Development and validation of an ICPMS method and its application in assessing heavy metals in whole blood samples among occupationally exposed Lead smelting plant workers

Development and validation of an ICPMS method and its application in assessing heavy metals in whole blood samples among occupationally exposed Lead smelting plant workers | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Development and validation of an ICPMS method and its application in assessing heavy metals in whole blood samples among occupationally exposed Lead smelting plant workers Dr. Kuldip Upadhyay This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3893267/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 Occupational exposure to heavy metals affecting various organ systems, poses a significant health risk to workers. Consequently, its precise estimation is of clinical concern and warrants the need for an analytical method with reliable precision and accuracy. Current study aimed to develop an analytical method using inductively coupled plasma mass spectrometry (ICPMS) to detect trace to elevated levels of potentially toxic elements in human blood. The sample preparation optimized using a two-step ramp temperature microwave acid digestion program. The toxic elements quantified using ICPMS operating in kinetic energy dispersion (KED) mode, adjusting data acquisition parameters and instrumental settings. The analytical method was validated using standard performance parameters. Each validation parameter aligned with the acceptable criteria outlined in standard guidelines. The method achieved optimal linearity (r 2 > 0.99), recovery (85.60–112.00%), precision (1.35–7.03%), capable of detecting the lowest concentration of 0.32, 0.28, 0.28, and 0.19 µg/L, and quantifying trace levels of 1.01, 0.88, 0.90, and 0.62 µg/L for arsenic (As), cadmium (Cd), mercury (Hg), and lead (Pb), respectively. Post-validation, the method was applied to estimate heavy metals in blood samples from 250 Pb smelting plant workers, revealing potential health implications of occupational exposure. The cohort analysis revealed demographic and employment factors were associated with elevated blood lead levels (BLL), leading to symptoms and health risks. Clinical analysis indicated 33.6% participants experienced hypertension, and 20 were anemic at BLL above 300 µg/L. It emphasizes the importance of continuous monitoring, interventions, and improved occupational hygiene to protect the well-being of workers. heavy metals whole blood trace level detection analytical method clinical assessment occupational exposure. Figures Figure 1 Introduction Occupational exposure to heavy metals, specifically lead (Pb), cadmium (Cd), Arsenic (As) and Mercury (Hg) remains a pressing concern due to their adverse health effects(Bakr et al., 2023 ). Heavy metals are absorbed into the body through inhalation or ingestion and distributed through the blood to bones and soft tissues (viz. brain, liver, kidney). As a cumulative toxicant, they adversely affect multiple body systems including hematological, neurological, cardiovascular, respiratory, gastrointestinal, renal systems, and bone effects(Assi et al., 2016 ; Satarug et al., 2010 ). Hence, the American Conference of Governmental Industrial Hygienists (ACGIH) has prescribed biological exposure indices (BEI) values of 200 µg/L for Pb and 5.0 µg/L for Cd to prevent health consequences in occupational exposure(ACGIH, 2022 ). Workers in Pb smelting plants face a heightened risk of exposure to these toxic metals, leading to potential health complications(An et al., 2017 ). In medical surveillance, the whole blood levels of potentially toxic metals are regarded as the primary benchmark for identifying individual exposure (Vergara-Murillo et al., 2022 ). Assessing blood levels of toxic elements serves as a critical indicator for understanding the extent of exposure and potential health risks among these workers(Goyal et al., 2021 ). Hence, precise analysis for the blood-based estimation of heavy metals in occupationally exposed individuals serves as a critical measure of exposure and aids in identifying potential health risks and establishing necessary interventions to safeguard the well-being of these workers(Upadhyay et al., 2023 ). Therefore, the development and validation of an accurate and precise analytical method for quantifying these toxic metals in blood samples become crucial. Different analytical techniques exist to estimate the levels of toxic and trace elements in whole blood samples, including, Graphite Furnace Atomic Absorption Spectrometry (GFAAS), anodic stripping voltammetry (ASV), inductively coupled plasma with atomic emission spectrometry (ICP-AES), and inductively coupled plasma mass spectrometry (ICPMS) (WHO, 2020 ). However, ICPMS is considered the most proficient technique for conducting extensive biomonitoring surveys due to its high sensitivity and robustness in determining a wide range of elements (Heitland & Köster, 2012 ). The present study aimed to develop and validate an ICP-MS method for the precise analysis of Pb, Cd, As and Hg levels in blood samples of occupationally exposed Pb-smelting plant workers. The method validation examined for wide range of performance parameters to ensure its reliability in determining metal concentrations within the samples. Following this validation, the method was applied in a comprehensive assessment of heavy metals in blood samples of occupationally exposed Pb smelting plant workers and elucidated the potential health implications associated with occupational exposure to these heavy metals. Materials and Methods Study design and recruitment of subjects: In this investigation, total 250 consenting adults (aged > 18 years) employed at a Pb smelting unit, underwent assessment for levels of heavy metals in their blood samples, along with an evaluation of their associated health status. Ethical clearance was obtained from the Institutional Human Ethics Committee (IHEC) before execution of the study, adhering to all recommended methods and protocols for human experiments outlined in the national ethical guidelines for biomedical and health research involving humans(Mathur & Swaminathan, 2018 ). Each participant obtained informed written consent to use their details to investigate the levels of heavy metals in their blood samples, along with an assessment of their associated health status. Sociodemographic and occupational details were collected through a semi-structured, pre-validated questionnaire. The study group was classified for their socioeconomic status using modified B. G. Prasad scale(Akram et al., 2023 ). Clinical assessment included a general health examination and workplace-specific investigations. All the consenting participants were collected 5 ml of venous blood in Pb free vacutainers under aseptic precautions. The samples were transported in a refrigerated conditions and analyzed at the parent institute. The levels of Hemoglobin were estimated using HemoCue Hb 301 point of care device and categorized as 'normal' or 'anemic' based on WHO guidelines(WHO, 2017 ). The clinical assessment involved identifying neurological, respiratory, gastrointestinal, and musculoskeletal symptoms that necessitated medical supervision, resulting in absence from work for more than 24 hours in the previous year. The blood pressure (BP) was measured following the method described in the literature (Muntner et al., 2019 ; Upadhyay et al., 2023 ), using a pre-calibrated digital sphygmomanometer (Omron Healthcare, Kyoto, Japan). The subsequent measurements of systolic BP (SBP) and diastolic BP (DBP) were recorded, and the average of the second and third measurements was considered for the study. Participants were classified as pre-hypertensive or hypertensive based on the guidelines recommended by the Joint National Committee in their seventh report on the prevention and control of high blood pressure (Chobanian et al., 2003 ). Reagents and Calibration Standards: Trace metal grade concentrated nitric acid (67–70%) for ICP-MS and 30% (w/v) hydrogen peroxide (ACS grade) were acquired from Fisher chemicals. NIST traceable standard reference material with 1000 mg/L concentration of As, Cd, Hg, Pb, and 10mg/L Rhodium internal standard procured from Merck GmBH. Ultrapure deionized water (18.2 MΩ at 25 o C) used for standards and sample preparations. Argon plasma and helium collision gas of research grade (purity > 99.999%) used for analysis. Calibration standards of 0.05, 0.1, 0.5, 1.0, 5.0, 10.0 and 50.0 µg/L concentration for each target element were prepared by serial dilution of NIST traceable standard reference material (1000 mg/L of each As, Cd, Hg, and Pb, Merck GmBH) with ultrapure deionized water. Method development and Optimization: The sample preparation was optimized to achieve thorough acid digestion using a two-step ramp temperature program. The quantification of the elements of interest was performed using an ICPMS equipped with a collision cell operating in kinetic energy discrimination (KED) mode. Parameters for data acquisition and optimal instrumental settings for the ICPMS equipment were carefully adjusted. To avoid potential carry-over, a two-minute wash with deionized water followed each run. The standard addition method was employed to offset matrix effects, and any variations in analytical signals were rectified using the internal standard (rhodium). Sample preparation: 1 ml of whole blood sample was placed in Teflon vessel along with 2 ml of concentrated nitric acid, 0.5 ml of 30% (w/v) hydrogen peroxide and 50µl of Rhodium internal standard. The sample underwent acid digestion in a multi-wave go microwave digestion system (Anton Parr, Germany) using two step temperature program shown in Table 1 . At the end of digestion cycle, the residue was cooled at ambient temperature and transferred into Pb free tubes. Finally, all the samples diluted with ultrapure deionized water up to a 10ml volume and preserved at 4 o C until analysis. Table 1 Microwave digestion program for acid digestion of blood samples Step Ramp (minutes) Temperature ( o C) Hold time (minutes) Microwave Power (W) 1 10 120 10 1000 2 20 180 15 1000 The table outlines the microwave digestion program used for acid digestion of blood samples. Each step includes information on ramp time, temperature, hold time, and microwave power settings. Instrumentation: The concentrations of heavy metals were measurement using an ICPMS (model 2030, AS-10 autosampler, Shimadzu, Japan) equipped with a collision cell operating in KED mode. Summary of data acquisition parameters and optimized instrumental settings is provided in Table 2 . A two-minute wash with deionized water was conducted after each run to prevent potential carryover. The standard addition method was employed to offset matrix effect, and any variations in analytical signals were corrected using the internal standard (rhodium). Table 2 Data acquisition parameters and optimized instrument setup Parameter Setting RF Power 1200 W Plasma gas flow (Argon) 15 (L/min) Auxiliary gas flow (Argon) 1.0 (L/min) Carrier gas flow (Argon) 1.2 (L/min) Nebulizer coaxial Sampling depth 6 mm Spray chamber water cooled double pass Spray chamber temperature ( o C) 5.0 Collision cell gas flow (Helium) 6 mL/min Lens voltage (eV) 4.5 Mass resolution (amu) 0.8 Integration time points/ms 3 Points per peak 3 Replicates 3 The table presents the data acquisition parameters and the optimized instrument setup for the experiment, including RF power, gas flows, nebulizer type, sampling depth, spray chamber configuration, temperature, collision cell gas flow, lens voltage, mass resolution, integration time points, points per peak, and the number of replicates used. Method Validation: The validation of the analytical method relied on established performance parameters, viz selectivity and linearity, accuracy, method detection limit ( LoD m ), method quantification limit ( LoQ m ), and precision. Calibration linearity was assessed through the correlation coefficient ( r 2 ), and linear curves with r 2 values exceeding 0.99 were chosen for estimation of As, Cd, Hg and Pb level in blood. Accuracy was determined using the standard addition method, and % recovery falling within the 80–120% range was deemed acceptable for validation. Precision, as indicated by a coefficient of variance (%CV) obtained from repeated measurements of the same sample, would be considered acceptable for analysis if it is less than 20%. LoD m and LoQ m were calculated based on the standard deviation (SD) from 7 replicates following standard spike method (ICH Guideline, 2022 ). ICPMS analysis of heavy metals in blood samples The digested whole blood samples were drawn into the ICP-MS through the AS-10 autosampler, which was calibrated for the analysis of As, Cd, Hg, and Pb across a range of concentrations, from trace to elevated levels. The aspirated fraction underwent ionization within an argon plasma and atomization in the spray chamber. Argon gas flowed at 15 L/min through a torch, consisting of concentric glass tubes, generating the argon plasma. The drive coil, surrounding the outlet end of the torch, received radio frequency power of up to 1.2 kW, maintaining a plasma