray (P = 0.023) (Table 2 ). Table 2 Frequency of COVID-19 side effects and symptoms in the exposed and unexposed groups Side effects of Covid 19 Exposed Unexposed P_value N (%) N (%) Admission to hospital 3 (12.0) 2 (6.7) 0.493* Short breathing 8 (32.0) 3 (10.0) 0.042* Wheezing 11 (44.0) 3 (10.0) 0.004* Asthma 2 (8.0) 0 (0.0) 0.115 Snoring 10 (40.0) 5 (16.7) 0.053 Using spray 4 (16.0) 0 (0.0) 0.023* *p-value < 0.05 The exposed individuals were more likely to report respiratory symptoms. Coughing, sputum, wheezing, and breathlessness were reported in 60.3%, 58.7%, 65.1%, and 55.6% of railway workers compared to 18.2%, 31.8%, 31.8%, and 43.9% in the control group, respectively. There was a significant difference between the two groups in terms of respiratory symptoms. Thus, chronic cough, sputum, wheezing, and breathlessness affected 38.1%, 41.3%, 52.4%, and 22.2% of the exposed individuals, respectively (Table 3 ). Table 3 Frequency distribution of respiratory symptoms in the exposed and unexposed groups Exposed Unexposed < 0.001* Cough None 25 (39.7) 54 (81.8) Mild 8 (12.7) 7 (10.6) Frequent 6 (9.5) 0 (0.0) Chronic 24 (38.1) 5 (7.6) Sputum < 0.001* None 26 (41.3) 45 (68.2) Mild 3 (4.8) 9 (13.6) Frequent 8 (12.7) 5 (7.6) Chronic 26 (41.3) 7 (10.6) Wheezing < 0.001* None 22 (34.9) 45 (68.2) Mild 2 (3.2) 9 (13.6) Frequent 6 (9.5) 2 (3.0) Chronic 33 (52.4) 10 (15.2) Breathless 0.003 Grade 0 28 (44.4) 37 (56.1) Grade 1 8 (12.7) 16 (24.2) Grade 2 5 (7.9) 7 (10.6) Grade 3 8 (12.7) 5 (7.6) Grade 4 14 (22.2) 1 (1.5) *p-value < 0.05 The FVC was not significantly different between the exposed and unexposed groups, even after adjusting for some possible confounders. The mean of FEV1 was significantly higher in unexposed individuals than in railway workers (P = 0.034,) but the difference became non-significant after adjusting for cigarette smoking and experiencing COVID-19 (P = 0.058). Although the mean of PEF was significantly higher in the control than the exposed group (P = 0.034), the difference between the two means were non-significant after adjusting for age and marital status (P = 0.144). The mean of FEV1/FVC was significantly higher in the control than the exposed group even after adjusting for possible confounders. Although the mean of FEF25-75 was not significantly different between the two groups (P = 0.072), it became significant after adjusting for age and marital status (P = 0.020) as well as systolic and diastolic blood pressure (P = 0.024) (Table 4 ). Table 4 Mean of pulmonary function indices in the exposed and unexposed groups Exposed Unexposed P_value a P_value b P_value c P_value d P_value e Mean ± SD Mean ± SD FVC 91.00 ± 18.82 90.42 ± 11.40 0.833 0.784 0.831 0.680 0.976 FEV1 81.19 ± 20.62 87.54 ± 12.29 0.034 0.045 0.035 0.058 0.016 PEF 60.52 ± 23.95 69.35 ± 22.81 0.034 0.144 0.035 0.040 0.009 FEV1/FVC 90.55 ± 13.63 96.58 ± 5.25 0.001 0.002 0.001 0.001 < 0.001 FEF25-75 72.41 ± 25.61 80.36 ± 24.13 0.072 0.020 0.071 0.107 0.024 *p-value < 0.05 a. unadjusted model; b.adjusted for age and marital status; c. adjusted for BMI; d. adjusted for cigarette smoking and experiencing COVID-19; e. adjusted for systolic and diastolic blood pressure Discussion Railroad maintenance workers are exposed to silica dust due to their work on railroad ballast. Silica dust is generated during the construction, maintenance, and repair processes of the railway bed ( 1 ). Long-term inhalation of these particles can lead to serious lung diseases such as pulmonary fibrosis and significantly reduce pulmonary function ( 4 – 7 ). Based on the results, the exposure group had significantly lower FEV1, PEF, and FEV1/FVC values than the control group (Table 4 ). Similarly, Fareed et al. (2018) found reduced FEV1, FVC, and FEV1/FVC among Riyadh metro tunnel workers. ( 39 ). Khairnar et al. (2011) reported respiratory disorders in populations exposed to dust from railway traffic. ( 46 ). Awang et al. (2014) studied Sentul Railway employees and found normal spirometry parameters in both exposed and non-exposed groups, though exposed subjects showed slightly lower respiratory function ( 47 ). Sohrabi et al. (2022) noted a significant decrease in FEV1, PEF, and FEV1/FVC among silica-exposed workers, with the greatest reduction in FEV1 ( 38 ). Islam et al. (2024) found a higher prevalence of interstitial lung diseases in occupationally exposed railway workers (1.49%) than in unexposed workers ( 48 ). Other studies also confirm silica dust exposure reduces pulmonary function ( 5 , 49 – 51 ). The inhalation of high concentrations of dust during sand-cleaning activities and chronic exposure to sandstorms lasting up to 120 days reduced FEV1, PEF, and FEV1/FVC in the exposed group compared to those without exposure. The dust penetrates into the respiratory tract and causes inflammation in the mucous membrane of the lungs, as reflected in abnormal pulmonary function tests ( 52 ). Additionally, the presence of hazardous pollutants like silica in the geographical area under study also contributed to the decline in pulmonary function.. Furthermore, the intensity, frequency, and duration of exposure to silica can influence the severity of the effects ( 38 ). The results of the present study showed that there is no statistically significant difference in FVC between two groups. Omidian Dost et al. also did not report a significant difference in the FVC parameter in cement factory workers who were exposed to silica dust, which is consistent with our findings ( 53 ). However, the results of some studies contradict the results of our study ( 39 , 48 , 54 ). The main reason for these inconsistencies is unclear, but it seems that differences such as the concentration of dust in the work environment and the duration of exposure to dust may partly explain these inconsistencies ( 53 ). In addition to exposure to silica dust, other factors, such as individual factors, sensitivity, aging, various diseases, smoking, hookah smoking, and other addictive substances, may contribute to the decline in lung function observed in previous studies. The results indicated that there is no significant difference between the FEF25-75 parameter between the two groups. The findings of previous studies support this result ( 55 , 56 ). It is interesting to note that after adjusting for age, marital status, and blood pressure, this parameter became significant. However, since the parameter shows no significant difference between the two groups even after controlling for other variables, and given the relatively small sample size, this conclusion may not be definitive. Therefore, further studies with larger sample sizes are needed to confirm these findings. In addition, there may be other confounding factors that were not measured in this study. After controlling for the effects of age and marital status, the FEV1 and FEV1/FVC values remained significant. Shanshal et al. reported similar findings in their study of 97 cement factory workers ( 7 ). The difference in the PEF variable between the exposed and non-exposed groups was not significant after controlling for the effects of these two variables. Aging can lead to decreased diaphragm muscle strength, diminished lung tissue flexibility, and airway constriction ( 57 ). Recent investigations have also shown a reduction in PEF among the elderly ( 58 ). As a result, the higher average age of the exposure group compared to the control group could explain the PEF parameter's non-significance after correcting for age. Furthermore, married people may work longer hours due to increasing family duties and economic demands ( 59 ). However, after correcting for this variable, the effect on the results was no longer significant. Peak expiratory flow is an essential index for assessing response to asthma treatment, short-term or long-term monitoring of asthma, and screening for COPD. In recent years, some researchers have found that PEF is not only associated with respiratory diseases but also strongly correlates with some adverse outcomes ( 58 ). The FEV1 and the FEV1/FVC values remained statistically different between the two groups after controlling for all demographic variables except smoking and COVID-19. The dust exposure faced by workers on the Zahedan-Fahraj railway line, despite individual variations between the control and exposed groups, led to a reduction in the FEV1. Additionally, the average work experience of the workers was higher than that of the control group, which supports the hypothesis of adverse effects of exposure to dust in this group of workers. In terms of the confounding effect of smoking, it should be acknowledged that smoking causes significant changes in both the lungs and the immune system ( 60 ). Studies have shown that smoking increases the number of macrophages, neutrophils, eosinophils, and mast cells in the lung, decreases the number of airway dendritic cells, and alters macrophage and neutrophil function ( 61 , 62 ). In the present study, body mass index did not affect pulmonary parameters. The effects of obesity on spirometric values ​​are not consistent in most studies either, with some studies showing no effect ( 63 – 66 ). However, some other studies show significant effects ( 67 – 70 ). This discrepancy between studies could be explained through wide variation in PFT values ​​in different ethnic populations or may be the result of methodological differences in them ( 71 ). There are reasons why obesity reduces lung compliance. First, the position of the diaphragm in the thoracic cavity clearly increases with increasing weight. This change leads to a decrease in lung function and additional work of breathing. Secondly, the accumulation of fat in the chest wall, combined with direct resistance or abnormal function of the intercostal muscle, prevents the movement of the chest. Third, obesity increases the release of inflammatory markers in the lung. Therefore, obesity is related to lung volume, not airway obstruction. In pulmonary function testing, FVC reflects lung volume and other variables are associated with airway obstruction ( 72 ). The findings of the present study demonstrated that occupational exposure to dust caused by the harsh climatic conditions of the region had a significant effect on the respiratory health of workers. A high prevalence of chronic cough (38.1%), chronic phlegm (41.3%), and chronic wheezing (52.4%) was observed in the exposed group, while the prevalence of these symptoms was significantly lower in the control group, which had no occupational exposure. Other studies have reported similar results ( 73 ). For example Aminian’s study on individual exposed to cement dust symptoms such as cough, phlegm, shortness of breath, and wheezing were significantly more prevalent in the exposed group than in the non-exposed group ( 26 ). In the current study, a statistically significant difference was noted between the two groups in terms of shortness of breath, such that 22.2% of the exposed group reported severe shortness of breath (Grade 4). These findings suggest that occupational exposure to dust in the adverse working conditions of the Zahedan-Fahraj railway line significantly increases the risk of chronic lung diseases among the workers. A similar study examined the lung capacity and respiratory symptoms of sweepers exposed to dust in Zahedan city. The findings revealed that pollutants in this geographical area significantly increased the risk of developing cough, phlegm, shortness of breath, and wheezing by 21.9, 4.3, 48.6, and 15.8 times, respectively ( 35 ). The results of the studies conducted by Fell ( 74 ) and Sohrabi ( 38 ) are in contrast to the findings of the present study. However, the results of other studies are in line with the current study ( 7 , 39 , 75 ). The workers did not use respiratory protective equipment such as masks due to the discomfort they experienced while using them. Therefore, the lack of appropriate personal protective equipment, such as breathing masks, can act as an important factor in aggravating respiratory symptoms in this occupational group. A study conducted on the attitude, safety behaviors, and use of personal protective equipment among employees of Isfahan Metro, Iran, showed that the most common personal protective equipment used was safety shoes and gloves, while helmets, dust masks, and suitable work clothes were rarely used ( 76 ). One of the limitations of the present study is the small sample size; however, all individuals who were eligible to participate were included. Additionally, the data were collected using self-reported questionnaires, which might have led to conservative responses from workers due to a lack of awareness or concerns about job security. The strengths of the study include the unique climatic conditions faced by railway workers along the Fahraj-Zahedan line, who manually clear sand from the tracks, and the scarcity of research in the field of lung disease screening among railway workers. Furthermore, considering that the study was conducted post-COVID-19, the potential effects on participants were also taken into account. Conclusion The present study demonstrated that railway workers experience a significant reduction in pulmonary function and an increased prevalence of respiratory symptoms due to exposure to silica dust. The significant decline in respiratory parameters such as FEV1, PEF, and FEV1/FVC in the exposed group compared to the control group supports this finding. Additionally, symptoms such as coughing, phlegm, wheezing, and shortness of breath were significantly more prevalent among railway workers than in the control group, with most of them experiencing shortness of breath classified as Grade 4. According to this study, factors such as blood pressure and body mass index did not affect pulmonary parameters, while smoking, marital status, COVID-19, and age are likely to influence lung function and, therefore, should be considered in future prevention and control programs. Declarations Ethics approval and consent to participate This study was reviewed and approved by the Ethics Committee of Zahedan University of Medical Sciences with the approval number [IR.ZAUMS.REC.1403.294]. All participants provided written informed consent to participate in the study and publication of data. Consent for publication Not applicable. Competing interests The authors declare no Competing interests. Funding This work was supported by the Zahedan University of Medical Sciences. Author contributions RH.H and M.M conceived and designed the study. MH.M and.S.SH collected the data. JD, S.SH, and F.P entered the data, analyzed the data and edited the manuscript. M.M, JD and F.P wrote the draft of manuscript. MH.M and M.M contributed to the final version of the manuscript and supervised the project. All authors provided critical feedback and helped shape the research, analysis and manuscript. Acknowledgements The authors would like to express their gratitude to Zahedan University of Medical Sciences for the financial support of this research and the management of Southeastern Railway administration for their cooperation. Data availability The data underlying this article will be shared on reasonable request to the corresponding author. References Ruttenberg, R., The social and economic impact of chronic obstructive pulmonary disease on maintenance-of-way railroad workers. 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Mostafa, I.M., et al., Evaluation of occupational and nonoccupational interstitial lung disease in railway workers. The Egyptian Journal of Chest Diseases and Tuberculosis, 2024. 73 (3): p. 217-224. Ehrlich, R., et al., Lung function loss in relation to silica dust exposure in South African gold miners. Occupational and environmental medicine, 2011. 68 (2): p. 96-101. Hertzberg, V.S., et al., Effect of occupational silica exposure on pulmonary function. Chest, 2002. 122 (2): p. 721-728. Möhner, M., N. Kersten, and J. Gellissen, Chronic obstructive pulmonary disease and longitudinal changes in pulmonary function due to occupational exposure to respirable quartz. Occupational and environmental medicine, 2013. 70 (1): p. 9-14. Sumana, P., et al., Cement dust exposure and pulmonary function tests in construction site workers. Asian Pac J Health Sci, 2016. 3 (2): p. 43-46. Omidianidost, A., et al., Occupational Exposure to Respirable Dust, Crystalline Silica and Its Pulmonary Effects among Workers of a Cement Factory in Kermanshah, Iran. Tanaffos, 2019. 18 (2): p. 157-162. Shaik, A., et al., Lung function test in quarry workers. Int. J. Innovat. Res. Dev, 2015. 4 (1): p. 50-55. Gholami, A., et al., Lung function and respiratory symptoms among mine workers in the Eastern part of Iran. Russian Open Medical Journal, 2018. 7 (3): p. 306. Poornajaf, A., et al., The effect of cement dust on the lung function in a cement factory, Iran. International Journal of Occupational Hygiene, 2010. 2 (2): p. 74-78. Roman, M.A., H.B. Rossiter, and R. Casaburi, Exercise, ageing and the lung. European Respiratory Journal, 2016. 48 (5): p. 1471-1486. Ji, C., et al., Reference values and related factors for peak expiratory flow in middle-aged and elderly Chinese. Frontiers in Public Health, 2021. 9 : p. 706524. Ramezani, J., Investigation of the Relationship of Pulmonary Indicators with Quality of Life and Mental Health of Workers and the Role of Physical Activity on These Indicators: A Case Study in Cement and Tile Factory, Yazd, Iran, during 2020. Journal of Ilam University of Medical Sciences, 2020. 28 (3): p. 11-20. Shiels, M.S., et al., Cigarette smoking and variations in systemic immune and inflammation markers. Journal of the national cancer institute, 2014. 106 (11): p. dju294. Sopori, M., Effects of cigarette smoke on the immune system. Nature Reviews Immunology, 2002. 2 (5): p. 372-377. Mehta, H., K. Nazzal, and R. Sadikot, Cigarette smoking and innate immunity. Inflammation Research, 2008. 57 : p. 497-503. Jenkins, S. and J. Moxham, The effects of mild obesity on lung function. Respiratory medicine, 1991. 85 (4): p. 309-311. Sutherland, T.J., et al., The association between obesity and asthma: interactions between systemic and airway inflammation. American journal of respiratory and critical care medicine, 2008. 178 (5): p. 469-475. Collins, L.C., et al., The effect of body fat distribution on pulmonary function tests. Chest, 1995. 107 (5): p. 1298-1302. Al Ghobain, M., The effect of obesity on spirometry tests among healthy non-smoking adults. BMC pulmonary medicine, 2012. 12 : p. 1-5. Watson, R.A. and N.B. Pride, Postural changes in lung volumes and respiratory resistance in subjects with obesity. Journal of Applied Physiology, 2005. 98 (2): p. 512-517. Jones, R.L. and M.-M.U. Nzekwu, The effects of body mass index on lung volumes. Chest, 2006. 