Exposure to Respirable Dust, Fine Particulates and Crystalline Silica and Comparative Respiratory Health Patterns Among Non-Smoking Workers in the Ceramic Industry

Exposure to Respirable Dust, Fine Particulates and Crystalline Silica and Comparative Respiratory Health Patterns Among Non-Smoking Workers in the Ceramic Industry | 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 Exposure to Respirable Dust, Fine Particulates and Crystalline Silica and Comparative Respiratory Health Patterns Among Non-Smoking Workers in the Ceramic Industry Ankit Sheth, Nikhil Kulkarni, Moinuddhin Mansuri, Ankit Viramgami This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8487804/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 The rapid expansion of ceramic tile industry in Morbi, Gujarat, has led to increased occupational exposure to respirable dust, fine particulates and crystalline silica, raising respiratory health concerns among workers. Limited data exist linking these exposures with respiratory health in this sector. Methods A cross-sectional comparative study was conducted among 256 lifelong non-smoking workers in ceramic tile factories, comprising production workers and administrative staff. Personal air sampling quantified respirable dust, PM2.5, and crystalline silica across major process zones. Respiratory symptoms were assessed using a validated questionnaire, and spirometry was performed following ATS-ERS guidelines. Multivariate regression models were adjusted for age, exposure duration, and job role to assess lung function parameters. Results Workers experienced higher exposure to respirable dust (up to 29.36 mg/m³) and PM2.5 (up to 3.85 mg/m³) compared to administrative staff. Crystalline silica exceeded recommended limits in high-exposure zones. The prevalence of upper and lower respiratory symptoms was 23.8% and 20.6% among workers versus 11.9% and 9.0% among administrative staff. Obstructive lung patterns were identified in 19% of workers compared with 9% of administrative staff. Across process zones, lung function values (FVC, FEV₁, and FEF25-75) showed a consistent decline with increasing dust and PM2.5 exposure levels. Age, exposure duration, and job role independently predicted significant declines in workers’ lung function. Conclusion Ceramic tile workers experience excessive exposure to respirable dust, PM2.5, and crystalline silica, with observed patterns indicating early obstructive lung function impairment. Targeted dust control, regular monitoring, and periodic spirometric surveillance are urgently needed. What is already known on this topic Occupational exposure to crystalline silica in ceramic tile manufacturing is known to cause adverse respiratory effects. However, previous studies often lacked comparison groups, included smokers, and did not adequately assess fine particulate matter (PM2.5) or control for confounding exposures such as biomass fuel use. What this study adds This comparative study among lifelong non-smoking ceramic tile workers demonstrates elevated exposure to respirable dust, PM2.5, and crystalline silica, with higher levels than permissible exposure limits in key production zones. It also establishes a clear association between exposure duration and declining lung function, while showing that even low-dust environments, such as administrative and reception sections, can contain significant proportions of PM2.5. How this study might affect research, practice or policy The findings highlight the need for strengthened dust control and routine monitoring of respirable dust, PM2.5, and crystalline silica in ceramic manufacturing. They support the inclusion of periodic spirometry and medical surveillance in worker health programs and call for stricter regulatory standards and longitudinal research on fine particulate exposure in similar industrial settings. INTRODUCTION The ceramic industry has witnessed remarkable growth in recent years, particularly in Morbi, Gujarat, emerging as one of the largest ceramic manufacturing clusters in the world. This industrial growth has resulted in increased workforce engagement and potential occupational exposure to respirable dust and crystalline silica generated during various production processes, including raw material handling, ball milling, spray drying, pressing, glazing, and kiln operations. Such exposure poses significant respiratory health risks for workers in these environments. Occupational exposure to respirable crystalline silica (RCS) has been strongly associated with a range of respiratory conditions, including silicosis, pneumoconiosis, chronic bronchitis, chronic obstructive pulmonary disease (COPD), and lung cancer. [ 1 – 6 ] While the long-term effects of silica exposure have been well documented, limited attention has been given to early or subclinical respiratory effects, such as airway obstruction, irritation, or acute inflammatory changes. Furthermore, most studies have focused on larger respirable particles, with scarce data on fine particulate matter (PM2.5) in ceramic work environments. Fine particulates can penetrate deeper into the lungs, induce oxidative stress and inflammation, and may contribute to the early onset of chronic respiratory impairment [ 7 ]. Another gap in the existing literature is the inadequate quantification of respirable crystalline silica within respirable dust samples. While regulatory agencies such as the Occupational Safety and Health Administration (OSHA) and the American Conference of Governmental Industrial Hygienists (ACGIH) have set permissible exposure limits (PELs) or threshold limit value (TLV) for crystalline silica, accurate field-level measurements of RCS remain limited in ceramic tile manufacturing [ 8 , 9 ]. This lack of empirical exposure data restricts reliable risk assessment and the development of effective dust control strategies. Previous studies on ceramic tile workers often suffered from methodological limitations, including the absence of comparison groups, the inclusion of smokers, and inadequate adjustment for confounders such as biomass fuel exposure and pre-existing respiratory illness. The present study addresses these gaps by including a comparison group of administrative staff, enrolling lifelong non-smokers, and adjusting for key confounders. It aims to assess occupational exposure to respirable dust, its fine particulate fraction (PM2.5), and crystalline silica using standard industrial hygiene protocols, and examines respiratory health patterns among ceramic tile workers. This approach provides a comprehensive assessment of exposure and health effects within a real-world ceramic manufacturing environment. METHODS Study Design and Setting This cross-sectional comparative study was conducted between June and December 2023 in the industrial zone of Morbi, Gujarat, which is India's largest and globally recognized hub for ceramic tile manufacturing. This region houses over 800 ceramic production units that account for ~ 90% of national output. The manufacturing process in these units typically includes ball mill wet grinding, spray drying, pressing, high-temperature baking (ranging from 1100°C to 1500°C), glazing, firing, polishing, 3D printing, sorting, and packaging. Due to the nature of these operations, especially those involving the handling and transformation of raw materials at elevated temperatures, the inhalation of airborne particulates emerges as the predominant route of occupational exposure in this setting. The study adhered to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines for cross-sectional reporting. [ 10 ] Study Population The study population included full-time ceramic tile workers engaged in production processes and administrative staff working in non-dusty sections of the same factories. To ensure chronic exposure assessment, only those with ≥ 2 years of employment were included. To minimize bias from non-occupational and pre-existing respiratory disease, the study included only lifelong non-smokers and excluded individuals with a documented history of childhood respiratory illnesses, acute respiratory infection within the prior four weeks, or prior chest injury or thoracic surgery before employment. Administrative staff were selected as a comparison group representing the low-exposure population. Sample Size and Sampling Strategy The sample size was calculated to detect a prevalence of chronic respiratory abnormality of 27% (from previous occupational study) with 95% confidence, 80% power and 20% relative precision [ 11 ]. Using the single-proportion formula: where \(\:{Z}_{1-\alpha\:/2}=1.96\) , \(\:p=0.268\) , and \(\:d=0.2\times\:p\) , the minimum required sample size was calculated as n = 256. A proportional allocation approach was used to recruit participants across four factory units representing different production scales and process zones (ball mill, spray dryer, kiln, and administrative/reception). Study Tools and Data Collection Exposure Assessment: Respirable Dust and Fine Particulate Matter (PM2.5) Measurement A preliminary walk-through survey identified representative high-exposure zones (ball mill, spray dryer, kiln) and a low-exposure zone (reception) within ceramic tile factories for personal air monitoring. Respirable dust was measured using battery-powered personal dust samplers (Model: SideKick-51MTX, Make: M/s. SKC Ltd., USA) fitted with a plastic cyclone and 37 mm polyvinyl chloride (PVC) filters (5 µm pore size) mounted in 3-piece cassette. For respirable dust sampling, the pumps were operated at 2.2 L/min , calibrated pre- and post-shift using a rotameter. The cyclone served as both the size-selective device and filter housing, in accordance with NIOSH Method 0600 and ISO 7708:1995 , ensuring collection of the respirable dust fraction on the filter cassette located within the cyclone [ 12 , 13 ]. Filters were conditioned in a desiccator with silica gel for 24 hours prior to pre-weighing using a precision microbalance (Shimadzu AUX-220; 0.001 g resolution). The assembly was positioned in the worker’s breathing zone and secured to the worker for the full shift. Field blanks were collected at each sampling event to assess contamination. After sampling, cassettes housing the filters were sealed and transported to the laboratory; each filter was re-conditioned and post-weighed under the same environmental conditions as pre-weighing. PM2.5 sampling was performed concurrently using the same model of pump fitted with a Personal Environmental Monitor (PEM) (Model/Part: 761 − 203, Make M/s SKC Inc., USA) and 37 mm polytetrafluoroethylene (PTFE) filters. The PM2.5 sampling flow was 2.0 L/min , the manufacturer-specified flow rate ensuring a 50% cut-point at 2.5 µm aerodynamic diameter. This setup aligns with NIOSH Method 0600 (adapted for fine particulates) and OSHA ID-142 conventions [ 12 , 14 ]. The pumps and PEM assemblies were calibrated before and after each sampling shift. The filter paper laden dust samples were transported to the laboratory in filter keepers and post weighing was carried out in similar conditions as outlined above. The 8-hour time-weighted average (TWA) concentration for each filter was calculated as: where \(\:{W}_{post}-{W}_{pre}\) is the mass gain on the filter (mg), \(\:Q\) is the mean sampler flow rate during sampling (L/min) and \(\:T\) is the sampling duration (minutes). The sampled air volume (L) was converted to cubic meters for the concentration calculation. Field blanks were subtracted where appropriate and samples below limit of detection were handled per laboratory standard operating procedures. Crystalline Silica Analysis Respirable dust filters were analysed for crystalline silica content using Fourier Transform Infrared (FTIR) (Model: Alpha T, Make: Bruker, USA) spectroscopy following NIOSH Method 7602 to ensure reproducibility [ 15 ]. The dust-laden PVC filters were washed with 13.8% w/w hydrochloric acid to remove impurities, rinsed, and oven-dried. Filters were then ashed in a furnace at 600°C for three hours. The residue was mixed with 0.2 g IR-grade potassium bromide (KBr) (Make: Fischer Scientific, USA), homogenised in an agate mortar pestle, and pressed into pellets using a hydraulic press. These pellets were then quantitatively analyzed for presence of crystalline silica against calibration curves prepared from certified reference quartz standards (NIST 1878a). Replicate analyses (10% of samples) and QC standards were run for accuracy and precision verification. Questionnaire A structured questionnaire was used to collect information on sociodemographic characteristics, occupational history, and medical history. Respiratory symptoms were assessed using a modified version of the American Thoracic Society–Division of Lung Diseases (ATS-DLD-78-A) questionnaire, a validated and widely used tool in occupational respiratory health research [ 16 ]. The questionnaire was translated into the local language and pre-tested for clarity and comprehension without modification of its core symptom items. The adapted version demonstrated good internal consistency (Cronbach’s α = 0.82). Work-related upper respiratory symptoms (WRURS) and work-related lower respiratory symptoms (WRLRS) were derived from symptom items included in the ATS-DLD-78-A questionnaire and used as operational outcome measures. WRURS was defined as the presence of more-than-usual nasal symptoms (prickling or watering nose, or sneezing) during work, while WRLRS was defined as more-than-usual cough, phlegm production, shortness of breath, or wheezing occurring at work. Nonsmokers were defined as individuals who had never smoked in their lifetime. Pulmonary Function Testing (PFT) Spirometry was performed using a pre-calibrated Schiller SP-10 device, following ATS-ERS guidelines [ 17 ]. Each participant performed a minimum of three acceptable and two reproducible manoeuvres, with the highest values of FVC and FEV₁ recorded for analysis. Lung function parameters such as Forced Vital Capacity (FVC), Forced Expiratory Volume in first second (FEV1), FEV1/FVC, Mid-Expiratory Flow Volume (FEF25-75%), Peak Expiratory Flow Rate (PEFR) – were recorded. Considering age, gender and ethnicity, predicted values were calculated using Indian reference standards [ 18 ]. Lung function patterns were categorized as: Normal (FEV₁/FVC ≥ 70% and FVC ≥ 80%), Obstructive (FEV₁/FVC 80%), Restrictive (FEV₁/FVC ≥ 70% and FVC < 80%), and Combined (FEV₁/FVC < 70% and FVC < 80%). Study variables and measures: Dependent variables included spirometry outcomes (FVC%, FEV₁%, FEV₁/FVC, FEF25–75%, PEFR) and presence of respiratory symptoms. Independent variables included job role, duration of exposure, respirable dust concentration and crystalline silica levels, age, biomass use, and specific workplace sections (e.g., spray dryer, kiln, and reception). Exposure standards: Occupational exposure limits (TWA) for respirable dust are 3 mg/m³ (ACGIH) and 5 mg/m³ (OSHA) [ 19 ]. For crystalline silica, OSHA and Safe Work Australia prescribe 0.05 mg/m³ (TWA), with OSHA’s action level at 0.025 mg/m³ and ACGIH’s TLV at 0.025 mg/m³ [ 8 , 9 , 20 ]. In India, the permissible limit for respirable dust is calculated using Eq. 1 : Permissible respirable dust (mg/m³) = 10 / (% RCS + 2) , per Directorate General Factory Advice Service & Labour Institutes (DGFASLI) guidelines under the Factories Act, 1948 [ 21 ]. Data Management and Statistical Analysis Quantitative data were analysed using SPSS version 26.0 (IBM Corp., USA). Descriptive statistics (means, standard deviations, frequencies, and percentages) were used to summarize demographic characteristics, exposure concentrations, respiratory symptoms, and spirometry parameters. Mean values of continuous variables such as age, height, weight, FEV₁, FVC, FEV₁/FVC ratio, and FEF25-75% were compared between production workers and administrative staff using Student’s t -tests. Associations between categorical variables such as education level, duration of employment, respiratory symptoms, and spirometry classification were evaluated using Chi-square tests. Multivariate linear regression models were applied to assess the independent effects of age, duration of exposure, and job role (production worker vs. administrative staff) on spirometry outcomes. Regression coefficients ( β ) and 95% confidence intervals (CI) were reported for each model. Statistical significance was defined at p < 0.05. Because personal exposure monitoring was conducted on representative workers from each zone rather than all individuals, direct correlation between individual exposure and spirometry outcomes was not computed. Instead, descriptive comparison of mean spirometry patterns across exposure zones was performed to interpret exposure–response relationships. RESULTS Table 1 presents exposure data across different work zones. The highest TWA for respirable dust was recorded in spray dryer operators (29.36 mg/m³), exceeding the permissible limit based on RCS content (4.47 mg/m³). Ball mill operators also exceeded their threshold (6.44 mg/m³ vs. permissible 3.89 mg/m³). Kiln operators and reception staff had lower levels (2.84 mg/m³ and 0.66 mg/m³, respectively), both within permissible limits. Although absolute RCS concentrations were low, the proportion of crystalline silica within respirable dust varied across zones, highest among reception areas (1.29%) despite lower total dust levels. Table 1 Exposure Assessment: Respirable Dust, PM2.5, and Crystalline Silica Levels by Work Zone Location Respirable Dust TWA (mg/m³) PM2.5 TWA (mg/m³) Ratio (PM2.5 / Resp. Dust) RCS Concentration in Resp. Dust (mg/m³) % RCS in Resp. Dust Permissible Limit (mg/m³)* Ball Mill 6.44 1.04 0.16 0.058 0.57 3.89 Spray Dryer 29.36 3.85 0.13 0.109 0.24 4.47 Kiln 2.84 1.15 0.40 0.003 0.07 4.84 Reception 0.66 0.31 0.47 0.013 1.29 3.04 *Permissible limit for respirable dust calculated using: 10 / (% RCS + 2) (DGFASLI, India). PM2.5 concentrations followed a similar pattern, being highest in the spray dryer area (3.85 mg/m³), followed by kiln (1.15 mg/m³) and ball mill (1.04 mg/m³). The PM2.5-to-respirable dust ratio was greatest in the reception area (0.47), indicating a relatively higher fraction of fine particulates in areas with lower total dust exposure. A total of 256 lifelong non-smoking workers participated, including 189 production workers and 67 administrative staff (Table 2 ). While both groups were comparable in age, height, and weight, significant differences were observed in education and years of experience. Table 2 Demographic and occupational characteristics of the study participants (n = 256) Variables Workers (n = 189) Admin staff (n = 67) Significance Age in years, n (%) 18–30 118 (62.4) 32 (47.8) p = 0.11 31–40 42 (22.2) 20 (29.9) > 40 29 (15.4) 15 (22.3) Height in cm, mean (SD) 163.3 ± 6.8 164.1 ± 6.9 p = 0.41 Weight in kg, mean (SD) 64.6 ± 7.4 66.3 ± 6.9 p = 0.10 Education, n (%) No formal education 23 (12.1) 0 (0) p = 0.00 Primary education 81 (42.9) 3 (4.4) Higher secondary 62 (32.8) 15 (22.4) Graduate and beyond 23 (12.2) 49 (73.2) Years working in ceramic industry, n (%) 1–3 89 (47.1) 28 (41.8) p = 0.00 3–7 81 (42.9) 21 (31.3) > 7 19 (10.0) 18 (26.9) As summarized in Table 3 , respiratory symptoms were significantly more frequent among production workers compared to administrative staff: WRURS (23.8% vs. 11.9%, p = 0.03) and WRLRS (20.6% vs. 9.0%, p = 0.03). Spirometry revealed obstructive lung patterns in 19.0% of workers compared to 9.0% of administrative staff (p = 0.04). No restrictive or mixed patterns were detected. Mean lung function parameters were lower among production workers, with significant differences in FVC (4.0 vs. 4.5 L, p < 0.001), FEV1/FVC (80% vs. 89%, p < 0.001), and FEF 25–75% (3.7 vs. 4.3 L/s, p < 0.001). Table 3 Respiratory Symptoms and Lung Function Parameters Among Study Participants. Workers (n = 189) Admin staff (n = 67) Significance Respiratory symptoms WRURS 45 (23.8%) 8 (11.9%) p = 0.03 WRLRS 39 (20.6%) 6 (9.0%) p = 0.03 Lung function diagnosis Normal 153 (81.0%) 61 (91.0%) p = 0.04 Obstructive lung disease 36 (19.0%) 6 (9.0%) Restrictive lung disease 0 (0%) 0 (0%) Lung function parameter FEV1 3.3 ± 0.6 3.5 ± 0.8 p = 0.06 FVC 4.0 ± 0.9 4.5 ± 0.7 p = 0.00 FEV1/FVC 80 ± 7.3 89 ± 5.5 p = 0.00 FEF 25%–75% 3.7 ± 0.9 4.3 ± 0.8 p = 0.00 Multivariate regression (Table 4 ) demonstrated that increasing age and longer exposure duration were independently associated with declines in all lung function parameters. Job role (worker vs. admin) was significantly associated with reduced FEV1/FVC ratio (B = -2.35; p = 0.03) and FEF 25–75% (B = -0.01; p = 0.03), after adjusting for confounders. Table 4 Multivariate regression model for predictors of lung function parameters Predictor FVC FEV1 FEV1/FVC FEF 25%-75% B (95% CI) p-value B (95% CI) p-value B (95% CI) p-value B (95% CI) p-value Age (years) -0.04 (-0.08, -0.01) 0.01 -0.04 (-0.07, -0.02) 0.00 -0.32 (-0.53, -0.10) 0.01 -0.09 (-0.14, -0.04) 0.00 Duration of exposure (months) -0.05 (-0.01, -0.90) 0.04 -0.01 (-0.003, -0.01) 0.00 -0.03 (-0.06, -0.02) 0.01 -0.02 (-0.03, -0.01) 0.01 Job profile (worker vs admin) -0.23 (-0.56, 1.02) 