discharge in the argon at a temperature of approximately 9,500 o K. The ions exited the plasma, traversed the instrument's interface, and reached the entrance of the collision cell, where helium gas was introduced at the flow rate of 6.0 mL/min to eliminate potential polyatomic interferences. The primary quadrupole filtered the ions from the collision cell, and the detector counted and summed electron abundances for each element. The concentration of elements of interest in the specimen was determined using the calibration curve. Result and discussion Interference study: Quantitative elemental analysis by ICPMS is known to be influenced by spectral or non-spectral interferences, resulting in fluctuations in the target analyte signal (D'Ilio et al., 2010 ). So, an interference study was conducted for selected isotopes 75 As, 111 Cd, 202 Hg, and 208 Pb prior to method validation. It was observed that measuring all the selected isotopes in KED mode using helium as a collision gas encountered potential interferences removal (eg. the detection of 75 As suffered from the overlapping of the typical molecular ion 40 Ar 35 Cl in standard mode) and ensured the reliability of the analysis for the precise estimation of target analytes in whole blood samples. Selectivity and Linearity: The selectivity of the method towards the blood matrix was confirmed by comparing aqueous standard and matrix match calibration curves. The comparison revealed that the slope of the calibration curve from aqueous standards resembles the slope of matrix match calibration curves, indicating no apparent of matrix interferences. Hence, aqueous calibration curves were applied for the calibration throughout the experiments. The linearity of the method was determined by preparing calibration standard solutions ranging from low to high concentrations of elements of interest to achieve the target concentrations. The values for the linear equation and the linear regression coefficient across the analytical measurement range (AMR), aligned with their respective whole blood reference range values (Bajaj et al., 2023 ) are illustrated in Figure-1 and Table 3 . The values of correlation coefficients ( r 2 ) obtained ≥ 0.99 for linear regression suggest best linear fit across AMR and acceptable for quantification for all toxic elements of interest. Table 3 Linearity across the AMR of multi-elements with their whole blood reference range values Element AMR (µg/L) Reference Range (whole blood) (µg/L) Correlation Coefficient (r 2 ) 75 As 0.05–50 ≤ 12.0 0.9999 111 Cd 0.05–50 ≤ 5.0 0.9999 202 Hg 0.05–50 ≤ 10.0 0.9979 208 Pb 0.05–50 ≤ 50.0 0.9992 The table illustrates the linearity across the Analytical Measurement Range (AMR) for various elements, along with their corresponding reference range values in whole blood. It includes information on the AMR, reference range, and the correlation coefficient (r²) for each element, demonstrating the precision and accuracy of the analytical method used. Accuracy: The accuracy of the method was examined by the recovery values of each of the elements of interest, spiked with three different levels of standard concentrations. The % recovery obtained from measured concentration against each spike concentration for each element was range between 85.60–112.00 as summarized in Table 4 . Table 4 Recoveries of the developed analytical method Analyte Spiked Concentration (µg/L) Measured Concentration (µg/L) % Recovery 75 As 2.0 2.12 106.00 40.0 42.5 106.25 100.0 103.0 103.00 111 Cd 3.5 3.49 99.71 10.0 11.2 112.00 30.0 31.6 105.33 202 Hg 10.0 8.56 85.60 30.0 31.4 104.67 70.0 69.9 99.86 208 Pb 35.0 33.8 96.57 150.0 148.0 98.67 180.0 177.0 98.33 The table presents the recoveries of the developed analytical method for different analytes at various spiked concentrations. It includes information on the spiked concentration, measured concentration, and the percentage recovery for each analyte, indicating the accuracy and reliability of the analytical procedure. The values obtained within ± 20% of the target concentration are considered acceptable for the performance of the method(Bajaj et al., 2023 ). The accuracy assessment suggests that the analytical method is effective in recovering the specified elements across the range of spiked concentrations. These findings provide evidence of the method's accuracy and reliability for the quantification of the analyzed elements in blood samples at different concentration levels. Limit of Detection (LoD) and Quantification (LoQ) The sensitivity of an analytical method is ascertained by LoD and LoQ . The method detection limit (LoD m ) refers to the ability to detect the lowest concentration of an analyte reliably, which can be distinguished from background noise but not necessarily quantified. In contrast, the method quantification limit (LoQ m ) pertains to the lowest concentration of an analyte that can be quantified with acceptable levels of precision and accuracy. The LoD m and LoQ m were determined based on the standard deviation (σ) of seven replicates of digested blood samples spiked with 1 µg/L of each 75 As, 111 Cd, 202 Hg and 208 Pb, along with the student t- test value (at 99% confidence that analyte concentration > 0 µg/L). The calculations were performed using the equations described in the literature method (Ripp, 1996 ) and are summarized in Table 5 . Table 5: Estimation of LoD m and LoQ m $$LoDm= \text{x} 3.14$$ $$LoQm= \text{x} 10$$ Where LoD m = method detection limit LoQ m = method quantification limit σ = standard deviation of measured concentrations of seven replicates 3.14 = t- test value at 99% confidence that analyte concentration > 0µg/L The presented values illustrate that the method is proficient in both detecting and quantifying the specified analytes in blood samples at ultra-trace levels with acceptable precision and accuracy. These results signify the sensitivity of the method in accurately estimating the target elements in whole blood samples at extremely low concentrations. Precision: The analytical precision was assessed by examining the repeatability and reproducibility (within laboratory) of individual test results obtained from repeated measurements of the same sample under distinct analytical conditions(Upadhyay et al., 2023 ). The precision of the proposed method for each target element was determined through repeated measurements of three replicates at three different concentrations over three consecutive days and expressed in terms of the %CV as summarized in Table-6. The %CV is calculated as per the following formula (Gupta et al., 2019 ). Table-6: Assessment of analytical precision The table assesses the analytical precision for various analytes at different spiked concentrations. It includes information on the spiked concentration, mean concentration of three replicates for three successive days, standard deviation (σ), and the coefficient of variation (%CV), demonstrating the repeatability and reliability of the analytical method. Where % CV = co-efficient of variance σ = standard deviation of three replicate measurements \(\overline{x}\) = mean concentration of three replicate measurements The obtained results revealed that proposed analytical method demonstrated satisfactory analytical precision for all the target elements across a range of concentrations. The %CV below 20% is considered acceptable and realistic for the concentrations be quantified (D'Ilio et al., 2010 ). The % CV values provide insights into the relative variability of the measurements, and the low standard deviations suggest good repeatability and reproducibility of the method over the three successive days. These findings support the reliability of the proposed analytical method for the quantification of the target elements in whole blood samples. Reference values for various heavy metals in human blood are publicly accessible in the literature(Bajaj et al., 2023 ). The newly developed method is capable of measuring the elements of interest even at lower levels with improved accuracy and precision, owing to better method detection and quantification limits. A synopsis of performance parameters of the present analytical method is summarized in Table 7 . Table-7 : Summary of performance parameters Parameter Obtained value Accepted range 75 As 111 Cd 202 Hg 208 Pb Linearity ( r 2 ) 0.9999 0.9999 0.9979 0.9992 ≥ 0.99 Accuracy (% recovery) 85.60 – 112.00 80 – 120 LoDm (μg/L) 0.32 0.28 0.28 0.19 - LoQm (μg/L) 1.01 0.88 0.90 0.62 - Precision (% CV) 1.35 – 7.03 < 20 Table 7 provides a summary of performance parameters for the analytical method, including linearity ( r² ), accuracy (% recovery), limit of detection ( LoDm ), limit of quantification ( LoQm ), and precision (% CV). The obtained values are compared to accepted ranges, demonstrating the reliability and suitability of the method for the analysis of 75 As, 111 Cd, 202 Hg, and 208 Pb. The evaluation of all test parameters confirmed the successful validation of the proposed method. The values obtained for each parameter fell within the acceptable limits outlined by standard guidelines(ICH Guideline, 2022 ; Ripp, 1996 ). Consequently, the developed method was applied for the clinical assessment of heavy metals in blood samples collected from occupationally exposed, Pb smelting plant workers. Estimation of heavy metals in blood samples among occupationally exposed individuals Workers engaged in the Pb smelting activities are predominantly exposed to elevated levels of Pb and potentially toxic other heavy metals. These individuals are possibly at elevated risk of developing heavy metal toxicity, especially if low awareness and poor hygiene practice exist at workplace. In this study, the individuals, who were occupationally exposed through various Pb smelting processes and activities, underwent clinical evaluation as a part of their periodic medical examination. The study included participants from both executive and worker categories, assigned to different sections of the plant, such as furnace, electrochemical refining, maintenance, and others (e.g., utility, sulfuric acid plant, captive power plant, etc.). Exposure to heavy metals in their blood samples was assessed using a newly developed analytical method. The distribution of the exposed population and blood-based levels of heavy metals concerning sociodemographic profiles, employment factors, system-specific symptoms, and representative clinical parameters is summarized in Table 8 . Table-8: Demographic details and distribution of study population with their blood levels of heavy metals Parameter Individual (n) (Mean ± SD) Age (years) 250 33.68 ± 6.89 Job duration (years) 6.99 ± 4.97 BMI (Kg/m 2 ) 24.28 ± 3.74 Systolic BP (mmHg) 130.67 ± 15.59 Diastolic BP (mmHg) 84.05 ± 13.54 Pulse rate (per minute) 82.77 ± 11.56 Haemoglobin (g/dL) 14.78 ± 1.16 75 As (µg/L) 2.46 ± 1.37 111 Cd (µg/L) 3.45 ± 5.28 202 Hg (µg/L) 9.27 ± 1.33 208 Pb (µg/L) 367.91 ± 147.91 Distribution of element in the exposed population (µg/L) 75 As 111 Cd 202 Hg 208 Pb As per sociodemographic factors Socio-economic status Upper class 154 2.41 ± 1.32 3.55 ± 6.49 9.22 ± 1.37 348.50 ± 152.74 Upper-middle-class 70 2.35 ± 1.38 3.07 ± 2.22 9.15 ± 1.35 405.28 ± 147.33 Middle class 25 3.03 ± 1.46 3.87 ± 2.46 9.82 ± 0.84 382.56 ± 95.58 Lower-middle-class 1 4.4 4.18 10.3 375.00 Personal addiction Tobacco chewing/smoking 103 2.72 ± 1.34 4.31 ± 1.34 9.59 ± 1.24 382.97 ± 154.68 No addiction 147 2.29 ± 1.36 2.85 ± 3.54 9.03 ± 1.35 357.36 ± 142.57 As per the employment factor Job profile Executive 122 2.13 ± 1.22 2.59 ± 3.97 8.92 ± 1.43 325.91 ± 150.91 Worker 128 2.76 ± 1.42 4.28 ± 6.19 9.60 ± 1.13 408.15 ± 134.26 Department Furnace 115 2.40 ± 1.40 3.04 ± 2.95 9.10 ± 1.40 397.65 ± 141.08 Electro-chemical refining 52 2.75 ± 1.44 3.27 ± 5.27 9.18 ± 1.36 349.12 ± 125.93 Maintenance 56 2.37 ± 1.24 4.69 ± 8.83 9.58 ± 1.13 399.52 ± 144.01 Other (utility, by-product, etc.) 27 2.39 ± 1.32 2.98 ± 2.22 9.48 ± 1.25 211.87 ± 123.40 As per system-specific symptoms Central nervous system Headache 28 1.80 ± 1.15 1.87 ± 1.44 8.66 ± 1.25 368.96 ± 153.6 Memory loss 17 2.79 ± 1.46 5.03 ± 8.62 9.35 ± 1.44 375.17 ± 186.69 Malaise 21 1.56 ± 1.13 2.30 ± 2.37 8.32 ± 1.29 367.33 ± 121.03 Respiratory Cough 12 2.29 ± 1.21 1.88 ± 1.49 9.51 ± 0.87 285.00 ± 62.10 Dyspnoea 68 2.27 ± 1.33 3.16 ± 4.72 9.10 ± 1.38 396.04 ± 146.14 Gastro-intestinal Loss of appetite 8 2.56 ± 1.57 7.19 ± 12.05 9.77 ± 0.30 365.12 ± 124.35 Gastritis 32 2.35 ± 1.40 2.72 ± 2.70 9.20 ± 1.30 394.75 ± 144.84 Musculoskeletal Knee pain 51 2.21 ± 1.46 3.37 ± 2.91 9.09 ± 1.40 401.11 ± 137.06 Neck pain 10 1.69 ± 1.27 2.25 ± 2.01 8.46 ± 1.22 308.09 ± 169.87 Back pain 16 2.13 ± 1.33 2.61 ± 1.68 9.25 ± 1.62 339.00 ± 108.78 Ankle ache 38 1.85 ± 1.37 3.34 ± 6.02 8.86 ± 1.41 332.50 ± 117.35 As per clinical parameters Hypertension (as per JNC-8 guidelines) Pre-hypertensive 155 2.42 ± 1.38 3.16 ± 3.84 9.24 ± 1.36 352.91 ± 145.19 Hypertensive 84 2.47 ± 1.41 3.28 ± 2.78 9.21 ± 1.39 389.94 ± 154.47 Anemia anemic (Haemoglobin based) 20 2.50 ± 1.20 5.32 ± 12.81 9.62 ± 1.01 338.50 ± 177.98 Table 8 provides the demographic details and the distribution of the study population along with their blood levels of heavy metals. It includes parameters such as age, job duration, BMI, blood