Assessment of Fractional Exhaled Nitric Oxide and Lung Function Among Quarry Workers

Assessment of Fractional Exhaled Nitric Oxide and Lung Function Among Quarry Workers | 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 Assessment of Fractional Exhaled Nitric Oxide and Lung Function Among Quarry Workers Muhammad Haziq Abdul Wahab, Mas Fazlin Mohamad Jailaini, Azat Azrai Azmel, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7497811/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: Occupational lung diseases are common among quarry workers due to exposure to dust and chemicals. This study examines FeNO levels, lung function, respiratory symptoms, and occupational lung disease prevalence, focusing on safety practices in a stone quarry. Methods: This cross-sectional study recruited 107 quarry workers using a universal sampling method. Health data were collected via a validated modified British Medical Research Council Questionnaire. Objective data included spirometry, chest imaging, FeNO measurement, and full lung function tests, followed by High-Resolution Computed Tomography (HRCT) of the Thorax if indicated. Results: Among quarry workers, 68.2% had normal spirometry, 25.2% showed Preserved Ratio Impaired Spirometry (PRISm) ventilatory defects, and 6.6% had obstructive ventilatory defects. Most had low FeNO levels (57%), with 25.2% at intermediate and 17.8% at high levels. Respiratory symptoms included breathlessness (25.2%), chest tightness (19.6%), and cough (15.9%). Administrators and site workers show similar results in FeNO and lung function tests. Only 52.3% occasionally adhered to respirators. Occupational lung disease prevalence was 5.6%. No significant correlations were identified between FeNO levels, symptoms, smoking, PPE use, or disease. However, more prolonged dust exposure was linked to reduced lung function. Conclusions: The findings indicate that site and administrative personnel within the quarry industry face comparable risks of occupational lung disease, with observed lung function impairment and variable FeNO levels across the workforce. The occupational lung disease prevalence rate of 5.6% exceeds previously reported local figures, underscoring the necessity for improved dust control measures and consistent use of personal protective equipment among all employees. Strengthening safety protocols, including rigorous enforcement of PPE usage and strategic workplace modifications, is essential to mitigate health risks and reduce the burden of occupational lung diseases in this sector. Fractional Exhaled Nitric Oxide (FeNO) Occupational Lung disease Quarry Spirometry Figures Figure 1 Figure 2 1. Introduction Occupational lung diseases (OLDs) are respiratory conditions that are caused, aggravated, or exacerbated by workplace exposures, including dust, fumes, gases, and chemicals, ranging from COPD and asthma to pneumoconiosis and mesothelioma ( 1 ). These diseases often cause lasting impairment and are especially prevalent in industries like construction, mining, and quarrying, where respiratory hazards are common. In Malaysian quarries, work-related illnesses significantly outnumber injuries, highlighting the need for strong health and safety protocols under the Occupational Safety and Health Act 1994 ( 2 , 3 ). Diseases such as asbestosis and silicosis remain significant in industries with silica and asbestos exposure, leading to impaired lung function and chronic respiratory symptoms. Additionally, inhalation of airborne pollutants, including dust and fumes, increases the risk of occupational asthma and other respiratory conditions, further impacting workers' health ( 4 , 5 ). Internationally, sources of occupational respiratory hazards have shifted over time ( 6 ). Historically, mining and metal production industries exposed workers to high levels of mineral dust, such as coal and silica. Occupational asthma remains the most common work-related respiratory disease, representing 15–20% of adult cases, though its prevalence is declining in Europe ( 7 ). Exposure to vapors, gases, dust, or fumes is linked to around 15% of COPD cases in Western countries ( 8 ). In 2015, asbestos exposure led to an estimated 23,000 mesothelioma and 155,000 lung cancer cases worldwide ( 9 ). In Malaysia, reported occupational lung disease cases rose from 86 in 2015 to 150 in 2016. The 2023 DOSH report notes 78 cases of occupational disease and injury among quarry workers, with only 2.6% due to lung disease. Despite significant construction hazards, reported lung disease cases remain low ( 10 , 11 ). Fractional Exhaled Nitric Oxide (FeNO) is useful for monitoring respiratory health in workers exposed to airborne irritants, especially in occupational lung diseases. More sensitive than spirometry for detecting airway inflammation, FeNO is mainly used in asthma management but also helps diagnose COPD and other lung conditions ( 12 ). Introducing FeNO into routine medical examinations in the workplace and employing it alongside spirometry, particularly Forced Expiratory Volume in one second (FEV1). A study by Lim et al. found that 9.6% of office workers had asthma, with mild FeNO elevations (> 25 ppb) in 25.8% of cases ( 13 ). FeNO has not been studied in relation to occupational lung disease among Malaysian quarry workers. The primary objective of this study was to ascertain FeNO levels among quarry workers utilizing a portable Niox® Vero hand-held analyser (Aerocrine AB, Solna, Sweden): categorized as low ( 50 ppb) ( 14 ). Secondary objectives included determining the prevalence of occupational lung disease and common respiratory symptoms. We also aimed to assess ventilatory capacity (FEV1 and FVC) following the 2019 American Thoracic Society (ATS) Consensus (ranging from normal to very severe impairment) through portable spirometry and to determine the type of ventilatory defect (e.g., obstructive ventilatory defect, preserved ratio impaired spirometry (PRISm), and restrictive ventilatory defect) ( 15 ). The study sought to establish correlations between occupational lung disease, severity of lung impairment, and FeNO levels, alongside evaluating worker compliance with safety protocols and safe work practices through a validated questionnaire. 2. Materials and Methods 2.1 Study Design This cross-sectional study was conducted in collaboration with Negeri Roadstone Sdn. Bhd. from October 2022 to October 2024, aims to assess respiratory health among quarry workers. Negeri Roadstone Sdn. Bhd. specializes in extracting and producing quarry materials for construction and infrastructure projects, primarily stone and gravel. Written informed consent was obtained from all participants before enrolment, per international guidelines, and the study received approval from the Research Ethics Committee of Universiti Kebangsaan Malaysia (FF-2022-332). Demographic data were collected from participants, followed by a modified British Medical Research Council (BMRC) Questionnaire translated into Malay with permission (Supplementary file 1). The questionnaire obtained information on respiratory symptoms, smoking status, occupational history, dust exposure, and mask usage frequency. Chest radiographs taken within the previous three months were then reviewed. After this, FeNO testing and portable lung function assessments were performed. The study also assessed participants’ adherence to respirator use. Individuals with abnormal results on initial lung function screening underwent further evaluation, which included comprehensive lung function tests and High-Resolution Computed Tomography (HRCT) of the thorax. Portable lung function testing was repeated yearly to monitor for any progression. 2.2 Participants The research was conducted among all personnel employed at the quarry site, encompassing administrative staff and site workers. Their supervisor approached them to partake in the study via email, telephone, or internal memorandum. Informed consent to participate was obtained from all participants in the study. 2.3 Eligibility Employees were deemed eligible if they exceeded 18 years of age and demonstrated the capability to perform spirometry and FeNO tests. Exclusion criteria included the inability or unwillingness to provide consent, a recent upper or lower respiratory tract infection within the preceding two weeks, and the presence of contraindications for spirometry. These contraindications encompass recent cardiac events, major surgical procedures, severe respiratory conditions, or cognitive and neurological impairments ( 15 – 17 ). 2.3 Sample size The calculation of our sample size was conducted utilizing Statulator. ' The sample size was estimated through an online sample size calculator designed for a single proportion, with a projected prevalence of occupational lung disease at 30%, derived from the average range of 15–30% as indicated by prior studies ( 18 , 19 ). The total population was approximated at 100,000, incorporating a 10% margin of error, a 95% confidence interval, and a design effect (DEFF) of 1 ( 20 ). Consequently, the calculated requisite sample size amounted to 81. 2.4 Measures 2.4.1 Demographic and Questionnaire: The participants were interviewed using a validated and modified BMRC Questionnaire (Supplementary 1) ( 21 ). The questionnaire was translated into Malay, pre-tested, and administered by trained interviewers (Supplementary file 2) to reduce recall bias ( 22 ). The corresponding author granted authorization to utilize the questionnaire, which was used for a prior study ( 22 ). The questionnaire encompassed respiratory symptoms, medical history, smoking habits, occupational history, dust exposure, and the utilization of masks. Following the collection of demographic information (age, sex, smoking status, comorbidities) and responses, a fundamental physical examination was conducted, which included the assessment of body mass index (BMI), blood pressure, heart rate, oxygen saturation, and a chest examination. 2.4.2 FeNO and Portable Spirometry FeNO measurements (in ppb) were conducted once by a trained technician utilizing the NIOX® VERO electrochemical handheld analyzer, adhering to the protocol established by the American Thoracic Society (ATS) and the European Respiratory Society (ERS) ( 14 , 23 ). The technician provided the breathing handle to the participant, who was instructed to completely exhale to evacuate the lungs before positioning the handle in the mouth, ensuring a proper seal. Subsequently, the participant was requested to inhale deeply through the filter, following guidance from on-screen animations. Upon prompting from the machine, the participant exhaled steadily for 10 seconds, as indicated by the NIOX® Panel animations. If the procedure was executed correctly, a FeNO report was generated. Participants exhibiting abnormal FeNO levels (intermediate or high; FeNO > 25 ppb) and those diagnosed with obstructive ventilatory defects, including a known diagnosis of asthma, were subjected to a bronchodilator reversibility test. Participants with normal FeNO levels underwent spirometry only. Before the FeNO and spirometry procedures, a Rapid Test Kit-Antigen (RTK-Ag) test was conducted on-site to ensure safety. Spirometry was performed biannually, while FeNO was measured once, and a trained respiratory technician conducted both procedures. Spirometry was performed using the SpiroUSB (CareFusion Germany 23X) in accordance with ATS/ERS guidelines ( 15 ). The technician ensured the participant's proper positioning, nose clip placement, and lips sealing around the mouthpiece. Participants were required to execute a minimum of three exhalations, with a maximum of eight permitted, based on the quality of the test. Each exhalation had to last at least six seconds, with results deemed acceptable if the difference between the two best readings was less than 5% or 150 milliliters ( 15 ). To mitigate the risk of COVID-19 transmission, participants were required to undergo an RTK-Ag test the same day before the FeNO and spirometry procedures. Additional protective measures included the utilization of level 3 PPE and disposable mouthpieces. 2.4.3 Further Testing (HRCT, Full lung function test) Individuals exhibiting abnormal lung function (PRISm) subsequently underwent a comprehensive lung function assessment, followed by a High-Resolution Computed Tomography (HRCT) of the thorax utilizing the TOSHIBA Aquilion One (640-slice) CT scanner to evaluate potential structural abnormalities. A thoracic radiologist interpreted the HRCT images. Participants were subjected to an additional comprehensive lung function assessment when abnormalities were identified in the chest radiograph or prior lung function evaluations. The lung function evaluation was conducted using the Vmax™ Autobox System from Vyaire Medical, United States, in accordance with the guidelines set forth by the American Thoracic Society (ATS) and the European Respiratory Society (ERS) ( 15 ). Throughout the procedure, all participants were closely monitored by a qualified respiratory technician. Before undergoing the comprehensive lung function assessment, each participant had a complete blood count performed by a trained phlebotomist to ensure accurate gas transfer values to hemoglobin, as these values can significantly affect the interpretation of lung function results. Additionally, all participants were required to complete a Rapid Test Kit-Antigen (RTK-Ag) on the same day as the procedure. 2.4.4 Data collection and Interpretation: Statistical analyses were performed utilizing the IBM Statistical Package for Social Sciences (SPSS) version 29.0 (IBM Corp., Armonk, NY, USA). Descriptive statistics were reported as mean and SD, number, and percentages. All statistical tests were two-tailed, with a significance threshold established at p < 0.05. A paired t-test was employed to compare the 1-year follow-up assessment. Multiple linear regression was applied to analyse variables related to FeNO and lung function tests, including FEV1, FVC, BMI, symptoms, compliance with respirator, and the correlation among the data. A probability value less than p < 0.05 was considered statistically significant. Individuals with confirmed occupational lung disease will be referred to the Department of Occupational Safety and Health (DOSH). 2.5 Operational Terms Definition 2.5.1 Occupational lung disease Occupational lung diseases, commonly referred to as work-related lung diseases, encompass a range of conditions that either develop or are exacerbated by prolonged exposure to specific irritants in the workplace. These irritants include dust particles, chemicals, fungal spores, and specific animal excretions, all of which can heighten the risk of developing occupational lung illnesses. Examples of such diseases include occupational asthma, chronic obstructive pulmonary disease (COPD), coccidioidomycosis, hypersensitivity pneumonitis, histoplasmosis, pneumoconiosis, and mesothelioma. In the context of our study, an individual is considered to have an occupational lung disease if they fulfill any of the following criteria: i) the presence of an obstructive ventilatory defect in spirometry with no known respiratory illness or significant smoking history (defined as fewer than 20 pack-years); ii) individuals with a known respiratory illness, such as asthma or COPD, who encounter exacerbated symptoms due to workplace exposure; iii) a restrictive pattern observed on a comprehensive lung function test, accompanied by characteristic high-resolution computed tomography (HRCT) thorax features indicative of a specific pattern of occupational lung disease or pneumoconiosis; iv) an inter-visit variability of FEV1 exceeding 200 mls and 12%, which suggests asthma. 2.5.2 Impaired Lung Function Individuals exhibiting impaired lung function may present with various conditions, including both obstructive and restrictive ventilatory defects, as well as PRISm. An obstructive ventilatory defect is characterized by an FEV1/FVC ratio of less than 0.7, or 70%. PRISm, conversely, is defined as an FEV1/FVC ratio greater than 0.7 or 70%, accompanied by an FVC below 80% of the predicted value, per ATS guidelines ( 15 ). Restrictive ventilatory defects are characterized by a reduction in TLC that falls below the 5th percentile of the predicted value, or less than 80% of the predicted value, coupled with a normal FEV1/FVC ratio ( 15 ). A mixed pattern of ventilatory defects is characterized by a decrease in TLC below the 5th percentile of the predicted value, or less than 80% of the predicted value, along with a reduced FEV1/FVC ratio ( 15 ). 2.5.3 Respiratory symptoms Common respiratory symptoms in occupational lung disease include cough, sputum production, wheezing, breathlessness or shortness of breath, and chest tightness. 2.5.4 FeNO values A low FeNO (< 25 ppb in adults): Eosinophilic airway inflammation is infrequently observed in symptomatic adult patients exhibiting a FeNO of less than 25 ppb. This threshold is substantiated by data from several studies, including those conducted by Shaw et al. and Porsbjerg et al., as well as investigations aimed at utilizing FeNO measurements for asthma diagnosis and studies designed to optimize the use of inhaled corticosteroids (ICS) ( 14 , 24 – 27 ). High FeNO (> 50 ppb in adults): Substantial airway eosinophilia is likely indicated by elevated FeNO ( 14 , 23 ). It may also imply that a symptomatic patient possesses inflamed, steroid-responsive airways ( 24 , 28 – 30 ). The findings of practical studies provided the basis for the clinically significant threshold of 50 ppb. Intermediate FeNO (in adults, between 25–50 ppb): The data indicate that a cautious interpretation is warranted for FeNO levels ranging from 25 to 50 ppb ( 14 , 23 , 31 ). In instances where a patient is being monitored longitudinally, or if the patient's FeNO has fluctuated from a previous assessment by what is considered a clinically significant degree, the importance ascribed to a FeNO result within this range will be contingent upon whether the test is employed as a diagnostic instrument in a symptomatic and steroid-naive individual ( 14 , 23 , 31 ). 