Abstract: Tractor and self-propelled machinery drivers experience significant vibration disturbance due to work on uneven terrain. Seat suspension is usually the key mitigation measure in agricultural tractors, typically using mechanical or pneumatic systems with stiffness ad-justment based on driver mass (50–140 kg). However, this adjustment is often overlooked or improperly set, reducing its protective effect. This study examines the impact of incorrect seat suspension adjustment on vibration exposure. Two tractors of similar size and mass, but equipped with different seats, were tested under identical conditions, to assess discomfort levels. Tests were conducted on an inter-farm road at varying travelling speeds and tyre pressures. An 84 kg driver partici-pated, first with correctly adjusted suspension, then with incorrect settings, both stiffer and softer. The collected data were compared with standard vibration exposure limits, to evalu-ate the negative effects of improper adjustment. Results highlight the importance of proper seat suspension calibration in minimizing driver discomfort as well as potential health risks.

Abstract: Background/Objectives: We aimed to identify differences in the relationship between patient activation, cancer-related symptoms, and job performance among young adult cancer survivors with low and high workplace support. Methods: Our cross-sectional observational study was conducted using an online survey across Japan in January 2022. The survey was designed to assess demographic and clinical characteristics, patient activation, physical fatigue, depression, cognitive impairments, and job performance. Multiple-group structural equation modeling (SEM) was conducted using data from 202 young adult cancer survivors. Results: Of the 202 participants, 53% were aged 35–39 years, 78% were female, and 67% were permanent workers. Patient activation was positively associated with job performance (β = 0.28, p < 0.01) and negatively related to cancer-related symptoms (β = -0.30, p = 0.01), and cancer-related symptoms were negatively associated with job performance (β = -0.29, p = 0.01), only among young adult cancer survivors with low workplace support. On the other hand, in the high support group, the path coefficients from patient activation to cancer-related symptoms (β = -0.06, p = 0.76), cancer-related symptoms to job performance (β = -0.12, p = 0.37), and patient activation to job performance (β = 0.20, p = 0.21) were not significant. Conclusions: Patient activation plays an important role in improving job performance, especially among young adult cancer survivors who lack workplace support. Even if obtaining workplace support is difficult for young adult cancer survivors, activation of self-management can improve their job performance.

Abstract: Expanding the WBE footprint to include low-resource settings where small, informal, and ad-hoc wastewater systems and high burdens of disease are co-located requires resource-efficient and adaptable methods. To that end, we deployed passive samplers made of granular activated carbon (GAC) into raw influent at a small wastewater treatment plant continuously over 90 days. Detections of SARS-CoV-2 RNA, respiratory syncytial virus RNA, and human adenovirus DNA on GAC passive samplers were coincident with regional clinical trends during a low-incidence period. GAC also recovered bacterial DNA, including mapA, a gene associated with Campylobacter jejuni. A set of antibiotic resistance genes – tetW, blaTEM, blaCTX – were also quantified from GAC passive samplers and did not show increased relative abundance over exposure durations up to 168 hours. Sequencing of 16S rRNA amplicons indicated the GAC samplers recovered bacterial families abundant in both wastewater and feces. Over 38 deployments up to 168 hours long, the average uptake rate decayed exponentially with exposure duration for 16S rRNA (R² = 0.972), pepper mild mottle virus (R² = 0.882), and human adenovirus (R² = 0.585). GAC passive samplers may afford a resource-efficient approach to producing quantitative data for a wide variety of infectious agents relevant to WBE.

Abstract: Dietary exposure to a high-dose cadmium (Cd) ≥ 100 µg/day for at least 50 years or a lifetime intake of Cd ≥ 1 g causes severe damage to kidneys and bones. Alarmingly, however, exposure to a dose of Cd between 10 and 15 µg/day increases worldwide prevalence of non-communicable diseases, including chronic kidney disease (CKD), non-alcoholic fatty liver disease, fragile bones, diabetes, and cancer. Because such a low-dose Cd exposure, results in urinary Cd excretion rates < 1 µg/g creatinine, it has cast considerable doubt on a “tolerable” Cd exposure of 58 µg/day for a 70 kg person, while questioning a threshold level at urinary Cd excretion rate at 5.24 µg/g creatinine. The present review addresses many unmet challenges in a threshold-based risk assessment for Cd. Special emphasis is given to the benchmark dose (BMD) methodology to estimate the Cd exposure limit that aligns with a no-observed adverse effect level (NOAEL). Reported results of BMDL modeling of Cd exposure levels using different nephrotoxicity endpoints are summarized to identify the most sensitive sign on which exposure guidelines should be based. It also aims to demonstrate that a health-protective exposure guideline for Cd should employ the most recent scientific research data, and the dose-response curves, constructed from an unbiased exposure indicator, and clinically relevant adverse effects such as proteinuria and a decrease in estimated glomerular filtration rate. These are signs of developing CKD and its progression to end stage, when dialysis or a kidney transplant is required for survival.

