Search Results (597)

Online Probability Panels (OPPs) have emerged as essential research infrastructures for social sciences, offering robust tools for longitudinal analysis and evidence-based policy-making. However, the growing role of the Open Science movement demands systematic evaluation of their compliance. This study compares major European OPPs—including LISS, GESIS, the GIP, ELIPSS, and the Swedish and Norwegian Citizen Panels—focusing on their practices of openness, recruitment, sampling, and maintenance. Through a qualitative analysis of public documentation and methodological reports, the study examines how their diverse approaches influence data accessibility, inclusivity, and long-term usability. Our findings highlight substantial variability across panels, reflecting the interplay between national contexts, governance models, technological infrastructures, and methodological choices related to recruitment, sampling, and panel maintenance. Some panels demonstrate stronger alignment with Open Science values—promoting transparency, interoperability, and inclusive engagement—while others operate within more constrained frameworks shaped by institutional or structural limitations. This comparative analysis contributes to the understanding of OPPs as evolving knowledge infrastructures and provides a reference framework for future panel development. In doing so, it offers valuable insights for enhancing the role of OPPs in advancing Open and socially engaged research practices. Full article

Background: Type 2 diabetes (T2D) has been placed among the risk factors for fragility (osteoporotic) fractures, particularly in menopausal women amid modern clinical practice. Objective: We aimed to analyze the bone status in terms of mineral metabolism assays, blood bone turnover markers (BTM), and bone mineral density (DXA-BMD), respectively, to assess the 10-year fracture probability of major osteoporotic fractures (MOF) and hip fracture (HF) upon using conventional FRAX without/with femoral neck BMD (MOF-FN/HF-FN and MOF+FN/HF+FN) and the novel model (FRAXplus) with adjustments for T2D (MOF+T2D/HF+T2D) and lumbar spine BMD (MOF+LS/HF+LS). Methods: This retrospective, cross-sectional, pilot study, from January 2023 until January 2024, in menopausal women (aged: 50–80 years) with/without T2D (group DM/nonDM). Inclusion criteria (group DM): prior T2D under diet ± oral medication or novel T2D (OGTT diagnostic). Exclusion criteria: previous anti-osteoporotic medication, prediabetes, insulin therapy, non-T2D. Results: The cohort (N = 136; mean age: 61.36 ± 8.2y) included T2D (22.06%). Groups DM vs. non-DM were age- and years since menopause (YSM)-matched; they had a similar osteoporosis rate (16.67% vs. 23.58%) and fracture prevalence (6.66% vs. 9.43%). In T2D, body mass index (BMI) was higher (31.80 ± 5.31 vs. 26.54 ± 4.87 kg/m²; p < 0.001), while osteocalcin and CrossLaps were lower (18.09 ± 8.35 vs. 25.62 ± 12.78 ng/mL, p = 0.002; 0.39 ± 0.18 vs. 0.48 ± 0.22 ng/mL, p = 0.048), as well as 25-hydroxyvitamin D (16.96 ± 6.76 vs. 21.29 ± 9.84, p = 0.013). FN-BMD and TH-BMD were increased in T2D (p = 0.007, p = 0.002). MOF+LS/HF+LS were statistically significant lower than MOF-FN/HF-FN, respectively, MOF+FN/HF+FN (N = 136). In T2D: MOF+T2D was higher (p < 0.05) than MOF-FN, respectively, MOF+FN [median(IQR) of 3.7(2.5, 5.6) vs. 3.4(2.1, 5.8), respectively, 3.1(2.3, 4.39)], but MOF+LS was lower [2.75(1.9, 3.25)]. HF+T2D was higher (p < 0.05) than HF-FN, respectively, HF+FN [0.8(0.2, 2.4) vs. 0.5(0.2, 1.5), respectively, 0.35(0.13, 0.8)] but HF+LS was lower [0.2(0.1, 0.45)]. Conclusion: Type 2 diabetic menopausal women when compared to age- and YSM-match controls had a lower 25OHD and BTM (osteocalcin, CrossLaps), increased TH-BMD and FN-BMD (with loss of significance upon BMI adjustment). When applying novel FRAX model, LS-BMD adjustment showed lower MOF and HF as estimated by the conventional FRAX (in either subgroup or entire cohort) or as found by T2D adjustment using FRAXplus (in diabetic subgroup). To date, all four types of 10-year fracture probabilities displayed a strong correlation, but taking into consideration the presence of T2D, statistically significant higher risks than calculated by the traditional FRAX were found, hence, the current model might underestimate the condition-related fracture risk. Addressing the practical aspects of fracture risk assessment in diabetic menopausal women might improve the bone health and further offers a prompt tailored strategy to reduce the fracture risk, thus, reducing the overall disease burden. Full article