2.5.5 Control Measures and Personal Protective Equipment (PPE) Personal protective equipment (PPE) for quarry workers refers to the specialized clothing or gear worn to protect individuals from workplace hazards and risks inherent in the quarrying environment. These hazards include dust, noise, falling debris, and heavy machinery exposure. In this study, we collected data on compliance with respirators and dust mask utilization for PPE adherence, as our focus was solely on evaluating occupational lung disease. 3. Results Using a universal sampling method, we initially recruited 110 participants from the quarry, including both administrative and site workers. Three participants were excluded from the follow-up visit, leaving 107 for the final analysis. The administrative group was included due to the office's proximity to the quarry, which is less than one kilometre away, thereby exposing them to a significant dust risk. The study flow can be seen in Figure 1 (CONSORT flow chart). The characteristics of the participants (Table 1) indicated that 88.1% (n=52) were male and 11.9% (n=7) were female in the site population group. In the administrative group, 33.3% (n=16) of participants were male, while 66.7% (n=32) were female. The median age of the workers was 32 (27-37) years; the site group had a median age of 34 (28-40) years, and the administrative group had a median age of 31 (26-34.75) years. The median BMI of the workers was 27 (22.7-30.2) kg/m²; the site workers group had a median BMI of 27 (21.8-28.6) kg/m², while the administrative group had a median BMI of 26.9 (23.3-31.8) kg/m². All participants had over one year of work experience, with the median years of exposure to dust being 3 (1-11) years for all workers; 3 (2-10.75) years for site workers, and 2 (1-9.75) years for administrative workers. The years worked correlate with years of exposure to dust. The site population group was exposed to dust for 7-8 hours per day (45.8%), while the administrative population was exposed for 1-2 hours per day (39.8%). The mean smoking pack-years for smokers was 14.49± 9; site workers had 15.17 ± 9.6 pack years, and the administrative group had 11.78 ± 5.8 pack years. All male workers in both groups smoked, while no female workers did. The most frequently reported symptom was shortness of breath, affecting 27 employees (25.2%). In the site group, 14 out of 59 workers (23.7%), and in the administrative group, 13 out of 48 workers (27.1%), indicated the presence of this symptom. A significant number of participants also reported experiencing coughing (n=17, 15.9%), with 12 out of 59 in the site group (20.3%) and five out of 48 in the administrative group (10.4%) encountering this symptom. Chest tightness or pain was noted in 21 participants (19.6%), which included 11 out of 59 site workers (18.6%) and 10 out of 48 administrative staff members (20.8%). Moreover, a notably higher percentage of site workers (15.3%) reported a deterioration in respiratory symptoms over the past three months, compared to only 6.3% in the administrative group. The mean FEV1% was 78.63%: the site group at 77.95% and the administrative group at 79.46%. The mean FVC was 78.63%, with site workers at 79.08% and administrative staff at 80%. Overall, 73 participants (68.2%) had normal spirometry results: site workers n=38 (64.4%) and administrative group n=35 (73%). An obstructive ventilatory defect pattern was observed in seven participants (6.6%): site group n=5 (8.5%) and administrative group n=2 (4.2%). A PRISm ventilatory defect pattern was seen in 27 participants (25.2%): site group n=16 (27.1%) and administrative group n=11 (22.9%). Only one participant exhibited notable reversibility in post-bronchodilator response (FEV1 >12% and 200 ml improvement). The results also indicate that most workers have low FeNO levels (50) comprise 13.5% of site workers and 22.9% of administrative workers. The mean FeNO level is higher among the administrative group, at 22 (13-40), compared to the site group, at 18 (11-32). A comparison of FeNO levels observed in both groups shows a similar distribution. Participants with normal spirometry results predominantly exhibited normal FeNO levels (50 ppb). Employees with obstructive ventilatory defects represented 6.6%, with most showing intermediate FeNO levels at 3.7% and low FeNO levels at 2.8%. None of the participants with obstructive ventilatory defects exhibited high FeNO. Among those with PRISm (25.2%), the majority displayed normal FeNO levels (13.1%), followed by intermediate levels (3.7%). Furthermore, 8.4% of the overall population with PRISm had high FeNO levels. A comparison of baseline spirometry with repeat spirometry was conducted after a one-year follow-up, utilizing a paired t-test for the comparative analysis. The results indicated that the p-values for FVC, FEV1, and FEV1/FVC in both groups exceeded 0.05, suggesting no statistically significant difference. Furthermore, three participants (2.8%) demonstrated inter-visit variability exceeding 200 ml and a 12% difference between visits. Table 1: Demographic, spirometry, and FeNO results All staff ( n =107) Group p -value Site worker ( n =59) Administrative Staff ( n =48) Gender: Male Female 68 (63.6%) 39 (36.4%) 52 (88.1%) 7 (11.9%) 16 (33.3%) 32 (66.7%) 50 Median (IQR) 29 (36.4%) 46 (43%) 12 (11.2%) 10 (9.3%) 32 (27-37) 17 (28.8%) 27 (45.7) 10 (16.9%) 5 (8.5%) 34 (28-40) 22 (45.8%) 19 (39.6%) 2 (4.2%) 5 (10.4%) 31 (26-34.75) 0.058 BMI (kg/m²) Underweight (30) Median (IQR) 5 (4.7%) 22 (20.6%) 11 (10.3%) 42 (39.3%) 27 (25.2%) 27 (22.7-30.2) 5 (8.5%) 13 (22%) 4 (6.8%) 27 (45.8%) 10 (16.9%) 27 (21.8-28.6) 0 (0%) 9 (18.7%) 7 (14.6%) 15 (31.3%) 17 (35.4%) 26.9 (23.3-31.8) 0.027 Work experience (years) 10 years Median (IQR) 28 (26.2%) 33 (30.8%) 19 (17.8%) 27 (25.2%) 3 (1-11) 7 (11.9%) 26 (44.1%) 6 (10.2%) 20 (33.8%) 3 (2-10.75) 21 (43.7%) 7 (14.6%) 13 (27.1%) 7 (14.6%) 2 (1-9.75) 0.348 Hours per day exposed to dust None 1-2 hours per day 3-4 hours per day 5-6 hours per day 7-8 hours per day Mean ± SD 5 (4.7%) 31 (29%) 20 (18.7%) 15 (14%) 36 (33.6%) 3.43 ± 1.34 0 (0%) 12 (20.3%) 12 (20.3%) 8 (13.5%) 27 (45.8%) 2.92 ± 1.32 5 (10.4%) 19 (39.6%) 8 (16.7%) 7 (14.6%) 9 (18.7%) 4.14 ±1.15 <0.01 Symptoms Cough Sputum production Shortness of breath Wheeze Chest tightness Worsening symptoms past 3 months 17 (15.9%) 8 (7.5%) 27 (25.2%) 14 (13.1%) 21 (19.6%) 12 (11.2%) 12 (20.3%) 5 (8.5%) 14 (23.7%) 7 (11.9%) 11 (18.6%) 9 (15.3%) 5 (10.4%) 3 (6.3%) 13 (27.1%) 7 (14.6%) 10 (20.8%) 3 (6.3%) 0.166 0.667 0.694 0.682 0.779 0.145 Cigarette smoking No Yes 1-5 pack years 6-10 pack years 11-15 pack years 16-20 pack years > 20 pack years Mean ± SD Smoking status by gender Male Female 62 (57.9%) 5 (4.7%) 14 (13.1%) 9 (8.4%) 8 (7.5%) 9 (8.4%) 14.49± 9 45 (100%) 0 (0%) 23 (39%) 4 (6.8%) 14 (23.7%) 7 (11.9) 10 (16.9%) 1 (1.7%) 15.17 ± 9.6 36 (100%) 0 (0%) 39 (81.3%) 1 (2.1%) 5 (10.4%) 1 (2.1%) 1 (2.1%) 1 (2.1%) 11.78 ± 5.8 9 (100%) 0 (0%) <0.01 Compliance to Respirator/ Face Mask Occasional Frequently All the time 58 (52.3%) 30 (28%) 21 (19.6%) 34 (57.6%) 15 (25.4%) 10 (16.9%) 22 (45.8%) 15 (31.3%) 11 (22.9%) FVC Severity % predicted Normal (>80%) Mild (70-79%) Moderate (60-69%) Moderate Severe (50-59%) Severe (35-49%) Very severe (80%) Mild (70-79%) Moderate (60-69%) Moderate Severe (50-59%) Severe (35-49%) Very severe ( 12% and 200ml improvement) Spirometry Interpretation Normal pattern Obstructive pattern PRISm pattern 58 (54.2%) 29 (27.1%) 17 (15.9%) 1 (0.9%) 2 (1.9%) 0 (0%) 78.63 ± 12.73 57 (53.3%) 25 (23.4%) 18 (16.8%) 5 (4.7%) 1 (0.9%) 1 (0.9%) 78.63 ±12.74 1 (0.9%) 73 (68.2%) 7 (6.6%) 27(25.2%) 31 (52.5%) 18 (30.5%) 8 (13.5%) 1 (1.7%) 1 (1.7%) 0 (0%) 79.08 ± 11.46 29 (49.2%) 16 (27.1%) 10 (16.9%) 3 (5.1.%) 0 (0%) 1 (1.7%) 77.95 ± 12.13 0 (0%) 38 (64.4%) 5 (8.5%) 16 (27.1%) 28 (58.3%) 9 (18.8%) 8 (16.7%) 2 (4.2%) 1 (2.1%) 0 (0%) 80 ± 12.34 27 (55.3%) 11 (22.9%) 9 (18.8%) 0 (0%) 1 (2.1%) 0 (0%) 79.46 ± 13.53 1 (2.1%) 35 (73%) 2 (4.2%) 11 (22.9%) 0.692 0.543 0.365 FeNO Low (50 ppb) Median (IQR) 61 (57%) 27 (25.2%) 19 (17.8%) 20 (13-35) 35 (59.3%) 16 (27.1%) 8 (13.5%) 18 (11-32) 26 (54.2%) 11 (22.9%) 11 (22.9%) 22 (13-40) 0.429 Normal Spirometry FeNO 50 ppb Obstructive Spirometry FeNO 50 ppb PRISm Spirometry FeNO 50 ppb 73 (68.2%) 44 (41.1%) 19 (17.8%) 10 (9.3%) 7 (6.6%) 3 (2.8%) 4 (3.7%) 0 (0%) 27 (25.2%) 14 (13.1%) 4 (3.7%) 9 (8.4%) 38 (64.6%) 23 (39.0%) 9 (15.3%) 4 (6.8%) 5 (8.5%) 3 (5.1%) 2 (3.4%) 0 (0%) 16 (27.1%) 9 (15.3%) 3 (5.1%) 4 6.8%) 35 (72.9%) 21 (43.8%) 8 (16.7%) 6 (12.5%) 2 (4.2%) 0 (0%) 2 (4.2%) 0 (0%) 11 (22.9%) 5 (10.4%) 1 (2.1%) 5 (10.4%) Variables in the follow-up visit 1 year time Baseline 1 year Mean Difference t p -value Site Group FVC (L) FEV1 (L) FEV1/FVC % Admin Group FVC (L) FEV1 (L) FEV1/FVC % 3.44 ± 0.7 2.83 ± 0.6 82.4 ± 6.8 2.96 ± 0.7 2.50 ± 0.6 84.4 ± 4.7 3,47 ± 0.7 2.82 ± 0.6 81.7 ± 7.1 3.00 ± 0.7 2.51 ± 0.6 83.8 ± 4.8 -0.292 0.002 0.711 -0.040 -0.012 0.583 -1.834 0.153 1.917 -2.371 -0.608 0.975 0.864 0.072 0.060 0.022 0.546 0.355 Variable Total n (%) Site worker Administrative staff Inter-visit Variability 200mls and 12% (n) 3 (2.8%) 1 (1.7%) 2 (4.2%) Bold indicates statistically significant. Table 1 indicates that 25% (n = 27) of participants showed a PRISm pattern. Of these, 18 underwent further lung function tests and HRCT thorax at HCTM. Among them, one had a purely restrictive defect, one had a mixed pattern, most (55.6%) had normal lung function, and 33.3% displayed an obstructive pattern. Most participants had normal chest radiographs. However, a higher proportion in the site group (33.9%) had minimal opacities, with one case of past pulmonary tuberculosis (PTB), compared to 6.3% in the administrative group. This may be due to greater dust exposure and heavier smoking among site workers. These participants were subsequently evaluated at HCTM, where a full lung function test was conducted to assess TLC and DLCO, alongside an HRCT of the thorax to identify any CT characteristics suggestive of occupational lung disease or pneumoconiosis, which is shown in Table 2. Among them, one had a purely restrictive defect, one had a mixed pattern, most (55.6%) had normal lung function, and 33.3% displayed an obstructive pattern. HRCT findings were mostly normal: five site group members (45.5%) and six administrative group members (85.7%). Sub-centimetre nodules appeared in four site group members; minimal mosaic attenuation was seen in one participant from each group. One participant had signs of previous PTB, acquired while working there a year earlier. Further evaluation diagnosed occupational lung disease in 5.6% (n = 6) of quarry workers, a lower prevalence than the reported average of 8-13% (32, 33). A detailed review of the six patients with occupational lung disease revealed the following profiles: The first, a 47-year-old male site worker (15 years’ experience, BMI 28.5 kg/m², 18 pack-years) with asthma, showed a post-bronchodilator obstructive spirometry pattern and low FeNO; HRCT was largely unremarkable. Improvement in FEV1 supported a diagnosis of asthma with pollutant exposure. The second, a 29-year-old female administrator (2 years, BMI 33.8 kg/m²), had new-onset cough and dyspnoea, intermediate FeNO (31 ppb), obstructive but non-reversible spirometry, and normal HRCT—suggesting possible occupational asthma. The third, a 35-year-old female (10 years, BMI 27 kg/m²), a non-smoker, presented with moderate, non-reversible obstruction and FeNO of 29 ppb; HRCT was normal, indicating probable pollutant-induced COPD. The fourth, a 33-year-old male (2 years, BMI 17.2 kg/m², 10 pack-years) with prior PTB, had intermediate FeNO (33 ppb), mixed spirometry findings, and HRCT showing early silicosis and residual PTB changes. Additionally, a 51-year-old female administrator (30 years, BMI 22.5 kg/m²) and a 27-year-old female administrator (1 year, BMI 31.6 kg/m²), both non-smokers, showed significant FEV1 variability suggestive of occupational asthma. Neither had elevated FeNO nor HRCT abnormalities. Table 2: Full lung function assessment, imaging, and Correlations Pulmonary Function and Imaging Assessments All staff ( n =18) Site worker ( n =11) Administrative Staff ( n =7) Full Lung Function Test FVC (L) FVC % TLC (L) TLC % DLCO mL/mmHg/min DLCO 3.07 ± 0.74 71.72± 11.7 5.42 ± 1.58 96.22 ± 21.4 20.69 ± 5.2 83.11 ±18.9 3.07 ± 0.35 72.64 ± 8.7 5.62 ± 1.34 100.73 ± 24.5 21.0 ± 4.57 90.0 ±19.1 3.07 ± 1.15 70.29 ± 16.2 5.10 ± 1.96 89.14 ± 14.3 20.21± 6.45 72.29 ±13.6 Full Lung Function Interpretation Normal Restrictive ventilatory disorder Obstructive ventilatory disorder Mixed ventilatory disorder 10 (55.6%) 1 (5.6%) 6 (33.3%) 1 (5.6%) 6 (54.5%) 0 (0%) 4 (36.4%) 1 (9.1%) 4 (57.1%) 1 (14.3%) 2 (33.3%) 0 (0%) Chest Radiograph Normal Minimal Opacities Large Opacities Cardiomegaly Old PTB changes 79 (73.8%) 23 (21.5%) 0 (0%) 4 (3.7%) 1 (0.9%) 36 (61%) 20 (33.9%) 0 (0%) 2 (3.4%) 1 (1.7%) 43 (89.6%) 3 (6.3%) 0 (0%) 2 (4.1%) 0 (0%) HRCT Thorax Normal Single Sub-centimetre nodule Mosaic attenuation Old PTB changes 11 (0.9%) 4 (22.2%) 2 (11.1%) 1 (5.6%) 5 (45.5%) 4 (36.4%) 1 (9.1%) 1 (9.1%) 6 (85,7%) 0 (0%) 1 (14.3%) 0 (0%) Manifestation of occupational lung disease Obstructive ventilatory defect, with no significant smoking history Known Respiratory illness with worsening symptoms Restrictive ventilatory defect from full Lung function test with HRCT Thorax HRCT thorax features of specific pattern of occupational lung disease or pneumoconiosis Normal spirometry with inter-visit variability (FEV1 >200ml and >12%) Total: 2(1.9%) 1 (0.9%) 1 (0.9%) 0 (0%) 2(1.9%) 6 (5.6%) 0 (0%) 1 (1.7%) 1 (1.7%) 0 (0%) 0 (0%) 2 (3.4%) 2 (4.2%) 0 (0%) 0 (0%) 0 (0%) 2 (4.2%) 4 (8.3%) Figure 2 shows a significant negative correlation between years of dust exposure and both FVC (r = -0.314, p < 0.01) and FEV1 (r = -0.347, p < 0.01), but not with FeNO (r = -0.084, p = 0.392). Table 3: Multilinear regression analysis of occupational lung disease on predictors. The results indicate that there is generally no significant correlation between occupational lung disease and FeNO, cigarette pack years, duration of dust exposure, symptoms, compliance with respirator use, or BMI. Notably, only cough symptoms demonstrate a significant association with occupational lung disease among site workers. Table 3: Multilinear regression analysis of occupational lung disease on predictors All staff ( n =107) Site worker ( n =59) Administrative Staff ( n =48) Stand B t static P- value Stand B t static P- value Stand B t static P - value Constant -0.825 0.411 -0.442 0.661 0.144 0.887 FeNO level 0.055 0.565 0.573 0.006 0.045 0.964 0.010 0.060 0.952 Cigarette Pack Years 0.022 0.222 0.825 0.150 1.155 0.254 -0.073 -.439 0.663 Compliance to the respirator 0.138 1.449 0.151 0.242 1.947 0.057 0.002 0.014 0.989 Years exposed to dust -0.010 -0.101 0.920 0.049 0.385 0.702 -0.033 -0.185 0.854 Symptom: Cough 0.178 1.797 0.075 0.438 3.351 0.002 -0.023 -0.124 0.902 Symptom: Shortness of breath 0.120 1.244 0.216 0.062 0.491 0.625 -0.106 -0.565 0.575 Symptom: Increased Sputum -0.162 -1.592 0.115 -0.208 -1.540 0.130 -0.047 -0.281 0.780 BMI -0.03 -0.035 0.972 -0.017 -0.128 0.898 0.040 0.240 0.812 Statistically significant if p <0.05 Discussion Our assessment indicated that the participants had three years of median dust exposure (range: 1–11). Shortness of breath was the most frequently reported symptom, followed by chest tightness and cough. The prevalence of dyspnoea in this study exceeded that reported in India (14.6%) and Nigeria (6.5%), where cough predominated and shortness of breath was less common (16.7% in India; 40.7% in Nigeria) ( 18 , 36 ). Although spirometry was normal in this study, 27.1% of participants exhibited impaired FeNO, suggesting possible eosinophilic airway inflammation or occupational asthma. A FeNO increase greater than 50% from baseline may indicate uncontrolled inflammation, which is relevant for diagnosing occupational asthma. ( 14 , 23 ). However, repeated FeNO testing was not performed due to financial limitations, as it remains costly in Malaysia Our analysis identified only six participants (5.6%) with evidence of occupational lung disease, and just one abnormal HRCT thorax result. This prevalence is notably lower than reports from studies in Australia (28.2%) and India (31.39%) ( 19 , 37 ). In comparison to the 2.6% incidence of occupational lung disease reported by the Department of Occupational Safety and Health (DOSH) Malaysia in 2023, our results align with this lower prevalence, which may be due to the strict regulations regarding respirator compliance and the policies implemented by the National Institute for Occupational Safety and Health (NIOSH) and the employing company aimed at preventing occupational lung disease. The study additionally reveals a significant negative correlation between