Risk Index Research Articles

Spatiotemporal characterization of heatwave exposure across historically vulnerable communities

Heatwaves pose a serious threat and are projected to amplify with changing climate and social demographics. A comprehensive understanding of heatwave exposure to the communities is imperative for the development of effective strategies and mitigation plans. This study explores spatiotemporal characterization of heatwaves across the historically vulnerable communities in Mississippi, United States. We derive multiple heatwave metrics including frequency, duration, and magnitude based on temperature data for urban-specific daytime, nighttime, and day–night combined conditions. Our analysis depicts a rising heatwave trend across all counties, with the most extreme shifts observed in prolonged day–night events lacking overnight relief. We integrate physical heatwave hazards with a socioeconomic vulnerability index to develop an integrated urban heatwave risk index. Integrated metric identifies the counties in northwest Mississippi as heat-prone areas, exhibiting an urgent need to prioritize heat resilience and adaptive strategies in these regions. The compounding urban heatwave and vulnerability risks in these communities highlights an environmental justice imperative to implement equitable policies that protect disadvantaged populations. Although this study is focused on Mississippi, our framework is scalable and can be employed to urban regions globally. This study provides a solid foundation for developing timely heatwave preparedness and mitigation to avert preventable heat-related tragedies as extremes intensify with climate change.

The dynamic evolution characteristics of PM2.5 concentrations and health risk assessment during typical forest fires in China

In the context of climate change, increasingly frequent wildfire events are exacerbating the air quality crisis in China and have become a significant source of atmospheric PM2.5. This study selected 12 major forest wildfire events in China from 2018 to 2023. Using atmospheric pollutant and component concentration data, as well as meteorological data, the study employed MK trend analysis, forward trajectory simulation, potential source contribution function (PSCF), and health risk indices to investigate the evolution patterns of PM2.5 concentrations before and after each wildfire event. The study explored the driving role of meteorological factors in this evolution process and quantitatively analyzed the spatial distribution characteristics of health risks in surrounding cities post-wildfire. The results indicated that: 1) PM2.5 levels changed significantly before and after each wildfire event, although the proportion of components remained relatively stable. 2) PM2.5 concentrations exhibited varying characteristics within different buffer zones of the wildfire areas. In the forest wildfire events in Foshan, Guangdong Province, and Jinzhong, Shanxi Province, the average PM2.5 concentrations within the 50 km buffer zones reached approximately 90 μg/m3, about 4–5 times the multi-year average for these areas. 3) Wildfire emissions were mainly influenced by meteorological and topographical factors. Wind field dependence diagrams showed that PM2.5 tended to accumulate in all wind directions, particularly at lower wind speeds of 0–5 m/s 4) Potential source analysis revealed that PM2.5 emissions from wildfires posed significant risks to surrounding areas. Multiple events had high-risk areas (WPSCF ≥0.8), and among the cities in these high-risk areas, the health risk value (ΔM) for Ya'an City reached an extremely high 85.1. This study provides a theoretical basis for policymakers to develop locally tailored wildfire management policies, ensuring the protection of the public's right to breathe clean air.

Seismic fragility and risk assessment of Reinforced Concrete bridges undergoing elastomeric bearing deformations induced by landslide

The paper presents a study on the seismic fragility of Reinforced Concrete (RC) bridges isolated by elastomeric bearing devices subjected to differential displacements induced by slow-moving landslides. The seismic behaviour of isolated bridges is ruled by the performance of elastomeric bearings to reduce and dissipate earthquake actions. These bridges are subjected to service loads that usually are accounted for in design, but possible additional actions from the surrounding environment, such as landslides affecting substructure components, can seriously undermine the seismic response. The paper describes a practical approach to investigate the seismic fragility and risk of RC bridges isolated by elastomeric bearings, which may undergo early deformations induced by the differential displacements of substructure components. On the basis of previous existing studies, the proposed methodology is based on numerical modelling accounting for landslide-induced substructure displacements and proper modifications on the constitutive law and hysteretic response of the elastomeric bearings. Subsequently, after establishing specific limit-states, nonlinear time history analyses of the seismic response are used to estimate fragility curves and risk indicators. The study points out that it is possible to quantify the influence of landslide-induced effects on seismic fragility and risk by using only two numerical models, in order to provide decision support to transportation authority responsible for ensuring the safety of bridges and road networks. The proposed approach has been tested on a real-life case study, the Santo Stefano Viaduct in Italy, which was subjected in the past to relevant deformations of the elastomeric bearings due to an active landslide phenomenon.