pressure, pulse rate, hemoglobin, and concentrations of heavy metals ( 75 As, 111 Cd, 202 Hg, 208 Pb). Additionally, the distribution of these elements based on sociodemographic factors, personal addiction, employment factors, system-specific symptoms, and clinical parameters is presented. The study population exhibited significantly higher BLL above the BEI (200 µg/L) recommended by American Conference of Governmental Industrial Hygienists (ACGIH, 2019). Socioeconomic status, including tobacco usage and employment factors were identified potential determinants for elevated BLL in this group. Individuals with lower economic status had higher BLL compared to socially advanced groups. Participants in the worker class, or those working in close proximity to hazardous processes like furnace smelting, electrochemical refining, and maintenance job showed elevated BLL. Individuals in the study group with BLL above 300 µg/L exhibited symptoms specific to central nervous system, respiratory system, gastrointestinal system and musculoskeletal system. Analysis of clinical parameters indicated that approximately 33.6% participants experienced hypertension, following the guidelines outlined by the Joint National Committee on the prevention and control of high blood pressure (Chobanian et al., 2003 ). Additionally, about 20 participants were found to be anemic (WHO, 2017 ) at BLL above 300 µg/L. Conclusion This study demonstrated development and validation of new ICPMS method for estimating heavy metals particularly Pb, Cd, As, and Hg from trace to elevated levels in human blood samples. The thorough validation process, including selectivity, linearity, accuracy, LoD, LoQ, and precision, confirmed the reliability of analytical method. The developed method exhibited high sensitivity and accuracy, even at ultra-low concentrations, providing a robust tool for the quantification of these toxic elements in whole blood samples. Application of the method to a cohort of 250 workers in a Pb smelting plant revealed concerning levels of heavy metals, particularly Pb, in their blood. The distribution of metal levels across various sociodemographic, employment, and health parameters highlighted specific risk factors. Individuals with lower socioeconomic status, tobacco users, and those engaged in direct contact with smelting processes exhibited higher BLL. Additionally, participants with elevated BLL experienced symptoms related to the central nervous, respiratory, gastrointestinal, and musculoskeletal systems. The prevalence of hypertension and anemia among participants with BLL exceeding 300 µg/L emphasized the potential health risks associated with occupational exposure to heavy metals. These findings underscore the need for continuous monitoring, intervention strategies, and improved occupational hygiene practices to mitigate the adverse health effects in this vulnerable population. In summary, this study contributes valuable insights into the health implications of occupational exposure to heavy metals, providing a basis for informed decision-making, workplace interventions, and policies aimed at safeguarding the well-being of Pb smelting plant workers. Declarations Authors’ contribution: KU: concept, design, definition of intellectual content, literature search, data acquisition, manuscript preparation, manuscript editing and review AV: concept, design, definition of intellectual content, literature search, data acquisition, data analysis RB: design, definition of intellectual content, literature search, data analysis, manuscript preparation, manuscript editing and review AS: concept, definition of intellectual content, data acquisition, data analysis PS: concept, design, literature search, data acquisition Acknowledgement: The authors express sincere gratitude to the management of the lead smelting plant unit for facilitating access to subjects and assisting with data collection for this study. A heartfelt acknowledgment is extended to all lead-smelting plant workers for their enthusiastic response and valuable contributions to the data collection process. Special recognition is given to the unwavering dedication of our technical staff for their efforts in field data collection and instrumental analysis. The authors also appreciate the support provided by the administration of the parent institute in executing this project. Gratitude is extended to all individuals, both directly and indirectly involved, for their contributions to this study. Funding: The present study was conducted with institutional support and no external funding was received. Data availability: Not applicable. Conflict of interest: No conflicts of interest to declare. Ethical approval statement: The required ethical clearance was obtained from the Human Ethics Committee of the parent institute before initiating the study. The study followed all the methods and protocols for human experiments as recommended by the national ethical guidelines for biomedical and health research involving humans. References ACGIH. 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Annals of Occupational and Environmental Medicine , 29 , 47. https://doi.org/10.1186/s40557-017-0202-z Assi, M. A., Hezmee, M. N., Haron, A. W., Sabri, M. Y., & Rajion, M. A. (2016). The detrimental effects of lead on human and animal health. Vet World , 9 (6), 660-671. https://doi.org/10.14202/vetworld.2016.660-671 Bajaj, A. O., Parker, R., Farnsworth, C., Law, C., & Johnson-Davis, K. L. (2023). Method validation of multi-element panel in whole blood by inductively coupled plasma mass spectrometry (ICP-MS). J Mass Spectrom Adv Clin Lab , 27 , 33-39. https://doi.org/10.1016/j.jmsacl.2022.12.005 Bakr, S., Sayed, M. A., Salem, K. M., Morsi, E. M., Masoud, M., & Ezzat, E. M. (2023). Lead (Pb) and cadmium (Cd) blood levels and potential hematological health risk among inhabitants of the claimed hazardous region around Qaroun Lake in Egypt. BMC Public Health , 23 (1), 1071. https://doi.org/10.1186/s12889-023-16007-w Chobanian, A. V., Bakris, G. L., Black, H. R., Cushman, W. C., Green, L. A., Izzo, J. L., Jr., . . . Roccella, E. J. (2003). Seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure. Hypertension , 42 (6), 1206-1252. https://doi.org/10.1161/01.HYP.0000107251.49515.c2 D'Ilio, S., Majorani, C., Petrucci, F., Violante, N., & Senofonte, O. (2010). Method validation for the quantification of As, Cd, Hg and Pb in blood by ICP-MS for monitoring purposes. Anal. Methods , 2 , 2049-2054. https://doi.org/10.1039/C0AY00429D Goyal, T., Mitra, P., Singh, P., Sharma, S., & Sharma, P. (2021). Assessement of Blood Lead and Cadmium Levels in Occupationally Exposed Workers of Jodhpur, Rajasthan. Indian J Clin Biochem , 36 (1), 100-107. https://doi.org/10.1007/s12291-020-00878-6 Gupta, P. C., Elanchezhiyan, A., Shukla, S. C., Sengar, A. S., Saha, A., Surendran, R., . . . Saxena, S. K. (2019). Development, validation, and accreditation of a method for the determination of 75As, 111Cd, 201Hg, and 208Pb in Cephalopods using inductively coupled plasma mass spectrometry (ICP-MS). SN Applied Sciences , 1 (4), 304. https://doi.org/10.1007/s42452-019-0294-x Heitland, P., & Köster, H. (2012). Applications of ICP-MS in Human Biomonitoring Studies. In (pp. 367-395). https://doi.org/10.1002/9781118271858.ch13 ICH Guideline. (2022). Bioanalytical method validation and study sample analysis M10. ICH Harmonised Guideline: Geneva, Switzerland . Mathur, R., & Swaminathan, S. (2018). National ethical guidelines for biomedical & health research involving human participants, 2017: A commentary. The Indian journal of medical research , 148 (3), 279. Muntner, P., Shimbo, D., Carey, R. M., Charleston, J. B., Gaillard, T., Misra, S., . . . Wright, J. T., Jr. (2019). Measurement of Blood Pressure in Humans: A Scientific Statement From the American Heart Association. Hypertension , 73 (5), e35-e66. https://doi.org/10.1161/hyp.0000000000000087 Ripp, J. (1996). Analytical detection limit guidance & laboratory guide for determining method detection limits . Wisconsin Department of Natural Resources, Laboratory Certification Program. Satarug, S., Garrett, S. H., Sens, M. A., & Sens, D. A. (2010). Cadmium, environmental exposure, and health outcomes. Environ Health Perspect , 118 (2), 182-190. https://doi.org/10.1289/ehp.0901234 Upadhyay, K., Viramgami, A., Balachandar, R., Pagdhune, A., Shaikh, I., & Sivaperumal, P. (2023). Development and validation of Graphite Furnace Atomic Absorption Spectrometry method and its application for clinical evaluation of blood lead levels among occupationally exposed lead smelting plant workers. Anal Sci , 39 (4), 517-526. https://doi.org/10.1007/s44211-022-00260-x Vergara-Murillo, F., Martinez-Yanez, K., Fortich-Revollo, A., Paternina-Caicedo, A., & Johnson-Restrepo, B. (2022). Biochemical and Hematological Markers in Workers with Chronical Exposure to Lead and Cadmium in Colombia. Toxics , 10 (9). https://doi.org/10.3390/toxics10090524 WHO. (2017). Nutritional anaemias: tools for effective prevention and control. WHO. (2020). Brief guide to analytical methods for measuring lead in blood, second edition. Geneva: World Health Organization; 2020. https://iris.who.int/bitstream/handle/10665/333914/9789240009776-eng.pdf?isAllowed=y&sequence=1 Additional Declarations The authors declare no competing interests. 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3893267","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":268958170,"identity":"478bce20-fe3f-4de1-ad90-688b605288cd","order_by":0,"name":"Dr. Kuldip Upadhyay","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+ElEQVRIiWNgGAWjYJACaTDJw8B44IMBXFCCKC0MB2eQrOUwDzGOMrjd/PB2YZtdYgPPGYPDNgV20eYN7Bcf8zBY5OHUcueYsfXMtuTEBt4eg8M5Bsm5cw7wFBvzMEgU49RyI8FMmreNObGBnwek5UDuDAaeNMkZDBKJDTi1pH8DaqmHaLEgTksOyJbDEIcxgLWwH5P4gEeL5J0zxdY8544bt/EcKzjYA/TLDGYeZoMPBri18N1u33ibp6xatp8neeODH3/scmewtz98kFBRh1MLOMoY2Rgc2+AizDzACDXApR6qheEPgz2SEPsDPOpHwSgYBaNgBAIAFchUvwlN6eMAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-0416-1923","institution":"ICMR-National Institute of Occupational Health","correspondingAuthor":true,"prefix":"Dr.","firstName":"Kuldip","middleName":"","lastName":"Upadhyay","suffix":""}],"badges":[],"createdAt":"2024-01-24 07:19:54","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-3893267/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3893267/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":50171883,"identity":"d22ab929-f073-41e1-80bd-bac437f4b971","added_by":"auto","created_at":"2024-01-25 15:49:34","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":28572,"visible":true,"origin":"","legend":"\u003cp\u003eLinearity of the calibration\u003c/p\u003e\n\u003cp\u003eLinearity for \u003csup\u003e75\u003c/sup\u003eAs, \u003csup\u003e111\u003c/sup\u003eCd, \u003csup\u003e202\u003c/sup\u003eHg, \u003csup\u003e208\u003c/sup\u003ePb. Seven-point calibration curve revealed linear relationship (r\u003csup\u003e2\u003c/sup\u003e ≥ 0.99) between measured intensity and standard concentration (0.05, 0.1, 0.5, 1.0, 5.0, 10.0 and 50.0 μg/L) for each of the four elements.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3893267/v1/67e50aec45bca2f5ff5704bf.png"},{"id":50172603,"identity":"464da407-cbf0-4170-8476-05b67af335b8","added_by":"auto","created_at":"2024-01-25 15:57:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":537435,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3893267/v1/68802d95-7fcd-4af5-8ef7-7d80c47ffb56.