the duration of exposure (in years) and both forced vital capacity (FVC) and forced expiratory volume in one second (FEV1), corroborating findings from a prior study conducted in India that reported a comparable negative correlation ( 34 ). Furthermore, an observed negative correlation exists with fractional exhaled nitric oxide (FeNO), although this is considered non-significant. This indicates that prolonged exposure to dust within the quarry environment may ultimately contribute to the development of occupational lung disease after ten years or more, thereby emphasizing the importance of safety protocols and the use of PPE to prevent future complications. Our study noted a non-significant negative correlation between cigarette pack-years and FeNO. This finding is consistent with numerous global studies that likewise report a comparable negative correlation between pack-years of smoking and FeNO. Our study's absence of statistical significance may be attributed to the relatively small sample size compared to studies conducted by Persson et al ( 38 ). We also found no significant association between occupational lung disease, FeNO, cigarette pack-years, or PPE compliance. The limited number of diagnosed cases with occupational lung disease likely reduced statistical power. A larger sample size may reveal stronger associations. In this study, occupational lung disease is diagnosed in individuals who exhibit characteristics of obstructive spirometry in the absence of a significant history of respiratory illness or smoking (defined as fewer than 20 pack-years). These individuals may also possess pre-existing respiratory conditions such as asthma or chronic obstructive pulmonary disease (COPD), with exacerbated symptoms attributed to workplace exposure, or demonstrate a restrictive pattern upon comprehensive lung function tests, accompanied by high-resolution computed tomography (HRCT) findings indicative of occupational lung disease or pneumoconiosis. Participants presenting with obstructive ventilatory defects and notable smoking histories were excluded from the diagnosis of occupational lung disease, as the obstructive pattern is likely associated with smoking (COPD) or lifestyle factors rather than occupational exposure. This exclusion criterion applies to numerous male participants with significant smoking histories in both groups. Further analysis showed that none of the six workers diagnosed with occupational lung disease had FeNO levels above 50 parts per billion (ppb). These results indicate that FeNO testing may have limited applicability in diagnosing occupational lung disease; however, it remains a valuable tool for assessing asthma and airway inflammation due to its association with methacholine hyperresponsiveness. Studies have also demonstrated that consistently high FeNO levels are associated with a more rapid decline in lung function among patients with asthma. ( 12 ). According to OSHA's Respirable Crystalline Silica Rule, employers must keep silica dust levels below the permissible exposure limit (PEL) of 50 µg/m³ averaged over an eight-hour workday ( 39 ). This limit protects workers from the long-term health effects of silica exposure, particularly during mining processes involving quartz. The Mine Safety and Health Administration (MSHA) enforces a Permissible Exposure Limit (PEL) of 100 µg/m³ for respirable quartz. At the same time, a proposed regulation seeks to align this limit with OSHA's standards ( 39 ). To lower silica exposure in quarries, measures include maintaining engineering controls, using wet methods and local exhaust ventilation, isolating work processes with enclosures, integrating water and ventilation systems, following filter replacement protocols, avoiding dry sweeping or compressed air during cleaning, conducting air monitoring, providing properly fitted personal protective equipment (PPE) such as N95 respirators, informing workers about silica-related risks and safe practices, creating an exposure control plan, rotating job assignments, and performing routine equipment maintenance ( 39 , 40 ). A key limitation of this study is the absence of repeated FeNO testing during follow-up, which may have provided additional insight into changes over time but was constrained by cost considerations. The low incidence of occupational lung disease may also reflect the exclusion of participants with significant smoking histories, as their symptoms are more likely related to smoking than occupational exposure. Proper diagnosis of occupational asthma requires comprehensive monitoring, including peak flow measurements and symptom diaries, to establish a clear link to workplace exposure. Without these, whether observed respiratory variability indicates occupational lung disease or late-onset asthma remains uncertain. Increasing the sample size would enhance the statistical power to detect significant associations. Future studies should incorporate repeated FeNO testing to track changes and better identify uncontrolled airway inflammation or occupational asthma. Larger, multicentre cohorts would more accurately reflect the prevalence of occupational lung disease among quarry workers. The low incidence observed may stem from effective health and safety practices, though indirect exposures remain a concern. Enhanced engineering controls, such as HEPA filters in the workplace and consistent use of face masks or respirators, are essential to reduce risk further. Declarations Acknowledgements: The authors would like to thank the Dean of the Faculty of Medicine, Universiti Kebangsaan Malaysia, Professor Datin Dr Marina Mat Baki, for her support and encouragement. We would also like to express our gratitude to Negeri Roadstone Sdn. Bhd. for their support and the facilities to conduct this study. Author contributions: Conceptualization: MFAH. Data curation: MHAW, AAA, MFMJ, MFAH. Formal analysis: MHAW, MFAH. Project administration: MHAW, AAA, MFMJ, MFAH. Funding acquisition: MFAH. Methodology: MHAW, MFAH. Supervision: MFAH. Writing -original draft: MHAW, MFMJ, AAA. Writing, reviewing, and editing manuscripts: MFAH. All authors read and approved the final manuscript Funding: AGrant was obtained from Negeri Roadstone Sdn. Bhd. Availability of data and materials: The data set used and/or analysed during the current study is available from the corresponding author on reasonable request at [email protected] . Ethics approval and consent to participate This study was approved by the Research Ethics Committee, Universiti Kebangsaan Malaysia (FF-2022-332). This study is in accordance with the Helsinki Declaration (IV adaptation). Informed consent to participate was obtained from all participants in the study. Consent for publication: Not applicable. Competing interests: The authors declare that the research was conducted without any commercial or financial relationship that could be construed as a potential conflict of interest. References Vlahovich KP, Sood A. A 2019 update on occupational lung diseases: a narrative review. Pulmonary Therapy. 2021;7(1):75-87. Hamzah NA, Samsudin K, Abdul Samad NI. RESPIRABLE DUST EXPOSURE AND RESPIRATORY HEALTH AMONG MALE GRANITE QUARRY WORKERS IN KELANTAN, MALAYSIA. The Southeast Asian journal of tropical medicine and public health. 2023;54:11-34. MALAYSIA-Act LO. Occupational Safety and Health Act 1994. 2008. "Cole RJ. The HSE strategy for improved health in the mining industry. United Kingdom: Institution of Mining and Metallurgy, London (United Kingdom); 1996. Medium: X; Size: pp. 9-24 p. Ehrlich RI, White N, Norman R, Laubscher R, Steyn K, Lombard C, et al. Predictors of chronic bronchitis in South African adults. Int J Tuberc Lung Dis. 2004;8(3):369-76. Siracusa A, De Blay F, Folletti I, Moscato G, Olivieri M, Quirce S, et al. Asthma and exposure to cleaning products–a European A cademy of Allergy and Clinical Immunology task force consensus statement Allergy. 2013;68(12):1532-45. Stocks SJ, McNamee R, Van Der Molen HF, Paris C, Urban P, Campo G, et al. Trends in incidence of occupational asthma, contact dermatitis, noise-induced hearing loss, carpal tunnel syndrome and upper limb musculoskeletal disorders in European countries from 2000 to 2012. Occupational and environmental medicine. 2015;72(4):294-303. Blanc PD. Occupation and COPD: a brief review. Journal of Asthma. 2012;49(1):2-4. Forouzanfar MH, Alexander L, Anderson HR, Bachman VF, Biryukov S, Brauer M, et al. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. The Lancet. 2015;386(10010):2287-323. Rajavel S, Raghav P, Gupta MK, Muralidhar V. Silico-tuberculosis, silicosis and other respiratory morbidities among sandstone mine workers in Rajasthan- a cross-sectional study. PLoS One. 2020;15(4):e0230574. Singh A. The prevalence of silicosis among granite quarry workers, of the government sector, in Peninsular Malaysia. Med J Malaysia. 1977;31(4):277-80. Oțelea MR, Fell AKM, Handra CM, Holm M, Filon FL, Mijakovski D, et al. The value of fractional exhaled nitric oxide in occupational diseases – a systematic review. Journal of Occupational Medicine and Toxicology. 2022;17(1):14. Lim FL, Hashim Z, Than LTL, Md Said S, Hashim JH, Norbäck D. Respiratory health among office workers in Malaysia and endotoxin and (1,3)-β-glucan in office dust. Int J Tuberc Lung Dis. 2019;23(11):1171-7. Dweik RA, Boggs PB, Erzurum SC, Irvin CG, Leigh MW, Lundberg JO, et al. An official ATS clinical practice guideline: interpretation of exhaled nitric oxide levels (FENO) for clinical applications. Am J Respir Crit Care Med. 2011;184(5):602-15. Graham BL, Steenbruggen I, Miller MR, Barjaktarevic IZ, Cooper BG, Hall GL, et al. Standardization of Spirometry 2019 Update. An Official American Thoracic Society and European Respiratory Society Technical Statement. Am J Respir Crit Care Med. 2019;200(8):e70-e88. Kharitonov SA, Yates D, Barnes PJ. Increased nitric oxide in exhaled air of normal human subjects with upper respiratory tract infections. Eur Respir J. 1995;8(2):295-7. Grünberg K, Kuijpers EA, de Klerk EP, de Gouw HW, Kroes AC, Dick EC, et al. Effects of experimental rhinovirus 16 infection on airway hyperresponsiveness to bradykinin in asthmatic subjects in vivo. Am J Respir Crit Care Med. 1997;155(3):833-8. Nwibo AN, Ugwuja E, Nwambeke NO, Emelumadu O, Ogbonnaya L. Pulmonary Problems among Quarry Workers of Stone Crushing Industrial Site at Umuoghara, Ebonyi State, Nigeria. The international journal of occupational and environmental medicine. 2012;3:178-85. Khetan M, Babu BV. Silicosis prevalence and related issues in India: a scoping review. Journal of Occupational Medicine and Toxicology. 2025;20(1):3. Dhand N, Khatkar M. Statulator: An online statistical calculator. Sample size calculator for estimating a single proportion. 2014. Cotes JE. Medical Research Council Questionnaire on Respiratory Symptoms (1986). Lancet. 1987 Oct 31;2(8566):1028. doi: 10.1016/s0140-6736(87)92593-1. PMID: 2889937. Hamzah NA, Tamrin SBM, Ismail NH. Respiratory Health of Male Steel Workers in the Eastern Coast of Peninsular Malaysia. American Journal of Applied Sciences. 2015;12(5). Society AT. ATS/ERS recommendations for standardized procedures for the online and offline measurement of exhaled lower respiratory nitric oxide and nasal nitric oxide. Am J Respir Crit Care Med. 2005;171:912-30. Smith AD, Cowan JO, Brassett KP, Filsell S, McLachlan C, Monti-Sheehan G, et al. Exhaled nitric oxide: a predictor of steroid response. Am J Respir Crit Care Med. 2005;172(4):453-9. Zacharasiewicz A, Wilson N, Lex C, Erin EM, Li AM, Hansel T, et al. Clinical use of noninvasive measurements of airway inflammation in steroid reduction in children. Am J Respir Crit Care Med. 2005;171(10):1077-82. Shaw DE, Berry MA, Thomas M, Green RH, Brightling CE, Wardlaw AJ, et al. The use of exhaled nitric oxide to guide asthma management: a randomized controlled trial. Am J Respir Crit Care Med. 2007;176(3):231-7. Porsbjerg C, Lund TK, Pedersen L, Backer V. Inflammatory subtypes in asthma are related to airway hyperresponsiveness to mannitol and exhaled NO. J Asthma. 2009;46(6):606-12. Szefler SJ, Martin RJ, King TS, Boushey HA, Cherniack RM, Chinchilli VM, et al. Significant variability in response to inhaled corticosteroids for persistent asthma. J Allergy Clin Immunol. 2002;109(3):410-8. Meijer RJ, Postma DS, Kauffman HF, Arends LR, Koëter GH, Kerstjens HA. Accuracy of eosinophils and eosinophil cationic protein to predict steroid improvement in asthma. Clin Exp Allergy. 2002;32(7):1096-103. Szefler SJ, Phillips BR, Martinez FD, Chinchilli VM, Lemanske RF, Strunk RC, et al. Characterization of within-subject responses to fluticasone and montelukast in childhood asthma. J Allergy Clin Immunol. 2005;115(2):233-42. Society BT, Network SIG. SIGN 158: British guideline on the management of asthma. SIGN. 2019. Awaluddin SM, Mahjom M, Lim KK, Shawaluddin NS, Tuan Lah TMA. Occupational Disease and Injury in Malaysia: A Thematic Review of Literature from 2016 to 2021. J Environ Public Health. 2023;2023:1798434. WHO. World Health Organization. Protecting workers’ health. 2017 2017 [Available from: https://www.who.int/news-room/fact-sheets/detail/protecting-workers'-health. Kutty K, Shankar V, Raghuramaiah S. Effects of Prolonged Silica Exposure on Pulmonary Function Among Stone Quarry Workers in South India. International Journal of Health Sciences and Research. 2023;Volume 13:322-31. Darbà J, Ascanio M, Syk J, Alving K. Economic evaluation of the use of FeNO for the diagnosis and management of Asthma patients in primary care in Sweden. ClinicoEconomics and Outcomes Research. 2021:289-97. Arumugam E, Rajkumar P, Dhanaraj B, Govindasamy E, Jaganathasamy N, Mathiyazhakan M, et al. Determining pulmonary function and the associated risk factors among stone quarry workers in a suburban area of Chennai, Tamil Nadu, India. Lung India. 2021;38(6):558-63. Hoy RF, Dimitriadis C, Abramson M, Glass DC, Gwini S, Hore-Lacy F, et al. Prevalence and risk factors for silicosis among a large cohort of stone benchtop industry workers. Occup Environ Med. 2023;80(8):439-46. MG P. Single-breath nitric oxide measurements in asthmatic patients and smokers. Lancet. 1994;343:133-5. Safety O, Administration H. Small entity compliance guide for the respirable crystalline silica standard for general industry and maritime. Washington, DC: Occupational Safety and Health. 2017. Gottesfeld P, Tirima S, Anka SM, Fotso A, Nota MM. Reducing Lead and Silica Dust Exposures in Small-Scale Mining in Northern Nigeria. Ann Work Expo Health. 2019;63(1):1-8. Additional Declarations No competing interests reported. Supplementary Files supplementaryfile1copy.docx supplementaryfile2.docx 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-7497811","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":517886774,"identity":"b4bc7dce-059e-45a2-8346-e67edfedd94a","order_by":0,"name":"Muhammad Haziq Abdul Wahab","email":"","orcid":"","institution":"Hospital Canselor Tuanku Muhriz, Universiti Kebangsaan Malaysia","correspondingAuthor":false,"prefix":"","firstName":"Muhammad","middleName":"Haziq Abdul","lastName":"Wahab","suffix":""},{"id":517886775,"identity":"71609d5d-0ca0-4a50-98b9-7c219ff50fa9","order_by":1,"name":"Mas Fazlin Mohamad Jailaini","email":"","orcid":"","institution":"Hospital Canselor Tuanku Muhriz, Universiti Kebangsaan Malaysia","correspondingAuthor":false,"prefix":"","firstName":"Mas","middleName":"Fazlin Mohamad","lastName":"Jailaini","suffix":""},{"id":517886776,"identity":"7ea080d3-ff2d-43be-9b3c-d1a9e36c73c6","order_by":2,"name":"Azat Azrai Azmel","email":"","orcid":"","institution":"Hospital Canselor Tuanku Muhriz, Universiti Kebangsaan Malaysia","correspondingAuthor":false,"prefix":"","firstName":"Azat","middleName":"Azrai","lastName":"Azmel","suffix":""},{"id":517886777,"identity":"581cc875-b385-4bb8-bc25-a86f35488d6d","order_by":3,"name":"Mohd Imree Azmi","email":"","orcid":"","institution":"Hospital Canselor Tuanku Muhriz, Universiti Kebangsaan Malaysia","correspondingAuthor":false,"prefix":"","firstName":"Mohd","middleName":"Imree","lastName":"Azmi","suffix":""},{"id":517886778,"identity":"9d2e9f8a-1084-4b9e-9827-6f7cb4b90fe6","order_by":4,"name":"Nazarudin Safian","email":"","orcid":"","institution":"Hospital Canselor Tuanku Muhriz, Universiti Kebangsaan Malaysia","correspondingAuthor":false,"prefix":"","firstName":"Nazarudin","middleName":"","lastName":"Safian","suffix":""},{"id":517886780,"identity":"daa69144-c0d5-433c-b57b-bf991bf15d5d","order_by":5,"name":"Mohamed Faisal Abdul Hamid","email":"data:image/png;base64,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","orcid":"","institution":"Hospital Canselor Tuanku Muhriz, Universiti Kebangsaan Malaysia","correspondingAuthor":true,"prefix":"","firstName":"Mohamed","middleName":"Faisal Abdul","lastName":"Hamid","suffix":""}],"badges":[],"createdAt":"2025-08-31 01:38:04","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7497811/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7497811/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91953843,"identity":"5e2d404c-b85e-4879-b013-9b9b54117f00","added_by":"auto","created_at":"2025-09-23 07:04:11","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2874508,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscriptforpublicationv1.1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7497811/v1/c0ad9c394c7c1f6400eb6a12.docx"},{"id":91956359,"identity":"d473edb4-fc7a-42d0-8215-94ef45b7c1b1","added_by":"auto","created_at":"2025-09-23 