0.56 -0.16 (-0.33, 0.65) 0.51 -2.35 (-3.65, -1.07) 0.03 -0.01 (-0.03, -0.002) 0.03 *type of cooking not included as all were using clean energy Table 5 shows the comparative patterns of exposure intensity and mean spirometry outcomes across different work zones. A clear inverse gradient was observed between exposure magnitude and lung function indices, with spray dryer and ball mill operators showing the lowest mean FEV₁ and FEV₁/FVC ratios, followed by kiln and reception staff. These findings collectively indicate an exposure–response trend consistent with occupational dust effects on respiratory health, even though individual-level exposure correlations could not be established due to smaller representative sampling by zone. Table 5 Comparative Patterns of Exposure Intensity and Mean Spirometry Values by Work Zone. Work Zone Mean Respirable Dust (mg/m³) Mean PM2.5 (mg/m³) % RCS in Resp. Dust Mean FEV₁ (L) Mean FEV₁/FVC (%) Interpretation Spray Dryer 29.36 3.85 0.24 3.1 77 Highest exposure, lowest lung function Ball Mill 6.44 1.04 0.57 3.2 80 Moderate exposure, mild reduction Kiln 2.84 1.15 0.07 3.4 84 Intermediate exposure Reception/ admin 0.66 0.31 1.29 3.5 89 Lowest exposure, normal function DISCUSSION This cross-sectional comparative study examined occupational exposure to respirable dust, fine particulate matter (PM2.5), and crystalline silica and their relationship with respiratory health patterns among non-smoking workers of ceramic tile industry. The study revealed markedly higher exposure levels among production workers compared with administrative staff, accompanied by a higher prevalence of respiratory symptoms and reduced lung function, underscoring a clear occupational influence. Occupational exposure of respirable dust and crystalline silica Ceramic manufacturing processes generate substantial amounts of airborne dust, yet effective local exhaust ventilation and personal protective practices are often lacking. In this study, the measured levels of respirable dust in high-exposure zones such as ball mill and spray-drying substantially exceeded permissible occupational exposure limits, reflecting inadequate dust control in these sections. Although crystalline silica content in respirable dust was relatively low in absolute concentration, it surpassed recommended thresholds in high-exposure zones, posing considerable health risks due to its fibrogenic and carcinogenic potential [ 22 ]. The observation that reception areas—nominally low-exposure zones—had a higher percentage of silica within dust samples suggests that airborne silica can disperse widely across facilities. This aligns with previous research in Iran and Egypt documenting cross-contamination of silica particles between production and administrative areas in ceramic and stone industries, emphasizing the need for comprehensive environmental control beyond production lines [ 23 – 25 ] Fine particulate matter (PM2.5) and its significance The study additionally highlights the neglected burden of fine particulate exposure in ceramic workplaces. The highest PM2.5 levels were observed in spray drying and ball milling areas, while the reception area showed the highest PM2.5-to-respirable dust ratio. Fine particulates, because of their small aerodynamic diameter, penetrate deep into alveoli, inducing oxidative stress and inflammatory injury [ 7 ]. Similar findings have been documented in tile and refractory industries, where PM2.5 exposures correlate with higher respiratory and cardiovascular morbidity [ 26 – 29 ]. This underscores the need to incorporate PM2.5 monitoring within routine occupational surveillance, which is often overlooked in current ceramic industry standards. Respiratory health outcomes and exposure–response pattern Workers in the production sections reported a significantly higher prevalence of both upper and lower respiratory symptoms compared to administrative staff, consistent with the elevated exposure levels observed. This pattern aligns with reports from other ceramic and silica-exposed occupational groups, where cough, phlegm, and breathlessness were common early symptoms of exposure-related airway irritation and inflammation [ 30 ]. Several studies in Iran, Egypt, and Italy have similarly documented higher respiratory symptom prevalence among production workers than administrative or control groups, reflecting the universal nature of these occupational risks [ 31 – 33 ]. Lung function assessment revealed a predominance of obstructive ventilatory patterns among exposed workers, suggesting early small airway involvement. This pattern likely reflects shorter employment duration (< 5 years for most participants), as obstructive changes from chronic bronchial inflammation occur earlier than the restrictive fibrotic defects seen with prolonged silica exposure. This interpretation is consistent with findings by Hoy et al. [ 34 ], Neghab et al. [ 35 ], and Golbabaei et al. [ 36 ], who reported obstructive patterns in early-stage exposure and mixed or restrictive patterns only after extended occupational tenure . Determinants of lung function decline Zone-wise comparison revealed an inverse gradient between exposure intensity and mean spirometry values, with spray dryer and ball mill operators showing the poorest lung function indices. Multivariate regression analysis showed that exposure duration was independently associated with declines in FVC, FEV₁, and mid-expiratory flows. The association between job role and airflow limitation remained significant. These findings indicate a clear exposure-response relationship and strengthen the occupational etiology of airway obstruction among ceramic tile workers. Comparable studies among industrial dust-exposed populations have consistently demonstrated that increasing duration of exposure correlates with progressive deterioration in lung function [ 31 , 37 ]. Public health implications The current findings have direct implications for occupational hygiene and worker protection. The persistently high dust levels in spray drying and milling sections call for stricter engineering controls, including local exhaust ventilation, process enclosure, and real-time dust monitoring. Regular spirometry and medical surveillance should be mandated for early detection of occupational airway disease. Finally, the inclusion of PM2.5 in workplace exposure standards—currently absent in most national frameworks—should be prioritized to address the growing burden of fine particulate pollution in industrial settings. Strengths and Limitations A key strength of the present study is the inclusion of an internal comparison group of administrative staff working within the same industrial premises, thereby controlling for shared environmental and socio-demographic factors. The exclusion of smokers and individuals with pre-existing respiratory diseases further minimized confounding. Moreover, the study combined environmental monitoring with health assessments, integrating quantitative exposure data, crystalline silica content, and respiratory health to provide a holistic understanding of exposure–response dynamics. Some limitations should be acknowledged. First, the cross-sectional design restricts causal inference between exposure and respiratory outcomes. Second, exposure assessment was based on representative sampling within each production zone rather than individual monitoring, precluding formal correlation analysis. Third, the healthy-worker effect cannot be ruled out, as severely affected workers might have left employment, leading to potential underestimation of disease prevalence. CONCLUSION This study identified substantially elevated levels of respirable dust in high-exposure processes such as spray drying and ball milling, exceeding permissible limits. Production workers exhibited a higher prevalence of respiratory symptoms and obstructive ventilatory patterns compared with administrative staff. An exposure-response gradient was evident, with lung function parameters progressively declining across zones of increasing dust intensity. These findings highlight the urgent need for comprehensive dust mitigation strategies such as engineering controls, enclosure of emission sources, and wet suppression coupled with routine exposure monitoring and periodic spirometry-based health surveillance to protect this workforce. Future longitudinal studies should further evaluate temporal changes in lung function and assess systemic health effects of chronic particulate exposure in the ceramic industry. Declarations Ethics approval and consent to participate: The study was approved by the Institutional Human Ethics Committee of ICMR-National Institute of Occupational Health (ICMR-NIOH/EC/2021-22) and conducted in accordance with the Helsinki Declaration. Written informed consent was obtained from all participants, who were assured of confidentiality, anonymity, and their right to withdraw at any time. Consent for publication: Written informed consent was taken from participants for use of data generated during the interviews for the purpose of publication. Competing interests: The authors declare no competing interests. Funding: Intramural seed funding from ICMR-National Institute of Occupational Health Declaration of Conflict of interest: None Author Contribution AS, NK, and AV conceived and designed the study. AS, NK, MM, and AV contributed to literature review, data collection, and manuscript revision. AS, NK, and AV performed data analysis and interpretation. AS drafted the manuscript. All authors reviewed and approved the final version. Acknowledgement We thank all study participants and the management of the participating industries for their cooperation and support. Data Availability The datasets generated are not publicly available due to privacy concerns but are available from the corresponding author upon reasonable request. 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Cincinnati, OH: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention; 2017. Ferris BG. Epidemiology Standardization Project (American Thoracic Society). Am Rev Respir Dis. 1978;118(6 Pt 2):1–120. Stanojevic S, Kaminsky DA, Miller MR, Thompson B, Aliverti A, Barjaktarevic I, et al. ERS/ATS technical standard on interpretive strategies for routine lung function tests. Eur Respir J. 2022;60(1):2101499. Aggarwal AN, Agarwal R, Dhooria S, Prasad KT, Sehgal IS, Muthu V, et al. Joint Indian Chest Society-National College of Chest Physicians (India) guidelines for spirometry. Lung India. 