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eDevelopment and validation of an ICPMS method and its application in assessing heavy metals in whole blood samples among occupationally exposed Lead smelting plant workers\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOccupational exposure to heavy metals, specifically lead (Pb), cadmium (Cd), Arsenic (As) and Mercury (Hg) remains a pressing concern due to their adverse health effects(Bakr et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Heavy metals are absorbed into the body through inhalation or ingestion and distributed through the blood to bones and soft tissues (viz. brain, liver, kidney). As a cumulative toxicant, they adversely affect multiple body systems including hematological, neurological, cardiovascular, respiratory, gastrointestinal, renal systems, and bone effects(Assi et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Satarug et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Hence, the American Conference of Governmental Industrial Hygienists (ACGIH) has prescribed biological exposure indices (BEI) values of 200 \u0026micro;g/L for Pb and 5.0 \u0026micro;g/L for Cd to prevent health consequences in occupational exposure(ACGIH, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Workers in Pb smelting plants face a heightened risk of exposure to these toxic metals, leading to potential health complications(An et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In medical surveillance, the whole blood levels of potentially toxic metals are regarded as the primary benchmark for identifying individual exposure (Vergara-Murillo et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Assessing blood levels of toxic elements serves as a critical indicator for understanding the extent of exposure and potential health risks among these workers(Goyal et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Hence, precise analysis for the blood-based estimation of heavy metals in occupationally exposed individuals serves as a critical measure of exposure and aids in identifying potential health risks and establishing necessary interventions to safeguard the well-being of these workers(Upadhyay et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Therefore, the development and validation of an accurate and precise analytical method for quantifying these toxic metals in blood samples become crucial. Different analytical techniques exist to estimate the levels of toxic and trace elements in whole blood samples, including, Graphite Furnace Atomic Absorption Spectrometry (GFAAS), anodic stripping voltammetry (ASV), inductively coupled plasma with atomic emission spectrometry (ICP-AES), and inductively coupled plasma mass spectrometry (ICPMS) (WHO, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, ICPMS is considered the most proficient technique for conducting extensive biomonitoring surveys due to its high sensitivity and robustness in determining a wide range of elements (Heitland \u0026amp; K\u0026ouml;ster, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe present study aimed to develop and validate an ICP-MS method for the precise analysis of Pb, Cd, As and Hg levels in blood samples of occupationally exposed Pb-smelting plant workers. The method validation examined for wide range of performance parameters to ensure its reliability in determining metal concentrations within the samples. Following this validation, the method was applied in a comprehensive assessment of heavy metals in blood samples of occupationally exposed Pb smelting plant workers and elucidated the potential health implications associated with occupational exposure to these heavy metals.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and recruitment of subjects:\u003c/h2\u003e \u003cp\u003eIn this investigation, total 250 consenting adults (aged\u0026thinsp;\u0026gt;\u0026thinsp;18 years) employed at a Pb smelting unit, underwent assessment for levels of heavy metals in their blood samples, along with an evaluation of their associated health status. Ethical clearance was obtained from the Institutional Human Ethics Committee (IHEC) before execution of the study, adhering to all recommended methods and protocols for human experiments outlined in the national ethical guidelines for biomedical and health research involving humans(Mathur \u0026amp; Swaminathan, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e Each participant obtained informed written consent to use their details to investigate the levels of heavy metals in their blood samples, along with an assessment of their associated health status. Sociodemographic and occupational details were collected through a semi-structured, pre-validated questionnaire. The study group was classified for their socioeconomic status using modified B. G. Prasad scale(Akram et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Clinical assessment included a general health examination and workplace-specific investigations. All the consenting participants were collected 5 ml of venous blood in Pb free vacutainers under aseptic precautions. The samples were transported in a refrigerated conditions and analyzed at the parent institute. The levels of Hemoglobin were estimated using HemoCue Hb 301 point of care device and categorized as 'normal' or 'anemic' based on WHO guidelines(WHO, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe clinical assessment involved identifying neurological, respiratory, gastrointestinal, and musculoskeletal symptoms that necessitated medical supervision, resulting in absence from work for more than 24 hours in the previous year. The blood pressure (BP) was measured following the method described in the literature (Muntner et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Upadhyay et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), using a pre-calibrated digital sphygmomanometer (Omron Healthcare, Kyoto, Japan). The subsequent measurements of systolic BP (SBP) and diastolic BP (DBP) were recorded, and the average of the second and third measurements was considered for the study. Participants were classified as pre-hypertensive or hypertensive based on the guidelines recommended by the Joint National Committee in their seventh report on the prevention and control of high blood pressure (Chobanian et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eReagents and Calibration Standards:\u003c/h2\u003e \u003cp\u003eTrace metal grade concentrated nitric acid (67\u0026ndash;70%) for ICP-MS and 30% (w/v) hydrogen peroxide (ACS grade) were acquired from Fisher chemicals. NIST traceable standard reference material with 1000 mg/L concentration of As, Cd, Hg, Pb, and 10mg/L Rhodium internal standard procured from Merck GmBH. Ultrapure deionized water (18.2 MΩ at 25 \u003csup\u003eo\u003c/sup\u003eC) used for standards and sample preparations. Argon plasma and helium collision gas of research grade (purity\u0026thinsp;\u0026gt;\u0026thinsp;99.999%) used for analysis. Calibration standards of 0.05, 0.1, 0.5, 1.0, 5.0, 10.0 and 50.0 \u0026micro;g/L concentration for each target element were prepared by serial dilution of NIST traceable standard reference material (1000 mg/L of each As, Cd, Hg, and Pb, Merck GmBH) with ultrapure deionized water.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eMethod development and Optimization:\u003c/h2\u003e \u003cp\u003eThe sample preparation was optimized to achieve thorough acid digestion using a two-step ramp temperature program. The quantification of the elements of interest was performed using an ICPMS equipped with a collision cell operating in kinetic energy discrimination (KED) mode. Parameters for data acquisition and optimal instrumental settings for the ICPMS equipment were carefully adjusted. To avoid potential carry-over, a two-minute wash with deionized water followed each run. The standard addition method was employed to offset matrix effects, and any variations in analytical signals were rectified using the internal standard (rhodium).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eSample preparation:\u003c/h2\u003e \u003cp\u003e1 ml of whole blood sample was placed in Teflon vessel along with 2 ml of concentrated nitric acid, 0.5 ml of 30% (w/v) hydrogen peroxide and 50\u0026micro;l of Rhodium internal standard. The sample underwent acid digestion in a multi-wave go microwave digestion system (Anton Parr, Germany) using two step temperature program shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. At the end of digestion cycle, the residue was cooled at ambient temperature and transferred into Pb free tubes. Finally, all the samples diluted with ultrapure deionized water up to a 10ml volume and preserved at 4 \u003csup\u003eo\u003c/sup\u003eC until analysis.\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\u003eMicrowave digestion program for acid digestion of blood samples\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRamp (minutes)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTemperature (\u003csup\u003eo\u003c/sup\u003eC)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHold time (minutes)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMicrowave Power (W)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eThe table outlines the microwave digestion program used for acid digestion of blood samples. Each step includes information on ramp time, temperature, hold time, and microwave power settings.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eInstrumentation:\u003c/h2\u003e \u003cp\u003eThe concentrations of heavy metals were measurement using an ICPMS (model 2030, AS-10 autosampler, Shimadzu, Japan) equipped with a collision cell operating in KED mode. Summary of data acquisition parameters and optimized instrumental settings is provided in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. A two-minute wash with deionized water was conducted after each run to prevent potential carryover. The standard addition method was employed to offset matrix effect, and any variations in analytical signals were corrected using the internal standard (rhodium).\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\u003eData acquisition parameters and optimized instrument setup\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSetting\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRF Power\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1200 W\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlasma gas flow (Argon)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (L/min)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAuxiliary gas flow (Argon)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.0 (L/min)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarrier gas flow (Argon)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.2 (L/min)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNebulizer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecoaxial\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSampling depth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 mm\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpray chamber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ewater cooled double pass\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpray chamber temperature (\u003csup\u003eo\u003c/sup\u003eC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCollision cell gas flow (Helium)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 mL/min\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLens voltage (eV)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMass resolution (amu)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntegration time points/ms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoints per peak\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReplicates\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eThe table presents the data acquisition parameters and the optimized instrument setup for the experiment, including RF power, gas flows, nebulizer type, sampling depth, spray chamber configuration, temperature, collision cell gas flow, lens voltage, mass resolution, integration time points, points per peak, and the number of replicates used.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eMethod Validation:\u003c/h2\u003e \u003cp\u003eThe validation of the analytical method relied on established performance parameters, \u003cem\u003eviz\u003c/em\u003e selectivity and linearity, accuracy, method detection limit (\u003cem\u003eLoD\u003c/em\u003e\u003csub\u003e\u003cem\u003em\u003c/em\u003e\u003c/sub\u003e), method quantification limit (\u003cem\u003eLoQ\u003c/em\u003e\u003csub\u003e\u003cem\u003em\u003c/em\u003e\u003c/sub\u003e), and precision. Calibration linearity was assessed through the correlation coefficient (\u003cem\u003er\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e), and linear curves with \u003cem\u003er\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e values exceeding 0.99 were chosen for estimation of As, Cd, Hg and Pb level in blood. Accuracy was determined using the standard addition method, and % recovery falling within the 80\u0026ndash;120% range was deemed acceptable for validation. Precision, as indicated by a coefficient of variance (%CV) obtained from repeated measurements of the same sample, would be considered acceptable for analysis if it is less than 20%. \u003cem\u003eLoD\u003c/em\u003e\u003csub\u003e\u003cem\u003em\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003eLoQ\u003c/em\u003e\u003csub\u003e\u003cem\u003em\u003c/em\u003e\u003c/sub\u003e were calculated based on the standard deviation (SD) from 7 replicates following standard spike method (ICH Guideline, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eICPMS analysis of heavy metals in blood samples\u003c/h2\u003e \u003cp\u003eThe digested whole blood samples were drawn into the ICP-MS through the AS-10 autosampler, which was calibrated for the analysis of As, Cd, Hg, and Pb across a range of concentrations, from trace to elevated levels. The aspirated fraction underwent ionization within an argon plasma and atomization in the spray chamber. Argon gas flowed at 15 L/min through a torch, consisting of concentric glass tubes, generating the argon plasma. The drive coil, surrounding the outlet end of the torch, received radio frequency power of up to 1.2 kW, maintaining a plasma discharge in the argon at a temperature of approximately 9,500 \u003csup\u003eo\u003c/sup\u003eK.\u003c/p\u003e \u003cp\u003eThe ions exited the plasma, traversed the instrument's interface, and reached the entrance of the collision cell, where helium gas was introduced at the flow rate of 6.0 mL/min to eliminate potential polyatomic interferences. The primary quadrupole filtered the ions from the collision cell, and the detector counted and summed electron abundances for each element. The concentration of elements of interest in the specimen was determined using the calibration curve.