Background: Environmental exposures, such as per- and polyfluoroalkyl substances (PFAS), in conjunction with social and behavioral factors, can significantly impact liver health. This research investigates the combined effects of PFAS (perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS), alcohol consumption, smoking, income, and education on liver function among the U.S. population, utilizing data from the 2017–2018 National Health and Nutrition Examination Survey (NHANES). Methods: PFAS concentrations in blood samples were analyzed using online solid-phase extraction combined with liquid chromatography–tandem mass spectrometry (LC-MS/MS), a highly sensitive and specific method for detecting levels of PFAS. Liver function was evaluated using biomarkers such as alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), gamma-glutamyltransferase (GGT), total bilirubin, and the fatty liver index (FLI). Descriptive statistics and multivariable linear regression analyses were employed to assess the associations between exposures and liver outcomes. Bayesian Kernel Machine Regression (BKMR) was utilized to explore the nonlinear and interactive effects of these exposures. To determine the relative influence of each factor on liver health, Posterior Inclusion Probabilities (PIPs) were calculated. Results: Linear regression analyses indicated that income and education were inversely associated with several liver injury biomarkers, while alcohol use and smoking demonstrated stronger and more consistent associations. Bayesian Kernel Machine Regression (BKMR) further highlighted alcohol and smoking as the most influential predictors, particularly for GGT and total bilirubin, with posterior inclusion probabilities (PIPs) close to 1.0. In contrast, PFAS showed weaker associations. Regression coefficients were small and largely non-significant, and PIPs were comparatively lower across most liver outcomes. Notably, education had a higher PIP for ALT and GGT than PFAS, suggesting a more protective role in liver health. People with higher education levels tend to live healthier lifestyles, have better access to healthcare, and are generally more aware of health risks. These factors can all help reduce the risk of liver problems. Overall mixture effects demonstrated nonlinear trends, including U-shaped relationships for ALT and GGT, and inverse associations for AST, FLI, and ALP. Conclusion: These findings underscore the importance of considering both environmental and social–behavioral determinants in liver health. While PFAS exposures remain a long-term concern, modifiable lifestyle and structural factors, particularly alcohol, smoking, income, and education, exert more immediate and pronounced effects on hepatic biomarkers in the general population. Full article

Background/Objectives: Niemann-Pick disease Type C (NPC) represents an autosomal recessive disorder with an incidence rate of 1 in 100,000 live births that belongs to the lysosomal storage diseases (LSDs). NPC is characterized by the abnormal accumulation of unesterified cholesterol, in addition to being an autosomal recessive inherited pathology, which belongs to LSDs. It occurs in 95% of cases due to mutations in the NPC1 gene, while 5% of cases are due to mutations in the NPC2 gene. In the cerebral cortex (CC), the disease shows lipid inclusions, increased cholesterol and multiple sphingolipids in neuronal membranes, and protein aggregates such as hyperphosphorylated tau, α-Synuclein, TDP-43, and β-amyloid peptide. Mitochondrial damage and oxidative stress are some alterations at the cellular level in NPC. Therefore, the aim of this work was to determine the gene expression profile in the CC of NPC1 mice in order to identify altered molecular pathways that may be related to the pathophysiology of the disease. Methods: In this study, we performed a microarray analysis of a 22,000-gene chip from the cerebral cortex of an NPC mutant mouse compared to a WT mouse. Subsequently, we performed a bioinformatic analysis in which we found groups of dysregulated genes, and their expression was corroborated by qPCR. Finally, we performed Western blotting to determine the expression of proteins probably dysregulated. Results: We found groups of dysregulated genes in the cerebral cortex of the NPC mouse involved in the ubiquitination, fatty acid metabolism, differentiation and development, and underexpression in genes with mitochondrial functions, which could be involved in intrinsic apoptosis reported in NPC, in addition, we found a generalized deregulation in the cortical circadian rhythm pathway, which could be related to the depressive behavior that has even been reported in NPC patients. Conclusions: Recognizing that there are changes in the expression of genes related to ubiquitination, mitochondrial functions, and cortical circadian rhythm in the NPC mutant mouse lays the basis for targeting treatments to new potential therapeutic targets. Full article