Abstract: Background/Objectives: This study is a pilot evaluation of the applicability of wearable digital healthcare devices for Korean male seafarers. Seafarers are exposed to health risks due to unstable and confined living conditions, and their access to healthcare services be-comes significantly challenging, especially with the substantial decrease in physical ac-tivity onboard. This study aimed to monitor the physical activity of these seafarers through wearable devices and evaluate the potential of managing their health using these technologies. Methods: During the 12-week study, which included 11 participants, it was confirmed that monitoring physical activity using wearable devices and smartphone ap-plications was effective. Results: The results showed significant differences in blood pressure reduction (p = .011) and positive changes in clinical indicators of metabolic syn-drome, such as weight loss. Satisfaction with the use of wearable devices was found to be moderate. Conclusions: Such digital healthcare can encourage the maintenance of healthy habits by continuously monitoring physical activity and providing feedback. Considering the difficulties seafarers face in accessing medical services, the adoption of digital healthcare through wearable devices is essential, contributing to the prevention of chronic diseases and overall health improvement of seafarers. Future research should explore the long-term benefits and potential challenges of these digital healthcare solutions on a larg-er scale.

Abstract: Background: Infection control is fundamental in dental practice, especially following the COVID-19 pandemic, which highlighted the variability in students’ adherence to disinfection protocols. This study aimed to evaluate the knowledge, attitudes, and practices of 4th- and 5th-year dental students at the National and Kapodistrian University of Athens regarding antisepsis and infection control, and to assess the effectiveness of an educational intervention. Methods: A pre-post interventional study was conducted involving two in-person seminars, supplementary e-learning materials, and a structured questionnaire administered before and after the intervention. The survey assessed knowledge, clinical practices, and attitudes toward infection control, including vaccination history and prior exposure incidents. Results: The intervention led to statistically significant improvements in infection control knowledge, especially in risk-based sterilization strategies, disinfectant classification, and PPE use. Students with prior hepatitis B vaccination and antibody testing demonstrated higher baseline scores and more significant knowledge gains. However, some misconceptions, particularly regarding surface disinfection and prosthetic care, persisted after the intervention. Conclusions: The findings support the effectiveness of structured educational interventions in improving infection control awareness among dental students. Practical, simulation-based training and earlier curriculum integration are recommended to enhance compliance and ensure safe clinical practice.

Abstract: Specific occupational factors among midwives—such as shift work, night duties, and significant professional responsibilities—are likely to contribute to a high perceived workload within this group. These factors may increase the risk of nutrition-related health issues, including abnormal body weight and disordered eating behaviors. Despite growing awareness of these concerns, research examining the predictors of nutrition-related health risks among midwives remains limited. The present study aimed to assess the prevalence and key occupational predictors of such risks in this population. A cross-sectional preliminary study was conducted among 703 midwives in Poland. Disordered eating behaviors were evaluated using the Eating Attitudes Test-26 (EAT-26), while workload intensity was measured with the Quantitative Workload Inventory (QWI). Additional data on BMI classification, work experience, and night shift history were collected. A Classification and Regression Tree (C&amp;RT) model was used to identify key predictors of nutritional health risk, defined as meeting at least one of the following criteria: abnormal BMI, EAT-26 score &gt; 20, behavioral indicators of disordered eating, or a history of treatment for an eating disorder. Of the participants, 56.76% (n = 399) were classified as being at nutritional health risk. The most salient predictors included work experience (more than 17.5 years), duration of night shift work, and QWI score. Among midwives with over 17.5 years of experience, both night shift duration and QWI score were significant predictors. For those with 17.5 years or less of experience, QWI score was the strongest predictor. Night shift work alone was not a significant factor in the model. Work experience and workload intensity are key predictors of nutrition-related health risks among midwives. Targeted workplace interventions—including schedule optimization, stress management programs, and nutrition-focused education—may help mitigate these risks. Further research is warranted to explore the long-term health consequences of occupational stress in this professional group.