International standards for cyber resilience assessment

The typical characteristics for cyber resilience assessment are defined. The concept and content of cyber resilience are detailed. The link between cyber security and cyber resilience is outlined. The main cyber risks that affect the state and process of cyber resilience are substantiated. Algorithms that affect the state of ensuring cyber resilience are revealed. The global methods of cyber resilience assessment are highlighted, in particular the cyber resilience review (Cyber Resilience Review – CRR), the cyber perception index (The Cyber Resilience Framework – CRF), and the cyber risk index (Cyber Risk Index – CRI) are disclosed. Based on the analysis of the best practices of international experience, the main purpose of the cyber resilience assessment was determined. Further steps with the aim to improve the practical implementation of the criteria for assessing the state of cyber resilience in order to strengthen cyber security and its components are outlined.

WT1 Expression Is Associated with Poor Overall Survival after Azacytidine and DLI in a Cohort of Adult AML and MDS Patients.

Introduction: Post-transplant relapse of acute myeloid leukemia and myelodysplastic syndrome faces restricted effective salvage regimens. We retrospectively analyzed the use of Azacitidine-donor lymphocyte infusion (AZA/DLI) in this setting. Furthermore, data on bone marrow Wilms tumor gene 1 (WT1) expression were collected. Methods: A Cox proportional hazards model, an outcome-oriented approach for the lowest smoothed plot of the martingale residuals, was performed for the cut-point determination of the respective WT1 expression levels. Finally, a Cox proportional hazards model investigated the association of overall survival (OS) with predictors. Results: An overall response of 41.4% with a median duration of 11.9 months for stable disease and 19.5 months for complete response (CR) patients was achieved. The disease risk index (DRI) high-/very high-risk patients had a shorter OS of 4.4 months than intermediate-risk patients, with 14.5 months, p = 0.007. At transplant, WT1-overexpressing patients (>150 copies) had a shorter median OS of 5.3 months than low-WT1-expressing ones, with 13.5 months, p = 0.024. Furthermore, patients with ≤1000 WT1 copies at relapse had a significantly longer OS with 15.3 months than patients overexpressing WT1, with 4.4 months, p = 0.0002. Conclusions: DRI and WT1 expression associate significantly with OS after AZA/DLI. Hence, WT1 may represent an MRD marker, especially in CR patients at high risk.

Deep learning with information fusion and model interpretation for long-term prenatal fetal heart rate data

Long-term fetal heart rate (FHR) monitoring during the antepartum period, increasingly popularized by electronic FHR monitoring, represents a growing approach in FHR monitoring. This kind of continuous monitoring, in contrast to the short-term one, collects an extended period of fetal heart data. This offers a more comprehensive understanding of fetus’s conditions. However, the interpretation of long-term antenatal fetal heart monitoring is still in its early stages, lacking corresponding clinical standards. Furthermore, the substantial amount of data generated by continuous monitoring imposes a significant burden on clinical work when analyzed manually. To address above challenges, this study develops an automatic analysis system named LARA (Long-term Antepartum Risk Analysis system) for continuous FHR monitoring, combining deep learning and information fusion methods. LARA’s core is a well-established convolutional neural network (CNN) model. It processes long-term FHR data as input and generates a Risk Distribution Map (RDM) and Risk Index (RI) as the analysis results. We evaluate LARA on inner test dataset, the performance metrics are as follows: AUC 0.872, accuracy 0.816, specificity 0.811, sensitivity 0.806, precision 0.271, and F1 score 0.415. In our study, we observe that long-term FHR monitoring data with higher RI is more likely to result in adverse outcomes (p = 0.0021). In conclusion, this study introduces LARA, the first automated analysis system for long-term FHR monitoring, initiating the further explorations into its clinical value in the future.

Individual, firearm, and purchasing characteristics associated with risk of firearm-related violent crime arrest: a nested case-control study

BackgroundFirearm purchasing records offer a potentially important administrative data source to identify individuals at elevated risk of perpetrating firearm violence. In this study, we describe individual, firearm, and transaction characteristics of purchasers in California who were arrested for a firearm-related violent crime (FRV) as compared to the general population of registered purchasers in the state.MethodsRelying on a dataset of all individuals with transaction records in California (1996–2021), linked to criminal records (1980–2021), we enrolled a cohort of individuals for whom we could capture the legal firearm purchase history. We identified those arrested for FRV post purchase, and using incidence density sampling, gender-matched cases to ten purchasers (controls) who remained “at risk” at the time the case was arrested. We focused on the purchase closest in time prior to the arrest (“index” purchase). We implemented conditional logistic regression and included models with controls for individual- and community-level demographics, as well as interactions between firearm and purchasing characteristics and criminal history.ResultsThe cohort included 1,212,144 individuals, of whom 6153 were arrested for FRV (0.5%). Cases were matched to 61,530 controls to form the study sample. The largest risk factor was a prior criminal history: purchasers had 5.84 times the risk of FRV if they had a prior arrest within three years of the index purchase (CI 5.44–6.27). Several transaction and firearm characteristics were also associated with FRV. For example, risk increased if the firearm was redeemed at a pawn shop (aIRR: 1.37, CI 1.05–1.77) and decreased if the transaction was a registered private party transfer (vs. retail purchase) (aIRR: 0.83, CI 0.76–0.90) or the firearm was a bolt action firearm (vs. semi-automatic) (aIRR: 0.64, CI 0.51–0.79). In the interaction models, most of the purchase and firearm features only remained significant among those with no criminal history.ConclusionsGiven limited data on firearm transactions, there has been little research on whether the type of firearm an individual purchases or the nature of the purchase might serve as indicators of risk for FRV. We found several transaction and firearm features were associated with risk of FRV. Notably, these features provided little evidence of additional risk for those with a prior criminal record.