Background/Objectives: To review the dimensions of the round window region (round window niche, bony structures surrounding the niche, and the membrane itself). Methods: Medline, EMBASE, Cochrane Library, and Google Scholar databases were searched by two independent reviewers. Anatomical and radiological studies on the round window region were screened. Studies reporting at least one dimension for the round window (RW) niche and/or the RW membrane were included. Results: Sixteen studies met the inclusion criteria (13 anatomical and 3 radiological studies) for a total number of 808 temporal bones with at least one dimension reported. The structures measured varied across the different studies with 12 reporting RW membrane dimensions (area and/or at least one distance), 8 detailing RW niche dimensions (height, width or depth) and 6 which measured at least one element of the RW bony overhangs (posterior or anterior pillar, RW tegmen). Surface area of the RW membrane varied between 0.32 mm² and 2.89 mm², with a minimum dimension (minimum diameter or height or width) comprising between 0.51 mm and 2.1 mm. When the bony overhangs surrounding the membrane were not considered, the minimum diameter was between 1.65 mm and 1.97 mm. Conclusions: The dimensions of the RW region are intrinsically variable, but the heterogeneity of the measurements reported also contributes to these variations. Posterior pillar, RW tegmen, anterior pillar, and their relative development probably account for a large part of this variability. The future RW membrane devices should be ≤1 mm in their maximum dimension, whether or not individually tailored, to fit most of the RW membranes. Full article

As part of its modernisation and economic diversification policies, Saudi Arabia is building smart, sustainable cities intended to improve quality of life and meet environmental goals. However, involving the public in urban planning remains complex, with traditional methods often proving expensive, time-consuming, and inaccessible to many groups. Integrating artificial intelligence (AI) into public participation may help to address these limitations. This study explores whether Saudi residents are ready to engage with AI-driven tools in urban planning, how they prefer to interact with them, and what ethical concerns may arise. Using a quantitative, survey-based approach, the study collected data from 232 Saudi residents using non-probability stratified sampling. The survey assessed demographic influences on AI readiness, preferred engagement methods, and perceptions of ethical risks. The results showed a strong willingness among participants (200 respondents, 86%)—especially younger and university-educated respondents—to engage through AI platforms. Visual tools such as image and video analysis were the most preferred (96 respondents, 41%), while chatbots were less favoured (16 respondents, 17%). However, concerns were raised about privacy (76 respondents, 33%), bias (52 respondents, 22%), and over-reliance on technology (84 respondents, 36%). By exploring the intersection of generative AI and participatory urban governance, this study contributes directly to the discourse on inclusive smart city development. The research also offers insights into how AI-driven public engagement tools can be integrated into urban planning workflows to enhance the design, governance, and performance of the built environment. The findings suggest that AI has the potential to improve inclusivity and responsiveness in urban planning, but that its success depends on public trust, ethical safeguards, and the thoughtful design of accessible, user-friendly engagement platforms. Full article

Background and Objectives: Schizophrenia is a disabling psychiatric condition, affecting around 1% of people worldwide. It has been ranked among the ten most disabling conditions globally. Alongside the psychological and social burdens imposed on individuals suffering from this disease, there are also serious complications regarding the physical health of these patients. Pneumonia is a significant cause of death in patients with schizophrenia. This group of patients also has a higher risk of developing pneumonia and all-cause mortality compared to those without schizophrenia, along with an increased overall mortality rate. A retrospective study revealed that advanced age, underweight, smoking, and the use of high-dose atypical antipsychotics increase the risk of pneumonia-related mortality in hospitalized patients. Our study aims to examine differences in factors associated with pneumonia in hospitalized patients with schizophrenia, before and after the COVID-19 pandemic, as well as to identify potential changes in clinical characteristics and outcomes. Materials and Methods: This is an observational, retrospective analysis, based on the review of medical records of psychiatric inpatients diagnosed with schizophrenia according to the DSM-5 criteria. Patients were selected according to the following criteria: both schizophrenia and pneumonia diagnoses, hospitalized in Spitalul Clinic de Psihiatrie si Neurologie Brasov during 1 March 2018–1 March 2020, and 1 March 2022–1 March 2024, respectively. Results: A total of 27 patients met the inclusion criteria; 13 patients (48%) were in the pre-pandemic group and 14 patients (52%) in the post-pandemic group. Contrary to other reports, our results showed relatively low pneumonia rates in hospitalized schizophrenia patients (1.02% pre-pandemic and 1.63% post-pandemic), and rates were higher in female patients (61.54% pre-pandemic and 71.43% post-pandemic). Post-pandemic, most cases (42.86%) were registered during summer, in a schizophrenia population with mostly urban residence and with lower smoking rates than the pre-pandemic group. Physical restraints were, however, more frequently utilized in the post-pandemic group. Conclusions: Pneumonia risk factors might register a change in the post-pandemic years. Polypharmacy and physical restraints are probably underestimated risk factors for pneumonia in schizophrenia patients, while a multidisciplinary approach and preventive measures might exert a protective role. Full article