07:12:11","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":457450,"visible":true,"origin":"","legend":"","description":"","filename":"Figure1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7497811/v1/739711a8500714056df11b97.docx"},{"id":91953427,"identity":"c2079244-b9ee-400e-98d0-cc91d0215bf1","added_by":"auto","created_at":"2025-09-23 06:56:11","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":100857,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2CorrelationofyearsofexposuretodustwithFVC.docx","url":"https://assets-eu.researchsquare.com/files/rs-7497811/v1/a0da3485178c2d605b460de1.docx"},{"id":91953429,"identity":"4c6a442f-5edf-46d2-a015-10b6d3057ebd","added_by":"auto","created_at":"2025-09-23 06:56:11","extension":"json","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":8351,"visible":true,"origin":"","legend":"","description":"","filename":"4c72178c7f084364a0c892ca87acb5f1.json","url":"https://assets-eu.researchsquare.com/files/rs-7497811/v1/c5e171179c561b4b5c12b8b7.json"},{"id":91951703,"identity":"7cd43e98-7a7c-402e-8448-dcee9c80dbfb","added_by":"auto","created_at":"2025-09-23 06:48:11","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":624376,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryfile1copy.docx","url":"https://assets-eu.researchsquare.com/files/rs-7497811/v1/9b5ee26b34f2735bcd18dabc.docx"},{"id":91953433,"identity":"6d6056cf-bb90-4ba1-8fa8-0564eee1d4b8","added_by":"auto","created_at":"2025-09-23 06:56:11","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":151585,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryfile2.docx","url":"https://assets-eu.researchsquare.com/files/rs-7497811/v1/c15793f9c5c46e563fac2a86.docx"},{"id":91953434,"identity":"cd4f9a9a-b2aa-431c-9340-3086de8e09fb","added_by":"auto","created_at":"2025-09-23 06:56:12","extension":"xml","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":145998,"visible":true,"origin":"","legend":"","description":"","filename":"4c72178c7f084364a0c892ca87acb5f11enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7497811/v1/14292445dd68fc9036138287.xml"},{"id":91951699,"identity":"7d1252b6-2ef6-4bc4-886f-cb8c89fee988","added_by":"auto","created_at":"2025-09-23 06:48:11","extension":"eps","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":801,"visible":true,"origin":"","legend":"","description":"","filename":"drawingimage1.eps","url":"https://assets-eu.researchsquare.com/files/rs-7497811/v1/21733702113609d9d9a270e2.eps"},{"id":91951697,"identity":"b47828df-ce83-40ff-b09d-420ce65407af","added_by":"auto","created_at":"2025-09-23 06:48:11","extension":"jpeg","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":442628,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7497811/v1/07fbe44130ede09292cd4060.jpeg"},{"id":91951701,"identity":"f947cb41-16ad-4dad-a2eb-04b6bcd4e1c2","added_by":"auto","created_at":"2025-09-23 06:48:11","extension":"png","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":85882,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7497811/v1/12e69a72ae7955aee5ccca09.png"},{"id":91953431,"identity":"d9427632-0cc1-4273-9b8c-11e20f65b763","added_by":"auto","created_at":"2025-09-23 06:56:11","extension":"png","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":65397,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7497811/v1/723d8bd1c7f491a79e6cb5ca.png"},{"id":91953432,"identity":"5e25fdba-1276-4477-ba30-c7f7b4d592bc","added_by":"auto","created_at":"2025-09-23 06:56:11","extension":"png","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":20192,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7497811/v1/e48ec406507ee1623a1134a3.png"},{"id":91951707,"identity":"ffd40518-7c1e-4070-ac8a-b399bc8ddff4","added_by":"auto","created_at":"2025-09-23 06:48:12","extension":"xml","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":143773,"visible":true,"origin":"","legend":"","description":"","filename":"4c72178c7f084364a0c892ca87acb5f11structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7497811/v1/8856fbdd2f87704afdedfd70.xml"},{"id":91951708,"identity":"528eb670-3b04-40da-85dd-593bcc3c48ae","added_by":"auto","created_at":"2025-09-23 06:48:12","extension":"html","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":153768,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7497811/v1/266babb7a80e123d85a2254e.html"},{"id":91951692,"identity":"ff65081f-8c56-472e-bda9-9378771bc28e","added_by":"auto","created_at":"2025-09-23 06:48:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":150948,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCONSORT Flow chart\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7497811/v1/6e429b1f01a00a2fb87429fd.png"},{"id":91951691,"identity":"47f9521f-b97d-4e45-92fc-f181f2024d63","added_by":"auto","created_at":"2025-09-23 06:48:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":86413,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCorrelation of years of exposure to dust with FVC, FEV1 and FeNO\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7497811/v1/963e26252a7917baf681f8ee.png"},{"id":92372027,"identity":"b76747c5-acfb-4b49-a437-83fe2f11952e","added_by":"auto","created_at":"2025-09-29 03:16:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1532412,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7497811/v1/acfd48a4-0641-47dc-b52c-441cde1e8470.pdf"},{"id":91951694,"identity":"8096ce45-2337-492a-b364-bc41d72dd6ff","added_by":"auto","created_at":"2025-09-23 06:48:11","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":624376,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryfile1copy.docx","url":"https://assets-eu.researchsquare.com/files/rs-7497811/v1/b0ab88745a7dfd9423e01c2e.docx"},{"id":91951705,"identity":"8106863c-085a-400c-9310-8035722c3ddb","added_by":"auto","created_at":"2025-09-23 06:48:12","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":151585,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryfile2.docx","url":"https://assets-eu.researchsquare.com/files/rs-7497811/v1/d0d99649f73334846ec11a11.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessment of Fractional Exhaled Nitric Oxide and Lung Function Among Quarry Workers","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eOccupational lung diseases (OLDs) are respiratory conditions that are caused, aggravated, or exacerbated by workplace exposures, including dust, fumes, gases, and chemicals, ranging from COPD and asthma to pneumoconiosis and mesothelioma (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). These diseases often cause lasting impairment and are especially prevalent in industries like construction, mining, and quarrying, where respiratory hazards are common. In Malaysian quarries, work-related illnesses significantly outnumber injuries, highlighting the need for strong health and safety protocols under the Occupational Safety and Health Act 1994 (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDiseases such as asbestosis and silicosis remain significant in industries with silica and asbestos exposure, leading to impaired lung function and chronic respiratory symptoms. Additionally, inhalation of airborne pollutants, including dust and fumes, increases the risk of occupational asthma and other respiratory conditions, further impacting workers' health (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eInternationally, sources of occupational respiratory hazards have shifted over time (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Historically, mining and metal production industries exposed workers to high levels of mineral dust, such as coal and silica. Occupational asthma remains the most common work-related respiratory disease, representing 15\u0026ndash;20% of adult cases, though its prevalence is declining in Europe (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Exposure to vapors, gases, dust, or fumes is linked to around 15% of COPD cases in Western countries (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). In 2015, asbestos exposure led to an estimated 23,000 mesothelioma and 155,000 lung cancer cases worldwide (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn Malaysia, reported occupational lung disease cases rose from 86 in 2015 to 150 in 2016. The 2023 DOSH report notes 78 cases of occupational disease and injury among quarry workers, with only 2.6% due to lung disease. Despite significant construction hazards, reported lung disease cases remain low (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFractional Exhaled Nitric Oxide (FeNO) is useful for monitoring respiratory health in workers exposed to airborne irritants, especially in occupational lung diseases. More sensitive than spirometry for detecting airway inflammation, FeNO is mainly used in asthma management but also helps diagnose COPD and other lung conditions (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Introducing FeNO into routine medical examinations in the workplace and employing it alongside spirometry, particularly Forced Expiratory Volume in one second (FEV1). A study by Lim et al. found that 9.6% of office workers had asthma, with mild FeNO elevations (\u0026gt;\u0026thinsp;25 ppb) in 25.8% of cases (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). FeNO has not been studied in relation to occupational lung disease among Malaysian quarry workers.\u003c/p\u003e\u003cp\u003eThe primary objective of this study was to ascertain FeNO levels among quarry workers utilizing a portable Niox\u0026reg; Vero hand-held analyser (Aerocrine AB, Solna, Sweden): categorized as low (\u0026lt;\u0026thinsp;25 ppb), intermediate (25\u0026ndash;50 ppb), and high (\u0026gt;\u0026thinsp;50 ppb) (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Secondary objectives included determining the prevalence of occupational lung disease and common respiratory symptoms. We also aimed to assess ventilatory capacity (FEV1 and FVC) following the 2019 American Thoracic Society (ATS) Consensus (ranging from normal to very severe impairment) through portable spirometry and to determine the type of ventilatory defect (e.g., obstructive ventilatory defect, preserved ratio impaired spirometry (PRISm), and restrictive ventilatory defect) (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). The study sought to establish correlations between occupational lung disease, severity of lung impairment, and FeNO levels, alongside evaluating worker compliance with safety protocols and safe work practices through a validated questionnaire.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Study Design\u003c/h2\u003e\u003cp\u003eThis cross-sectional study was conducted in collaboration with Negeri Roadstone Sdn. Bhd. from October 2022 to October 2024, aims to assess respiratory health among quarry workers. Negeri Roadstone Sdn. Bhd. specializes in extracting and producing quarry materials for construction and infrastructure projects, primarily stone and gravel. Written informed consent was obtained from all participants before enrolment, per international guidelines, and the study received approval from the Research Ethics Committee of Universiti Kebangsaan Malaysia (FF-2022-332).\u003c/p\u003e\u003cp\u003eDemographic data were collected from participants, followed by a modified British Medical Research Council (BMRC) Questionnaire translated into Malay with permission (Supplementary file 1). The questionnaire obtained information on respiratory symptoms, smoking status, occupational history, dust exposure, and mask usage frequency. Chest radiographs taken within the previous three months were then reviewed. After this, FeNO testing and portable lung function assessments were performed. The study also assessed participants\u0026rsquo; adherence to respirator use. Individuals with abnormal results on initial lung function screening underwent further evaluation, which included comprehensive lung function tests and High-Resolution Computed Tomography (HRCT) of the thorax. Portable lung function testing was repeated yearly to monitor for any progression.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Participants\u003c/h2\u003e\u003cp\u003eThe research was conducted among all personnel employed at the quarry site, encompassing administrative staff and site workers. Their supervisor approached them to partake in the study via email, telephone, or internal memorandum. Informed consent to participate was obtained from all participants in the study.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Eligibility\u003c/h2\u003e\u003cp\u003eEmployees were deemed eligible if they exceeded 18 years of age and demonstrated the capability to perform spirometry and FeNO tests. Exclusion criteria included the inability or unwillingness to provide consent, a recent upper or lower respiratory tract infection within the preceding two weeks, and the presence of contraindications for spirometry. These contraindications encompass recent cardiac events, major surgical procedures, severe respiratory conditions, or cognitive and neurological impairments (\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Sample size\u003c/h2\u003e\u003cp\u003eThe calculation of our sample size was conducted utilizing Statulator. ' The sample size was estimated through an online sample size calculator designed for a single proportion, with a projected prevalence of occupational lung disease at 30%, derived from the average range of 15\u0026ndash;30% as indicated by prior studies (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). The total population was approximated at 100,000, incorporating a 10% margin of error, a 95% confidence interval, and a design effect (DEFF) of 1 (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Consequently, the calculated requisite sample size amounted to 81.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Measures\u003c/h2\u003e\u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\u003ch2\u003e2.4.1 Demographic and Questionnaire:\u003c/h2\u003e\u003cp\u003eThe participants were interviewed using a validated and modified BMRC Questionnaire (Supplementary 1) (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). The questionnaire was translated into Malay, pre-tested, and administered by trained interviewers (Supplementary file 2) to reduce recall bias (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). The corresponding author granted authorization to utilize the questionnaire, which was used for a prior study (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). The questionnaire encompassed respiratory symptoms, medical history, smoking habits, occupational history, dust exposure, and the utilization of masks. Following the collection of demographic information (age, sex, smoking status, comorbidities) and responses, a fundamental physical examination was conducted, which included the assessment of body mass index (BMI), blood pressure, heart rate, oxygen saturation, and a chest examination.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003e2.4.2 FeNO and Portable Spirometry\u003c/h2\u003e\u003cp\u003eFeNO measurements (in ppb) were conducted once by a trained technician utilizing the NIOX\u0026reg; VERO electrochemical handheld analyzer, adhering to the protocol established by the American Thoracic Society (ATS) and the European Respiratory Society (ERS) (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). The technician provided the breathing handle to the participant, who was instructed to completely exhale to evacuate the lungs before positioning the handle in the mouth, ensuring a proper seal. Subsequently, the participant was requested to inhale deeply through the filter, following guidance from on-screen animations. Upon prompting from the machine, the participant exhaled steadily for 10 seconds, as indicated by the NIOX\u0026reg; Panel animations. If the procedure was executed correctly, a FeNO report was generated. Participants exhibiting abnormal FeNO levels (intermediate or high; FeNO\u0026thinsp;\u0026gt;\u0026thinsp;25 ppb) and those diagnosed with obstructive ventilatory defects, including a known diagnosis of asthma, were subjected to a bronchodilator reversibility test. Participants with normal FeNO levels underwent spirometry only. Before the FeNO and spirometry procedures, a Rapid Test Kit-Antigen (RTK-Ag) test was conducted on-site to ensure safety.\u003c/p\u003e\u003cp\u003eSpirometry was performed biannually, while FeNO was measured once, and a trained respiratory technician conducted both procedures. Spirometry was performed using the SpiroUSB (CareFusion Germany 23X) in accordance with ATS/ERS guidelines (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). The technician ensured the participant's proper positioning, nose clip placement, and lips sealing around the mouthpiece. Participants were required to execute a minimum of three exhalations, with a maximum of eight permitted, based on the quality of the test. Each exhalation had to last at least six seconds, with results deemed acceptable if the difference between the two best readings was less than 5% or 150 milliliters (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). To mitigate the risk of COVID-19 transmission, participants were required to undergo an RTK-Ag test the same day before the FeNO and spirometry procedures. Additional protective measures included the utilization of level 3 PPE and disposable mouthpieces.