Abstract: Hand hygiene (HH) related illnesses, such as diarrhea, are one of the leading causes of death in children under 5, whereas handwashing with soap can reduce infection rates in this age group. This study monitored whether a simple intervention in the form of a hand washing exercise, could reduce pathogens on preschool children’s hands, poten-tially reducing HH-related diseases. Hand bag-wash samples were collected from pre-school children (N=160) participating in an intervention study. Samples were collected pre- and post-intervention from the intervention (IG) and control groups (CG). Sam-ples were analysed using flow cytometry, where microbiological counts and turbidity were compared between left and right hands, between genders, and pre- and post-intervention groups. Results indicated no significant difference in the microbio-logical counts of left and right hands or between the gender of participants, with a sig-nificant reduction in intact live cells of IG children’s hands post-intervention (p=0.000). There was a significant positive correlation (p=0.000) between turbidity pre- and post-hand washing, with a decreased mean in turbidity recorded for both groups. Handwashing either with or without soap reduced microbiological counts on pre-schoolers hands. Reinforcing handwashing at critical times and correct hand-washing procedures can assist in reducing hand hygiene-related diseases in preschool children.

Abstract: Background/Objective: This study aimed to review the neurologic and cognitive complications of the Respiratory Syncytial Virus (RSV) disease through studies involving infants, children, and adolescents up to 17 years of age. Methods: The PubMed, Scopus, Cochrane Library, and PsycINFO databases were com-prehensively searched for prospective clinical trials written in the English language that assess the neurologic and/or cognitive manifestations of RSV. The “PRISMA” guidelines were used for the following review. Results: The key findings from the 11 included studies highlighted a range of neurologic complications, including central apnea, febrile seizures, encephalopathy, and more se-vere outcomes such as hypoxic or excitotoxic encephalopathy. While most studies focused on younger children under six years, adolescents and long-term cognitive outcomes were significantly underrepresented. One study reported delayed language development and potential memory impairments, highlighting the virus's impact on early cognitive processes. Conclusions: The findings from the review underscore the need for expanded research into RSV's neurologic and cognitive impacts, particularly in underexplored populations such as adolescents and the importance of early detection, targeted therapeutic inter-ventions, and preventive measures like vaccines to mitigate the burden of RSV on pe-diatric health. Future investigations should focus on longitudinal assessments to elucidate long-term effects and standardize methodologies for enhanced comparability.

Abstract: High pathogenicity avian influenza viruses (AIV) are a constant worldwide threat to animals and humans. The ongoing spread of the H5N1 virus underlines the pressing need for enhanced monitoring and containment strategies. Here, we report the development and validation of a novel workflow for investigating AIV genes in environmental water. This approach integrates three key components: concentration via QuickConc, extraction using a COPMAN kit, and detection through reverse transcription-preamplification-quantitative PCR. Spike experiments demonstrated that our workflow exhibits a 100-fold increase in sensitivity for AIV gene detection, compared to a combination of hemagglutination assay, QIAamp RNA Blood Mini, and one-step RT-qPCR as a control method. The efficacy of this approach was further corroborated by the successful identification of influenza M and H5 genes in field samples, specifically from surface water volumes not exceeding 500 mL collected from a body of water frequented by migratory birds. This workflow represents a significant advancement in environmental AIV surveillance, potentially augmenting our capacity to monitor and track AIV dynamics in wild bird populations using aquatic ecosystems.

Abstract: This study aimed to detect Schistosoma haematobium DNA in the urine samples of school-age children (SAC) in Otamokun, Oyo State, South-west Nigeria. A communi-ty-based cross-sectional study involving 165 SAC aged 5-16 years selected through multi-stage sampling was carried out. S. haematobium DNA was extracted from the urine samples containing S. haematobium eggs after microscopy and the mitochondria gene (COX1) was amplified using conventional Polymerase Chain Reaction (PCR). S. haemato-bium eggs were found in 12 out of 165 (7.3%) urine samples after microscopy, 11 SAC had light infection and one had moderate infection. Nine of the 12 urine samples amplified af-ter PCR and S. haematobium DNA was identified in six of the nine samples. Three of the six samples containing S. haematobium DNA were related to hybrid species of S. hae-matobium and S. bovis in the NCBI gene bank. Urinary Schistosomiasis is still prevalent in Otamokun with the possibility of hybridization between cattle and humans. Cross-reactivity with related species may be responsible for the amplified sequences not related to any known organism in the NCBI database. It is imperative to educate the community on the factors associated with Schistosomiasis, especially the implication of sharing water sources between humans and cattle.