Background and Objectives: Blood shortages are a national crisis, creating dangerous scenarios for patients requiring the use of a massive transfusion protocol (MTP). A judicious use of blood products is critical to rescue salvageable patients while refraining from unnecessary MTP to save precious resources. This study examines effect of trauma characteristics, socioeconomic variables and markers of futility on the likelihood of activating and receiving MTP in the trauma setting. Materials and Methods: In this retrospective study, emergency department (ED) trauma activations from a database of an urban Level I trauma center were analyzed from 1 January 2017 to 30 June 2022, inclusive. In-ED mortality, RBC transfusion volumes during initial resuscitation, patient sociodemographic data, and trauma event factors were analyzed. The primary outcomes were the dichotomous outcomes of MTP activation and MTP transfusion. Univariable analyses and logistic regressions were conducted, with class balancing sensitivities applied to the multivariable regressions to adjust for imbalance in the data. p < 0.05 was considered statistically significant. Results: Among the 8670 trauma activations, there was a 0.3% in-ED mortality rate. MTP activation and MTP transfusion were associated with higher in-ED mortality rates (3.8% and 15.4%, respectively, compared to 0.2% without MTP). Younger patients, male patients, and Medicaid recipients were more likely to undergo MTP activation; Medicare patients were less likely. Penetrating trauma substantially increased the likelihood of both MTP activation (odds ratio (OR) 5.81) and transfusion (OR 3.63). The logistic regression models identified the presence of penetrating trauma, lower probability of survival, and age as the most important covariates. Models demonstrated high discriminatory value (area under the curve (AUC) of the receiver operating characteristic curve (ROC) of 0.876 for MTP activation, 0.935 for MTP transfusion) and precision (0.974 for activation, 0.994 for transfusion), with class balancing further improving model performance and precision scores. Conclusions: These results are significant as assessing the futility of MTP should be equitable, and future transfusion guidelines should consider salvageability in cases with a low probability of survival despite age and mechanism. Full article

As cities globally prioritize sustainable transportation, understanding gender-differentiated responses to the urban built environment is critical for equitable mobility planning. This study combined the Social Ecological Model (SEM) with the theoretical perspective of Gendered Spatial Experience to explore the differentiated impacts of the Perceived Street Built Environment (PSBE) on the cycling behavior of men and women. Questionnaire data from 285 e-bike and traditional bicycle riders (236 e-bike riders and 49 traditional cyclists, 138 males and 147 females) from Gulou District, Nanjing, between May and October 2023, were used to investigate gender differences in cycling behavior and PSBE using the Mann–Whitney U-test and crossover analysis. Linear regression and logistic regression analyses examined the PSBE impact on gender differences in cycling probability and route choice. The cycling frequency of women was significantly higher than that of men, and their cycling behavior was obviously driven by family responsibilities. Greater gender differences were observed in the PSBE among e-bike riders. Women rated facility accessibility, road accessibility, sense of safety, and spatial comfort significantly lower than men. Clear traffic signals and zebra crossings positively influenced women’s cycling probability. Women were more sensitive to the width of bicycle lanes and street noise, while men’s detours were mainly driven by the convenience of bus connections. We recommend constructing a gender-inclusive cycling environment through intersection optimization, family-friendly routes, lane widening, and noise reduction. This study advances urban science by identifying gendered barriers in cycling infrastructure, providing actionable strategies for equitable transport planning and urban design. Full article