130 (3): p. 827-833. Salome, C.M., G.G. King, and N. Berend, Physiology of obesity and effects on lung function. Journal of applied physiology, 2010. 108 (1): p. 206-211. Dixon, A.E. and U. Peters, The effect of obesity on lung function. Expert review of respiratory medicine, 2018. 12 (9): p. 755-767. Banerjee, J., et al., Association of body mass index (BMI) with lung function parameters in non-asthmatics identified by spirometric protocols. Journal of clinical and diagnostic research: JCDR, 2014. 8 (2): p. 12. Wang, S., et al., The effects of body mass index on spirometry tests among adults in Xi’an, China. Medicine, 2017. 96 (15): p. e6596. Mohammadi, H., et al., Pulmonary Functions and Health-Related Quality of Life among Silica-Exposed Workers. TANAFFOS (Respiration), 2017. 16 (1): p. 60-67. Fell, A.K.M., et al., Respiratory symptoms and ventilatory function in workers exposed to Portland cement dust. Journal of occupational and environmental medicine, 2003. 45 (9): p. 1008-1014. Arcangeli, G., et al., Respiratory risks in tunnel construction workers. International Journal of Immunopathology and Pharmacology, 2004. 17 (2_suppl): p. 91-96. Shamsi, M., M. Shams, and A.N. Tabatabaei, Study of attitude and behaviors related to using personal protective equipment in employees of constructing subway stations in Esfahan, Iran. Iran Occupational Health, 2013. 10 (3). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6741939","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":489112235,"identity":"dd85e7df-98fa-4d52-aad8-52de1503184a","order_by":0,"name":"Fatemeh Paridokht","email":"","orcid":"","institution":"Shahid Beheshti University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Fatemeh","middleName":"","lastName":"Paridokht","suffix":""},{"id":489112236,"identity":"3185fa6c-bcb6-4617-888d-4915b79ed418","order_by":1,"name":"Raheleh Hashemi Habybabady","email":"","orcid":"","institution":"Zahedan University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Raheleh","middleName":"Hashemi","lastName":"Habybabady","suffix":""},{"id":489112237,"identity":"30a7a189-d8a8-4fec-9a6c-649299f68fa4","order_by":2,"name":"Mahdi Mohammadi","email":"","orcid":"","institution":"Zahedan University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Mahdi","middleName":"","lastName":"Mohammadi","suffix":""},{"id":489112238,"identity":"a3588757-cecf-47ea-af12-ca9893645cfe","order_by":3,"name":"MohammadHosein Mahmoodi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYFACHiA2AGIJEIdNQg5EHXhAihZjsJYEgloY4FoYEhtAND4tuu29hz98KLjDoDu7O/HBhzKL9Plhhx8CbbGT023ArsXszLk0yRkGzxjM7pzdbDjjnETuxttpBkAtycZmB3BouZFjxsxjcBjIyN0mzdsG1DI7AaTlQOI23FqMP/9B0pJuODv9AyEtBtIMSFoS5KVzCNhy5oyZZI/BYR6gFrBfDDdI5xQcSDDA45fjPcYffvw5LAfUshEYYnXy8rPTN3/4UGEnh0sLDPDAWQZglQb4laMC+QZSVI+CUTAKRsFIAAAn2GOD7Mt7RQAAAABJRU5ErkJggg==","orcid":"","institution":"Zahedan University of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"MohammadHosein","middleName":"","lastName":"Mahmoodi","suffix":""},{"id":489112239,"identity":"85d8987a-8a98-4260-b70b-07243640bf85","order_by":4,"name":"Siavash Shahnavazi","email":"","orcid":"","institution":"Zahedan University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Siavash","middleName":"","lastName":"Shahnavazi","suffix":""},{"id":489112240,"identity":"3388468c-cb12-4b76-bff0-c277222979f2","order_by":5,"name":"jalil derakhshan","email":"","orcid":"","institution":"Hamadan University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"jalil","middleName":"","lastName":"derakhshan","suffix":""}],"badges":[],"createdAt":"2025-05-25 05:53:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6741939/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6741939/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87577036,"identity":"ee15ab87-e1c3-4b53-bd53-7312e8cea1e0","added_by":"auto","created_at":"2025-07-25 11:47:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":121715,"visible":true,"origin":"","legend":"\u003cp\u003eDust accumulations on the railway line\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6741939/v1/d67936bf6df5debd8c5678fd.png"},{"id":87576073,"identity":"962eb587-c428-417f-81e5-a27ad7376cb9","added_by":"auto","created_at":"2025-07-25 11:39:33","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":195342,"visible":true,"origin":"","legend":"\u003cp\u003eSand-cleaning workers carrying out sandblasting activities\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6741939/v1/92917007e2b1d034c4a3da62.png"},{"id":95313651,"identity":"ac9d3047-2a53-4493-97f3-21712eb556a2","added_by":"auto","created_at":"2025-11-06 15:51:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1450907,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6741939/v1/76fd5b8e-4cce-437f-8c72-51946646eb91.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Pulmonary Function and Respiratory Symptoms in Railway Workers Exposed to Silica Dust in Southeastern Iran","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRailway maintenance workers represent of the occupational groups most frequently exposed to dust. Their responsibilities include the construction, maintenance, inspection, and repair of the railway bed, which is supported by ballast. The disturbance, manipulation, distribution, and spreading of ballast along the railway track during track maintenance operations generates silica dust (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), which is one of the most common minerals on Earth and a primary component of sand, granite, soil, and glass. Workers in various industries, including foundries, stone cutting, construction, tile making, glazing, sandblasting, and sculpting, are exposed to crystalline silica dust (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Chronic exposure to excessive levels of dust can result in respiratory diseases such as pulmonary fibrosis and reduced respiratory capacity (\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAccording to the National Institute for Occupational Safety and Health (NIOSH), occupational exposure to silica poses a significant health risk to railway maintenance workers. In the United States, approximately 35,000 active railway maintenance workers are affected by silica exposure during maintenance activities (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Over 23\u0026nbsp;million workers in China were exposed to silica in 2009 (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Additionally, more than 2.3\u0026nbsp;million workers came into contact with silica dust in the United States in 2016 (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e), while this number accounted for more than 2\u0026nbsp;million workers in Europe in 2007 (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOccupational silica exposure is a major health concern in developed and developing countries (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). The International Agency for Research on Cancer (IARC) has classified crystalline silica as a human carcinogen (Group 1A) (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Also, studies have shown that exposure to silica dust can lead to lung cancer (\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). In 2016, lung cancer caused by silica exposure accounted for approximately 13.8% of all occupational cancer deaths, with a total of 47,999 cases (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSilica particles can cause serious lung damage. When inhaled, these particles can travel deep into the lungs, reaching the delicate alveoli and bronchioles. This may lead to inflammation and tissue damage, which can in turn result in chronic lung diseases (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Consequently, workers who inhale silica dust particles are at risk of developing serious silica-related diseases (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Occupational exposure to silica dust can also lead to several serious health issues, including Chronic Obstructive Pulmonary Disease (COPD), silicosis, and tuberculosis (\u003cspan additionalcitationids=\"CR19 CR20 CR21 CR22\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Additionally, silica exposure is associated with other complications, such as kidney and autoimmune diseases (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Epidemiological studies have also shown a link between silica exposure and sarcoidosis (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Moreover, numerous studies have demonstrated reduced pulmonary function in workers exposed to silica dust (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAccording to studies, more than 548 kilometers of Iran's railway network passes through sandy regions, with approximately 200 kilometers heavily impacted by sand buildup (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). The Rudshur-Shoreghez block on the Bam-Zahedan line is one of the most critical railway lines in Iran due to severe sand accumulation, requiring 24-hour maintenance (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFurthermore, studies have shown that this region experiences strong and persistent winds, excessive dryness, and abundant sand and soil, leading to air pollution (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Based on Environmental Protection Agency standards, the permissible level of PM10 (Particulate Matter 10) in the air is a maximum of 150 