2019;36(Supplement):S1–35. Particulates Not Otherwise Regulated, Total and Respirable Dust (PNOR) Washington, DC: Occupational Safety and Health Administration (OSHA). 2023 [updated 2023/06/26. Available from: https://www.osha.gov/chemicaldata/801 Workplace exposure limits for airborne contaminants. Canberra, Australia: Safe Work Australia; 2024. Model Rules under the Factories Act. 1948 (Corrected up to 15-12-2020). Mumbai, India: Directorate General, Factory Advice Service and Labour Institutes, Ministry of Labour and Employment, Government of India; 2020. Mohamed SH, El-Ansary AL, El-Aziz EMA. Determination of crystalline silica in respirable dust upon occupational exposure for Egyptian workers. Ind Health. 2018;56(3):255–63. Mohammadyan M, Rokni M, Yosefinejad R. Occupational exposure to respirable crystalline silica in the Iranian Mazandaran province industry workers. Arh Hig Rada Toksikol. 2013;64(1):139–43. Omidianidost A, Ghasemkhani M, Kakooei H, Shahtaheri SJ, Ghanbari M. Risk Assessment of Occupational Exposure to Crystalline Silica in Small Foundries in Pakdasht, Iran. Iran J Public Health. 2016;45(1):70–5. Rahimimoghadam S, Ganjali A, Khanjani N, Normohammadi M, Yari S. Application of Multiple Occupational Health Risk Assessment Models for Crystalline Silica Dust among Stone Carvers. Asian Pac J Cancer Prev. 2023;24(11):3999–4005. Basith S, Manavalan B, Shin TH, Park CB, Lee WS, Kim J et al. The Impact of Fine Particulate Matter 2.5 on the Cardiovascular System: A Review of the Invisible Killer. Nanomaterials (Basel). 2022;12(15). Guo J, Chai G, Song X, Hui X, Li Z, Feng X, et al. Long-term exposure to particulate matter on cardiovascular and respiratory diseases in low- and middle-income countries: A systematic review and meta-analysis. Front Public Health. 2023;11:1134341. Krittanawong C, Qadeer YK, Hayes RB, Wang Z, Thurston GD, Virani S, et al. PM(2.5) and cardiovascular diseases: State-of-the-Art review. Int J Cardiol Cardiovasc Risk Prev. 2023;19:200217. Nasri SM, Putri FA, Sunarno S, Fauzia S, Ramdhan DH. PM(2.5) exposure and lung function impairment among fiber-cement industry workers. J Public Health Res. 2023;12(1):22799036221148989. Dehghan F, Mohammadi S, Sadeghi Z, Attarchi M. Respiratory Complaints and Spirometric Parameters in Tile and Ceramic Factory Workers. TANAFFOS (Respiration). 2009;8(4autumn):19–25. Halvani GH, Zare M, Halvani A, Barkhordari A. Evaluation and comparison of respiratory symptoms and lung capacities in tile and ceramic factory workers of Yazd. Arh Hig Rada Toksikol. 2008;59(3):197–204. Rondon EN, Silva RM, Botelho C. Respiratory symptoms as health status indicators in workers at ceramics manufacturing facilities. J Bras Pneumol. 2011;37(1):36–45. Saad-Hussein A, Morcos NY, Rizk SA, Ibrahim KS, El-Zaher NA, Moubarz G. Aspergillus hazardous problem in ceramic workers. Toxicol Ind Health. 2012;28(10):886–93. Hoy RF, Chambers DC. Silica-related diseases in the modern world. Allergy. 2020;75(11):2805–17. Neghab M, Zadeh JH, Fakoorziba MR. Respiratory toxicity of raw materials used in ceramic production. Ind Health. 2009;47(1):64–9. Golbabaei F, Abedinlou R, Fekri N, Shapasandi A, Mohammadi H. A study on the five-year change trend in pulmonary function of workers in tile and ceramic industry. J Health Saf Work. 2020;10(1):37–45. Abdel Monaem AM, Abdel Rasoul GM, Gabr HM, Allam HK, Badr S. Respiratory and auditory disorders in a ceramic manufacturing factory (Queisna City, Menoufia Governorate). Menoufia Med J. 2017;30(2):595–601. Additional Declarations No competing interests reported. Supplementary Files SupplementaryFile1.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. 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09:45:20","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":14552,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8487804/v1/4cf8275f64b651d682ffc3be.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Exposure to Respirable Dust, Fine Particulates and Crystalline Silica and Comparative Respiratory Health Patterns Among Non-Smoking Workers in the Ceramic Industry","fulltext":[{"header":"What is already known on this topic","content":"\u003cp\u003eOccupational exposure to crystalline silica in ceramic tile manufacturing is known to cause adverse respiratory effects. However, previous studies often lacked comparison groups, included smokers, and did not adequately assess fine particulate matter (PM2.5) or control for confounding exposures such as biomass fuel use.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhat this study adds\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis comparative study among lifelong non-smoking ceramic tile workers demonstrates elevated exposure to respirable dust, PM2.5, and crystalline silica, with higher levels than permissible exposure limits in key production zones. It also establishes a clear association between exposure duration and declining lung function, while showing that even low-dust environments, such as administrative and reception sections, can contain significant proportions of PM2.5.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHow this study might affect research, practice or policy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe findings highlight the need for strengthened dust control and routine monitoring of respirable dust, PM2.5, and crystalline silica in ceramic manufacturing. They support the inclusion of periodic spirometry and medical surveillance in worker health programs and call for stricter regulatory standards and longitudinal research on fine particulate exposure in similar industrial settings.\u003c/p\u003e"},{"header":"INTRODUCTION","content":"\u003cp\u003eThe ceramic industry has witnessed remarkable growth in recent years, particularly in Morbi, Gujarat, emerging as one of the largest ceramic manufacturing clusters in the world. This industrial growth has resulted in increased workforce engagement and potential occupational exposure to respirable dust and crystalline silica generated during various production processes, including raw material handling, ball milling, spray drying, pressing, glazing, and kiln operations. Such exposure poses significant respiratory health risks for workers in these environments.\u003c/p\u003e \u003cp\u003eOccupational exposure to respirable crystalline silica (RCS) has been strongly associated with a range of respiratory conditions, including silicosis, pneumoconiosis, chronic bronchitis, chronic obstructive pulmonary disease (COPD), and lung cancer. [\u003cspan additionalcitationids=\"CR2 CR3 CR4 CR5\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] While the long-term effects of silica exposure have been well documented, limited attention has been given to early or subclinical respiratory effects, such as airway obstruction, irritation, or acute inflammatory changes. Furthermore, most studies have focused on larger respirable particles, with scarce data on fine particulate matter (PM2.5) in ceramic work environments. Fine particulates can penetrate deeper into the lungs, induce oxidative stress and inflammation, and may contribute to the early onset of chronic respiratory impairment [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAnother gap in the existing literature is the inadequate quantification of respirable crystalline silica within respirable dust samples. While regulatory agencies such as the Occupational Safety and Health Administration (OSHA) and the American Conference of Governmental Industrial Hygienists (ACGIH) have set permissible exposure limits (PELs) or threshold limit value (TLV) for crystalline silica, accurate field-level measurements of RCS remain limited in ceramic tile manufacturing [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. This lack of empirical exposure data restricts reliable risk assessment and the development of effective dust control strategies.\u003c/p\u003e \u003cp\u003ePrevious studies on ceramic tile workers often suffered from methodological limitations, including the absence of comparison groups, the inclusion of smokers, and inadequate adjustment for confounders such as biomass fuel exposure and pre-existing respiratory illness. The present study addresses these gaps by including a comparison group of administrative staff, enrolling lifelong non-smokers, and adjusting for key confounders. It aims to assess occupational exposure to respirable dust, its fine particulate fraction (PM2.5), and crystalline silica using standard industrial hygiene protocols, and examines respiratory health patterns among ceramic tile workers. This approach provides a comprehensive assessment of exposure and health effects within a real-world ceramic manufacturing environment.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Setting\u003c/h2\u003e \u003cp\u003eThis cross-sectional comparative study was conducted between June and December 2023 in the industrial zone of Morbi, Gujarat, which is India's largest and globally recognized hub for ceramic tile manufacturing. This region houses over 800 ceramic production units that account for ~\u0026thinsp;90% of national output. The manufacturing process in these units typically includes ball mill wet grinding, spray drying, pressing, high-temperature baking (ranging from 1100\u0026deg;C to 1500\u0026deg;C), glazing, firing, polishing, 3D printing, sorting, and packaging. Due to the nature of these operations, especially those involving the handling and transformation of raw materials at elevated temperatures, the inhalation of airborne particulates emerges as the predominant route of occupational exposure in this setting. The study adhered to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines for cross-sectional reporting. [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Population\u003c/h3\u003e\n\u003cp\u003eThe study population included full-time ceramic tile workers engaged in production processes and administrative staff working in non-dusty sections of the same factories. To ensure chronic exposure assessment, only those with \u0026ge;\u0026thinsp;2 years of employment were included.\u003c/p\u003e \u003cp\u003eTo minimize bias from non-occupational and pre-existing respiratory disease, the study included only lifelong non-smokers and excluded individuals with a documented history of childhood respiratory illnesses, acute respiratory infection within the prior four weeks, or prior chest injury or thoracic surgery before employment. Administrative staff were selected as a comparison group representing the low-exposure population.