Per- and polyfluoroalkyl substances (PFASs) are ubiquitous environmental contaminants with potential endocrine-disrupting properties. This study examines the association between exposure to multiple PFASs and pan-cancers associated with sex hormones (PCSH) while accounting for potential non-linear relationships and interactions. We analyzed data from the National Health and Nutrition Examination Survey (NHANES), spanning two-year cycles from 1999 to 2012 and including 14,373 participants. Serum concentrations of six PFAS—perfluorooctanoic acid (PFOA), perfluorooctanesulfonic acid (PFOS), perfluorohexanesulfonic acid (PFHxS), perfluorodecanoic acid (PFDE), perfluorononanoic acid (PFNA), and perfluoroundecanoic acid (PFUA)—were assessed for their relationship with PCSH. The statistical analyses included descriptive statistics, Spearman and Pearson correlation analyses, and both linear and logistic regression models. Additionally, Bayesian kernel machine regression (BKMR) was applied to capture potential nonlinear relationships and interactions. The initial t-tests showed a statistically significant difference in PFOS levels between individuals with and without PCSH (p = 0.0022), with higher mean PFOS levels in the PCSH group. Chi-square tests revealed a significant association between ethnicity and PCSH (p < 0.001). Linear and logistic regression analyses revealed significant associations for PFOS. BKMR analysis identified PFOA as having the highest posterior inclusion probability, indicating its importance in explaining PCSH risk. Univariate exposure-response analysis revealed limited individual PFAS effects. However, bivariate analysis indicated a complex U-shaped interaction pattern among many joint PFAS assessments. The overall exposure effect analysis suggested that the combined impact of all PFASs was more strongly associated with PCSH at exposure levels below the 0.5 quantile compared to higher levels. Single-variable interaction analyses highlighted PFOA and PFOS as the most interactive PFASs when evaluating their interaction with combined exposure to all other PFASs. In summary, while the initial findings suggested a positive association between PFOS and PCSH, the BKMR analysis revealed complex non-linear relationships and interactions among PFAS. These findings highlight the importance of evaluating PFASs as a mixture rather than as individual chemicals and using techniques that can capture non-linear relationships and interactions. Full article

Vitamin D is a key micronutrient in the function of the skeletomuscular system. Athletes are at increased risk of developing vitamin D deficiency during the execution of very demanding disciplines such as CrossFit^®. Single-nucleotide polymorphisms (SNPs) may influence circulating 25-hydroxy-vitamin D (25(OH)D) levels. An observational, longitudinal pilot study was conducted with 50 trained males according to specific inclusion criteria. Blood samples were obtained to determine 25(OH)D, vitamin D-binding protein (VDBP), vitamin D-receptor (VDR)circulating levels, and the presence of SNPs after DNA isolation and genotyping: rs10741657 to CYP2R1, rs2282679 to GC and rs2228570 to VDR genes. Significant differences (p < 0.05) in 25(OH)D concentration were determined between the biallelic combinations of rs228679 (GC) and rs228570 (VDR). The VDBP and VDR proteins did not show different levels in the case of the rs10741657 (CYP2R1) alleles. Statistically significant weak positive correlations (p < 0.05) were observed between 25(OH)D and AA-alleles of the CYP2R1 and VDR genes, and TT-alleles of the GC gene. Additionally, AA (rs10741657 and rs2228570) and TT (rs2282679) have a probability between 2 and 4 of having major effects on the concentration of 25(OH)D. Conversely, GG alleles present a probability of suboptimal values of 25(OH)D of 69%, 34%, and 24% for VDR, GC, and CYP2R1, respectively, showing a strong moderate positive correlation (r = 0.41) between the degrees of sports performance and 25(OH)D plasma levels. CYP2R1 (rs10741657), GC (rs2282679), and VDR (rs2228570) affect the concentration of serum 25(OH)D, as an indicator of vitamin D status and play a critical role in the sports performance of CrossFit^® practitioners. Full article

This study proposes an extension of Seasonal Autoregressive Integrated Moving Average models with exogenous regressors (SARIMAX) by incorporating skew-normal and zero-inflated skew-normal error structures to better accommodate asymmetry and excess zeros in time series data. The proposed framework demonstrates improved flexibility and robustness compared to traditional Gaussian-based models. Simulation experiments reveal that the skewness parameter significantly affect forecasting accuracy, with reductions in mean absolute error (MAE) and root mean square error (RMSE) observed across both positively and negatively skewed scenarios. Notably, in negative-skew contexts, the model achieved an MAE of 0.40 and RMSE of 0.49, outperforming its symmetric-error counterparts. The inclusion of zero-inflation probabilities further enhances model performance in sparse datasets, yielding superior values in goodness-of-fit criteria such as the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). To illustrate the practical value of the methodology, a real-world case study is presented involving the modeling of optical density (OD₆₀₀) data from Escherichia coli during stationary-phase growth. A SARIMAX(1,1,1) model with skew-normal errors was fitted to 200 time-stamped absorbance measurements, revealing significant positive skewness in the residuals. Bootstrap-derived confidence intervals confirmed the significance of the estimated skewness parameter ($\alpha =14.033$ with 95% CI [12.07, 15.99]). The model outperformed the classical ARIMA benchmark in capturing the asymmetry of the stochastic structure, underscoring its relevance for biological, environmental, and industrial applications in which non-Gaussian features are prevalent. Full article