micrograms per cubic meter, which should not be exceeded more than once per year. However, in Zahedan, the level of suspended particles often exceeds this limit (averaging 189 micrograms per cubic meter), especially in the summer, with the seasonal winds known as the \u0026ldquo;120-day wind\u0026rdquo; in the northern areas and monsoon systems in the southern areas (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). Previous studies have indicated that the dust in this region contains crystalline silica, constituting 30\u0026ndash;40% of the total composition (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Given that silica is present in rocks, sand, and soil, any activity that generates respirable-sized particles can lead to silica exposure (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). This situation, combined with the region's climatic conditions and the nature of the sand-cleaning workers\u0026rsquo; activities in this line\u0026mdash;where workers clear tracks of soil and sand amid stormy conditions\u0026ndash; results in severe exposure to silica-containing dust and sand. Additionally, studies have shown that the airborne dust in the Sistan and Baluchestan region reduces the lung capacity of workers (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePulmonary function tests, particularly spirometry, play a key role in diagnosing respiratory diseases, especially asthma and COPD. Spirometry measures the volume of air exhaled during a forced complete exhalation following a maximal inhalation. Key parameters reported include Forced Vital Capacity (FVC), Forced Expiratory Volume in One Second (FEV1), and their ratios. These results are graphically represented, which can serve as a diagnostic tool (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eEvaluating the pulmonary function of workers exposed to crystalline silica dust, Sohrabi et al. (2022) demonstrated significant reductions in all pulmonary function parameters in the exposed group compared to the non-exposed group, with the FEV\u003csub\u003e1\u003c/sub\u003e parameter showing the greatest decrease (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Other studies have also shown significant reductions in spirometry indices and pulmonary function among individuals occupationally exposed to silica dust compared to non-exposed individuals (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eNo research has yet been conducted on Zahedan-Fahraj railway workers, despite the health risks associated with respiratory exposure to silica, and given the exposure of maintenance workers on this railway line to silica and sand dust as observed by the authors of this study. Therefore, This study aimed to quantify the impact of silica dust exposure on pulmonary function and respiratory symptoms among railway maintenance workers in southeastern Iran.\u003c/p\u003e"},{"header":"Material and methods","content":"\u003cp\u003eStudy design and participants\u003c/p\u003e\u003cp\u003eThe current case-control study was conducted among sand-cleaning workers at the Zahedan-Fahraj railway line in the year 2024.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eA census sampling approach was employed. As there are 74 sand maintenance workers at this railway, the sample size was set at 74. Also, 74 individuals were selected as controls, comprising those with no past and current dust exposure. The decision to include all available sandblasting workers in the study was driven by the limited number of workers in this specific occupation at the study site, ensuring comprehensive representation of the target population. As a result, the same number of control participants was selected for comparison. The exclusion criteria included any patients with a history of asthma, COPD, tuberculosis, acute and chronic respiratory infections, abdominal or chest surgery, cardiovascular diseases, diabetes, and hypertension. Individuals previously working at other occupations were also excluded. Inclusion criteria required at least one year of work experience. All the participants gave informed consent to participate in the study and publication of data. All participants signed written consent to participate in the study voluntarily. The participants of the present study provided written informed consent for the publication of their personal or clinical information along with any images that may identify them. This study was conducted in accordance with the ethical standards of the Helsinki Declaration (1964, amended most recently in 2013), as developed by the World Medical Association. Our study adhered to the Declaration of Helsinki. The study protocol was reviewed and approved by the Ethics Committee of Zahedan University of Medical Sciences with the approval code: [IR.ZAUMS.REC.1403.294]. Clinical trial number: not applicable.\u003c/p\u003e\u003cp\u003eData collection\u003c/p\u003e\u003cp\u003eTo gather data, the researcher conducted on-site observations of sandblasting workers after securing managerial approval for the project. Participants were initially presented with informed consent documents. Following their agreement, the researcher administered demographic and respiratory symptoms questionnaire face-to-face. Subsequently, participants\u0026rsquo; blood pressure was measured and recorded using a digital device. Finally, the participants received practical training on the FVC spirometry test. Once they learned how to perform the test correctly, they were provided with the device to conduct it themselves.\u003c/p\u003e\u003cp\u003eDemographic information\u003c/p\u003e\u003cp\u003eDemographic information, including gender, age, weight, height, body mass index, work experience, education level, marital status, smoking history was collected from both groups. Participants who smoked one or more cigarettes per day or who had smoked cigarettes within the past month were considered smokers. Those who had smoked 100 cigarettes in their lifetime but had quit at the time of the study (at least for 30 days) were classified as ex-smokers while those who had never smoked were considered non-smokers (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eRespiratory symptoms questionnaire\u003c/p\u003e\u003cp\u003eThe ATS (American Thoracic Society) questionnaire was used to assess individuals\u0026rsquo; respiratory status in terms of symptoms such as cough, phlegm, wheezing, and shortness of breath, while also considering their smoking habits, work history, and medical history. Cough, phlegm, and wheezing were categorized into four levels of severity: no symptoms, mild (lasting less than three months), frequent (occurring for three consecutive months), and chronic (lasting more than two years). Shortness of breath was categorized into 5 grades according to the Modified Medical Research Council Dyspnea Scale: Grade 0 (Not troubled with breathlessness, except during strenuous exercise); Grade1 (Troubled by shortness of breath when hurrying or walking up a slight hill); Grade 2 (Walks slower than people of the same age due to breathlessness or has to stop for breath when walking at their own pace on a level surface); Grade 3 (Stops for breath after walking about 100 m or after a few minutes on a level surface); and Grade 4 (Too breathless to leave the house or breathless when dressing or undressing) (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). The information obtained from this questionnaire was used to determine the prevalence of respiratory symptoms between the two groups. The Persian version of this questionnaire has also been used in other studies (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). The ATS questionnaire (American Thoracic Society) has been published elsewhere (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePulmonary function test\u003c/p\u003e\u003cp\u003ePulmonary Function Tests (PFTs) were performed according to the guidelines of the American Thoracic Society (ATS) (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). A calibrated spirometer (Spirobank II advanced; MIR Medical International Research, Rome, Italy) was used for the tests, ensuring an accuracy of 3% and a flow of 5%. In order to evaluate pulmonary function, the parameters of forced vital volume (the maximum amount of air that can be exhaled when blowing out as fast as possible)(\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e), forced expiratory volume in the first second, FEV1/FVC ratios, Peak Expiratory Flow (PEF), the maximal flow that can be exhaled when blowing out as fast as possible(\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e), and forced expiratory flow at 25\u0026ndash;75% of expiratory volume (FEF 25\u0026ndash;75%) were evaluated. The spirometer calculated predicted pulmonary function parameters based on age, height, weight, sex, smoking and race. Each participant was advised to refrain from eating and drinking alcohol, smoking, and heavy exercise two hours before the test, and to wear comfortable clothes (tight clothing can restrict chest movements). Additionally, suitable exercises were provided to all participants, their weight and height were measured while standing, and BMI was calculated.