Abstract: Background: Ambient air pollution is a modifiable determinant of lung cancer survival, affecting early-stage Non-Small Cell Lung Cancer (NSCLC) incidence and mortality. Methods: This retrospective cohort study examined the association of all-cause mortality and exposure to air pollution among stage 1A NSCLC-treated patients from the U.S. National Cancer Registry from 1988 to 2015. The Cox hazard model and Kaplan-Meier survival plots were provided. Air pollutants were included separately and together in the models, accounting for spatiotemporal weather variability affecting air pollution exposure levels pre and post-diagnosed lung cancer. Results: NO2 (above median sample mean=25.66 ppb, 12.97 ppb below median), SO2 (above median sample mean=3.98 ppb, 1.81 ppb below median), and CO (above median sample mean=1010.84 ppb, 447.91 ppb below median) air pollutant levels and weather conditions were calculated for county-day units. The median survival months for those exposed to above median NO2 is 27 months (SD=17.61 months) and 30 months (SD=15.93 months) for those exposed to below median. Multipollutant analyses indicated that an average monthly NO2 increase of 1 part per billion (ppb) in the county of NSCLC diagnosis was associated with 4%, 6%, and 9%; SO2 were 16%, 17%, and 17%; 53%, 51%, and 42% for CO increase in the all-cause mortality hazard rate one, three, and five years after diagnosis, respectively. Conclusion: It is vital to implement environmental policies that control emissions to reduce preventable deaths in stage 1A NSCLC patients with adenocarcinoma or squamous cell carcinoma histology types who reside in metropolitan areas.

Abstract: Background/Objectives: Wastewater treatment plants (WWTP) serve as a sink for both antimicrobial residues and bacteria carrying resistant genes which are later disseminated into the environment, facilitating the spread of antimicrobial resistance. This study investigated the presence of extended spectrum beta-lactamase (ESBL) producing Escherichia coli (Ec), Klebsiella pneumoniae (Kp) and Enterobacter cloacae (Enc) in effluent from WWTP in Blantyre, Malawi, to generate evidence and provide baseline information for interventions. Methods: Selective chromogenic agar was used to identify ESBL-producing bacteria. Results: A total of 288 samples were collected between April, 2023 and March, 2024 and 97.6% (281/288) yielded one or more presumptive ESBL isolates. Bacterial growth was confirmed as 48.9% Ec (255/522), 33.0% Kp (172/522) and 10.0% Enc (52/522). Antibiotic susceptibility testing showed higher resistance to ceftriaxone (Ec, 100.0%; Kp, 98.3%; Enc, 100.0%) and lower resistance to meropenem (Ec, 6.3%, Kp, 1.2%; Enc, 3.8%) among the antibiotics that were tested. Multiple antibiotic resistance phenotypes were observed in 73.1% of the isolates with the most prevalent phenotype as AUG-SXT-DXT-CIP-GM-ATH-CRO (55, 15.7%). Conclusions: The study demonstrated ongoing environmental contamination with antibiotic resistant bacteria from sewage effluent. Therefore, the functionality of WWTP should be improved to minimize the release of these organisms into the environment.

Abstract: This study analyzes the impact of heatwaves on hospital admissions in the Matam region, Senegal, by integrating climate modeling and advanced machine-learning techniques. Given the increasing frequency and severity of heatwaves, particularly in vulnerable regions such as the Sahel, it is critical to understand their health impacts to enhance public health responses. The primary objective of this research is to characterize the temporal dynamics of heatwave-induced hospitalizations and to identify key climatic and socio-demographic factors influencing these admissions. Our methodological approach involved detecting and characterizing heatwaves using climatic indices, such as daily maximum temperatures (TMAX) and maximum heat index (HI), and assessing their impacts on hospital admissions using Ourossogui Regional Hospital data from January 2017 to May 2022. Advanced predictive models, including Random Forest (RF), Extreme Gradient Boosting (XGB), and traditional Generalized Additive Models (GAM), were developed and compared to evaluate their effectiveness in capturing complex interactions between climatic and health variables. To ensure the robustness of our findings, a bootstrapping approach with 1000 iterations was applied, allowing for the estimation of confidence intervals and reducing dependence on a single training sample. The results revealed a significant delayed increase in hospitalizations occurring approximately three to five days after heatwave events, suggesting that physiological deterioration and behavioral factors, such as delayed health-seeking due to environmental constraints and social behaviors, contribute to this latency. Among the predictive models tested, RF achieved the best performance with an R² of [0.51; 0.72], clearly outperforming traditional statistical approaches. Bootstrapping further confirmed the stability of these predictions, reinforcing the reliability of machine learning models in climate-health studies. These findings highlight the critical need for enhancing heatwave monitoring and establishing robust early-warning systems. Integrating climate predictions into public health strategies could significantly improve preparedness and enable health systems to respond more effectively to extreme heat events. Targeted prevention measures, particularly focused on vulnerable groups such as the elderly, children, and outdoor workers, should be prioritized. In future research, incorporating additional environmental factors such as air pollution, wind, and others could further refine predictions. Moreover, expanding the study to include a greater number of healthcare facilities and integrating vulnerability factors such as the availability of healthcare structures, access to potable water, energy access, vegetation cover, hydrology, mobile network coverage, poverty dimension, and other socioeconomic indicators would enhance the analysis. The use of advanced Deep Learning techniques could also improve prediction accuracy by effectively modeling complex and nonlinear interactions. Additionally, it would be relevant to extend the study to other regions particularly vulnerable to extreme heat, to gain a more comprehensive understanding of its health and climatic impacts.