\u003c/p\u003e \u003c/div\u003e"},{"header":"Result and discussion","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eInterference study:\u003c/h2\u003e\n \u003cp\u003eQuantitative elemental analysis by ICPMS is known to be influenced by spectral or non-spectral interferences, resulting in fluctuations in the target analyte signal (D\u0026apos;Ilio et al., \u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e). So, an interference study was conducted for selected isotopes \u003csup\u003e75\u003c/sup\u003eAs, \u003csup\u003e111\u003c/sup\u003eCd, \u003csup\u003e202\u003c/sup\u003eHg, and \u003csup\u003e208\u003c/sup\u003ePb prior to method validation. It was observed that measuring all the selected isotopes in KED mode using helium as a collision gas encountered potential interferences removal (eg. the detection of \u003csup\u003e75\u003c/sup\u003eAs suffered from the overlapping of the typical molecular ion \u003csup\u003e40\u003c/sup\u003eAr\u003csup\u003e35\u003c/sup\u003eCl in standard mode) and ensured the reliability of the analysis for the precise estimation of target analytes in whole blood samples.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eSelectivity and Linearity:\u003c/h2\u003e\n \u003cp\u003eThe selectivity of the method towards the blood matrix was confirmed by comparing aqueous standard and matrix match calibration curves. The comparison revealed that the slope of the calibration curve from aqueous standards resembles the slope of matrix match calibration curves, indicating no apparent of matrix interferences. Hence, aqueous calibration curves were applied for the calibration throughout the experiments.\u003c/p\u003e\n \u003cp\u003eThe linearity of the method was determined by preparing calibration standard solutions ranging from low to high concentrations of elements of interest to achieve the target concentrations. The values for the linear equation and the linear regression coefficient across the analytical measurement range (AMR), aligned with their respective whole blood reference range values (Bajaj et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e) are illustrated in Figure-1 and Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. The values of correlation coefficients (\u003cem\u003er\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e) obtained\u0026thinsp;\u0026ge;\u0026thinsp;0.99 for linear regression suggest best linear fit across AMR and acceptable for quantification for all toxic elements of interest.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eLinearity across the AMR of multi-elements with their whole blood reference range values\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eElement\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAMR (\u0026micro;g/L)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eReference Range (whole blood) (\u0026micro;g/L)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCorrelation Coefficient (r\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003csup\u003e75\u003c/sup\u003eAs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.05\u0026ndash;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026le;\u0026thinsp;12.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.9999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003csup\u003e111\u003c/sup\u003eCd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.05\u0026ndash;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026le;\u0026thinsp;5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.9999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003csup\u003e202\u003c/sup\u003eHg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.05\u0026ndash;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026le;\u0026thinsp;10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.9979\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003csup\u003e208\u003c/sup\u003ePb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.05\u0026ndash;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026le;\u0026thinsp;50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.9992\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eThe table illustrates the linearity across the Analytical Measurement Range (AMR) for various elements, along with their corresponding reference range values in whole blood. It includes information on the AMR, reference range, and the correlation coefficient (r\u0026sup2;) for each element, demonstrating the precision and accuracy of the analytical method used.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eAccuracy:\u003c/h2\u003e\n \u003cp\u003eThe accuracy of the method was examined by the recovery values of each of the elements of interest, spiked with three different levels of standard concentrations. The % recovery obtained from measured concentration against each spike concentration for each element was range between 85.60\u0026ndash;112.00 as summarized in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRecoveries of the developed analytical method\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAnalyte\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpiked Concentration (\u0026micro;g/L)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMeasured Concentration (\u0026micro;g/L)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e% Recovery\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003csup\u003e75\u003c/sup\u003eAs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e106.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e40.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e42.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e106.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e103.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e103.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003csup\u003e111\u003c/sup\u003eCd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e99.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e112.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e31.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e105.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003csup\u003e202\u003c/sup\u003eHg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e85.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e31.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e104.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e70.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e69.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e99.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003csup\u003e208\u003c/sup\u003ePb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e96.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e150.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e148.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e98.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e180.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e177.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e98.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eThe table presents the recoveries of the developed analytical method for different analytes at various spiked concentrations. It includes information on the spiked concentration, measured concentration, and the percentage recovery for each analyte, indicating the accuracy and reliability of the analytical procedure.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eThe values obtained within \u0026plusmn;\u0026thinsp;20% of the target concentration are considered acceptable for the performance of the method(Bajaj et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). The accuracy assessment suggests that the analytical method is effective in recovering the specified elements across the range of spiked concentrations. These findings provide evidence of the method\u0026apos;s accuracy and reliability for the quantification of the analyzed elements in blood samples at different concentration levels.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003eLimit of Detection (LoD) and Quantification (LoQ)\u003c/h2\u003e\n \u003cp\u003eThe sensitivity of an analytical method is ascertained by \u003cem\u003eLoD\u003c/em\u003e and \u003cem\u003eLoQ\u003c/em\u003e. The method detection limit \u003cem\u003e(LoD\u003c/em\u003e\u003csub\u003e\u003cem\u003em\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e refers to the ability to detect the lowest concentration of an analyte reliably, which can be distinguished from background noise but not necessarily quantified. In contrast, the method quantification limit \u003cem\u003e(LoQ\u003c/em\u003e\u003csub\u003e\u003cem\u003em\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e pertains to the lowest concentration of an analyte that can be quantified with acceptable levels of precision and accuracy. The \u003cem\u003eLoD\u003c/em\u003e\u003csub\u003e\u003cem\u003em\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003eLoQ\u003c/em\u003e\u003csub\u003e\u003cem\u003em\u003c/em\u003e\u003c/sub\u003e were determined based on the standard deviation (\u0026sigma;) of seven replicates of digested blood samples spiked with 1 \u0026micro;g/L of each \u003csup\u003e75\u003c/sup\u003eAs, \u003csup\u003e111\u003c/sup\u003eCd, \u003csup\u003e202\u003c/sup\u003eHg and \u003csup\u003e208\u003c/sup\u003ePb, along with the student t- test value (at 99% confidence that analyte concentration\u0026thinsp;\u0026gt;\u0026thinsp;0 \u0026micro;g/L). The calculations were performed using the equations described in the literature method (Ripp, \u003cspan class=\"CitationRef\"\u003e1996\u003c/span\u003e) and are summarized in Table \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003cstrong\u003eTable 5:\u003c/strong\u003e Estimation of \u003cem\u003eLoD\u003csub\u003em\u003c/sub\u003e\u003c/em\u003e and \u003cem\u003eLoQ\u003csub\u003em\u003c/sub\u003e\u003c/em\u003e\u003c/div\u003e\n \u003cdiv id=\"Equa\" class=\"Equation\"\u003e\n \u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e$$LoDm= \\text{x} 3.14$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Equb\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e$$LoQm= \\text{x} 10$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003eWhere \u003cem\u003eLoD\u003c/em\u003e\u003csub\u003e\u003cem\u003em\u003c/em\u003e\u003c/sub\u003e = method detection limit\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eLoQ\u003c/em\u003e \u003csub\u003e\u0026nbsp;\u003cem\u003em\u003c/em\u003e\u0026nbsp;\u003c/sub\u003e = method quantification limit\u003c/p\u003e\n \u003cp\u003e\u0026sigma;\u0026thinsp;=\u0026thinsp;standard deviation of measured concentrations of seven replicates\u003c/p\u003e\n \u003cp\u003e3.14\u0026thinsp;=\u0026thinsp;t- test value at 99% confidence that analyte concentration\u0026thinsp;\u0026gt;\u0026thinsp;0\u0026micro;g/L\u003c/p\u003e\n \u003cp\u003eThe presented values illustrate that the method is proficient in both detecting and quantifying the specified analytes in blood samples at ultra-trace levels with acceptable precision and accuracy. These results signify the sensitivity of the method in accurately estimating the target elements in whole blood samples at extremely low concentrations.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003ePrecision:\u003c/h2\u003e\n \u003cp\u003eThe analytical precision was assessed by examining the repeatability and reproducibility (within laboratory) of individual test results obtained from repeated measurements of the same sample under distinct analytical conditions(Upadhyay et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). The precision of the proposed method for each target element was determined through repeated measurements of three replicates at three different concentrations over three consecutive days and expressed in terms of the %CV as summarized in Table-6. The %CV is calculated as per the following formula (Gupta et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable-6:\u003c/strong\u003e\u0026nbsp; \u0026nbsp; Assessment of analytical precision \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cimg 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\"\u003e\u003cbr\u003e\u003c/p\u003eThe table assesses the analytical precision for various analytes at different spiked concentrations. It includes information on the spiked concentration, mean concentration of three replicates for three successive days, standard deviation (\u0026sigma;), and the coefficient of variation (%CV), demonstrating the repeatability and reliability of the analytical method.\u003cdiv id=\"Equc\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003eWhere % CV\u0026thinsp;=\u0026thinsp;co-efficient of variance\u003c/p\u003e\n \u003cp\u003e\u0026sigma;\u0026thinsp;=\u0026thinsp;standard deviation of three replicate measurements\u003c/p\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u0026nbsp;\u003cspan class=\"mathinline\"\u003e\\(\\overline{x}\\)\u003c/span\u003e\u0026nbsp;\u003c/span\u003e = mean concentration of three replicate measurements\u003c/p\u003e\n \u003cp\u003eThe obtained results revealed that proposed analytical method demonstrated satisfactory analytical precision for all the target elements across a range of concentrations. The %CV below 20% is considered acceptable and realistic for the concentrations be quantified (D\u0026apos;Ilio et al., \u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e). The % CV values provide insights into the relative variability of the measurements, and the low standard deviations suggest good repeatability and reproducibility of the method over the three successive days. These findings support the reliability of the proposed analytical method for the quantification of the target elements in whole blood samples.