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\u003ch2\u003e2.4.3 Further Testing (HRCT, Full lung function test)\u003c/h2\u003e\u003cp\u003eIndividuals exhibiting abnormal lung function (PRISm) subsequently underwent a comprehensive lung function assessment, followed by a High-Resolution Computed Tomography (HRCT) of the thorax utilizing the TOSHIBA Aquilion One (640-slice) CT scanner to evaluate potential structural abnormalities. A thoracic radiologist interpreted the HRCT images. Participants were subjected to an additional comprehensive lung function assessment when abnormalities were identified in the chest radiograph or prior lung function evaluations. The lung function evaluation was conducted using the Vmax\u0026trade; Autobox System from Vyaire Medical, United States, in accordance with the guidelines set forth by the American Thoracic Society (ATS) and the European Respiratory Society (ERS) (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Throughout the procedure, all participants were closely monitored by a qualified respiratory technician. Before undergoing the comprehensive lung function assessment, each participant had a complete blood count performed by a trained phlebotomist to ensure accurate gas transfer values to hemoglobin, as these values can significantly affect the interpretation of lung function results. Additionally, all participants were required to complete a Rapid Test Kit-Antigen (RTK-Ag) on the same day as the procedure.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\u003ch2\u003e2.4.4 Data collection and Interpretation:\u003c/h2\u003e\u003cp\u003eStatistical analyses were performed utilizing the IBM Statistical Package for Social Sciences (SPSS) version 29.0 (IBM Corp., Armonk, NY, USA). Descriptive statistics were reported as mean and SD, number, and percentages. All statistical tests were two-tailed, with a significance threshold established at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. A paired t-test was employed to compare the 1-year follow-up assessment. Multiple linear regression was applied to analyse variables related to FeNO and lung function tests, including FEV1, FVC, BMI, symptoms, compliance with respirator, and the correlation among the data. A probability value less than p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. Individuals with confirmed occupational lung disease will be referred to the Department of Occupational Safety and Health (DOSH).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Operational Terms Definition\u003c/h2\u003e\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\u003ch2\u003e2.5.1 Occupational lung disease\u003c/h2\u003e\u003cp\u003eOccupational lung diseases, commonly referred to as work-related lung diseases, encompass a range of conditions that either develop or are exacerbated by prolonged exposure to specific irritants in the workplace. These irritants include dust particles, chemicals, fungal spores, and specific animal excretions, all of which can heighten the risk of developing occupational lung illnesses. Examples of such diseases include occupational asthma, chronic obstructive pulmonary disease (COPD), coccidioidomycosis, hypersensitivity pneumonitis, histoplasmosis, pneumoconiosis, and mesothelioma.\u003c/p\u003e\u003cp\u003eIn the context of our study, an individual is considered to have an occupational lung disease if they fulfill any of the following criteria: i) the presence of an obstructive ventilatory defect in spirometry with no known respiratory illness or significant smoking history (defined as fewer than 20 pack-years); ii) individuals with a known respiratory illness, such as asthma or COPD, who encounter exacerbated symptoms due to workplace exposure; iii) a restrictive pattern observed on a comprehensive lung function test, accompanied by characteristic high-resolution computed tomography (HRCT) thorax features indicative of a specific pattern of occupational lung disease or pneumoconiosis; iv) an inter-visit variability of FEV1 exceeding 200 mls and 12%, which suggests asthma.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\u003ch2\u003e2.5.2 Impaired Lung Function\u003c/h2\u003e\u003cp\u003eIndividuals exhibiting impaired lung function may present with various conditions, including both obstructive and restrictive ventilatory defects, as well as PRISm. An obstructive ventilatory defect is characterized by an FEV1/FVC ratio of less than 0.7, or 70%. PRISm, conversely, is defined as an FEV1/FVC ratio greater than 0.7 or 70%, accompanied by an FVC below 80% of the predicted value, per ATS guidelines (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Restrictive ventilatory defects are characterized by a reduction in TLC that falls below the 5th percentile of the predicted value, or less than 80% of the predicted value, coupled with a normal FEV1/FVC ratio (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). A mixed pattern of ventilatory defects is characterized by a decrease in TLC below the 5th percentile of the predicted value, or less than 80% of the predicted value, along with a reduced FEV1/FVC ratio (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003ch2\u003e2.5.3 Respiratory symptoms\u003c/h2\u003e\u003cp\u003eCommon respiratory symptoms in occupational lung disease include cough, sputum production, wheezing, breathlessness or shortness of breath, and chest tightness.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\u003ch2\u003e\u003cb\u003e2.5.4\u003c/b\u003e FeNO \u003cb\u003evalues\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eA low FeNO (\u0026lt;\u0026thinsp;25 ppb in adults):\u003c/p\u003e\u003cp\u003eEosinophilic airway inflammation is infrequently observed in symptomatic adult patients exhibiting a FeNO of less than 25 ppb. This threshold is substantiated by data from several studies, including those conducted by Shaw et al. and Porsbjerg et al., as well as investigations aimed at utilizing FeNO measurements for asthma diagnosis and studies designed to optimize the use of inhaled corticosteroids (ICS) (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan additionalcitationids=\"CR25 CR26\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHigh FeNO (\u0026gt;\u0026thinsp;50 ppb in adults):\u003c/p\u003e\u003cp\u003eSubstantial airway eosinophilia is likely indicated by elevated FeNO (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). It may also imply that a symptomatic patient possesses inflamed, steroid-responsive airways (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). The findings of practical studies provided the basis for the clinically significant threshold of 50 ppb.\u003c/p\u003e\u003cp\u003eIntermediate FeNO (in adults, between 25\u0026ndash;50 ppb):\u003c/p\u003e\u003cp\u003eThe data indicate that a cautious interpretation is warranted for FeNO levels ranging from 25 to 50 ppb (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). In instances where a patient is being monitored longitudinally, or if the patient's FeNO has fluctuated from a previous assessment by what is considered a clinically significant degree, the importance ascribed to a FeNO result within this range will be contingent upon whether the test is employed as a diagnostic instrument in a symptomatic and steroid-naive individual (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section3\"\u003e\u003ch2\u003e2.5.5 Control Measures and Personal Protective Equipment (PPE)\u003c/h2\u003e\u003cp\u003ePersonal protective equipment (PPE) for quarry workers refers to the specialized clothing or gear worn to protect individuals from workplace hazards and risks inherent in the quarrying environment. These hazards include dust, noise, falling debris, and heavy machinery exposure. In this study, we collected data on compliance with respirators and dust mask utilization for PPE adherence, as our focus was solely on evaluating occupational lung disease.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eUsing a universal sampling method, we initially recruited 110 participants from the quarry, including both administrative and site workers. Three participants were excluded from the follow-up visit, leaving 107 for the final analysis. The administrative group was included due to the office\u0026apos;s proximity to the quarry, which is less than one kilometre away, thereby exposing them to a significant dust risk. The study flow can be seen in Figure 1 (CONSORT flow chart). The characteristics of the participants (Table 1) indicated that 88.1% (n=52) were male and 11.9% (n=7) were female in the site population group. In the administrative group, 33.3% (n=16) of participants were male, while 66.7% (n=32) were female. The median age of the workers was 32 (27-37) years; the site group had a median age of 34 (28-40) years, and the administrative group had a median age of 31 (26-34.75) years. The median BMI of the workers was 27 (22.7-30.2) kg/m\u0026sup2;; the site workers group had a median BMI of 27 (21.8-28.6) kg/m\u0026sup2;, while the administrative group had a median BMI of 26.9 (23.3-31.8) kg/m\u0026sup2;. All participants had over one year of work experience, with the median years of exposure to dust being 3 (1-11) years for all workers; 3 (2-10.75) years for site workers, and 2 (1-9.75) years for administrative workers. The years worked correlate with years of exposure to dust. The site population group was exposed to dust for 7-8 hours per day (45.8%), while the administrative population was exposed for 1-2 hours per day (39.8%). The mean smoking pack-years for smokers was 14.49\u0026plusmn; 9; site workers had 15.17 \u0026plusmn; 9.6 pack years, and the administrative group had 11.78 \u0026plusmn; 5.8 pack years. All male workers in both groups smoked, while no female workers did.\u003c/p\u003e\n\u003cp\u003eThe most frequently reported symptom was shortness of breath, affecting 27 employees (25.2%). In the site group, 14 out of 59 workers (23.7%), and in the administrative group, 13 out of 48 workers (27.1%), indicated the presence of this symptom. A significant number of participants also reported experiencing coughing (n=17, 15.9%), with 12 out of 59 in the site group (20.3%) and five out of 48 in the administrative group (10.4%) encountering this symptom. Chest tightness or pain was noted in 21 participants (19.6%), which included 11 out of 59 site workers (18.6%) and 10 out of 48 administrative staff members (20.8%). Moreover, a notably higher percentage of site workers (15.3%) reported a deterioration in respiratory symptoms over the past three months, compared to only 6.3% in the administrative group.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe mean FEV1% was 78.63%: the site group at 77.95% and the administrative group at 79.46%. The mean FVC was 78.63%, with site workers at 79.08% and administrative staff at 80%. Overall, 73 participants (68.2%) had normal spirometry results: site workers n=38 (64.4%) and administrative group n=35 (73%). An obstructive ventilatory defect pattern was observed in seven participants (6.6%): site group n=5 (8.5%) and administrative group n=2 (4.2%). A PRISm ventilatory defect pattern was seen in 27 participants (25.2%): site group n=16 (27.1%) and administrative group n=11 (22.9%). Only one participant exhibited notable reversibility in post-bronchodilator response (FEV1 \u0026gt;12% and 200 ml improvement).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe results also indicate that most workers have low FeNO levels (\u0026lt;25), with 59.3% in the site group and 54.2% in the administrative group. Those with significantly high FeNO levels (\u0026gt;50) comprise 13.5% of site workers and 22.9% of administrative workers. The mean FeNO level is higher among the administrative group, at 22 (13-40), compared to the site group, at 18 (11-32). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA comparison of FeNO levels observed in both groups shows a similar distribution. Participants with normal spirometry results predominantly exhibited normal FeNO levels (\u0026lt;25 ppb), making up 41.1% of the total participants. Additionally, 17.8% of participants had intermediate FeNO levels (25-50 ppb), while 9.3% demonstrated high FeNO levels (\u0026gt;50 ppb). Employees with obstructive ventilatory defects represented 6.6%, with most showing intermediate FeNO levels at 3.7% and low FeNO levels at 2.8%. None of the participants with obstructive ventilatory defects exhibited high FeNO. Among those with PRISm (25.2%), the majority displayed normal FeNO levels (13.1%), followed by intermediate levels (3.7%). Furthermore, 8.4% of the overall population with PRISm had high FeNO levels. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA comparison of baseline spirometry with repeat spirometry was conducted after a one-year follow-up, utilizing a paired t-test for the comparative analysis. The results indicated that the p-values for FVC, FEV1, and FEV1/FVC in both groups exceeded 0.05, suggesting no statistically significant difference. Furthermore, three participants (2.8%) demonstrated inter-visit variability exceeding 200 ml and a 12% difference between visits.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1: Demographic, spirometry, and FeNO results \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"612\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 182px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003eAll staff (\u003cem\u003en\u003c/em\u003e=107)\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 247px;\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eSite worker (\u003cem\u003en\u003c/em\u003e=59)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003eAdministrative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;Staff (\u003cem\u003en\u003c/em\u003e=48)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Male\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e68 (63.6%)\u003c/p\u003e\n \u003cp\u003e39 (36.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e52 (88.1%)\u003c/p\u003e\n \u003cp\u003e7 (11.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e16 (33.3%)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e32 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.00\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Malay\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Indian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e102 (95.3%)\u003c/p\u003e\n \u003cp\u003e5 (4.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e55 (93.2%)\u003c/p\u003e\n \u003cp\u003e4 (6.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e47 (97.9%)\u003c/p\u003e\n \u003cp\u003e1 (2.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.256\u003c/p\u003e\u0026nbsp;\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (years)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; 20-29\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; 30-39\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; 40-49\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026gt; 50\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Median (IQR)\u003c/p\u003e\u0026nbsp;\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e29 (36.4%)\u003c/p\u003e\n \u003cp\u003e46 (43%)\u003c/p\u003e\n \u003cp\u003e12 (11.2%)\u003c/p\u003e\n \u003cp\u003e10 (9.3%)\u003c/p\u003e\n \u003cp\u003e32 (27-37)\u003c/p\u003e\u0026nbsp;\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e17 (28.8%)\u003c/p\u003e\n \u003cp\u003e27 (45.7)\u003c/p\u003e\n \u003cp\u003e10 (16.9%)\u003c/p\u003e\n \u003cp\u003e5 (8.5%)\u003c/p\u003e\n \u003cp\u003e34 (28-40)\u003c/p\u003e\u0026nbsp;\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e22 (45.8%)\u003c/p\u003e\n \u003cp\u003e19 (39.6%)\u003c/p\u003e\n \u003cp\u003e2 (4.2%)\u003c/p\u003e\n \u003cp\u003e5 (10.4%)\u003c/p\u003e\n \u003cp\u003e31 (26-34.75)\u003c/p\u003e\u0026nbsp;\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.058\u003c/p\u003e\u0026nbsp;\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI (kg/m\u0026sup2;)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Underweight (\u0026lt;18.5)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Normal (18.5-22.9)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Overweight (23-24.9)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Obese class I (25-29.9)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Obese class II (\u0026gt;30)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5 (4.7%)\u003c/p\u003e\n \u003cp\u003e22 (20.6%)\u003c/p\u003e\n \u003cp\u003e11 (10.3%)\u003c/p\u003e\n \u003cp\u003e42 (39.3%)\u003c/p\u003e\n \u003cp\u003e27 (25.2%)\u003c/p\u003e\n \u003cp\u003e27 (22.7-30.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e5 (8.5%)\u003c/p\u003e\n \u003cp\u003e13 (22%)\u003c/p\u003e\n \u003cp\u003e4 (6.8%)\u003c/p\u003e\n \u003cp\u003e27 (45.8%)\u003c/p\u003e\n \u003cp\u003e10 (16.9%)\u003c/p\u003e\n \u003cp\u003e27 (21.8-28.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e9 (18.7%)\u003c/p\u003e\n \u003cp\u003e7 (14.6%)\u003c/p\u003e\n \u003cp\u003e15 (31.3%)\u003c/p\u003e\n \u003cp\u003e17 (35.4%)\u003c/p\u003e\n \u003cp\u003e26.9 (23.3-31.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003eWork experience (years)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026lt; 1 years\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; 1-5 years\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; 6-10 years\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026gt; 10 years\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e28 (26.2%)\u003c/p\u003e\n \u003cp\u003e33 (30.8%)\u003c/p\u003e\n \u003cp\u003e19 (17.8%)\u003c/p\u003e\n \u003cp\u003e27 (25.2%)\u003c/p\u003e\n \u003cp\u003e3 (1-11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e7 (11.9%)\u003c/p\u003e\n \u003cp\u003e26 (44.1%)\u003c/p\u003e\n \u003cp\u003e6 (10.2%)\u003c/p\u003e\n \u003cp\u003e20 (33.8%)\u003c/p\u003e\n \u003cp\u003e3 (2-10.