Abstract: (1) Background: This study examines the relationship between hospital pharmacists' psychological contracts and their attitudes and behaviors in managing patient medication adherence. The goal is to provide a solid scientific foundation and practical recommendations for improving pharmacists' involvement in adherence management; (2) Methods: A Delphi evaluation, involving pharmacy experts from healthcare institutions, was conducted to refine the Pharmacists' Attitudes and Behaviors Toward Patient Medication Adherence Management Scale. This scale, alongside other relevant instruments, was used to survey pharmacists working in public healthcare institutions across two cities in Guizhou, China; (3) Results: The Attitudes Toward Patient Medication Adherence Management Scale exhibited strong reliability, with a Cronbach’s α coefficient of 0.796 and a KMO value of 0.899. The Behaviors Toward Patient Medication Adherence Management Scale demonstrated even higher reliability, with a Cronbach’s α of 0.986 and a KMO value of 0.963. A significant positive correlation was found between pharmacists' psychological contracts and their attitudes and behaviors toward patient medication adherence management (P &lt; 0.01). Additionally, job burnout was identified as a partial mediator, accounting for 23.41% of the total effect; Targeted interventions to strengthen psychological contracts should be implemented to improve pharmacists' motivation and performance, ultimately boosting patient safety and treatment outcomes. (4) Conclusions: The fulfillment of pharmacists' psychological contracts plays a key role in enhancing their involvement in medication adherence management. Targeted interventions to strengthen these psychological contracts should be implemented to improve pharmacists' motivation and performance, ultimately boosting patient safety and treatment outcomes.

Abstract: Baylisascariasis is a debilitating and potentially lethal zoonotic, parasitic disease caused by an intestinal ascarid that has a northern hemisphere distribution. Baylisascaris spp. are carried by a variety of mammalian hosts, which their larva can infect a large diversity of paratenic hosts that includes birds and mammals, and even humans. Herein, I demonstrate the potential exposure risk of this zoonotic parasite to suburbia America who resides commensally with Baylisascaris-infected raccoons (Procyon lotor). I surveyed soil of 100 properties within neighborhoods of southern Corpus Christi, Texas, USA, for the presence of viable Baylisascaris procyonis eggs, and found 27% of the residential properties were contaminated. Positive soil samples, on average, contained 31,287 ± 6,943 B. procyonis eggs, of which, on average, 92% (92.1 ± 2.3; x‾ SE) of the B. procyonis eggs had motile larvae. Locations of contaminated soils appeared random; no specific habitat feature appeared to have a greater likelihood of contamination. I offer residence of Baylisascaris-contaminated properties suggestions to reduce their risks of exposure to this potentially debilitating parasite.