\u003c/p\u003e\n \u003cp\u003eReference values for various heavy metals in human blood are publicly accessible in the literature(Bajaj et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). The newly developed method is capable of measuring the elements of interest even at lower levels with improved accuracy and precision, owing to better method detection and quantification limits. A synopsis of performance parameters of the present analytical method is summarized in Table \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable-7 :\u003c/strong\u003e Summary of performance parameters\u003c/p\u003e\n \u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.489795918367346%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.775510204081634%\" colspan=\"4\" valign=\"top\" style=\"width: 61.8294%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eObtained value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.734693877551024%\" rowspan=\"2\" style=\"width: 13.0221%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAccepted range\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\" style=\"width: 18.4766%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003csup\u003e75\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003eAs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\" style=\"width: 20.2363%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003csup\u003e111\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003eCd\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\" style=\"width: 12.7495%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003csup\u003e202\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003eHg\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\" style=\"width: 10.4432%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003csup\u003e208\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003ePb\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\"\u003e\n \u003cp\u003eLinearity (\u003cem\u003er\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 18.4766%;\"\u003e\n \u003cp\u003e0.9999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 20.2363%;\"\u003e\n \u003cp\u003e0.9999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 12.7495%;\"\u003e\n \u003cp\u003e0.9979\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 10.4432%;\"\u003e\n \u003cp\u003e0.9992\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37.5%\" style=\"width: 13.0221%;\"\u003e\n \u003cp\u003e\u0026ge; 0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eAccuracy (% recovery)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.775510204081634%\" colspan=\"4\" style=\"width: 61.8294%;\"\u003e\n \u003cp\u003e85.60 \u0026ndash; 112.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.734693877551024%\" style=\"width: 13.0221%;\"\u003e\n \u003cp\u003e80 \u0026ndash; 120\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\"\u003e\n \u003cp\u003eLoDm (\u0026mu;g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 18.4766%;\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 20.2363%;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 12.7495%;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 10.4432%;\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37.5%\" style=\"width: 13.0221%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\"\u003e\n \u003cp\u003eLoQm (\u0026mu;g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 18.4766%;\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 20.2363%;\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 12.7495%;\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 10.4432%;\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37.5%\" style=\"width: 13.0221%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003ePrecision (% CV)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.775510204081634%\" colspan=\"4\" style=\"width: 61.8294%;\"\u003e\n \u003cp\u003e1.35 \u0026ndash; 7.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.734693877551024%\" style=\"width: 13.0221%;\"\u003e\n \u003cp\u003e\u0026lt; 20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eTable 7 provides a summary of performance parameters for the analytical method, including linearity (\u003cem\u003er\u0026sup2;\u003c/em\u003e), accuracy (% recovery), limit of detection (\u003cem\u003eLoDm\u003c/em\u003e), limit of quantification (\u003cem\u003eLoQm\u003c/em\u003e), and precision (% CV). The obtained values are compared to accepted ranges, demonstrating the reliability and suitability of the method for the analysis of \u003csup\u003e75\u003c/sup\u003eAs, \u003csup\u003e111\u003c/sup\u003eCd, \u003csup\u003e202\u003c/sup\u003eHg, and \u003csup\u003e208\u003c/sup\u003ePb.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cp\u003eThe evaluation of all test parameters confirmed the successful validation of the proposed method. The values obtained for each parameter fell within the acceptable limits outlined by standard guidelines(ICH Guideline, \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e; Ripp, \u003cspan class=\"CitationRef\"\u003e1996\u003c/span\u003e). Consequently, the developed method was applied for the clinical assessment of heavy metals in blood samples collected from occupationally exposed, Pb smelting plant workers.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003eEstimation of heavy metals in blood samples among occupationally exposed individuals\u003c/h2\u003e\n \u003cp\u003eWorkers engaged in the Pb smelting activities are predominantly exposed to elevated levels of Pb and potentially toxic other heavy metals. These individuals are possibly at elevated risk of developing heavy metal toxicity, especially if low awareness and poor hygiene practice exist at workplace. In this study, the individuals, who were occupationally exposed through various Pb smelting processes and activities, underwent clinical evaluation as a part of their periodic medical examination. The study included participants from both executive and worker categories, assigned to different sections of the plant, such as furnace, electrochemical refining, maintenance, and others (e.g., utility, sulfuric acid plant, captive power plant, etc.).\u003c/p\u003e\n \u003cp\u003eExposure to heavy metals in their blood samples was assessed using a newly developed analytical method. The distribution of the exposed population and blood-based levels of heavy metals concerning sociodemographic profiles, employment factors, system-specific symptoms, and representative clinical parameters is summarized in Table \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable-8:\u003c/strong\u003e\u0026nbsp; \u0026nbsp;Demographic details and distribution of study population with their blood levels of heavy metals\u0026nbsp;\u003c/p\u003e\n \u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"109%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.69387755102041%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.204081632653061%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndividual \u0026nbsp; \u0026nbsp;(n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"55.10204081632653%\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e(Mean \u0026plusmn; SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.69387755102041%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.204081632653061%\" colspan=\"2\" rowspan=\"11\"\u003e\n \u003cp\u003e250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"55.10204081632653%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e33.68 \u0026plusmn; 6.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.63636363636363%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eJob duration (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"61.36363636363637%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e6.99 \u0026plusmn; 4.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.63636363636363%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eBMI (Kg/m\u003csup\u003e2\u003c/sup\u003e)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"61.36363636363637%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e24.28 \u0026plusmn; 3.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.63636363636363%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eSystolic BP (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"61.36363636363637%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e130.67 \u0026plusmn; 15.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.63636363636363%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eDiastolic BP (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"61.36363636363637%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e84.05 \u0026plusmn; 13.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.63636363636363%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003ePulse rate (per minute)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"61.36363636363637%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e82.77 \u0026plusmn; 11.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.63636363636363%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eHaemoglobin (g/dL)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"61.36363636363637%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e14.78 \u0026plusmn; 1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.63636363636363%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003csup\u003e75\u003c/sup\u003eAs (\u0026micro;g/L)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"61.36363636363637%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e2.46 \u0026plusmn; 1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.63636363636363%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003csup\u003e111\u003c/sup\u003eCd (\u0026micro;g/L)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"61.36363636363637%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e3.45 \u0026plusmn; 5.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.63636363636363%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003csup\u003e202\u003c/sup\u003eHg (\u0026micro;g/L)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"61.36363636363637%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e9.27 \u0026plusmn; 1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.63636363636363%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003csup\u003e208\u003c/sup\u003ePb (\u0026micro;g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"61.36363636363637%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e367.91 \u0026plusmn; 147.91\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.755102040816325%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistribution of element in the exposed population (\u0026micro;g/L)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.16326530612245%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003csup\u003e75\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003eAs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.244897959183673%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003csup\u003e111\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003eCd\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.244897959183673%\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003csup\u003e202\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003eHg\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.306122448979592%\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003csup\u003e208\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003ePb\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"60.60606060606061%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAs per sociodemographic factors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.121212121212121%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.121212121212121%\" valign=\"top\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\" valign=\"top\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.52577319587629%\" rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eSocio-economic status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003eUpper class\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\" colspan=\"2\"\u003e\n \u003cp\u003e154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e2.41 \u0026plusmn; 1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e3.55 \u0026plusmn; 6.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e9.22 \u0026plusmn; 1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e348.50 \u0026plusmn; 152.74\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.25%\"\u003e\n \u003cp\u003eUpper-middle-class\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\" colspan=\"2\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.5%\"\u003e\n \u003cp\u003e2.35 \u0026plusmn; 1.38\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e3.07 \u0026plusmn; 2.