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e21 (43.7%)\u003c/p\u003e\n \u003cp\u003e7 (14.6%)\u003c/p\u003e\n \u003cp\u003e13 (27.1%)\u003c/p\u003e\n \u003cp\u003e7 (14.6%)\u003c/p\u003e\n \u003cp\u003e2 (1-9.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.348\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003eHours per day exposed to dust\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; None\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; 1-2 hours per day\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; 3-4 hours per day\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; 5-6 hours per day\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; 7-8 hours per day\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Mean \u0026plusmn; SD\u003c/p\u003e\u0026nbsp;\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5 (4.7%)\u003c/p\u003e\n \u003cp\u003e31 (29%)\u003c/p\u003e\n \u003cp\u003e20 (18.7%)\u003c/p\u003e\n \u003cp\u003e15 (14%)\u003c/p\u003e\n \u003cp\u003e36 (33.6%)\u003c/p\u003e\n \u003cp\u003e3.43 \u0026plusmn; 1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e12 (20.3%)\u003c/p\u003e\n \u003cp\u003e12 (20.3%)\u003c/p\u003e\n \u003cp\u003e8 (13.5%)\u003c/p\u003e\n \u003cp\u003e27 (45.8%)\u003c/p\u003e\n \u003cp\u003e2.92 \u0026plusmn; 1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5 (10.4%)\u003c/p\u003e\n \u003cp\u003e19 (39.6%)\u003c/p\u003e\n \u003cp\u003e8 (16.7%)\u003c/p\u003e\n \u003cp\u003e7 (14.6%)\u003c/p\u003e\n \u003cp\u003e9 (18.7%)\u003c/p\u003e\n \u003cp\u003e4.14 \u0026plusmn;1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"604\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003eSymptoms\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Cough\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Sputum production\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Shortness of breath\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Wheeze\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Chest tightness\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Worsening symptoms\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; past 3 months\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e17 (15.9%)\u003c/p\u003e\n \u003cp\u003e8 (7.5%)\u003c/p\u003e\n \u003cp\u003e27 (25.2%)\u003c/p\u003e\n \u003cp\u003e14 (13.1%)\u003c/p\u003e\n \u003cp\u003e21 (19.6%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e12 (11.2%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e12 (20.3%)\u003c/p\u003e\n \u003cp\u003e5 (8.5%)\u003c/p\u003e\n \u003cp\u003e14 (23.7%)\u003c/p\u003e\n \u003cp\u003e7 (11.9%)\u003c/p\u003e\n \u003cp\u003e11 (18.6%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e9 (15.3%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e5 (10.4%)\u003c/p\u003e\n \u003cp\u003e3 (6.3%)\u003c/p\u003e\n \u003cp\u003e13 (27.1%)\u003c/p\u003e\n \u003cp\u003e7 (14.6%)\u003c/p\u003e\n \u003cp\u003e10 (20.8%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e3 (6.3%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.166\u003c/p\u003e\n \u003cp\u003e0.667\u003c/p\u003e\n \u003cp\u003e0.694\u003c/p\u003e\n \u003cp\u003e0.682\u003c/p\u003e\n \u003cp\u003e0.779\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.145\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCigarette smoking\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; No\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Yes\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 1-5 pack years\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 6-10 pack years\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 11-15 pack years\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 16-20 pack years\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026gt; 20 pack years\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Mean \u0026plusmn; SD\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSmoking status by gender\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Male\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Female\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e62 (57.9%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e5 (4.7%)\u003c/p\u003e\n \u003cp\u003e14 (13.1%)\u003c/p\u003e\n \u003cp\u003e9 (8.4%)\u003c/p\u003e\n \u003cp\u003e8 (7.5%)\u003c/p\u003e\n \u003cp\u003e9 (8.4%)\u003c/p\u003e\n \u003cp\u003e14.49\u0026plusmn; 9\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e45 (100%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e23 (39%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e4 (6.8%)\u003c/p\u003e\n \u003cp\u003e14 (23.7%)\u003c/p\u003e\n \u003cp\u003e7 (11.9)\u003c/p\u003e\n \u003cp\u003e10 (16.9%)\u003c/p\u003e\n \u003cp\u003e1 (1.7%)\u003c/p\u003e\n \u003cp\u003e15.17 \u0026plusmn; 9.6\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e36 (100%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e39 (81.3%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e1 (2.1%)\u003c/p\u003e\n \u003cp\u003e5 (10.4%)\u003c/p\u003e\n \u003cp\u003e1 (2.1%)\u003c/p\u003e\n \u003cp\u003e1 (2.1%)\u003c/p\u003e\n \u003cp\u003e1 (2.1%)\u003c/p\u003e\n \u003cp\u003e11.78 \u0026plusmn; 5.8\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e9 (100%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003eCompliance to Respirator/\u003c/p\u003e\n \u003cp\u003eFace Mask\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Occasional\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Frequently\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; All the time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e58 (52.3%)\u003c/p\u003e\n \u003cp\u003e30 (28%)\u003c/p\u003e\n \u003cp\u003e21 (19.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e34 (57.6%)\u003c/p\u003e\n \u003cp\u003e15 (25.4%)\u003c/p\u003e\n \u003cp\u003e10 (16.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e22 (45.8%)\u003c/p\u003e\n \u003cp\u003e15 (31.3%)\u003c/p\u003e\n \u003cp\u003e11 (22.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003eFVC Severity % predicted\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Normal (\u0026gt;80%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Mild (70-79%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Moderate (60-69%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Moderate Severe (50-59%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Severe (35-49%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Very severe (\u0026lt;35%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Mean \u0026plusmn; SD (%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eFEV1 Severity % predicted\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Normal (\u0026gt;80%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Mild (70-79%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Moderate (60-69%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Moderate Severe (50-59%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Severe (35-49%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Very severe (\u0026lt;35%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Mean \u0026plusmn; SD (%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSignificant Bronchodilator Response\u003c/p\u003e\n \u003cp\u003e(Increment FEV1 \u003cu\u003e\u0026gt;\u003c/u\u003e12%\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eand 200ml improvement)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSpirometry Interpretation\u003c/p\u003e\n \u003cp\u003eNormal pattern\u003c/p\u003e\n \u003cp\u003eObstructive pattern\u003c/p\u003e\n \u003cp\u003ePRISm pattern\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e58 (54.2%)\u003c/p\u003e\n \u003cp\u003e29 (27.1%)\u003c/p\u003e\n \u003cp\u003e17 (15.9%)\u003c/p\u003e\n \u003cp\u003e1 (0.9%)\u003c/p\u003e\n \u003cp\u003e2 (1.9%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e78.63 \u0026plusmn; 12.73\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e57 (53.3%)\u003c/p\u003e\n \u003cp\u003e25 (23.4%)\u003c/p\u003e\n \u003cp\u003e18 (16.8%)\u003c/p\u003e\n \u003cp\u003e5 (4.7%)\u003c/p\u003e\n \u003cp\u003e1 (0.9%)\u003c/p\u003e\n \u003cp\u003e1 (0.9%)\u003c/p\u003e\n \u003cp\u003e78.63 \u0026plusmn;12.74\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1 (0.9%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e73 (68.2%)\u003c/p\u003e\n \u003cp\u003e7 (6.6%)\u003c/p\u003e\n \u003cp\u003e27(25.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e31 (52.5%)\u003c/p\u003e\n \u003cp\u003e18 (30.5%)\u003c/p\u003e\n \u003cp\u003e8 (13.5%)\u003c/p\u003e\n \u003cp\u003e1 (1.7%)\u003c/p\u003e\n \u003cp\u003e1 (1.7%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e79.08 \u0026plusmn; 11.46\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e29 (49.2%)\u003c/p\u003e\n \u003cp\u003e16 (27.1%)\u003c/p\u003e\n \u003cp\u003e10 (16.9%)\u003c/p\u003e\n \u003cp\u003e3 (5.1.%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e1 (1.7%)\u003c/p\u003e\n \u003cp\u003e77.95 \u0026plusmn; 12.13\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e38 (64.4%)\u003c/p\u003e\n \u003cp\u003e5 (8.5%)\u003c/p\u003e\n \u003cp\u003e16 (27.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e28 (58.3%)\u003c/p\u003e\n \u003cp\u003e9 (18.8%)\u003c/p\u003e\n \u003cp\u003e8 (16.7%)\u003c/p\u003e\n \u003cp\u003e2 (4.2%)\u003c/p\u003e\n \u003cp\u003e1 (2.1%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e80 \u0026plusmn; 12.34\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e27 (55.3%)\u003c/p\u003e\n \u003cp\u003e11 (22.9%)\u003c/p\u003e\n \u003cp\u003e9 (18.8%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e1 (2.1%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e79.46 \u0026plusmn; 13.53\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1 (2.1%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e35 (73%)\u003c/p\u003e\n \u003cp\u003e2 (4.2%)\u003c/p\u003e\n \u003cp\u003e11 (22.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.692\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.543\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.365\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003eFeNO\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Low (\u0026lt;25 ppb)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Intermediate (25-50 ppb)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; High (\u0026gt;50 ppb)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e61 (57%)\u003c/p\u003e\n \u003cp\u003e27 (25.2%)\u003c/p\u003e\n \u003cp\u003e19 (17.8%)\u003c/p\u003e\n \u003cp\u003e20 (13-35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e35 (59.3%)\u003c/p\u003e\n \u003cp\u003e16 (27.1%)\u003c/p\u003e\n \u003cp\u003e8 (13.5%)\u003c/p\u003e\n \u003cp\u003e18 (11-32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e26 (54.2%)\u003c/p\u003e\n \u003cp\u003e11 (22.9%)\u003c/p\u003e\n \u003cp\u003e11 (22.9%)\u003c/p\u003e\n \u003cp\u003e22 (13-40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.429\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003eNormal Spirometry\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; FeNO \u0026lt; 25 ppb\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; FeNO 25-50 ppb\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; FeNO \u0026gt;50 ppb\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eObstructive Spirometry\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; FeNO \u0026lt; 25 ppb\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; FeNO 25-50 ppb\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; FeNO \u0026gt;50 ppb\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ePRISm Spirometry\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; FeNO \u0026lt; 25 ppb\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; FeNO 25-50 ppb\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; FeNO \u0026gt;50 ppb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e73 (68.2%)\u003c/p\u003e\n \u003cp\u003e44 (41.1%)\u003c/p\u003e\n \u003cp\u003e19 (17.8%)\u003c/p\u003e\n \u003cp\u003e10 (9.3%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e7 (6.6%)\u003c/p\u003e\n \u003cp\u003e3 (2.8%)\u003c/p\u003e\n \u003cp\u003e4 (3.7%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e27 (25.2%)\u003c/p\u003e\n \u003cp\u003e14 (13.1%)\u003c/p\u003e\n \u003cp\u003e4 (3.7%)\u003c/p\u003e\n \u003cp\u003e9 (8.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e38 (64.6%)\u003c/p\u003e\n \u003cp\u003e23 (39.0%)\u003c/p\u003e\n \u003cp\u003e9 (15.3%)\u003c/p\u003e\n \u003cp\u003e4 (6.8%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e5 (8.5%)\u003c/p\u003e\n \u003cp\u003e3 (5.1%)\u003c/p\u003e\n \u003cp\u003e2 (3.4%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e16 (27.1%)\u003c/p\u003e\n \u003cp\u003e9 (15.3%)\u003c/p\u003e\n \u003cp\u003e3 (5.1%)\u003c/p\u003e\n \u003cp\u003e4 6.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e35 (72.9%)\u003c/p\u003e\n \u003cp\u003e21 (43.8%)\u003c/p\u003e\n \u003cp\u003e8 (16.7%)\u003c/p\u003e\n \u003cp\u003e6 (12.5%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e2 (4.2%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e2 (4.2%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e11 (22.9%)\u003c/p\u003e\n \u003cp\u003e5 (10.4%)\u003c/p\u003e\n \u003cp\u003e1 (2.1%)\u003c/p\u003e\n \u003cp\u003e5 (10.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eVariables in the follow-up visit 1 year time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003eBaseline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e1 year\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003cp\u003eDifference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003et\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eSite Group\u003c/p\u003e\n \u003cp\u003eFVC (L)\u003c/p\u003e\n \u003cp\u003eFEV1 (L)\u003c/p\u003e\n \u003cp\u003eFEV1/FVC %\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eAdmin Group\u003c/p\u003e\n \u003cp\u003eFVC (L)\u003c/p\u003e\n \u003cp\u003eFEV1 (L)\u003c/p\u003e\n \u003cp\u003eFEV1/FVC %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e3.44 \u0026plusmn; 0.7\u003c/p\u003e\n \u003cp\u003e2.83 \u0026plusmn; 0.6\u003c/p\u003e\n \u003cp\u003e82.4 \u0026plusmn; 6.8\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e2.96 \u0026plusmn; 0.7\u003c/p\u003e\n \u003cp\u003e2.50 \u0026plusmn; 0.6\u003c/p\u003e\n \u003cp\u003e84.4 \u0026plusmn; 4.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e3,47 \u0026plusmn; 0.7\u003c/p\u003e\n \u003cp\u003e2.82 \u0026plusmn; 0.6\u003c/p\u003e\n \u003cp\u003e81.7 \u0026plusmn; 7.1\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e3.00 \u0026plusmn; 0.7\u003c/p\u003e\n \u003cp\u003e2.51 \u0026plusmn; 0.6\u003c/p\u003e\n \u003cp\u003e83.8 \u0026plusmn; 4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e-0.292\u003c/p\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003cp\u003e0.711\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e-0.040\u003c/p\u003e\n \u003cp\u003e-0.012\u003c/p\u003e\n \u003cp\u003e0.583\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e-1.834\u003c/p\u003e\n \u003cp\u003e0.153\u003c/p\u003e\n \u003cp\u003e1.917\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e-2.371\u003c/p\u003e\n \u003cp\u003e-0.608\u003c/p\u003e\n \u003cp\u003e0.975\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.864\u003c/p\u003e\n \u003cp\u003e0.072\u003c/p\u003e\n \u003cp\u003e0.060\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.022\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.546\u003c/p\u003e\n \u003cp\u003e0.355\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSite worker\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdministrative staff\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eInter-visit\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eVariability\u003c/p\u003e\n \u003cp\u003e200mls and\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e12% (n)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e3 (2.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003e1 (1.7%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e2 (4.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eBold indicates statistically significant.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 1\u0026nbsp;indicates that 25% (n = 27) of participants showed a PRISm pattern. Of these, 18 underwent further lung function tests and HRCT thorax at HCTM. Among them, one had a purely restrictive defect, one had a mixed pattern, most (55.6%) had normal lung function, and 33.3% displayed an obstructive pattern. Most participants had normal chest radiographs. However, a higher proportion in the site group (33.9%) had minimal opacities, with one case of past pulmonary tuberculosis (PTB), compared to 6.3% in the administrative group. This may be due to greater dust exposure and heavier smoking among site workers.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThese participants were subsequently evaluated at HCTM, where a full lung function test was conducted to assess TLC and DLCO, alongside an HRCT of the thorax to identify any CT characteristics suggestive of occupational lung disease or pneumoconiosis, which is shown in Table 2.