\u003c/p\u003e\n\u003ch3\u003eSample Size and Sampling Strategy\u003c/h3\u003e\n\u003cp\u003eThe sample size was calculated to detect a prevalence of chronic respiratory abnormality of 27% (from previous occupational study) with 95% confidence, 80% power and 20% relative precision [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Using the single-proportion formula:\u003c/p\u003e\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\" style=\"width: 217px; height: 77.1556px;\" width=\"217\" height=\"77.1556\"\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{Z}_{1-\\alpha\\:/2}=1.96\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:p=0.268\\)\u003c/span\u003e\u003c/span\u003e, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:d=0.2\\times\\:p\\)\u003c/span\u003e\u003c/span\u003e, the minimum required sample size was calculated as n\u0026thinsp;=\u0026thinsp;256.\u003c/p\u003e \u003cp\u003eA proportional allocation approach was used to recruit participants across four factory units representing different production scales and process zones (ball mill, spray dryer, kiln, and administrative/reception).\u003c/p\u003e\n\u003ch3\u003eStudy Tools and Data Collection\u003c/h3\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eExposure Assessment: Respirable Dust and Fine Particulate Matter (PM2.5) Measurement\u003c/h2\u003e \u003cp\u003eA preliminary walk-through survey identified representative high-exposure zones (ball mill, spray dryer, kiln) and a low-exposure zone (reception) within ceramic tile factories for personal air monitoring.\u003c/p\u003e \u003cp\u003e \u003cb\u003eRespirable dust\u003c/b\u003e was measured using battery-powered personal dust samplers (Model: SideKick-51MTX, Make: M/s. SKC Ltd., USA) fitted with a plastic cyclone and 37 mm polyvinyl chloride (PVC) filters (5 \u0026micro;m pore size) mounted in 3-piece cassette. For respirable dust sampling, the pumps were operated at \u003cb\u003e2.2 L/min\u003c/b\u003e, calibrated pre- and post-shift using a rotameter. The cyclone served as both the size-selective device and filter housing, in accordance with \u003cem\u003eNIOSH Method 0600\u003c/em\u003e and \u003cem\u003eISO 7708:1995\u003c/em\u003e, ensuring collection of the respirable dust fraction on the filter cassette located within the cyclone [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Filters were conditioned in a desiccator with silica gel for 24 hours prior to pre-weighing using a precision microbalance (Shimadzu AUX-220; 0.001 g resolution). The assembly was positioned in the worker\u0026rsquo;s breathing zone and secured to the worker for the full shift. Field blanks were collected at each sampling event to assess contamination. After sampling, cassettes housing the filters were sealed and transported to the laboratory; each filter was re-conditioned and post-weighed under the same environmental conditions as pre-weighing.\u003c/p\u003e \u003cp\u003e \u003cb\u003ePM2.5\u003c/b\u003e sampling was performed concurrently using the same model of pump fitted with a Personal Environmental Monitor (PEM) (Model/Part: 761\u0026thinsp;\u0026minus;\u0026thinsp;203, Make M/s SKC Inc., USA) and 37 mm polytetrafluoroethylene (PTFE) filters. The PM2.5 sampling flow was \u003cb\u003e2.0 L/min\u003c/b\u003e, the manufacturer-specified flow rate ensuring a 50% cut-point at 2.5 \u0026micro;m aerodynamic diameter. This setup aligns with \u003cem\u003eNIOSH Method 0600\u003c/em\u003e (adapted for fine particulates) and \u003cem\u003eOSHA ID-142\u003c/em\u003e conventions [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The pumps and PEM assemblies were calibrated before and after each sampling shift. The filter paper laden dust samples were transported to the laboratory in filter keepers and post weighing was carried out in similar conditions as outlined above.\u003c/p\u003e \u003cp\u003eThe \u003cb\u003e8-hour time-weighted average (TWA) concentration\u003c/b\u003e for each filter was calculated as:\u003c/p\u003e \u003cp\u003e\u003cimg src=\"data:image/png;base64,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\" style=\"width: 236px; height: 50.4214px;\" width=\"236\" height=\"50.4214\"\u003e\u003c/p\u003e\u003cp\u003e where \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{W}_{post}-{W}_{pre}\\)\u003c/span\u003e\u003c/span\u003e is the mass gain on the filter (mg), \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:Q\\)\u003c/span\u003e\u003c/span\u003e is the mean sampler flow rate during sampling (L/min) and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:T\\)\u003c/span\u003e\u003c/span\u003e is the sampling duration (minutes). The sampled air volume (L) was converted to cubic meters for the concentration calculation. Field blanks were subtracted where appropriate and samples below limit of detection were handled per laboratory standard operating procedures.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eCrystalline Silica Analysis\u003c/h2\u003e \u003cp\u003eRespirable dust filters were analysed for crystalline silica content using Fourier Transform Infrared (FTIR) (Model: Alpha T, Make: Bruker, USA) spectroscopy following \u003cb\u003eNIOSH Method 7602\u003c/b\u003e to ensure reproducibility [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The dust-laden PVC filters were washed with 13.8% w/w hydrochloric acid to remove impurities, rinsed, and oven-dried. Filters were then ashed in a furnace at 600\u0026deg;C for three hours. The residue was mixed with 0.2 g IR-grade potassium bromide (KBr) (Make: Fischer Scientific, USA), homogenised in an agate mortar pestle, and pressed into pellets using a hydraulic press. These pellets were then quantitatively analyzed for presence of crystalline silica against calibration curves prepared from certified reference quartz standards (NIST 1878a). Replicate analyses (10% of samples) and QC standards were run for accuracy and precision verification.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eQuestionnaire\u003c/h3\u003e\n\u003cp\u003eA structured questionnaire was used to collect information on sociodemographic characteristics, occupational history, and medical history. Respiratory symptoms were assessed using a modified version of the American Thoracic Society\u0026ndash;Division of Lung Diseases (ATS-DLD-78-A) questionnaire, a validated and widely used tool in occupational respiratory health research [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The questionnaire was translated into the local language and pre-tested for clarity and comprehension without modification of its core symptom items. The adapted version demonstrated good internal consistency (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;0.82).\u003c/p\u003e \u003cp\u003eWork-related upper respiratory symptoms (WRURS) and work-related lower respiratory symptoms (WRLRS) were derived from symptom items included in the ATS-DLD-78-A questionnaire and used as operational outcome measures. WRURS was defined as the presence of more-than-usual nasal symptoms (prickling or watering nose, or sneezing) during work, while WRLRS was defined as more-than-usual cough, phlegm production, shortness of breath, or wheezing occurring at work. Nonsmokers were defined as individuals who had never smoked in their lifetime.\u003c/p\u003e\n\u003ch3\u003ePulmonary Function Testing (PFT)\u003c/h3\u003e\n\u003cp\u003eSpirometry was performed using a pre-calibrated Schiller SP-10 device, following ATS-ERS guidelines [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Each participant performed a minimum of three acceptable and two reproducible manoeuvres, with the highest values of FVC and FEV₁ recorded for analysis. Lung function parameters such as Forced Vital Capacity (FVC), Forced Expiratory Volume in first second (FEV1), FEV1/FVC, Mid-Expiratory Flow Volume (FEF25-75%), Peak Expiratory Flow Rate (PEFR) \u0026ndash; were recorded. Considering age, gender and ethnicity, predicted values were calculated using Indian reference standards [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Lung function patterns were categorized as: \u003cb\u003eNormal\u003c/b\u003e (FEV₁/FVC\u0026thinsp;\u0026ge;\u0026thinsp;70% and FVC\u0026thinsp;\u0026ge;\u0026thinsp;80%), \u003cb\u003eObstructive\u003c/b\u003e (FEV₁/FVC\u0026thinsp;\u0026lt;\u0026thinsp;70% and FVC\u0026thinsp;\u0026gt;\u0026thinsp;80%), \u003cb\u003eRestrictive\u003c/b\u003e (FEV₁/FVC\u0026thinsp;\u0026ge;\u0026thinsp;70% and FVC\u0026thinsp;\u0026lt;\u0026thinsp;80%), and \u003cb\u003eCombined\u003c/b\u003e (FEV₁/FVC\u0026thinsp;\u0026lt;\u0026thinsp;70% and FVC\u0026thinsp;\u0026lt;\u0026thinsp;80%).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStudy variables and measures:\u003c/h2\u003e \u003cp\u003eDependent variables included spirometry outcomes (FVC%, FEV₁%, FEV₁/FVC, FEF25\u0026ndash;75%, PEFR) and presence of respiratory symptoms.\u003c/p\u003e \u003cp\u003eIndependent variables included job role, duration of exposure, respirable dust concentration and crystalline silica levels, age, biomass use, and specific workplace sections (e.g., spray dryer, kiln, and reception).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eExposure standards:\u003c/h2\u003e \u003cp\u003eOccupational exposure limits (TWA) for respirable dust are 3 mg/m\u0026sup3; (ACGIH) and 5 mg/m\u0026sup3; (OSHA) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. For crystalline silica, OSHA and Safe Work Australia prescribe 0.05 mg/m\u0026sup3; (TWA), with OSHA\u0026rsquo;s action level at 0.025 mg/m\u0026sup3; and ACGIH\u0026rsquo;s TLV at 0.025 mg/m\u0026sup3; [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In India, the permissible limit for respirable dust is calculated using \u003cb\u003eEq.