Kowit Nambunmee

Industrial disasters in high-risk sectors such as the petrochemical industry continue to occur, despite significant advancements in process safety and technological controls over the years. This suggests ongoing operational challenges and a lack of consistent academic understanding across both technical and regulatory dimensions. While earlier bibliometric studies have focused on specific thematic areas such as domino effects and risk analysis, a thorough synthesis of the thematic evolution and collaboration structures in industrial disaster research remains limited. To address this gap, this study provides a systematic bibliometric mapping of research focused on industrial disasters, analyzing the themes, impact, and collaboration trends over the past thirty years. The analysis assessed publication trends, co-authorship networks, citation dynamics, bibliographic coupling and keyword co-occurrence through the evaluation of 357 Scopus-indexed publications from 1995 to 2025. The findings indicate a gradual transition from technical risk assessment to more comprehensive integrative perspectives. While domino effects and process safety remain the primary focus of study, recent publication trends demonstrate a growing interest in safety culture and organizational factors. European nations, especially Italy, the Netherlands, and Belgium, have become significant players in global research collaborations, suggesting a wider European focus on industrial safety management and regulatory structures such as the Seveso Directive. Thematic clustering revealed three main themes: technical risk assessment, human and organizational factors, and the environmental and societal impacts of disasters, highlighting a growing integration of technical and socio-regulatory issues. Through a comprehensive longitudinal and network-based synthesis that addresses various themes, this study highlights significant works, overlooked correlations, and new research domains such as resilience-oriented risk governance, establishing a basis for more integrated industrial safety research, policy formulation and organizational risk management strategies.

Objectives: Exposure determinant modeling can help industrial hygienists understand where, when, and how to control occupational exposures for their particular work environment. Yet, in practice, the ability to evaluate exposure determinants is degraded by selection bias (where only a subset of all exposed workers is sampled) and the statistical issue of “small n, large p” (few samples but many exposure determinants). This study explored the application of the causal inference framework and machine learning algorithms in exposure determinant modeling using a “small n, large p” example of potential determinants of heavy metal concentrations among informal electronic waste recycling workers. Methods: As a case study, we used a multivariable logistic regression model to construct inverse probability weights to account for selection bias into a video substudy of 41 of 226 possible workers monitored for exposures to heavy metals. Forty-four determinants of biomarkers (eg tool use, job tasks, and personal protective equipment use) were quantified through video monitoring. Concentrations of heavy metals in blood (Pb and Mn) and urine (Ni and Cu) were sampled. We identified the best-performing biomarker determinant model by comparing the leave-one-out cross-validation root-mean-squared error (LOOCV-RMSE) of 5 models: 2 traditional models (multivariate linear regression and forward selection), and 3 machine learning algorithms (LASSO, boosted regression trees, and random forests). Using the best-performing model, we estimated reductions in heavy metal concentrations through hypothetical workplace controls to identify the most important determinant of biomarker concentrations. Results: The random forest model had the lowest LOOCV-RMSE and was used as the final biomarker determinant model. Stopping workers from bending their backs while dismantling e-waste was the most important determinant of heavy metal concentrations. Using blood Pb as an example, this translated to an estimated reduction of 0.81 µg/dL (95% confidence interval: 0.66, 0.98) in comparison with maintaining the status quo. Using a traditional regression model (forward selection without inverse probability weights), back bending was not identified as an important determinant of blood Pb. Discussion: Our causal inference approach with machine learning algorithms overcomes the common limitations of exposure determinant modeling and produces easy-to-interpret estimates of biomarker concentration reductions from hypothetical workplace controls. This can aid industrial hygienists in choosing the most effective hazard controls that can be contextualized to their particular work setting.

Control of the COVID-19 pandemic requires significant changes in people’s health behaviors. We offer this multidisciplinary perspective on the extent of compliance with social distancing recommendations and on coping with these measures around the globe in the first months of the pandemic. We present descriptive data from our survey of 17,650 respondents across 18 countries and territories in June 2020. The majority of respondents worried about contracting the virus. Nearly all engaged in at least some preventive behaviors, particularly handwashing, mask wearing, and avoiding social events. Most reported that it would be difficult to continue these behaviors for more than a few months, and about half reported feeling more anxious since the start of the pandemic. Commonly reported coping behaviors included news consumption, watching television, and sleeping. Our cross-national study highlights areas for developing and implementing health behavior interventions in the global fight to stop the spread of COVID-19.

The informal recycling of electronic waste (“e-waste”) is a lucrative business for workers in low- and middle-income countries across the globe. Workers dismantle e-waste to recover valuable materials that can be sold for income. However, workers expose themselves and the surrounding environment to hazardous agents during the process, including toxic metals like lead (Pb). To assess which tools, tasks, and job characteristics result in higher concentrations of urine and blood lead levels among workers, ten random samples of 2 min video clips were analyzed per participant from video recordings of workers at e-waste recycling sites in Thailand and Chile to enumerate potential predictors of lead burden. Blood and urine samples were collected from participants to measure lead concentration. Boosted regression trees (BRTs) were run to determine the relative importance of video-derived work variables and demographics, and their relationship with the urine and blood concentrations. Of 45 variables considered, five job characteristics consisting of close-toed shoes (relative importance of 43.9%), the use of blunt striking instruments (14%), bending the back (5.7%), dismantling random parts (4.4%), and bending the neck (3.5%) were observed to be the most important predictors of urinary Pb levels. A further five job characteristics, including lifting objects 20 pounds (3.2%) were observed to be among the most important factors of blood Pb levels. Overall, our findings indicate ten job characteristics that may strongly influence Pb levels in e-waste recycling workers’ urine and blood.