Fludarabine Melphalan, Reduced-dose Busulfan Versus Fludarabine, Melphalan, Full-dose Busulfan in Patients Receiving Cord Blood Transplantation

BackgroundVarious reduced-intensity conditioning/reduced-toxicity conditioning regimens have been developed for patients receiving allogeneic hematopoietic cell transplantation. The balance between disease relapse and toxicity can be partly dependent on reduced-intensity conditioning/reduced-toxicity conditioning regimens.This retrospective study aimed to compare the nonrelapse mortality, relapse incidence, progression-free survival, and overall survival rates between the fludarabine/melphalan/reduced-dose busulfan (Flu/Mel/Bu2; busulfan at a dose of 6.4 mg/kg intravenously) and fludarabine/melphalan/full-dose busulfan (Flu/Mel/Bu4; busulfan at a dose of 12.8 mg/kg intravenously) regimens in patients receiving umbilical cord blood transplantation (UCBT). MethodEighty-seven adult patients who received the Flu/Mel/Bu2 (n = 45) or Flu/Mel/Bu4 (n = 42) regimen as a conditioning regimen before UCBT at our institution between January 2013 and December 2022 were included in this study. ResultsThere were no significant differences in terms of clinical outcomes including nonrelapse mortality, relapse incidence, progression-free survival, and overall survival rates between the two regimens. Further, even in higher risk patients classified according to the Refined Disease Risk Index, the Flu/Mel/Bu2 regimen was comparable to the Flu/Mel/Bu4 regimen. ConclusionThe novel Flu/Mel/Bu2 regimen could be applied in clinical settings as it can be tolerated and effective in older patients.

A reliable ensemble forecasting modeling approach for complex time series with distributionally robust optimization

Accurate ensemble forecast results provide strong support for management decisions. While the existing ensemble forecasting model ignores the requirement of directional accuracy making its prediction direction is usually error-prone. To address this issue, we develop a convex directional prediction error measure and subsequently construct a reliable ensemble forecasting model that minimizes the horizontal prediction error with the bounded directional prediction error. Mathematically, we provided the proper range of the required directional error level. Furthermore, we find the classical ensemble forecasting model is a special case of our study when the directional error level is larger than the upper bound we gave in this study. To deal with the possible deterioration of the individual model over time, we also considered its worst possible prediction performance by introducing the distributionally robust optimization (DRO) technique into the proposed reliable ensemble forecasting model. Technically, we showed that the DRO-based reliable ensemble forecasting model is convex and can be reformulated into a second-order cone problem which can be readily solved by off-the-shelf solvers. Finally, the effectiveness of the proposed reliable ensemble forecasting model and the DRO-based reliable ensemble forecasting model were validated on three different datasets, e.g., the exchange rate, the oil price, and the country risk index. To sum up, we construct a reliable ensemble forecasting model to simultaneously control the horizontal prediction error and directional prediction error of ensemble forecasting, and thus enhance the reliability of ensemble forecasting.

The relative importance of economic policy uncertainty and geopolitical risk on U.S. REITs returns