\u0026nbsp;1\u003c/b\u003e: \u003cb\u003ePermissible respirable dust (mg/m\u0026sup3;)\u0026thinsp;=\u0026thinsp;10 / (% RCS\u0026thinsp;+\u0026thinsp;2)\u003c/b\u003e, per Directorate General Factory Advice Service \u0026amp; Labour Institutes (DGFASLI) guidelines under the Factories Act, 1948 [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eData Management and Statistical Analysis\u003c/h2\u003e \u003cp\u003eQuantitative data were analysed using SPSS version 26.0 (IBM Corp., USA). Descriptive statistics (means, standard deviations, frequencies, and percentages) were used to summarize demographic characteristics, exposure concentrations, respiratory symptoms, and spirometry parameters. Mean values of continuous variables such as age, height, weight, FEV₁, FVC, FEV₁/FVC ratio, and FEF25-75% were compared between production workers and administrative staff using Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e-tests. Associations between categorical variables such as education level, duration of employment, respiratory symptoms, and spirometry classification were evaluated using Chi-square tests. Multivariate linear regression models were applied to assess the independent effects of age, duration of exposure, and job role (production worker vs. administrative staff) on spirometry outcomes. Regression coefficients (\u003cem\u003eβ\u003c/em\u003e) and 95% confidence intervals (CI) were reported for each model. Statistical significance was defined at \u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/em\u003e\u003c/p\u003e \u003cp\u003eBecause personal exposure monitoring was conducted on representative workers from each zone rather than all individuals, direct correlation between individual exposure and spirometry outcomes was not computed. Instead, descriptive comparison of mean spirometry patterns across exposure zones was performed to interpret exposure\u0026ndash;response relationships.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents exposure data across different work zones. The highest TWA for respirable dust was recorded in spray dryer operators (29.36 mg/m\u0026sup3;), exceeding the permissible limit based on RCS content (4.47 mg/m\u0026sup3;). Ball mill operators also exceeded their threshold (6.44 mg/m\u0026sup3; vs. permissible 3.89 mg/m\u0026sup3;). Kiln operators and reception staff had lower levels (2.84 mg/m\u0026sup3; and 0.66 mg/m\u0026sup3;, respectively), both within permissible limits. Although absolute RCS concentrations were low, the proportion of crystalline silica within respirable dust varied across zones, highest among reception areas (1.29%) despite lower total dust levels.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eExposure Assessment: Respirable Dust, PM2.5, and Crystalline Silica Levels by Work Zone\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRespirable Dust TWA (mg/m\u0026sup3;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePM2.5 TWA (mg/m\u0026sup3;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRatio (PM2.5 / Resp. Dust)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRCS Concentration in Resp. Dust (mg/m\u0026sup3;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e% RCS in Resp. Dust\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePermissible Limit (mg/m\u0026sup3;)*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBall Mill\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e6.44\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpray Dryer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e29.36\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKiln\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReception\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e*Permissible limit for respirable dust calculated using: 10 / (% RCS\u0026thinsp;+\u0026thinsp;2) (DGFASLI, India).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e PM2.5 concentrations followed a similar pattern, being highest in the spray dryer area (3.85 mg/m\u0026sup3;), followed by kiln (1.15 mg/m\u0026sup3;) and ball mill (1.04 mg/m\u0026sup3;). The PM2.5-to-respirable dust ratio was greatest in the reception area (0.47), indicating a relatively higher fraction of fine particulates in areas with lower total dust exposure.\u003c/p\u003e \u003cp\u003eA total of 256 lifelong non-smoking workers participated, including 189 production workers and 67 administrative staff (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). While both groups were comparable in age, height, and weight, significant differences were observed in education and years of experience.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic and occupational characteristics of the study participants (n\u0026thinsp;=\u0026thinsp;256)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWorkers (n\u0026thinsp;=\u0026thinsp;189)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdmin staff (n\u0026thinsp;=\u0026thinsp;67)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSignificance\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eAge in years, n (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u0026ndash;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e118 (62.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (47.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e31\u0026ndash;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (29.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt; 40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (22.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight in cm, mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e163.3 \u0026plusmn; 6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e164.1 \u0026plusmn; 6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight in kg, mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64.6 \u0026plusmn; 7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.3 \u0026plusmn; 6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eEducation, n (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo formal education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (12.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u0026thinsp;\u003cb\u003e=\u0026thinsp;0.00\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81 (42.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (4.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher secondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62 (32.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (22.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGraduate and beyond\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (12.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49 (73.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eYears working in ceramic industry, n (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89 (47.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (41.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u0026thinsp;\u003cb\u003e=\u0026thinsp;0.00\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u0026ndash;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81 (42.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (31.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt; 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (10.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (26.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs summarized in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, respiratory symptoms were significantly more frequent among production workers compared to administrative staff: WRURS (23.8% vs. 11.9%, p\u0026thinsp;=\u0026thinsp;0.03) and WRLRS (20.6% vs. 9.0%, p\u0026thinsp;=\u0026thinsp;0.03). Spirometry revealed obstructive lung patterns in 19.0% of workers compared to 9.0% of administrative staff (p\u0026thinsp;=\u0026thinsp;0.04). No restrictive or mixed patterns were detected. Mean lung function parameters were lower among production workers, with significant differences in FVC (4.0 vs. 4.5 L, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), FEV1/FVC (80% vs. 89%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and FEF 25\u0026ndash;75% (3.7 vs. 4.3 L/s, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRespiratory Symptoms and Lung Function Parameters Among Study Participants.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWorkers (n\u0026thinsp;=\u0026thinsp;189)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdmin staff (n\u0026thinsp;=\u0026thinsp;67)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSignificance\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eRespiratory symptoms\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWRURS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45 (23.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (11.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u0026thinsp;\u003cb\u003e=\u0026thinsp;0.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWRLRS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39 (20.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (9.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u0026thinsp;\u003cb\u003e=\u0026thinsp;0.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eLung function diagnosis\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e153 (81.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61 (91.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u0026thinsp;\u003cb\u003e=\u0026thinsp;0.04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObstructive lung disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 (19.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (9.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRestrictive lung disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eLung function parameter\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFEV1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.3 \u0026plusmn; 0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.5 \u0026plusmn; 0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFVC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.0 \u0026plusmn; 0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.5 \u0026plusmn; 0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u0026thinsp;\u003cb\u003e=\u0026thinsp;0.00\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFEV1/FVC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80 \u0026plusmn; 7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89 \u0026plusmn; 5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u0026thinsp;\u003cb\u003e=\u0026thinsp;0.00\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFEF 25%\u0026ndash;75%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.7 \u0026plusmn; 0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.3 \u0026plusmn; 0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u0026thinsp;\u003cb\u003e=\u0026thinsp;0.00\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMultivariate regression (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) demonstrated that increasing age and longer exposure duration were independently associated with declines in all lung function parameters. Job role (worker vs. admin) was significantly associated with reduced FEV1/FVC ratio (B = -2.35; p\u0026thinsp;=\u0026thinsp;0.03) and FEF 25\u0026ndash;75% (B = -0.01; p\u0026thinsp;=\u0026thinsp;0.03), after adjusting for confounders.