\u0026nbsp;Among them, one had a purely restrictive defect, one had a mixed pattern, most (55.6%) had normal lung function, and 33.3% displayed an obstructive pattern.\u003c/p\u003e\n\u003cp\u003eHRCT findings were mostly normal: five site group members (45.5%) and six administrative group members (85.7%). Sub-centimetre nodules appeared in four site group members; minimal mosaic attenuation was seen in one participant from each group. One participant had signs of previous PTB, acquired while working there a year earlier.\u003c/p\u003e\n\u003cp\u003eFurther evaluation diagnosed occupational lung disease in 5.6% (n = 6) of quarry workers, a lower prevalence than the reported average of 8-13% (32, 33).\u003c/p\u003e\n\u003cp\u003eA detailed review of the six patients with occupational lung disease revealed the following profiles:\u003c/p\u003e\n\u003cp\u003eThe first, a 47-year-old male site worker (15 years\u0026rsquo; experience, BMI 28.5 kg/m\u0026sup2;, 18 pack-years) with asthma, showed a post-bronchodilator obstructive spirometry pattern and low FeNO; HRCT was largely unremarkable. Improvement in FEV1 supported a diagnosis of asthma with pollutant exposure.\u003c/p\u003e\n\u003cp\u003eThe second, a 29-year-old female administrator (2 years, BMI 33.8 kg/m\u0026sup2;), had new-onset cough and dyspnoea, intermediate FeNO (31 ppb), obstructive but non-reversible spirometry, and normal HRCT\u0026mdash;suggesting possible occupational asthma.\u003c/p\u003e\n\u003cp\u003eThe third, a 35-year-old female (10 years, BMI 27 kg/m\u0026sup2;), a non-smoker, presented with moderate, non-reversible obstruction and FeNO of 29 ppb; HRCT was normal, indicating probable pollutant-induced COPD.\u003c/p\u003e\n\u003cp\u003eThe fourth, a 33-year-old male (2 years, BMI 17.2 kg/m\u0026sup2;, 10 pack-years) with prior PTB, had intermediate FeNO (33 ppb), mixed spirometry findings, and HRCT showing early silicosis and residual PTB changes.\u003c/p\u003e\n\u003cp\u003eAdditionally, a 51-year-old female administrator (30 years, BMI 22.5 kg/m\u0026sup2;) and a 27-year-old female administrator (1 year, BMI 31.6 kg/m\u0026sup2;), both non-smokers, showed significant FEV1 variability suggestive of occupational asthma. Neither had elevated FeNO nor HRCT abnormalities.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: Full lung function assessment, imaging, and Correlations\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"601\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003ePulmonary Function and\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eImaging Assessments\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eAll staff\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(\u003cem\u003en\u003c/em\u003e=18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003eSite worker\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(\u003cem\u003en\u003c/em\u003e =11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003eAdministrative Staff (\u003cem\u003en\u003c/em\u003e=7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFull Lung Function Test\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eFVC (L)\u003c/p\u003e\n \u003cp\u003eFVC %\u003c/p\u003e\n \u003cp\u003eTLC (L)\u003c/p\u003e\n \u003cp\u003eTLC %\u003c/p\u003e\n \u003cp\u003eDLCO mL/mmHg/min\u003c/p\u003e\n \u003cp\u003eDLCO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.07 \u0026plusmn; 0.74\u003c/p\u003e\n \u003cp\u003e71.72\u0026plusmn; 11.7\u003c/p\u003e\n \u003cp\u003e5.42 \u0026plusmn; 1.58\u003c/p\u003e\n \u003cp\u003e96.22 \u0026plusmn; 21.4\u003c/p\u003e\n \u003cp\u003e20.69 \u0026plusmn; 5.2\u003c/p\u003e\n \u003cp\u003e83.11 \u0026plusmn;18.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.07 \u0026plusmn; 0.35\u003c/p\u003e\n \u003cp\u003e72.64 \u0026plusmn; 8.7\u003c/p\u003e\n \u003cp\u003e5.62 \u0026plusmn; 1.34\u003c/p\u003e\n \u003cp\u003e100.73 \u0026plusmn; 24.5\u003c/p\u003e\n \u003cp\u003e21.0 \u0026plusmn; 4.57\u003c/p\u003e\n \u003cp\u003e90.0 \u0026plusmn;19.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.07 \u0026plusmn; 1.15\u003c/p\u003e\n \u003cp\u003e70.29 \u0026plusmn; 16.2\u003c/p\u003e\n \u003cp\u003e5.10 \u0026plusmn; 1.96\u003c/p\u003e\n \u003cp\u003e89.14 \u0026plusmn; 14.3\u003c/p\u003e\n \u003cp\u003e20.21\u0026plusmn; 6.45\u003c/p\u003e\n \u003cp\u003e72.29 \u0026plusmn;13.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFull Lung Function Interpretation\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Normal\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Restrictive ventilatory disorder\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Obstructive ventilatory disorder\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Mixed ventilatory disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e10 (55.6%)\u003c/p\u003e\n \u003cp\u003e1 (5.6%)\u003c/p\u003e\n \u003cp\u003e6 (33.3%)\u003c/p\u003e\n \u003cp\u003e1 (5.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6 (54.5%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e4 (36.4%)\u003c/p\u003e\n \u003cp\u003e1 (9.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4 (57.1%)\u003c/p\u003e\n \u003cp\u003e1 (14.3%)\u003c/p\u003e\n \u003cp\u003e2 (33.3%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChest Radiograph\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNormal\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eMinimal Opacities\u003c/p\u003e\n \u003cp\u003eLarge Opacities\u003c/p\u003e\n \u003cp\u003eCardiomegaly\u003c/p\u003e\n \u003cp\u003eOld PTB changes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e79 (73.8%)\u003c/p\u003e\n \u003cp\u003e23 (21.5%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e4 (3.7%)\u003c/p\u003e\n \u003cp\u003e1 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e36 (61%)\u003c/p\u003e\n \u003cp\u003e20 (33.9%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e2 (3.4%)\u003c/p\u003e\n \u003cp\u003e1 (1.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e43 (89.6%)\u003c/p\u003e\n \u003cp\u003e3 (6.3%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e2 (4.1%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHRCT Thorax\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Normal\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Single Sub-centimetre nodule\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Mosaic attenuation\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Old PTB changes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e11 (0.9%)\u003c/p\u003e\n \u003cp\u003e4 (22.2%)\u003c/p\u003e\n \u003cp\u003e2 (11.1%)\u003c/p\u003e\n \u003cp\u003e1 (5.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5 (45.5%)\u003c/p\u003e\n \u003cp\u003e4 (36.4%)\u003c/p\u003e\n \u003cp\u003e1 (9.1%)\u003c/p\u003e\n \u003cp\u003e1 (9.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6 (85,7%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e1 (14.3%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eManifestation of occupational lung disease\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eObstructive ventilatory defect, with no significant smoking history Known Respiratory illness with worsening symptoms\u003c/p\u003e\n \u003cp\u003eRestrictive ventilatory defect from full Lung function test with HRCT\u003c/p\u003e\n \u003cp\u003eThorax\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eHRCT thorax features of specific pattern of occupational lung disease or pneumoconiosis\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eNormal spirometry with inter-visit\u003c/p\u003e\n \u003cp\u003evariability (FEV1 \u0026gt;200ml and \u0026gt;12%)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eTotal:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2(1.9%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e1 (0.9%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e1 (0.9%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2(1.9%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6 (5.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e1 (1.7%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e1 (1.7%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2 (3.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2 (4.2%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2 (4.2%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4 (8.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;Figure 2 shows a significant negative correlation between years of dust exposure and both FVC (r = -0.314, p \u0026lt; 0.01) and FEV1 (r = -0.347, p \u0026lt; 0.01), but not with FeNO (r = -0.084, p = 0.392).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3: Multilinear regression analysis of occupational lung disease on predictors. The results indicate that there is generally no significant correlation between occupational lung disease and FeNO, cigarette pack years, duration of dust exposure, symptoms, compliance with respirator use, or BMI. Notably, only cough symptoms demonstrate a significant association with occupational lung disease among site workers. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: Multilinear regression analysis of occupational lung disease on predictors\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"1011\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eAll staff (\u003cem\u003en\u003c/em\u003e=107)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eSite worker (\u003cem\u003en\u003c/em\u003e =59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eAdministrative Staff (\u003cem\u003en\u003c/em\u003e=48)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eStand B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003et static\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cem\u003eP-\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eStand B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003et static\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cem\u003eP-\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eStand B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003et static\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e- value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eConstant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-0.825\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.411\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-0.442\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.661\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.887\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFeNO level\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.565\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.573\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.964\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.952\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCigarette Pack Years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.222\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.825\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e1.155\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.254\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-0.073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-.439\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.663\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCompliance to the respirator\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e1.449\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.151\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.242\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e1.947\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.057\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.989\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYears exposed to dust\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.920\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.702\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-0.185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.854\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSymptom: Cough\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e1.797\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.438\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e3.351\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-0.124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.902\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSymptom: Shortness of breath\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e1.244\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.491\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.625\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-0.106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-0.565\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.575\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSymptom: Increased Sputum\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-0.162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-1.592\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-0.208\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-1.540\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-0.281\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.780\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.972\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-0.128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.898\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.240\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.812\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eStatistically significant if p \u0026lt;0.05\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e Our assessment indicated that the participants had three years of median dust exposure (range: 1\u0026ndash;11). Shortness of breath was the most frequently reported symptom, followed by chest tightness and cough. The prevalence of dyspnoea in this study exceeded that reported in India (14.6%) and Nigeria (6.5%), where cough predominated and shortness of breath was less common (16.7% in India; 40.7% in Nigeria) (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAlthough spirometry was normal in this study, 27.1% of participants exhibited impaired FeNO, suggesting possible eosinophilic airway inflammation or occupational asthma. A FeNO increase greater than 50% from baseline may indicate uncontrolled inflammation, which is relevant for diagnosing occupational asthma. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). However, repeated FeNO testing was not performed due to financial limitations, as it remains costly in Malaysia\u003c/p\u003e\u003cp\u003eOur analysis identified only six participants (5.6%) with evidence of occupational lung disease, and just one abnormal HRCT thorax result. This prevalence is notably lower than reports from studies in Australia (28.2%) and India (31.39%) (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). In comparison to the 2.6% incidence of occupational lung disease reported by the Department of Occupational Safety and Health (DOSH) Malaysia in 2023, our results align with this lower prevalence, which may be due to the strict regulations regarding respirator compliance and the policies implemented by the National Institute for Occupational Safety and Health (NIOSH) and the employing company aimed at preventing occupational lung disease.\u003c/p\u003e\u003cp\u003eThe study additionally reveals a significant negative correlation between the duration of exposure (in years) and both forced vital capacity (FVC) and forced expiratory volume in one second (FEV1), corroborating findings from a prior study conducted in India that reported a comparable negative correlation (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Furthermore, an observed negative correlation exists with fractional exhaled nitric oxide (FeNO), although this is considered non-significant. This indicates that prolonged exposure to dust within the quarry environment may ultimately contribute to the development of occupational lung disease after ten years or more, thereby emphasizing the importance of safety protocols and the use of PPE to prevent future complications. Our study noted a non-significant negative correlation between cigarette pack-years and FeNO. This finding is consistent with numerous global studies that likewise report a comparable negative correlation between pack-years of smoking and FeNO. Our study's absence of statistical significance may be attributed to the relatively small sample size compared to studies conducted by Persson et al (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWe also found no significant association between occupational lung disease, FeNO, cigarette pack-years, or PPE compliance. The limited number of diagnosed cases with occupational lung disease likely reduced statistical power. A larger sample size may reveal stronger associations.\u003c/p\u003e\u003cp\u003eIn this study, occupational lung disease is diagnosed in individuals who exhibit characteristics of obstructive spirometry in the absence of a significant history of respiratory illness or smoking (defined as fewer than 20 pack-years). These individuals may also possess pre-existing respiratory conditions such as asthma or chronic obstructive pulmonary disease (COPD), with exacerbated symptoms attributed to workplace exposure, or demonstrate a restrictive pattern upon comprehensive lung function tests, accompanied by high-resolution computed tomography (HRCT) findings indicative of occupational lung disease or pneumoconiosis. Participants presenting with obstructive ventilatory defects and notable smoking histories were excluded from the diagnosis of occupational lung disease, as the obstructive pattern is likely associated with smoking (COPD) or lifestyle factors rather than occupational exposure. This exclusion criterion applies to numerous male participants with significant smoking histories in both groups.