\u003c/p\u003e\u003cp\u003eThe researchers taught each participant individually how to perform the spirometry test. Then, they were asked to rest for about 5 minutes and then prepare themselves for the test by using a nose clip. The test was repeated three times for each participant, and the maximum value from the consecutive tests was recorded. Participants who did not complete the maneuvers successfully after three attempts were excluded from the study.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eMean and standard deviation were used to describe quantitative variables, while frequency and percentage were employed for qualitative variables. The Shapiro-Wilk test was conducted to check the normality assumption of quantitative variables. To compare pulmonary function parameters in two groups, a t-test was utilized for two independent samples; however, if the normal assumption was not met, Mann-Whitney test was applied instead. The Chi-square test was used to compare the frequency of respiratory symptoms in the two groups. A classical regression model was used to control for confounding factors in the comparison of pulmonary parameters in two groups, while a logistic regression model was used to account for the effect of confounding factors in the comparison of the frequency of symptoms in the two groups. Analyses were performed using SPSS version 26.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 63 railway workers and 66 controls participated in this study. Four participants were excluded from the study due to recent cardiovascular surgery, and seven individuals declined to participate in the study. The mean age of individuals was 41.71\u0026thinsp;\u0026plusmn;\u0026thinsp;7.31 in the exposed group and 33.52\u0026thinsp;\u0026plusmn;\u0026thinsp;10.55 years in the unexposed (control) group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Single individuals comprised 63.6% of the control group, while all railway workers in the other group were single (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In terms of education, 50% of the unexposed group had a university degree, compared to 15.8% in the exposed group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Regarding weight, most participants were either normal or overweight, and BMI was not significantly different between the two groups (P\u0026thinsp;=\u0026thinsp;0.756). The mean work experience was 12.79\u0026thinsp;\u0026plusmn;\u0026thinsp;3.94 in the exposed group and 10.24\u0026thinsp;\u0026plusmn;\u0026thinsp;8.03 years in the unexposed group (P\u0026thinsp;=\u0026thinsp;0.025). Cigarette smoking was reported by 14.3% and 27.3% in the exposed and unexposed groups, respectively (P\u0026thinsp;=\u0026thinsp;0.070). Furthermore, there was no significant difference in tobacco use (P\u0026thinsp;=\u0026thinsp;0.164) and COVID-19 history (P\u0026thinsp;=\u0026thinsp;0.508) between the two groups. Exposure to dust occurred for only 9.1% of the control group, but all railway workers were exposed to dust (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The mean of systolic and diastolic blood pressure was 12.29\u0026thinsp;\u0026plusmn;\u0026thinsp;1.30 in the exposed group and 11.54\u0026thinsp;\u0026plusmn;\u0026thinsp;1.44 in the unexposed group (P\u0026thinsp;=\u0026thinsp;0.003). However, the mean of diastolic blood pressure was not significantly different between the two groups (P\u0026thinsp;=\u0026thinsp;0.231).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eFrequency distribution of demographic factors in the exposed and unexposed groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eExposed (n\u0026thinsp;=\u0026thinsp;63)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnexposed (n\u0026thinsp;=\u0026thinsp;66)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eN (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eN (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (year)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;=25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15 (22.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26\u0026ndash;35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11 (17.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e24 (36.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e51 (81.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27 (40.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarital status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSingle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e42 (63.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e63 (100.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e24 (36.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e0.756\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnderweight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (4.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNormal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29 (46.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27 (40.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOverweight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23 (36.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26 (39.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eObese\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10 (15.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 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colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6\u0026ndash;10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14 (22.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (13.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11\u0026ndash;20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e45 (71.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23 (35.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8 (12.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrimary/Secondary school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e36 (57.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (3.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh school \u0026amp; Diploma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17 (27.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31 (47.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAssociate degree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (9.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14 (21.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBSc or higher degree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (6.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19 (28.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCigarette smoking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.070\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e54 (85.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e48 (72.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9 (14.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18 (27.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNon-cigarette tobacco use\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.164\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e61 (96.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e60 (90.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (9.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCOVID-19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.508\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e38 (60.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36 (54.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25 (39.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30 (45.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e*p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eRailway workers were more likely to be affected by COVID-19 symptoms and side effects. Specifically, there was a significant difference between the exposed and unexposed groups in terms of shortness of breath (P\u0026thinsp;=\u0026thinsp;0.042), wheezing (P\u0026thinsp;=\u0026thinsp;0.004), and using spray (P\u0026thinsp;=\u0026thinsp;0.023) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eFrequency of COVID-19 side effects and symptoms in the exposed and unexposed groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSide effects of Covid 19\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eExposed\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnexposed\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP_value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eN (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdmission to hospital\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (12.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (6.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.493*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eShort breathing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8 (32.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (10.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.042*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWheezing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11 (44.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (10.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.004*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAsthma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (8.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.115\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSnoring\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10 (40.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5 (16.