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e9.15 \u0026plusmn; 1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e405.28 \u0026plusmn; 147.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.25%\"\u003e\n \u003cp\u003eMiddle class\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\" colspan=\"2\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.5%\"\u003e\n \u003cp\u003e3.03 \u0026plusmn; 1.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e3.87 \u0026plusmn; 2.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e9.82 \u0026plusmn; 0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e382.56 \u0026plusmn; 95.58\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.25%\"\u003e\n \u003cp\u003eLower-middle-class\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\" colspan=\"2\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.5%\"\u003e\n \u003cp\u003e4.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e4.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e10.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e375.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.52577319587629%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003ePersonal addiction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003eTobacco chewing/smoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\" colspan=\"2\"\u003e\n \u003cp\u003e103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e2.72 \u0026plusmn; 1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e4.31 \u0026plusmn; 1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e9.59 \u0026plusmn; 1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e382.97 \u0026plusmn; 154.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.25%\" valign=\"top\"\u003e\n \u003cp\u003eNo addiction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\" colspan=\"2\"\u003e\n \u003cp\u003e147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.5%\"\u003e\n \u003cp\u003e2.29 \u0026plusmn; 1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e2.85 \u0026plusmn; 3.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e9.03 \u0026plusmn; 1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e357.36 \u0026plusmn; 142.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"60.60606060606061%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAs per the employment factor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.121212121212121%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.121212121212121%\" valign=\"top\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\" valign=\"top\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.52577319587629%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eJob profile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003eExecutive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\" valign=\"top\"\u003e\n \u003cp\u003e2.13 \u0026plusmn; 1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e2.59 \u0026plusmn; 3.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e8.92 \u0026plusmn; 1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e325.91 \u0026plusmn; 150.91\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.25%\"\u003e\n \u003cp\u003eWorker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\" colspan=\"2\"\u003e\n \u003cp\u003e128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.5%\"\u003e\n \u003cp\u003e2.76 \u0026plusmn; 1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\"\u003e\n \u003cp\u003e4.28 \u0026plusmn; 6.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e9.60 \u0026plusmn; 1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e408.15 \u0026plusmn; 134.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003eDepartment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003eFurnace\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\" valign=\"top\"\u003e\n \u003cp\u003e2.40 \u0026plusmn; 1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e3.04 \u0026plusmn; 2.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e9.10 \u0026plusmn; 1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e397.65 \u0026plusmn; 141.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003eElectro-chemical refining\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\" valign=\"top\"\u003e\n \u003cp\u003e2.75 \u0026plusmn; 1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e3.27 \u0026plusmn; 5.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e9.18 \u0026plusmn; 1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e349.12 \u0026plusmn; 125.93\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003eMaintenance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\" valign=\"top\"\u003e\n \u003cp\u003e2.37 \u0026plusmn; 1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e4.69 \u0026plusmn; 8.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e9.58 \u0026plusmn; 1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e399.52 \u0026plusmn; 144.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003eOther (utility, by-product, etc.)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\" valign=\"top\"\u003e\n \u003cp\u003e2.39 \u0026plusmn; 1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e2.98 \u0026plusmn; 2.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e9.48 \u0026plusmn; 1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e211.87 \u0026plusmn; 123.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"60.60606060606061%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAs per system-specific symptoms\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.121212121212121%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.121212121212121%\" valign=\"top\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\" valign=\"top\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.52577319587629%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eCentral nervous system\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003eHeadache\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\" colspan=\"2\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e1.80 \u0026plusmn; 1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e1.87 \u0026plusmn; 1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e8.66 \u0026plusmn; 1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e368.96 \u0026plusmn; 153.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.25%\" valign=\"top\"\u003e\n \u003cp\u003eMemory loss\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\" colspan=\"2\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.5%\"\u003e\n \u003cp\u003e2.79 \u0026plusmn; 1.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e5.03 \u0026plusmn; 8.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e9.35 \u0026plusmn; 1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e375.17 \u0026plusmn; 186.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.25%\" valign=\"top\"\u003e\n \u003cp\u003eMalaise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\" colspan=\"2\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.5%\"\u003e\n \u003cp\u003e1.56 \u0026plusmn; 1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e2.30 \u0026plusmn; 2.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e8.32 \u0026plusmn; 1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e367.33 \u0026plusmn; 121.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.52577319587629%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eRespiratory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003eCough\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\" colspan=\"2\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e2.29 \u0026plusmn; 1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e1.88 \u0026plusmn; 1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e9.51 \u0026plusmn; 0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e285.00 \u0026plusmn; 62.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.25%\" valign=\"top\"\u003e\n \u003cp\u003eDyspnoea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\" colspan=\"2\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.5%\"\u003e\n \u003cp\u003e2.27 \u0026plusmn; 1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e3.16 \u0026plusmn; 4.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e9.10 \u0026plusmn; 1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e396.04 \u0026plusmn; 146.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.52577319587629%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eGastro-intestinal\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003eLoss of appetite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\" colspan=\"2\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e2.56 \u0026plusmn; 1.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e7.19 \u0026plusmn; 12.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e9.77 \u0026plusmn; 0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e365.12 \u0026plusmn; 124.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.25%\" valign=\"top\"\u003e\n \u003cp\u003eGastritis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\" colspan=\"2\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.5%\"\u003e\n \u003cp\u003e2.35 \u0026plusmn; 1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e2.72 \u0026plusmn; 2.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e9.20 \u0026plusmn; 1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e394.75 \u0026plusmn; 144.84\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.52577319587629%\" rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eMusculoskeletal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003eKnee pain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\" colspan=\"2\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e2.21 \u0026plusmn; 1.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003e3.37 \u0026plusmn; 2.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e9.09 \u0026plusmn; 1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" valign=\"top\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e401.11 \u0026plusmn; 137.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.25%\"\u003e\n \u003cp\u003eNeck pain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\" colspan=\"2\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.5%\"\u003e\n \u003cp\u003e1.69 \u0026plusmn; 1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e2.25 \u0026plusmn; 2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e8.46 \u0026plusmn; 1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e308.09 \u0026plusmn; 169.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.25%\"\u003e\n \u003cp\u003eBack pain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\" colspan=\"2\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.5%\"\u003e\n \u003cp\u003e2.13 \u0026plusmn; 1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e2.61 \u0026plusmn; 1.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e9.25 \u0026plusmn; 1.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e339.00 \u0026plusmn; 108.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.25%\"\u003e\n \u003cp\u003eAnkle ache\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\" colspan=\"2\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.5%\"\u003e\n \u003cp\u003e1.85 \u0026plusmn; 1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e3.34 \u0026plusmn; 6.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e8.86 \u0026plusmn; 1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e332.50 \u0026plusmn; 117.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"60.60606060606061%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAs per clinical parameters\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.121212121212121%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.121212121212121%\" valign=\"top\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\" valign=\"top\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.52577319587629%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eHypertension (as per JNC-8 guidelines)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003ePre-hypertensive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\" colspan=\"2\"\u003e\n \u003cp\u003e155\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e2.42 \u0026plusmn; 1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e3.16 \u0026plusmn; 3.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e9.24 \u0026plusmn; 1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e352.91 \u0026plusmn; 145.19\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.25%\"\u003e\n \u003cp\u003eHypertensive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\" colspan=\"2\"\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.5%\"\u003e\n \u003cp\u003e2.47 \u0026plusmn; 1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\"\u003e\n \u003cp\u003e3.28 \u0026plusmn; 2.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e9.21 \u0026plusmn; 1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e389.94 \u0026plusmn; 154.