\u003c/p\u003e\u003cp\u003eFurther analysis showed that none of the six workers diagnosed with occupational lung disease had FeNO levels above 50 parts per billion (ppb). These results indicate that FeNO testing may have limited applicability in diagnosing occupational lung disease; however, it remains a valuable tool for assessing asthma and airway inflammation due to its association with methacholine hyperresponsiveness. Studies have also demonstrated that consistently high FeNO levels are associated with a more rapid decline in lung function among patients with asthma. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAccording to OSHA's Respirable Crystalline Silica Rule, employers must keep silica dust levels below the permissible exposure limit (PEL) of 50 \u0026micro;g/m\u0026sup3; averaged over an eight-hour workday (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). This limit protects workers from the long-term health effects of silica exposure, particularly during mining processes involving quartz.\u003c/p\u003e\u003cp\u003eThe Mine Safety and Health Administration (MSHA) enforces a Permissible Exposure Limit (PEL) of 100 \u0026micro;g/m\u0026sup3; for respirable quartz. At the same time, a proposed regulation seeks to align this limit with OSHA's standards (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). To lower silica exposure in quarries, measures include maintaining engineering controls, using wet methods and local exhaust ventilation, isolating work processes with enclosures, integrating water and ventilation systems, following filter replacement protocols, avoiding dry sweeping or compressed air during cleaning, conducting air monitoring, providing properly fitted personal protective equipment (PPE) such as N95 respirators, informing workers about silica-related risks and safe practices, creating an exposure control plan, rotating job assignments, and performing routine equipment maintenance (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eA key limitation of this study is the absence of repeated FeNO testing during follow-up, which may have provided additional insight into changes over time but was constrained by cost considerations. The low incidence of occupational lung disease may also reflect the exclusion of participants with significant smoking histories, as their symptoms are more likely related to smoking than occupational exposure. Proper diagnosis of occupational asthma requires comprehensive monitoring, including peak flow measurements and symptom diaries, to establish a clear link to workplace exposure. Without these, whether observed respiratory variability indicates occupational lung disease or late-onset asthma remains uncertain. Increasing the sample size would enhance the statistical power to detect significant associations.\u003c/p\u003e\u003cp\u003eFuture studies should incorporate repeated FeNO testing to track changes and better identify uncontrolled airway inflammation or occupational asthma. Larger, multicentre cohorts would more accurately reflect the prevalence of occupational lung disease among quarry workers. The low incidence observed may stem from effective health and safety practices, though indirect exposures remain a concern. Enhanced engineering controls, such as HEPA filters in the workplace and consistent use of face masks or respirators, are essential to reduce risk further.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the Dean of the Faculty of Medicine, Universiti Kebangsaan Malaysia, Professor Datin Dr Marina Mat Baki, for her support and encouragement. We would also like to express our gratitude to Negeri Roadstone Sdn. Bhd. for their support and the facilities to conduct this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: MFAH. Data curation: MHAW, \u0026nbsp;AAA, MFMJ, MFAH. Formal analysis: MHAW, MFAH. Project administration: MHAW, \u0026nbsp;AAA, MFMJ, MFAH. Funding acquisition: MFAH. Methodology: MHAW, MFAH. Supervision: MFAH. Writing -original draft: MHAW, MFMJ, AAA. Writing, reviewing, and editing manuscripts: MFAH. All authors read and approved the final manuscript\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eAGrant was obtained from Negeri Roadstone Sdn. Bhd.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data set used and/or analysed during the current study is available from the corresponding author on reasonable request at [email protected].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Research Ethics Committee, Universiti Kebangsaan Malaysia (FF-2022-332). This study is in accordance with the Helsinki Declaration (IV adaptation). Informed consent to participate was obtained from all participants in the study.\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 that the research was conducted without any commercial or financial relationship that could be construed as a potential conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eVlahovich KP, Sood A. A 2019 update on occupational lung diseases: a narrative review. Pulmonary Therapy. 2021;7(1):75-87.\u003c/li\u003e\n\u003cli\u003eHamzah NA, Samsudin K, Abdul Samad NI. RESPIRABLE DUST EXPOSURE AND RESPIRATORY HEALTH AMONG MALE GRANITE QUARRY WORKERS IN KELANTAN, MALAYSIA. The Southeast Asian journal of tropical medicine and public health. 2023;54:11-34.\u003c/li\u003e\n\u003cli\u003eMALAYSIA-Act LO. Occupational Safety and Health Act 1994. 2008.\u003c/li\u003e\n\u003cli\u003e\u0026quot;Cole RJ. The HSE strategy for improved health in the mining industry. United Kingdom: Institution of Mining and Metallurgy, London (United Kingdom); 1996. Medium: X; Size: pp. 9-24 p.\u003c/li\u003e\n\u003cli\u003eEhrlich RI, White N, Norman R, Laubscher R, Steyn K, Lombard C, et al. Predictors of chronic bronchitis in South African adults. Int J Tuberc Lung Dis. 2004;8(3):369-76.\u003c/li\u003e\n\u003cli\u003eSiracusa A, De Blay F, Folletti I, Moscato G, Olivieri M, Quirce S, et al. Asthma and exposure to cleaning products\u0026ndash;a European A cademy of Allergy and Clinical Immunology task force consensus statement Allergy. 2013;68(12):1532-45.\u003c/li\u003e\n\u003cli\u003eStocks SJ, McNamee R, Van Der Molen HF, Paris C, Urban P, Campo G, et al. Trends in incidence of occupational asthma, contact dermatitis, noise-induced hearing loss, carpal tunnel syndrome and upper limb musculoskeletal disorders in European countries from 2000 to 2012. Occupational and environmental medicine. 2015;72(4):294-303.\u003c/li\u003e\n\u003cli\u003eBlanc PD. Occupation and COPD: a brief review. Journal of Asthma. 2012;49(1):2-4.\u003c/li\u003e\n\u003cli\u003eForouzanfar MH, Alexander L, Anderson HR, Bachman VF, Biryukov S, Brauer M, et al. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990\u0026ndash;2013: a systematic analysis for the Global Burden of Disease Study 2013. The Lancet. 2015;386(10010):2287-323.\u003c/li\u003e\n\u003cli\u003eRajavel S, Raghav P, Gupta MK, Muralidhar V. Silico-tuberculosis, silicosis and other respiratory morbidities among sandstone mine workers in Rajasthan- a cross-sectional study. PLoS One. 2020;15(4):e0230574.\u003c/li\u003e\n\u003cli\u003eSingh A. The prevalence of silicosis among granite quarry workers, of the government sector, in Peninsular Malaysia. Med J Malaysia. 1977;31(4):277-80.\u003c/li\u003e\n\u003cli\u003eOțelea MR, Fell AKM, Handra CM, Holm M, Filon FL, Mijakovski D, et al. The value of fractional exhaled nitric oxide in occupational diseases \u0026ndash; a systematic review. Journal of Occupational Medicine and Toxicology. 2022;17(1):14.\u003c/li\u003e\n\u003cli\u003eLim FL, Hashim Z, Than LTL, Md Said S, Hashim JH, Norb\u0026auml;ck D. Respiratory health among office workers in Malaysia and endotoxin and (1,3)-\u0026beta;-glucan in office dust. Int J Tuberc Lung Dis. 2019;23(11):1171-7.\u003c/li\u003e\n\u003cli\u003eDweik RA, Boggs PB, Erzurum SC, Irvin CG, Leigh MW, Lundberg JO, et al. An official ATS clinical practice guideline: interpretation of exhaled nitric oxide levels (FENO) for clinical applications. Am J Respir Crit Care Med. 2011;184(5):602-15.\u003c/li\u003e\n\u003cli\u003eGraham BL, Steenbruggen I, Miller MR, Barjaktarevic IZ, Cooper BG, Hall GL, et al. Standardization of Spirometry 2019 Update. An Official American Thoracic Society and European Respiratory Society Technical Statement. Am J Respir Crit Care Med. 2019;200(8):e70-e88.\u003c/li\u003e\n\u003cli\u003eKharitonov SA, Yates D, Barnes PJ. Increased nitric oxide in exhaled air of normal human subjects with upper respiratory tract infections. Eur Respir J. 1995;8(2):295-7.\u003c/li\u003e\n\u003cli\u003eGr\u0026uuml;nberg K, Kuijpers EA, de Klerk EP, de Gouw HW, Kroes AC, Dick EC, et al. Effects of experimental rhinovirus 16 infection on airway hyperresponsiveness to bradykinin in asthmatic subjects in vivo. Am J Respir Crit Care Med. 1997;155(3):833-8.\u003c/li\u003e\n\u003cli\u003eNwibo AN, Ugwuja E, Nwambeke NO, Emelumadu O, Ogbonnaya L. Pulmonary Problems among Quarry Workers of Stone Crushing Industrial Site at Umuoghara, Ebonyi State, Nigeria. The international journal of occupational and environmental medicine. 2012;3:178-85.\u003c/li\u003e\n\u003cli\u003eKhetan M, Babu BV. Silicosis prevalence and related issues in India: a scoping review. Journal of Occupational Medicine and Toxicology. 2025;20(1):3.\u003c/li\u003e\n\u003cli\u003eDhand N, Khatkar M. Statulator: An online statistical calculator. Sample size calculator for estimating a single proportion. 2014.\u003c/li\u003e\n\u003cli\u003eCotes JE. Medical Research Council Questionnaire on Respiratory Symptoms (1986). Lancet. 1987 Oct 31;2(8566):1028. doi: 10.1016/s0140-6736(87)92593-1. PMID: 2889937.\u003c/li\u003e\n\u003cli\u003eHamzah NA, Tamrin SBM, Ismail NH. Respiratory Health of Male Steel Workers in the Eastern Coast of Peninsular Malaysia. American Journal of Applied Sciences. 2015;12(5).\u003c/li\u003e\n\u003cli\u003eSociety AT. ATS/ERS recommendations for standardized procedures for the online and offline measurement of exhaled lower respiratory nitric oxide and nasal nitric oxide. Am J Respir Crit Care Med. 2005;171:912-30.\u003c/li\u003e\n\u003cli\u003eSmith AD, Cowan JO, Brassett KP, Filsell S, McLachlan C, Monti-Sheehan G, et al. Exhaled nitric oxide: a predictor of steroid response. Am J Respir Crit Care Med. 2005;172(4):453-9.\u003c/li\u003e\n\u003cli\u003eZacharasiewicz A, Wilson N, Lex C, Erin EM, Li AM, Hansel T, et al. Clinical use of noninvasive measurements of airway inflammation in steroid reduction in children. Am J Respir Crit Care Med. 2005;171(10):1077-82.\u003c/li\u003e\n\u003cli\u003eShaw DE, Berry MA, Thomas M, Green RH, Brightling CE, Wardlaw AJ, et al. The use of exhaled nitric oxide to guide asthma management: a randomized controlled trial. Am J Respir Crit Care Med. 2007;176(3):231-7.\u003c/li\u003e\n\u003cli\u003ePorsbjerg C, Lund TK, Pedersen L, Backer V. Inflammatory subtypes in asthma are related to airway hyperresponsiveness to mannitol and exhaled NO. J Asthma. 2009;46(6):606-12.\u003c/li\u003e\n\u003cli\u003eSzefler SJ, Martin RJ, King TS, Boushey HA, Cherniack RM, Chinchilli VM, et al. Significant variability in response to inhaled corticosteroids for persistent asthma. J Allergy Clin Immunol. 2002;109(3):410-8.\u003c/li\u003e\n\u003cli\u003eMeijer RJ, Postma DS, Kauffman HF, Arends LR, Ko\u0026euml;ter GH, Kerstjens HA. Accuracy of eosinophils and eosinophil cationic protein to predict steroid improvement in asthma. Clin Exp Allergy. 2002;32(7):1096-103.\u003c/li\u003e\n\u003cli\u003eSzefler SJ, Phillips BR, Martinez FD, Chinchilli VM, Lemanske RF, Strunk RC, et al. Characterization of within-subject responses to fluticasone and montelukast in childhood asthma. J Allergy Clin Immunol. 2005;115(2):233-42.\u003c/li\u003e\n\u003cli\u003eSociety BT, Network SIG. SIGN 158: British guideline on the management of asthma. SIGN. 2019.\u003c/li\u003e\n\u003cli\u003eAwaluddin SM, Mahjom M, Lim KK, Shawaluddin NS, Tuan Lah TMA. Occupational Disease and Injury in Malaysia: A Thematic Review of Literature from 2016 to 2021. J Environ Public Health. 2023;2023:1798434.\u003c/li\u003e\n\u003cli\u003eWHO. World Health Organization. Protecting workers\u0026rsquo; health. 2017 2017 [Available from: https://www.who.int/news-room/fact-sheets/detail/protecting-workers\u0026apos;-health.\u003c/li\u003e\n\u003cli\u003eKutty K, Shankar V, Raghuramaiah S. Effects of Prolonged Silica Exposure on Pulmonary Function Among Stone Quarry Workers in South India. International Journal of Health Sciences and Research. 2023;Volume 13:322-31.\u003c/li\u003e\n\u003cli\u003eDarb\u0026agrave; J, Ascanio M, Syk J, Alving K. Economic evaluation of the use of FeNO for the diagnosis and management of Asthma patients in primary care in Sweden. ClinicoEconomics and Outcomes Research. 2021:289-97.\u003c/li\u003e\n\u003cli\u003eArumugam E, Rajkumar P, Dhanaraj B, Govindasamy E, Jaganathasamy N, Mathiyazhakan M, et al. Determining pulmonary function and the associated risk factors among stone quarry workers in a suburban area of Chennai, Tamil Nadu, India. Lung India. 2021;38(6):558-63.\u003c/li\u003e\n\u003cli\u003eHoy RF, Dimitriadis C, Abramson M, Glass DC, Gwini S, Hore-Lacy F, et al. Prevalence and risk factors for silicosis among a large cohort of stone benchtop industry workers. Occup Environ Med. 2023;80(8):439-46.\u003c/li\u003e\n\u003cli\u003eMG P. Single-breath nitric oxide measurements in asthmatic patients and smokers. Lancet. 1994;343:133-5.\u003c/li\u003e\n\u003cli\u003eSafety O, Administration H. Small entity compliance guide for the respirable crystalline silica standard for general industry and maritime. Washington, DC: Occupational Safety and Health. 2017.\u003c/li\u003e\n\u003cli\u003eGottesfeld P, Tirima S, Anka SM, Fotso A, Nota MM. Reducing Lead and Silica Dust Exposures in Small-Scale Mining in Northern Nigeria. Ann Work Expo Health. 2019;63(1):1-8.\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":"Fractional Exhaled Nitric Oxide (FeNO), Occupational Lung disease, Quarry, Spirometry","lastPublishedDoi":"10.21203/rs.3.rs-7497811/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7497811/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Occupational lung diseases are common among quarry workers due to exposure to dust and chemicals. This study examines FeNO levels, lung function, respiratory symptoms, and occupational lung disease prevalence, focusing on safety practices in a stone quarry.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e This cross-sectional study recruited 107 quarry workers using a universal sampling method. Health data were collected via a validated modified British Medical Research Council Questionnaire. Objective data included spirometry, chest imaging, FeNO measurement, and full lung function tests, followed by High-Resolution Computed Tomography (HRCT) of the Thorax if indicated.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eAmong quarry workers, 68.2% had normal spirometry, 25.2% showed Preserved Ratio Impaired Spirometry (PRISm) ventilatory defects, and 6.6% had obstructive ventilatory defects. Most had low FeNO levels (57%), with 25.2% at intermediate and 17.8% at high levels. Respiratory symptoms included breathlessness (25.2%), chest tightness (19.6%), and cough (15.9%). Administrators and site workers show similar results in FeNO and lung function tests. Only 52.3% occasionally adhered to respirators. Occupational lung disease prevalence was 5.6%. No significant correlations were identified between FeNO levels, symptoms, smoking, PPE use, or disease. However, more prolonged dust exposure was linked to reduced lung function.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eThe findings indicate that site and administrative personnel within the quarry industry face comparable risks of occupational lung disease, with observed lung function impairment and variable FeNO levels across the workforce. The occupational lung disease prevalence rate of 5.6% exceeds previously reported local figures, underscoring the necessity for improved dust control measures and consistent use of personal protective equipment among all employees. Strengthening safety protocols, including rigorous enforcement of PPE usage and strategic workplace modifications, is essential to mitigate health risks and reduce the burden of occupational lung diseases in this sector.\u003c/p\u003e","manuscriptTitle":"Assessment of Fractional Exhaled Nitric Oxide and Lung Function Among Quarry Workers","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-23 06:48:07","doi":"10.21203/rs.3.rs-7497811/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":"363c85a4-2a81-47d8-97e2-1e17cc5d3112","owner":[],"postedDate":"September 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-29T03:08:41+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-23 06:48:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7497811","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7497811","identity":"rs-7497811","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}