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.053\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUsing spray\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (16.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.023*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e*p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe exposed individuals were more likely to report respiratory symptoms. Coughing, sputum, wheezing, and breathlessness were reported in 60.3%, 58.7%, 65.1%, and 55.6% of railway workers compared to 18.2%, 31.8%, 31.8%, and 43.9% in the control group, respectively. There was a significant difference between the two groups in terms of respiratory symptoms. Thus, chronic cough, sputum, wheezing, and breathlessness affected 38.1%, 41.3%, 52.4%, and 22.2% of the exposed individuals, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eFrequency distribution of respiratory symptoms in the exposed and unexposed groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eExposed\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnexposed\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCough\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNone\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25 (39.7)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e54 (81.8)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMild\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8 (12.7)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (10.6)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrequent\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (9.5)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0.0)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChronic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24 (38.1)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5 (7.6)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSputum\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNone\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26 (41.3)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e45 (68.2)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMild\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (4.8)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (13.6)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrequent\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8 (12.7)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5 (7.6)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChronic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26 (41.3)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (10.6)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWheezing\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNone\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22 (34.9)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e45 (68.2)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMild\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (3.2)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (13.6)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrequent\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (9.5)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (3.0)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChronic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33 (52.4)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 (15.2)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBreathless\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGrade 0\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28 (44.4)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37 (56.1)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGrade 1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8 (12.7)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16 (24.2)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGrade 2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5 (7.9)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (10.6)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGrade 3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8 (12.7)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5 (7.6)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGrade 4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14 (22.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1 (1.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e*p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe FVC was not significantly different between the exposed and unexposed groups, even after adjusting for some possible confounders. The mean of FEV1 was significantly higher in unexposed individuals than in railway workers (P\u0026thinsp;=\u0026thinsp;0.034,) but the difference became non-significant after adjusting for cigarette smoking and experiencing COVID-19 (P\u0026thinsp;=\u0026thinsp;0.058). Although the mean of PEF was significantly higher in the control than the exposed group (P\u0026thinsp;=\u0026thinsp;0.034), the difference between the two means were non-significant after adjusting for age and marital status (P\u0026thinsp;=\u0026thinsp;0.144). The mean of FEV1/FVC was significantly higher in the control than the exposed group even after adjusting for possible confounders. Although the mean of FEF25-75 was not significantly different between the two groups (P\u0026thinsp;=\u0026thinsp;0.072), it became significant after adjusting for age and marital status (P\u0026thinsp;=\u0026thinsp;0.020) as well as systolic and diastolic blood pressure (P\u0026thinsp;=\u0026thinsp;0.024) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMean of pulmonary function indices in the exposed and unexposed groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eExposed\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnexposed\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP_value\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP_value\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eP_value\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eP_value\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eP_value\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFVC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e91.00\u0026thinsp;\u0026plusmn;\u0026thinsp;18.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e90.42\u0026thinsp;\u0026plusmn;\u0026thinsp;11.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.833\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.784\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.831\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.680\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.976\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFEV1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e81.19\u0026thinsp;\u0026plusmn;\u0026thinsp;20.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e87.54\u0026thinsp;\u0026plusmn;\u0026thinsp;12.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.034\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.045\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.035\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.058\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.016\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePEF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60.52\u0026thinsp;\u0026plusmn;\u0026thinsp;23.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e69.35\u0026thinsp;\u0026plusmn;\u0026thinsp;22.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.034\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.144\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.035\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.040\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFEV1/FVC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e90.55\u0026thinsp;\u0026plusmn;\u0026thinsp;13.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e96.58\u0026thinsp;\u0026plusmn;\u0026thinsp;5.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFEF25-75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e72.41\u0026thinsp;\u0026plusmn;\u0026thinsp;25.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e80.36\u0026thinsp;\u0026plusmn;\u0026thinsp;24.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.072\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.071\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.024\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003e*p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 a. unadjusted model; b.adjusted for age and marital status; c. adjusted for BMI; d. adjusted for cigarette smoking and experiencing COVID-19; e. adjusted for systolic and diastolic blood pressure\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eRailroad maintenance workers are exposed to silica dust due to their work on railroad ballast. Silica dust is generated during the construction, maintenance, and repair processes of the railway bed (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Long-term inhalation of these particles can lead to serious lung diseases such as pulmonary fibrosis and significantly reduce pulmonary function (\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBased on the results, the exposure group had significantly lower FEV1, PEF, and FEV1/FVC values than the control group (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Similarly, Fareed et al. (2018) found reduced FEV1, FVC, and FEV1/FVC among Riyadh metro tunnel workers. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). Khairnar et al. (2011) reported respiratory disorders in populations exposed to dust from railway traffic. (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). Awang et al. (2014) studied Sentul Railway employees and found normal spirometry parameters in both exposed and non-exposed groups, though exposed subjects showed slightly lower respiratory function (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). Sohrabi et al. (2022) noted a significant decrease in FEV1, PEF, and FEV1/FVC among silica-exposed workers, with the greatest reduction in FEV1 (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Islam et al. (2024) found a higher prevalence of interstitial lung diseases in occupationally exposed railway workers (1.49%) than in unexposed workers (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). Other studies also confirm silica dust exposure reduces pulmonary function (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan additionalcitationids=\"CR50\" citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe inhalation of high concentrations of dust during sand-cleaning activities and chronic exposure to sandstorms lasting up to 120 days reduced FEV1, PEF, and FEV1/FVC in the exposed group compared to those without exposure. The dust penetrates into the respiratory tract and causes inflammation in the mucous membrane of the lungs, as reflected in abnormal pulmonary function tests (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e). Additionally, the presence of hazardous pollutants like silica in the geographical area under study also contributed to the decline in pulmonary function.. Furthermore, the intensity, frequency, and duration of exposure to silica can influence the severity of the effects (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe results of the present study showed that there is no statistically significant difference in FVC between two groups. Omidian Dost et al. also did not report a significant difference in the FVC parameter in cement factory workers who were exposed to silica dust, which is consistent with our findings (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHowever, the results of some studies contradict the results of our study (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e). The main reason for these inconsistencies is unclear, but it seems that differences such as the concentration of dust in the work environment and the duration of exposure to dust may partly explain these inconsistencies (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). In addition to exposure to silica dust, other factors, such as individual factors, sensitivity, aging, various diseases, smoking, hookah smoking, and other addictive substances, may contribute to the decline in lung function observed in previous studies.\u003c/p\u003e\u003cp\u003eThe results indicated that there is no significant difference between the FEF25-75 parameter between the two groups. The findings of previous studies support this result (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e). It is interesting to note that after adjusting for age, marital status, and blood pressure, this parameter became significant. However, since the parameter shows no significant difference between the two groups even after controlling for other variables, and given the relatively small sample size, this conclusion may not be definitive. Therefore, further studies with larger sample sizes are needed to confirm these findings. In addition, there may be other confounding factors that were not measured in this study. After controlling for the effects of age and marital status, the FEV1 and FEV1/FVC values remained significant. Shanshal et al. reported similar findings in their study of 97 cement factory workers (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe difference in the PEF variable between the exposed and non-exposed groups was not significant after controlling for the effects of these two variables. Aging can lead to decreased diaphragm muscle strength, diminished lung tissue flexibility, and airway constriction (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). Recent investigations have also shown a reduction in PEF among the elderly (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e). As a result, the higher average age of the exposure group compared to the control group could explain the PEF parameter's non-significance after correcting for age. Furthermore, married people may work longer hours due to increasing family duties and economic demands (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e). However, after correcting for this variable, the effect on the results was no longer significant.\u003c/p\u003e\u003cp\u003ePeak expiratory flow is an essential index for assessing response to asthma treatment, short-term or long-term monitoring of asthma, and screening for COPD. In recent years, some researchers have found that PEF is not only associated with respiratory diseases but also strongly correlates with some adverse outcomes (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe FEV1 and the FEV1/FVC values remained statistically different between the two groups after controlling for all demographic variables except smoking and COVID-19. The dust exposure faced by workers on the Zahedan-Fahraj railway line, despite individual variations between the control and exposed groups, led to a reduction in the FEV1. Additionally, the average work experience of the workers was higher than that of the control group, which supports the hypothesis of adverse effects of exposure to dust in this group of workers.\u003c/p\u003e\u003cp\u003eIn terms of the confounding effect of smoking, it should be acknowledged that smoking causes significant changes in both the lungs and the immune system (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e). Studies have shown that smoking increases the number of macrophages, neutrophils, eosinophils, and mast cells in the lung, decreases the number of airway dendritic cells, and alters macrophage and neutrophil function (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn the present study, body mass index did not affect pulmonary parameters. The effects of obesity on spirometric values ​​are not consistent in most studies either, with some studies showing no effect (\u003cspan additionalcitationids=\"CR64 CR65\" citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e). However, some other studies show significant effects (\u003cspan additionalcitationids=\"CR68 CR69\" citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e). This discrepancy between studies could be explained through wide variation in PFT values ​​in different ethnic populations or may be the result of methodological differences in them (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e). There are reasons why obesity reduces lung compliance. First, the position of the diaphragm in the thoracic cavity clearly increases with increasing weight. This change leads to a decrease in lung function and additional work of breathing. Secondly, the accumulation of fat in the chest wall, combined with direct resistance or abnormal function of the intercostal muscle, prevents the movement of the chest. Third, obesity increases the release of inflammatory markers in the lung. Therefore, obesity is related to lung volume, not airway obstruction. In pulmonary function testing, FVC reflects lung volume and other variables are associated with airway obstruction (\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe findings of the present study demonstrated that occupational exposure to dust caused by the harsh climatic conditions of the region had a significant effect on the respiratory health of workers. A high prevalence of chronic cough (38.1%), chronic phlegm (41.3%), and chronic wheezing (52.4%) was observed in the exposed group, while the prevalence of these symptoms was significantly lower in the control group, which had no occupational exposure. Other studies have reported similar results (\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e). For example Aminian\u0026rsquo;s study on individual exposed to cement dust symptoms such as cough, phlegm, shortness of breath, and wheezing were significantly more prevalent in the exposed group than in the non-exposed group (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). In the current study, a statistically significant difference was noted between the two groups in terms of shortness of breath, such that 22.2% of the exposed group reported severe shortness of breath (Grade 4). These findings suggest that occupational exposure to dust in the adverse working conditions of the Zahedan-Fahraj railway line significantly increases the risk of chronic lung diseases among the workers. A similar study examined the lung capacity and respiratory symptoms of sweepers exposed to dust in Zahedan city. The findings revealed that pollutants in this geographical area significantly increased the risk of developing cough, phlegm, shortness of breath, and wheezing by 21.9, 4.3, 48.6, and 15.8 times, respectively (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). The results of the studies conducted by Fell (\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e) and Sohrabi (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e) are in contrast to the findings of the present study. However, the results of other studies are in line with the current study (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe workers did not use respiratory protective equipment such as masks due to the discomfort they experienced while using them. Therefore, the lack of appropriate personal protective equipment, such as breathing masks, can act as an important factor in aggravating respiratory symptoms in this occupational group. A study conducted on the attitude, safety behaviors, and use of personal protective equipment among employees of Isfahan Metro, Iran, showed that the most common personal protective equipment used was safety shoes and gloves, while helmets, dust masks, and suitable work clothes were rarely used (\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOne of the limitations of the present study is the small sample size; however, all individuals who were eligible to participate were included. Additionally, the data were collected using self-reported questionnaires, which might have led to conservative responses from workers due to a lack of awareness or concerns about job security. The strengths of the study include the unique climatic conditions faced by railway workers along the Fahraj-Zahedan line, who manually clear sand from the tracks, and the scarcity of research in the field of lung disease screening among railway workers. Furthermore, considering that the study was conducted post-COVID-19, the potential effects on participants were also taken into account.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe present study demonstrated that railway workers experience a significant reduction in pulmonary function and an increased prevalence of respiratory symptoms due to exposure to silica dust. The significant decline in respiratory parameters such as FEV1, PEF, and FEV1/FVC in the exposed group compared to the control group supports this finding. Additionally, symptoms such as coughing, phlegm, wheezing, and shortness of breath were significantly more prevalent among railway workers than in the control group, with most of them experiencing shortness of breath classified as Grade 4. According to this study, factors such as blood pressure and body mass index did not affect pulmonary parameters, while smoking, marital status, COVID-19, and age are likely to influence lung function and, therefore, should be considered in future prevention and control programs.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was reviewed and approved by the Ethics Committee of Zahedan University of Medical Sciences with the approval number\u0026nbsp;[IR.ZAUMS.REC.1403.294]. All participants provided written informed consent to participate in the study and publication of data.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no Competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Zahedan University of Medical Sciences.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRH.H and M.M conceived and designed the study. MH.M and.S.SH collected the data. JD, S.SH, and F.P entered the data, analyzed the data and edited the manuscript. M.M, JD and F.P wrote the draft of manuscript. MH.M and M.M contributed to the final version of the manuscript and supervised the project. All authors provided critical feedback and helped shape the research, analysis and manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to express their gratitude to Zahedan University of Medical Sciences for the financial support of this research and the management of Southeastern Railway administration for their cooperation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data underlying this article will be shared on reasonable request to the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eRuttenberg, R., \u003cem\u003eThe social and economic impact of chronic obstructive pulmonary disease on maintenance-of-way railroad workers.\u003c/em\u003e Journal of Occupational and Environmental Medicine, 2020. \u003cstrong\u003e62\u003c/strong\u003e(1): p. 58-63.\u003c/li\u003e\n\u003cli\u003eYassin, A., F. Yebesi, and R. Tingle, \u003cem\u003eOccupational exposure to crystalline silica dust in the United States, 1988\u0026ndash;2003.\u003c/em\u003e Environmental health perspectives, 2005. \u003cstrong\u003e113\u003c/strong\u003e(3): p. 255-260.\u003c/li\u003e\n\u003cli\u003eMohammadi, H., et al., \u003cem\u003eOccupational exposure assessment to crystalline silica in an insulator industry: Determination the risk of mortality from silicosis and lung cancer.\u003c/em\u003e Journal of Health and Safety at Work, 2017. \u003cstrong\u003e7\u003c/strong\u003e(1): p. 45-52.\u003c/li\u003e\n\u003cli\u003eHosseini, D.K., et al., \u003cem\u003ePrevalence of respiratory symptoms and spirometric changes among non-smoker male wood workers.\u003c/em\u003e PLOS ONE, 2020. \u003cstrong\u003e15\u003c/strong\u003e(3): p. 1-10.\u003c/li\u003e\n\u003cli\u003eMoghadam, S.R., et al., \u003cem\u003eChanges in spirometry indices and lung cancer mortality risk estimation in concrete workers exposed io crystalline silica.\u003c/em\u003e Asian Pacific journal of cancer prevention: APJCP, 2020. \u003cstrong\u003e21\u003c/strong\u003e(9): p. 2811.\u003c/li\u003e\n\u003cli\u003eHnizdo, E. and V. Vallyathan, \u003cem\u003eChronic obstructive pulmonary disease due to occupational exposure to silica dust: a review of epidemiological and pathological evidence.\u003c/em\u003e Occupational and environmental medicine, 2003. \u003cstrong\u003e60\u003c/strong\u003e(4): p. 237-243.\u003c/li\u003e\n\u003cli\u003eShanshal, S.A. and H.K. Al‐Qazaz, \u003cem\u003eConsequences of cement dust exposure on pulmonary function in cement factory workers.\u003c/em\u003e American Journal of Industrial Medicine, 2021. \u003cstrong\u003e64\u003c/strong\u003e(3): p. 192-197.\u003c/li\u003e\n\u003cli\u003ePiacitelli, C. and M. 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Shams, and A.N. Tabatabaei, \u003cem\u003eStudy of attitude and behaviors related to using personal protective equipment in employees of constructing subway stations in Esfahan, Iran.\u003c/em\u003e Iran Occupational Health, 2013. \u003cstrong\u003e10\u003c/strong\u003e(3).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"pulmonary function, respiratory symptoms, spirometry, Silica dust exposure, railway workers","lastPublishedDoi":"10.21203/rs.3.rs-6741939/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6741939/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Railway maintenance workers are exposed to various pollutants, including silica dust, which can impair pulmonary function. This study aimed to quantify the impact of silica dust exposure on pulmonary function and respiratory symptoms among railway maintenance workers in southeastern Iran.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterial and Methods\u003c/strong\u003e: This case-control study was conducted on 63 sand-cleaning workers from the Zahedan-Fahraj railway line. Demographic variables including age, height, weight, body mass index, marital status, work history, smoking, and COVID-19 history USING demographic questionnaire. Blood pressure were measured using a Sphygmomanometer. Pulmonary function was assessed through spirometry, measuring FEV1, FVC, FEV1/FVC, PEF, and FEF25-75 parameters. All participants completed the American Thoracic Society Respiratory Symptom Questionnaire. Data were analyzed using SPSS version 26.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: The exposed group showed significantly lower pulmonary function indices, including FEV1, FEV1/FVC, and PEF compared to the non-exposed group (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). However, no significant differences were found in FVC and FEF25-75 indices between the two groups (\u003cem\u003eP\u003c/em\u003e \u0026gt; 0.05). The mean of FEV1/FVC was significantly higher in the control than the exposed group even after adjusting for possible confounders (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001). Additionally, all respiratory symptoms including cough, phlegm, wheezing, and breathlessness were significantly higher in the exposed group compared the control group (\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: Inhaling silica dust decreased pulmonary function and caused adverse respiratory symptoms in railway workers. This indicates a critical need for interventions to protect railway workers' respiratory health. These findings should inform local health policies aimed at reducing occupational exposures to dust in similar settings.\u003c/p\u003e","manuscriptTitle":"Pulmonary Function and Respiratory Symptoms in Railway Workers Exposed to Silica Dust in Southeastern Iran","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-25 11:39:28","doi":"10.21203/rs.3.rs-6741939/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"697e5fca-024b-4c96-8a71-be8d0d0bafae","owner":[],"postedDate":"July 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-06T09:09:14+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-25 11:39:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6741939","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6741939","identity":"rs-6741939","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}