This study assessed the relationship between environmental chemical mixtures—including metals, per- and polyfluoroalkyl substances (PFAS), phthalates, and plasticizers—and key cardiovascular health markers using data from the 2013–2014 National Health and Nutrition Examination Survey (NHANES). The combined effects of these pollutants on cardiovascular markers were evaluated using Bayesian Kernel Machine Regression (BKMR), a flexible, non-parametric modeling approach that accommodates nonlinear and interactive relationships among exposures. BKMR was applied to assess both the joint and individual associations of the chemical mixture with systolic blood pressure (SBP), high-density lipoprotein (HDL), low-density lipoprotein (LDL), diastolic blood pressure (DBP), total cholesterol, and triglycerides. As part of the BKMR analysis, posterior inclusion probabilities (PIPs) were estimated to identify the relative importance of each exposure within the mixture. These results highlighted phthalates as major contributors to LDL, SBP, total cholesterol, HDL, and triglycerides while plasticizers were associated with LDL, SBP, HDL, and triglycerides. Metals and PFAS were most strongly linked to LDL, DBP, total cholesterol, and SBP. The overall mixture effect indicated that cumulative exposures were associated with lower LDL and SBP and elevated DBP, suggesting an increased cardiovascular risk. Triglycerides exhibited a complex quantile-dependent trend, with higher exposures associated with reduced levels. These findings underscore the importance of mixture-based risk assessments that reflect real-world exposure scenarios. Full article

This paper examines the dynamic relationship between economic indicators, law enforcement mechanisms, and property-related crimes in Mongolia using a time-series econometric approach. Relying on the theoretical frameworks of Becker’s economic model of crime and Cantor and Land’s motivation–opportunity hypothesis, the study explores the effects of unemployment, detection probability, and incarceration rates on four crime categories: total crime, theft, robbery, and fraud. An error correction model (ECM) is employed to capture both short-run fluctuations and long-run equilibrium relationships over the period 1992–2022. The empirical findings reveal that detection rates exert a statistically significant deterrent effect on robbery in the short term, while incarceration rates are effective in reducing theft. Unemployment shows a positive and significant long-run effect on theft prior to 2009 but weakens thereafter due to methodological changes in labor statistics. Fraud demonstrates a distinct response pattern, exhibiting negative associations with both incarceration and unemployment, and showing no sensitivity to detection probability. Diagnostic tests support the model’s robustness, with heteroskedasticity in the theft model addressed using robust standard errors. This study contributes to the literature by providing the first country-specific empirical evidence on crime determinants in Mongolia. It highlights the heterogeneous impact of economic and institutional factors on different crime types in a transition economy. The findings underscore the need for integrated policy responses that combine improvements in law enforcement with inclusive economic and social development strategies. Full article

Worker safety has been relatively overlooked in the rapidly growing aquaculture industry. To address this gap, industrial accident compensation insurance data—mainly from floating cage and seaweed farming—were analyzed to quantify accident types and frequencies, with a focus on human elements as root causes. Basic causes were selected based on IMO Resolution A/Res.884 and assessed through a worker awareness survey. Fault Tree Analysis (FTA), a Formal Safety Assessment technique, was applied to evaluate risks associated with these causes. The analysis identified organization at the farm site (23.3%), facility and equipment factors (22.8%), and people factors (21.4%) as the primary causes. Among secondary causes, personal negligence (13.2%), aging gear and poor maintenance (11.4%), and insufficient risk training (10.4%) were the most significant. Selective removal of these causes reduced the probability of human element-related accidents from 64.6% to 48.6%. While limited in scope to Korean data and self-reported surveys, the study demonstrates the value of combining quantitative data with worker perspectives. It provides foundational data for developing tailored safety strategies and institutional improvements—such as standardized procedures, multilingual education, and inclusive risk management—for sustainable safety in aquaculture. Full article