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariate regression model for predictors of lung function parameters\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePredictor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eFVC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eFEV1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eFEV1/FVC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eFEF 25%-75%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eB (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eB (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eB (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.04\u003c/p\u003e \u003cp\u003e(-0.08, -0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.04\u003c/p\u003e \u003cp\u003e(-0.07, -0.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.00\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e-0.32\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(-0.53, -0.10)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-0.09\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(-0.14, -0.04)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.00\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of exposure (months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.05\u003c/p\u003e \u003cp\u003e(-0.01, -0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003cp\u003e(-0.003, -0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.00\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.03\u003c/p\u003e \u003cp\u003e(-0.06, -0.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003cp\u003e(-0.03, -0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJob profile (worker vs admin)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.23\u003c/p\u003e \u003cp\u003e(-0.56, 1.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.16\u003c/p\u003e \u003cp\u003e(-0.33, 0.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.35\u003c/p\u003e \u003cp\u003e(-3.65, -1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003cp\u003e(-0.03, -0.002)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e*type of cooking not included as all were using clean energy\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows the comparative patterns of exposure intensity and mean spirometry outcomes across different work zones. A clear inverse gradient was observed between exposure magnitude and lung function indices, with spray dryer and ball mill operators showing the lowest mean FEV₁ and FEV₁/FVC ratios, followed by kiln and reception staff. These findings collectively indicate an exposure\u0026ndash;response trend consistent with occupational dust effects on respiratory health, even though individual-level exposure correlations could not be established due to smaller representative sampling by zone.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparative Patterns of Exposure Intensity and Mean Spirometry Values by Work Zone.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWork Zone\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean Respirable Dust (mg/m\u0026sup3;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean PM2.5 (mg/m\u0026sup3;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e% RCS in Resp. Dust\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean FEV₁ (L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean FEV₁/FVC (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eInterpretation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpray Dryer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHighest exposure, lowest lung function\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBall Mill\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eModerate exposure, mild reduction\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKiln\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate exposure\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReception/ admin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLowest exposure, normal function\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis cross-sectional comparative study examined occupational exposure to respirable dust, fine particulate matter (PM2.5), and crystalline silica and their relationship with respiratory health patterns among non-smoking workers of ceramic tile industry. The study revealed markedly higher exposure levels among production workers compared with administrative staff, accompanied by a higher prevalence of respiratory symptoms and reduced lung function, underscoring a clear occupational influence.\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eOccupational exposure of respirable dust and crystalline silica\u003c/h2\u003e \u003cp\u003eCeramic manufacturing processes generate substantial amounts of airborne dust, yet effective local exhaust ventilation and personal protective practices are often lacking. In this study, the measured levels of respirable dust in high-exposure zones such as ball mill and spray-drying substantially exceeded permissible occupational exposure limits, reflecting inadequate dust control in these sections. Although crystalline silica content in respirable dust was relatively low in absolute concentration, it surpassed recommended thresholds in high-exposure zones, posing considerable health risks due to its fibrogenic and carcinogenic potential [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The observation that reception areas\u0026mdash;nominally low-exposure zones\u0026mdash;had a higher percentage of silica within dust samples suggests that airborne silica can disperse widely across facilities. This aligns with previous research in Iran and Egypt documenting cross-contamination of silica particles between production and administrative areas in ceramic and stone industries, emphasizing the need for comprehensive environmental control beyond production lines [\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eFine particulate matter (PM2.5) and its significance\u003c/h2\u003e \u003cp\u003eThe study additionally highlights the neglected burden of fine particulate exposure in ceramic workplaces. The highest PM2.5 levels were observed in spray drying and ball milling areas, while the reception area showed the highest PM2.5-to-respirable dust ratio. Fine particulates, because of their small aerodynamic diameter, penetrate deep into alveoli, inducing oxidative stress and inflammatory injury [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Similar findings have been documented in tile and refractory industries, where PM2.5 exposures correlate with higher respiratory and cardiovascular morbidity [\u003cspan additionalcitationids=\"CR27 CR28\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. This underscores the need to incorporate PM2.5 monitoring within routine occupational surveillance, which is often overlooked in current ceramic industry standards.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eRespiratory health outcomes and exposure\u0026ndash;response pattern\u003c/h2\u003e \u003cp\u003eWorkers in the production sections reported a significantly higher prevalence of both upper and lower respiratory symptoms compared to administrative staff, consistent with the elevated exposure levels observed. This pattern aligns with reports from other ceramic and silica-exposed occupational groups, where cough, phlegm, and breathlessness were common early symptoms of exposure-related airway irritation and inflammation [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Several studies in Iran, Egypt, and Italy have similarly documented higher respiratory symptom prevalence among production workers than administrative or control groups, reflecting the universal nature of these occupational risks [\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Lung function assessment revealed a predominance of obstructive ventilatory patterns among exposed workers, suggesting early small airway involvement. This pattern likely reflects shorter employment duration (\u0026lt;\u0026thinsp;5 years for most participants), as obstructive changes from chronic bronchial inflammation occur earlier than the restrictive fibrotic defects seen with prolonged silica exposure. This interpretation is consistent with findings by Hoy et al. [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], Neghab et al. [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], and Golbabaei et al. [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], who reported obstructive patterns in early-stage exposure and mixed or restrictive patterns only after extended occupational tenure .\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eDeterminants of lung function decline\u003c/h2\u003e \u003cp\u003eZone-wise comparison revealed an inverse gradient between exposure intensity and mean spirometry values, with spray dryer and ball mill operators showing the poorest lung function indices. Multivariate regression analysis showed that exposure duration was independently associated with declines in FVC, FEV₁, and mid-expiratory flows. The association between job role and airflow limitation remained significant. These findings indicate a clear exposure-response relationship and strengthen the occupational etiology of airway obstruction among ceramic tile workers. Comparable studies among industrial dust-exposed populations have consistently demonstrated that increasing duration of exposure correlates with progressive deterioration in lung function [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003ePublic health implications\u003c/h2\u003e \u003cp\u003eThe current findings have direct implications for occupational hygiene and worker protection. The persistently high dust levels in spray drying and milling sections call for stricter engineering controls, including local exhaust ventilation, process enclosure, and real-time dust monitoring. Regular spirometry and medical surveillance should be mandated for early detection of occupational airway disease. Finally, the inclusion of PM2.5 in workplace exposure standards\u0026mdash;currently absent in most national frameworks\u0026mdash;should be prioritized to address the growing burden of fine particulate pollution in industrial settings.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Limitations\u003c/h2\u003e \u003cp\u003eA key strength of the present study is the inclusion of an internal comparison group of administrative staff working within the same industrial premises, thereby controlling for shared environmental and socio-demographic factors. The exclusion of smokers and individuals with pre-existing respiratory diseases further minimized confounding. Moreover, the study combined environmental monitoring with health assessments, integrating quantitative exposure data, crystalline silica content, and respiratory health to provide a holistic understanding of exposure\u0026ndash;response dynamics.