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.52577319587629%\" valign=\"top\"\u003e\n \u003cp\u003eAnemia\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.52577319587629%\"\u003e\n \u003cp\u003eanemic (Haemoglobin based)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\" colspan=\"2\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e2.50 \u0026plusmn; 1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e5.32 \u0026plusmn; 12.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" style=\"width: 10.9582%;\"\u003e\n \u003cp\u003e9.62 \u0026plusmn; 1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" style=\"width: 8.4536%;\"\u003e\n \u003cp\u003e338.50 \u0026plusmn; 177.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eTable 8 provides the demographic details and the distribution of the study population along with their blood levels of heavy metals. It includes parameters such as age, job duration, BMI, blood pressure, pulse rate, hemoglobin, and concentrations of heavy metals (\u003csup\u003e75\u003c/sup\u003eAs, \u003csup\u003e111\u003c/sup\u003eCd, \u003csup\u003e202\u003c/sup\u003eHg, \u003csup\u003e208\u003c/sup\u003ePb). Additionally, the distribution of these elements based on sociodemographic factors, personal addiction, employment factors, system-specific symptoms, and clinical parameters is presented.\u003c/p\u003e\n \u003cp\u003eThe study population exhibited significantly higher BLL above the BEI (200 \u0026micro;g/L) recommended by American Conference of Governmental Industrial Hygienists (ACGIH, 2019). Socioeconomic status, including tobacco usage and employment factors were identified potential determinants for elevated BLL in this group. Individuals with lower economic status had higher BLL compared to socially advanced groups. Participants in the worker class, or those working in close proximity to hazardous processes like furnace smelting, electrochemical refining, and maintenance job showed elevated BLL. Individuals in the study group with BLL above 300 \u0026micro;g/L exhibited symptoms specific to central nervous system, respiratory system, gastrointestinal system and musculoskeletal system. Analysis of clinical parameters indicated that approximately 33.6% participants experienced hypertension, following the guidelines outlined by the Joint National Committee on the prevention and control of high blood pressure (Chobanian et al., \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e). Additionally, about 20 participants were found to be anemic (WHO, \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e) at BLL above 300 \u0026micro;g/L.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study demonstrated development and validation of new ICPMS method for estimating heavy metals particularly Pb, Cd, As, and Hg from trace to elevated levels in human blood samples. The thorough validation process, including selectivity, linearity, accuracy, LoD, LoQ, and precision, confirmed the reliability of analytical method. The developed method exhibited high sensitivity and accuracy, even at ultra-low concentrations, providing a robust tool for the quantification of these toxic elements in whole blood samples. Application of the method to a cohort of 250 workers in a Pb smelting plant revealed concerning levels of heavy metals, particularly Pb, in their blood. The distribution of metal levels across various sociodemographic, employment, and health parameters highlighted specific risk factors. Individuals with lower socioeconomic status, tobacco users, and those engaged in direct contact with smelting processes exhibited higher BLL. Additionally, participants with elevated BLL experienced symptoms related to the central nervous, respiratory, gastrointestinal, and musculoskeletal systems. The prevalence of hypertension and anemia among participants with BLL exceeding 300 \u0026micro;g/L emphasized the potential health risks associated with occupational exposure to heavy metals. These findings underscore the need for continuous monitoring, intervention strategies, and improved occupational hygiene practices to mitigate the adverse health effects in this vulnerable population. In summary, this study contributes valuable insights into the health implications of occupational exposure to heavy metals, providing a basis for informed decision-making, workplace interventions, and policies aimed at safeguarding the well-being of Pb smelting plant workers.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors’ contribution:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKU:\u003c/strong\u003e concept, design, definition of intellectual content, literature search, data acquisition, manuscript preparation, manuscript editing and review\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAV:\u003c/strong\u003e concept, design, definition of intellectual content, literature search, data acquisition, data analysis\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRB:\u003c/strong\u003e design, definition of intellectual content, literature search, data analysis, manuscript preparation, manuscript editing and review\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAS:\u003c/strong\u003e concept, definition of intellectual content, data acquisition, data analysis\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePS:\u003c/strong\u003e concept, design, literature search, data acquisition\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors express sincere gratitude to the management of the lead smelting plant unit for facilitating access to subjects and assisting with data collection for this study. A heartfelt acknowledgment is extended to all lead-smelting plant workers for their enthusiastic response and valuable contributions to the data collection process. Special recognition is given to the unwavering dedication of our technical staff for their efforts in field data collection and instrumental analysis. The authors also appreciate the support provided by the administration of the parent institute in executing this project. Gratitude is extended to all individuals, both directly and indirectly involved, for their contributions to this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e The present study was conducted with institutional support and no external funding was received.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest:\u003c/strong\u003e No conflicts of interest to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval statement:\u003c/strong\u003e The required ethical clearance was obtained from the Human Ethics Committee of the parent institute before initiating the study. The study followed all the methods and protocols for human experiments as recommended by the national ethical guidelines for biomedical and health research involving humans.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eACGIH. 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Seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure. \u003cem\u003eHypertension\u003c/em\u003e,\u003cem\u003e 42\u003c/em\u003e(6), 1206-1252. https://doi.org/10.1161/01.HYP.0000107251.49515.c2\u003c/li\u003e\n\u003cli\u003eD\u0026apos;Ilio, S., Majorani, C., Petrucci, F., Violante, N., \u0026amp; Senofonte, O. (2010). Method validation for the quantification of As, Cd, Hg and Pb in blood by ICP-MS for monitoring purposes. \u003cem\u003eAnal. Methods\u003c/em\u003e,\u003cem\u003e 2\u003c/em\u003e, 2049-2054. https://doi.org/10.1039/C0AY00429D\u003c/li\u003e\n\u003cli\u003eGoyal, T., Mitra, P., Singh, P., Sharma, S., \u0026amp; Sharma, P. (2021). 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Bioanalytical method validation and study sample analysis M10. \u003cem\u003eICH Harmonised Guideline: Geneva, Switzerland\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eMathur, R., \u0026amp; Swaminathan, S. (2018). National ethical guidelines for biomedical \u0026amp; health research involving human participants, 2017: A commentary. \u003cem\u003eThe Indian journal of medical research\u003c/em\u003e,\u003cem\u003e 148\u003c/em\u003e(3), 279.\u003c/li\u003e\n\u003cli\u003eMuntner, P., Shimbo, D., Carey, R. M., Charleston, J. B., Gaillard, T., Misra, S., . . . Wright, J. T., Jr. (2019). Measurement of Blood Pressure in Humans: A Scientific Statement From the American Heart Association. \u003cem\u003eHypertension\u003c/em\u003e,\u003cem\u003e 73\u003c/em\u003e(5), e35-e66. https://doi.org/10.1161/hyp.0000000000000087\u003c/li\u003e\n\u003cli\u003eRipp, J. (1996). \u003cem\u003eAnalytical detection limit guidance \u0026amp; laboratory guide for determining method detection limits\u003c/em\u003e. Wisconsin Department of Natural Resources, Laboratory Certification Program.\u003c/li\u003e\n\u003cli\u003eSatarug, S., Garrett, S. H., Sens, M. A., \u0026amp; Sens, D. A. (2010). Cadmium, environmental exposure, and health outcomes. \u003cem\u003eEnviron Health Perspect\u003c/em\u003e,\u003cem\u003e 118\u003c/em\u003e(2), 182-190. https://doi.org/10.1289/ehp.0901234\u003c/li\u003e\n\u003cli\u003eUpadhyay, K., Viramgami, A., Balachandar, R., Pagdhune, A., Shaikh, I., \u0026amp; Sivaperumal, P. (2023). Development and validation of Graphite Furnace Atomic Absorption Spectrometry method and its application for clinical evaluation of blood lead levels among occupationally exposed lead smelting plant workers. \u003cem\u003eAnal Sci\u003c/em\u003e,\u003cem\u003e 39\u003c/em\u003e(4), 517-526. https://doi.org/10.1007/s44211-022-00260-x\u003c/li\u003e\n\u003cli\u003eVergara-Murillo, F., Martinez-Yanez, K., Fortich-Revollo, A., Paternina-Caicedo, A., \u0026amp; Johnson-Restrepo, B. (2022). Biochemical and Hematological Markers in Workers with Chronical Exposure to Lead and Cadmium in Colombia. \u003cem\u003eToxics\u003c/em\u003e,\u003cem\u003e 10\u003c/em\u003e(9). https://doi.org/10.3390/toxics10090524\u003c/li\u003e\n\u003cli\u003eWHO. (2017). Nutritional anaemias: tools for effective prevention and control.\u003c/li\u003e\n\u003cli\u003eWHO. (2020). \u003cem\u003eBrief guide to analytical methods for measuring lead in blood, second edition. Geneva: World Health Organization; 2020.\u003c/em\u003e https://iris.who.int/bitstream/handle/10665/333914/9789240009776-eng.pdf?isAllowed=y\u0026amp;sequence=1\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"ICMR-National Institute of Occupational Health","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":"heavy metals, whole blood, trace level detection, analytical method, clinical assessment, occupational exposure. ","lastPublishedDoi":"10.21203/rs.3.rs-3893267/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3893267/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eOccupational exposure to heavy metals affecting various organ systems, poses a significant health risk to workers. Consequently, its precise estimation is of clinical concern and warrants the need for an analytical method with reliable precision and accuracy. Current study aimed to develop an analytical method using inductively coupled plasma mass spectrometry (ICPMS) to detect trace to elevated levels of potentially toxic elements in human blood. The sample preparation optimized using a two-step ramp temperature microwave acid digestion program. The toxic elements quantified using ICPMS operating in kinetic energy dispersion (KED) mode, adjusting data acquisition parameters and instrumental settings. The analytical method was validated using standard performance parameters. Each validation parameter aligned with the acceptable criteria outlined in standard guidelines. The method achieved optimal linearity (r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.99), recovery (85.60\u0026ndash;112.00%), precision (1.35\u0026ndash;7.03%), capable of detecting the lowest concentration of 0.32, 0.28, 0.28, and 0.19 \u0026micro;g/L, and quantifying trace levels of 1.01, 0.88, 0.90, and 0.62 \u0026micro;g/L for arsenic (As), cadmium (Cd), mercury (Hg), and lead (Pb), respectively. Post-validation, the method was applied to estimate heavy metals in blood samples from 250 Pb smelting plant workers, revealing potential health implications of occupational exposure. The cohort analysis revealed demographic and employment factors were associated with elevated blood lead levels (BLL), leading to symptoms and health risks. Clinical analysis indicated 33.6% participants experienced hypertension, and 20 were anemic at BLL above 300 \u0026micro;g/L. It emphasizes the importance of continuous monitoring, interventions, and improved occupational hygiene to protect the well-being of workers.\u003c/p\u003e","manuscriptTitle":"Development and validation of an ICPMS method and its application in assessing heavy metals in whole blood samples among occupationally exposed Lead smelting plant workers","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-25 15:49:29","doi":"10.21203/rs.3.rs-3893267/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"061d0401-6081-42f5-bb7e-12a53aea0823","owner":[],"postedDate":"January 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-01-25T15:49:29+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-25 15:49:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3893267","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3893267","identity":"rs-3893267","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}