Farming is an important occupation in Thai hill tribe communities, which are often remote, and lack other economic opportunities along with basic educational, health care, and occupational health and safety services. Additionally, these communities have a unique culture and language. The present study was conducted in northern Thailand to evaluate pesticide exposures and associated health impacts among hill tribe farmers, and to compare them to Thai farmers. Lahu hill tribe farmers in a mountain community were recruited by public health hospital staff, along with a reference group of lowland Thai farmers. Participants completed a survey on demographic factors and work practices, and blood and urine samples were collected by a trained nurse. Acetylcholinesterase activity (AChE) was quantified to assess pesticide exposure, whereas liver and kidney functions were evaluated using clinical biomarkers. A large fraction (nearly 50%) of Lahu farmers were illiterate and could not speak Thai. Thai farmers worked fewer hours per week (39.4) than did Lahu farmers. Among Lahu farmers, AChE levels were significantly lower (worse) than those of Thai farmers. However, other health outcomes in these populations were similar. Formal education and language skills were not associated with pesticide exposures or health outcomes. Pesticide spraying was found to be a significant predictor of reduced AChE (OR=8.5, 95% CI 1.1–69.6). Pesticide exposures are a significant occupational health hazard among Thai hill tribe farmers. Training, potentially delivered by community health volunteers, is needed to communicate safe pesticide work practices to these farmers. Obtained The study protocol was approved by the Institutional Review Board of Mae Fah Luang University (REH-61080). The authors declare no competing financial interests.

Go/no-go decisions require engineering design teams to evaluate whether a concept is worth further investment of resources. These decisions can be difficult when product success depends on multiple stakeholders in addition to the end-user. This study proposes the Stakeholder Disagreement Metric (SDM) framework to estimate the level of disagreement between stakeholder preferences

Background: Papanicolaou test is widely used to screening cervical cancer but low attend rate. There is one mountainous area found high participation rate. Objective: This study aimed to determine the factors associated with successful Pap test among Lahu hill tribe women. Materials and Methods: The quantitative cross-sectional study was used in this study. Data were collected from 650 Lahu hill tribe women by simple random sampling. The interview forms with reliability coefficient and validity of 0.78 and 0.91 were administered to participants. The data were analyzed by using descriptive statistics and Chi-square test. Results: The 96.15% of the Lahu hill tribe women had taken Pap test and 74.31% obtained the screening more than once. The contraceptive use and frequency of Pap test obtaining significantly associated with cervical cancer screening (p <0.001). The participants showed good level of knowledge in cervical cancer and the screening test (64.31% and 76.46% respectively). Most of participants received the cervical cancer disease information (87.17%) and screening information (66.92%) from health care professionals, which may influence on well cervical screening co-operation. Conclusions: The suitable health promotion model should provide to promote knowledge, attitude and motivate continuous cooperation in cervical cancer screening among hill tribe women.

Objectives To assess pesticide exposure and understand the resultant health effects of agricultural workers in Northern Thailand. Methods This was a cross‐sectional study. We quantified exposure to pesticides, including chlorpyrifos, methomyl, and metalaxyl, by air sampling and liquid chromatography/mass spectrometry. We estimated differences in self‐reported health outcomes, complete blood counts, cholinesterase activity, and serum/urine calcium and creatinine concentrations at baseline between farmworkers and comparison workers, and after pesticide spraying in farmworkers only. Results This study included 97 men between the ages of 22 and 76 years; 70 were conventional farmworkers; and 27 did not report any prior farmwork or pesticide spraying. None of the farmworkers wore standardized personal protective equipment (PPE) for the concentrated chemicals they were working with. Methomyl (8.4‐13 481.9 ng/m³), ethyl chlorpyrifos (11.6‐67 759 ng/m³), and metalaxyl (13.9‐41 191.3 ng/m³) were detected via personal air sampling. When it came to reporting confidence in the ability to handle personal problems, only 43% of farmworkers reported feeling confident, which reflects higher stress levels in comparison to 78% of comparison workers (P = .028). Farmworkers also had significantly lower monocyte counts (P = .01), serum calcium (P = .01), red blood count (P = .01), white blood cell count (P = .04), and butyrylcholinesterase activity (P < .0001), relative to comparison workers. After adjusting for body mass index (BMI), age, and smoking, methomyl air concentrations were associated with a decrease in farmworker acetylcholinesterase activity (beta = −0.327, P = .016). Conclusions This population of farmworkers had significant alterations in stress measures and clinical biomarkers, including decreased blood cell counts and cholinesterase activity, relative to matched controls. These changes are potentially linked to occupational pesticide exposures. Improving PPE use presents a likely route for preventive intervention in this population.

Go/no-go decisions require engineering design teams to evaluate whether a concept is worth further investment of resources. These decisions can be difficult when product success depends on multiple stakeholders in addition to the end-user. This study proposes the Stakeholder Agreement Metric (SAM) framework to estimate the level of agreement between stakeholder preferences via the distance between optimal designs calculated from a preference model derived from conjoint analysis. The framework was tested in an empirical case study describing the design and piloting of a hand tool for informal electronic waste workers in Thailand. Data from a follow-up assessment indicate the SAM estimate aligned with future metrics of stakeholder satisfaction. The case study also qualitatively compared SAM to the analytical hierarchy process (AHP). Data collection issues with AHP illustrated some of the practical limitations of the framework. This study suggests that the SAM framework is a promising tool to further explore as a way to support designers making go/no-go decisions that involve multiple stakeholders. Further exploration should include additional case studies to investigate potential outcomes of different SAM values and comparing multiple stakeholder groups.