\u003c/p\u003e \u003cp\u003eSome limitations should be acknowledged. First, the cross-sectional design restricts causal inference between exposure and respiratory outcomes. Second, exposure assessment was based on representative sampling within each production zone rather than individual monitoring, precluding formal correlation analysis. Third, the healthy-worker effect cannot be ruled out, as severely affected workers might have left employment, leading to potential underestimation of disease prevalence.\u003c/p\u003e \u003c/div\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study identified substantially elevated levels of respirable dust in high-exposure processes such as spray drying and ball milling, exceeding permissible limits. Production workers exhibited a higher prevalence of respiratory symptoms and obstructive ventilatory patterns compared with administrative staff. An exposure-response gradient was evident, with lung function parameters progressively declining across zones of increasing dust intensity. These findings highlight the urgent need for comprehensive dust mitigation strategies such as engineering controls, enclosure of emission sources, and wet suppression coupled with routine exposure monitoring and periodic spirometry-based health surveillance to protect this workforce. Future longitudinal studies should further evaluate temporal changes in lung function and assess systemic health effects of chronic particulate exposure in the ceramic industry.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e \u003cp\u003e The study was approved by the Institutional Human Ethics Committee of ICMR-National Institute of Occupational Health (ICMR-NIOH/EC/2021-22) and conducted in accordance with the Helsinki Declaration. Written informed consent was obtained from all participants, who were assured of confidentiality, anonymity, and their right to withdraw at any time.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication:\u003c/strong\u003e \u003cp\u003eWritten informed consent was taken from participants for use of data generated during the interviews for the purpose of publication.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests:\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eIntramural seed funding from ICMR-National Institute of Occupational Health\u003c/p\u003e \u003cp\u003eDeclaration of Conflict of interest: None\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAS, NK, and AV conceived and designed the study. AS, NK, MM, and AV contributed to literature review, data collection, and manuscript revision. AS, NK, and AV performed data analysis and interpretation. AS drafted the manuscript. All authors reviewed and approved the final version.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe thank all study participants and the management of the participating industries for their cooperation and support.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated are not publicly available due to privacy concerns but are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eChen W, Liu Y, Wang H, Hnizdo E, Sun Y, Su L, et al. Long-term exposure to silica dust and risk of total and cause-specific mortality in Chinese workers: a cohort study. 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Mumbai, India: Directorate General, Factory Advice Service and Labour Institutes, Ministry of Labour and Employment, Government of India; 2020.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMohamed SH, El-Ansary AL, El-Aziz EMA. Determination of crystalline silica in respirable dust upon occupational exposure for Egyptian workers. Ind Health. 2018;56(3):255\u0026ndash;63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMohammadyan M, Rokni M, Yosefinejad R. Occupational exposure to respirable crystalline silica in the Iranian Mazandaran province industry workers. Arh Hig Rada Toksikol. 2013;64(1):139\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOmidianidost A, Ghasemkhani M, Kakooei H, Shahtaheri SJ, Ghanbari M. Risk Assessment of Occupational Exposure to Crystalline Silica in Small Foundries in Pakdasht, Iran. Iran J Public Health. 2016;45(1):70\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRahimimoghadam S, Ganjali A, Khanjani N, Normohammadi M, Yari S. Application of Multiple Occupational Health Risk Assessment Models for Crystalline Silica Dust among Stone Carvers. Asian Pac J Cancer Prev. 2023;24(11):3999\u0026ndash;4005.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBasith S, Manavalan B, Shin TH, Park CB, Lee WS, Kim J et al. The Impact of Fine Particulate Matter 2.5 on the Cardiovascular System: A Review of the Invisible Killer. Nanomaterials (Basel). 2022;12(15).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuo J, Chai G, Song X, Hui X, Li Z, Feng X, et al. Long-term exposure to particulate matter on cardiovascular and respiratory diseases in low- and middle-income countries: A systematic review and meta-analysis. Front Public Health. 2023;11:1134341.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKrittanawong C, Qadeer YK, Hayes RB, Wang Z, Thurston GD, Virani S, et al. PM(2.5) and cardiovascular diseases: State-of-the-Art review. Int J Cardiol Cardiovasc Risk Prev. 2023;19:200217.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNasri SM, Putri FA, Sunarno S, Fauzia S, Ramdhan DH. PM(2.5) exposure and lung function impairment among fiber-cement industry workers. J Public Health Res. 2023;12(1):22799036221148989.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDehghan F, Mohammadi S, Sadeghi Z, Attarchi M. Respiratory Complaints and Spirometric Parameters in Tile and Ceramic Factory Workers. TANAFFOS (Respiration). 2009;8(4autumn):19\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHalvani GH, Zare M, Halvani A, Barkhordari A. Evaluation and comparison of respiratory symptoms and lung capacities in tile and ceramic factory workers of Yazd. Arh Hig Rada Toksikol. 2008;59(3):197\u0026ndash;204.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRondon EN, Silva RM, Botelho C. Respiratory symptoms as health status indicators in workers at ceramics manufacturing facilities. J Bras Pneumol. 2011;37(1):36\u0026ndash;45.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSaad-Hussein A, Morcos NY, Rizk SA, Ibrahim KS, El-Zaher NA, Moubarz G. Aspergillus hazardous problem in ceramic workers. Toxicol Ind Health. 2012;28(10):886\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHoy RF, Chambers DC. Silica-related diseases in the modern world. Allergy. 2020;75(11):2805\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNeghab M, Zadeh JH, Fakoorziba MR. Respiratory toxicity of raw materials used in ceramic production. Ind Health. 2009;47(1):64\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGolbabaei F, Abedinlou R, Fekri N, Shapasandi A, Mohammadi H. A study on the five-year change trend in pulmonary function of workers in tile and ceramic industry. J Health Saf Work. 2020;10(1):37\u0026ndash;45.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbdel Monaem AM, Abdel Rasoul GM, Gabr HM, Allam HK, Badr S. Respiratory and auditory disorders in a ceramic manufacturing factory (Queisna City, Menoufia Governorate). Menoufia Med J. 2017;30(2):595\u0026ndash;601.\u003c/span\u003e\u003c/li\u003e\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":"","lastPublishedDoi":"10.21203/rs.3.rs-8487804/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8487804/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe rapid expansion of ceramic tile industry in Morbi, Gujarat, has led to increased occupational exposure to respirable dust, fine particulates and crystalline silica, raising respiratory health concerns among workers. Limited data exist linking these exposures with respiratory health in this sector.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA cross-sectional comparative study was conducted among 256 lifelong non-smoking workers in ceramic tile factories, comprising production workers and administrative staff. Personal air sampling quantified respirable dust, PM2.5, and crystalline silica across major process zones. Respiratory symptoms were assessed using a validated questionnaire, and spirometry was performed following ATS-ERS guidelines. Multivariate regression models were adjusted for age, exposure duration, and job role to assess lung function parameters.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWorkers experienced higher exposure to respirable dust (up to 29.36 mg/m\u0026sup3;) and PM2.5 (up to 3.85 mg/m\u0026sup3;) compared to administrative staff. Crystalline silica exceeded recommended limits in high-exposure zones. The prevalence of upper and lower respiratory symptoms was 23.8% and 20.6% among workers versus 11.9% and 9.0% among administrative staff. Obstructive lung patterns were identified in 19% of workers compared with 9% of administrative staff. Across process zones, lung function values (FVC, FEV₁, and FEF25-75) showed a consistent decline with increasing dust and PM2.5 exposure levels. Age, exposure duration, and job role independently predicted significant declines in workers\u0026rsquo; lung function.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eCeramic tile workers experience excessive exposure to respirable dust, PM2.5, and crystalline silica, with observed patterns indicating early obstructive lung function impairment. Targeted dust control, regular monitoring, and periodic spirometric surveillance are urgently needed.\u003c/p\u003e","manuscriptTitle":"Exposure to Respirable Dust, Fine Particulates and Crystalline Silica and Comparative Respiratory Health Patterns Among Non-Smoking Workers in the Ceramic Industry","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-13 09:45:11","doi":"10.21203/rs.3.rs-8487804/v1","editorialEvents":[{"type":"communityComments","content":1}],"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":"911bd7cb-84c9-457f-b813-28abb5ec6c8d","owner":[],"postedDate":"January 13th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-18T07:41:44+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-13 09:45:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8487804","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8487804","identity":"rs-8487804","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}