Abstract: Burnout and anger are prevalent among healthcare professionals in high-stress envi-ronments, particularly in addiction services. This study explores the relationship between burnout and anger among 124 operators working in public addiction services (SERD) in Calabria and Sicily. The objective is to assess how different anger dimensions contribute to burnout and identify protective factors that could inform targeted interventions. Methods: Burnout was measured using the Maslach Burnout Inventory (MBI), assessing emotional exhaustion, depersonalization, and personal accomplishment. Anger was evaluated through the State-Trait Anger Expression Inventory-2 (STAXI-2), examining trait anger, state anger, anger expression (anger-in, anger-out), and anger control. A cross-sectional design was used, with correlation and regression analyses controlling for gender and years of service. Results: High levels of burnout, particularly emotional exhaustion and depersonalization, were found. Emotional exhaustion correlated strongly with trait anger, indicating that individuals with a chronic predisposition to anger are more vulnerable to burnout. Suppression of anger (anger-in) significantly predicted depersonalization, exacerbating emotional disengagement from patients. Conversely, anger control acted as a protective factor, helping maintain a sense of personal accom-plishment. Conclusions: These findings underscore the importance of emotional regu-lation in mitigating burnout among addiction service workers. Interventions such as emotional regulation training and anger management programs could help reduce psychological distress and promote resilience. Workplace strategies that support emo-tional well-being may improve both staff retention and patient care quality. Further research should explore longitudinal trends and intervention effectiveness.

Abstract: Despite their potential impact on meat safety and occupational health, fungi are often underestimated contaminants in slaughterhouses. Moulds and yeasts may be associated with meat contamination in multiple processing stages, and mycotoxigenic species, such as Aspergillus, Fusarium, and Penicillium, pose food safety concerns. Bioaerosols may carry infectious fungi at the slaughterhouse that are capable of causing respiratory conditions and allergies. Chronic exposure to mycotoxins can have hepatotoxic, nephrotoxic, and carcinogenic effects in humans. While bacterial meat contamination has been extensively studied, fungal contamination remains overlooked due to insufficient research, awareness, and standardised surveillance protocols. This review compiles published data on fungal occurrence in slaughterhouses from the past twenty-five years. It aims to highlight the primary mould and yeast isolated species, providing a context on their role in meat safety and occupational health. The findings emphasise the need for improved risk assessment and fungal monitoring in meat plants. Standardised fungal detection and control protocols are also suggested to be implemented to enhance meat safety and workplace conditions.

Abstract: Background: Burnout is a significant problem for employees—particularly concerning COVID-19 and involving healthcare workers. One way for employees to avoid work-related burnout is to experience the psychological flow investigated by Csikszentmihalyi. Yet, COVID-19 may have contributed to the unattainability of psychological flow for burnout-prone employees. The objective is to determine the COVID-19 achievability of flow by employees and, if attained, whether flow resulted in burnout avoidance during the pandemic. Method: To examine the topic range of research, a scoping review includes searches of six primary databases (CINAHL, OVID, ProQuest, PubMed, Scopus, Web of Science), two searches of one supplementary database (Google Scholar), and one register (Cochrane COVID-19 register) of the keywords “burnout, COVID-19, employees, healthcare providers, psychological flow, Csikszentmihalyi”. Included are peer-reviewed, COVID-19-related, 2020-2025 journal publications. The exclusions are duplicates, non-COVID-19-related publications, reports lacking a research study, keywords, or relevant information. Results: In identifying 754 records, five records met the inclusion criteria. Conclusions: Psychological flow was possible during COVID-19 for various employee types, represents the opposite of burnout regarding a workplace stimulation scale, and attaining it permitted burnout avoidance, suggesting a focus on achieving flow in the workplace during pandemics would diminish the incidence of employee burnout.

Abstract: Physical fatigue is a significant concern in repetitive production line operations, often contributing to musculoskeletal disorders (MSDs) and high absenteeism rates. This study focuses on a pharmaceutical packaging line where workers frequently develop MSDs due to the repetitive nature of their tasks. To address this issue, biometric data from smartwatches, including pulse rate, internal temperature, electrodermal activity, and movement patterns, were collected alongside demographic factors such as age and experience and occupational factors related to task demands, including physical load, and operational conditions such as production line location, day of the week, work shift, and timing within the shift. Principal Component Analysis was first applied to reduce the dataset's dimensionality, extracting the most relevant features. Subsequently, fuzzy logic was employed to label the data into two and four levels of fatigue based on prior research. The resulting features and labels were then used as inputs for machine learning classification models to predict fatigue states. Our findings demonstrate that integrating wearable sensor data significantly enhances classification performance. In binary classification, the Random Forest model achieved an F1 score of 0.935 with biometric data and 0.681 without it. For the four-level classification, incorporating biometric data improved the F1 score from 0.573 to 0.903, highlighting its importance in fatigue prediction. This study contributes by developing a generalized predictive fatigue model and establishing a foundation for a real-time fatigue alert system to enhance worker safety and productivity.