PurposeOur aim in this study is to investigate the relative importance of the economic policy uncertainty and of the geopolitical risk on U.S. REITs (Real Estate Investment Trusts) returns with a special focus on the different real estate sectors.Design/methodology/approachWe use an augmented Fama-French (1993)’s asset pricing model, including economic policy uncertainty indices (EPU), introduced by Baker et al. (2016), and geopolitical risk indices (GPR) recently developed by Caldara and Iacoviello (2022), to price the potential risk factors for U.S. Nareit indices returns. To obtain robust economic results, we correct for the problems of errors-in-variables in linear asset pricing models; we advocate the use of higher moments estimators as instruments in a generalized method of moments (GMM) framework.FindingsOur results report that economic policy uncertainty (EPU), and geopolitical risk (GPR) are priced for the different Nareit sectors for the last three decades. The GPR index stands as a relevant risk factor. The coefficient estimates are low compared to Fama-French risk factors. They are higher for Shopping Centers, Retail and Region Malls and lower for Health Care and Lodging/Resorts. EPU indices are also priced and less statistically significant. Health Care sector, followed by Shopping Centers and Retail are the most policy-sensitive sectors.Practical implicationsIn their “2023–2024 Top Ten Issues Affecting Real Estate” “political unrest and global economic health” is ranked 1 issue by the Counselors of Real Estate. Our results report that economic policy uncertainty and geopolitical risk are priced for the different Nareit sectors. They suggest implications for investors, insurers, bankers, policymakers and other stakeholders. The geopolitical risk index (GPR) stands as a relevant and significant risk factor for REITs returns.Originality/valueBased on parsimonious robust asset pricing models, the results shed a new light on the relative importance of geopolitical risk and economic policy uncertainty in the real estate sector, with a special focus on the different U.S. REITs sectors. They suggest possible implications for investors, insurers, bankers, policymakers and other stakeholders in a context marked by higher uncertainty shocks and geopolitical risks.

The number of episodes of major psychiatric and substance use disorders as an index of genetic risk and genetic heterogeneity.

We investigate whether number of episodes (NoEs) meaningfully reflect genetic risk and genetic heterogeneity for five primary disorders-Drug Use Disorder (DUD), Alcohol Use Disorder (AUD), Major Depression (MD), Bipolar Disorder (BD), and Schizophrenia (SZ) ascertained from Swedish population registries. We utilize Genetic Risk Ratios (GRR)-defined as the ratio of the genetic risk for secondary disorders to the genetic risk for the primary disorder-derived from Family Genetic Risk Scores (FGRS). For all five primary disorders, genetic risk rose robustly with increasing NoEs. For both AUD and DUD, the GRR for all six secondary disorders-selected to have a likely genetic relationship with the particular primary disorder-declined with increasing NoEs so that cases of AUD and DUD with high versus low NoEs had both a higher genetic risk and a purer genetic signal. With MD, genetic risk maximized at an intermediate NoEs. While the GRRs for AUD and DUD in MD cases dropped sharply with increasing NoEs, GRR for BD increased. For BD, genetic risk rose sharply with increasing NoEs while for all secondary disorders the GRRs showed a mixture of modest increases and decreases. Like AUD and DUD, but even more markedly, selecting BD cases with high rates of recurrence would produce a sample with a high overall genetic risk and a relatively homogeneous genetic signal. For SZ, genetic risk rose moderately with increases in NoEs. GRRs for other non-affective psychoses (ONAP) and autism spectrum disorder (ASD) fell quite slowly with increasing NoEs, and more rapidly for other secondary disorders. Cases of SZ with high recurrence rates had a high genetic risk and a relatively pure signal, albeit with contributions from ONAP and ASD. In summary, NOEs are a robust index of genetic risk and genetic heterogeneity across our primary disorders with important inter-disorder differences.

Human health risk and water quality assessment due to fluoride and nitrate around Cauvery River basin, southern India.

Good quality water for human consumption, irrigation, and industrial use is very important. Today, around the world, water is contaminated by natural processes and human activities. This study aimed to evaluate the suitability of groundwater for drinking and irrigation, identifythe source of fluoride and nitrate contamination, and assess thehuman health risks around the Cauvery River basin in southern India. A total of 30 groundwater samples were collected and analyzed for hydrochemical parameters, including EC, TDS, pH, Ca, Mg, Na, K, HCO3, Cl, SO4, NO3, and F-. The majority of groundwater samples in the study area are used for drinking and irrigation. The pH of groundwater in the study area was observed to be dominantly alkaline. The levels of TDS, Ca, Na, K, F, and TH exceeded the permissible limits recommended by BIS and WHO. Fluoride and nitrate levels in groundwater exceeded the permissible limits for drinking purposes in 43% and 50% of the samples, respectively. The excessive concentration of fluoride and nitrate in groundwater could pose serious human health problems. Fluoride and nitrate concentrations in groundwater vary between 0.1 and 2mg/l and 12 and 95mg/l, respectively. Based on the computation of the drinking water quality index, about 73% of groundwater samples were classified asexcellent to good. Health risk was assessed for infants, children, and adults using non-carcinogenic risk indices such as hazard quotients (HQ), hazard indexes (HI), total hazard indices (THI), and carcinogenic risk indices (CR). Infants, children, and adults have different total hazards indexes ranging from 1.508 to 5.733, 1.579 to 6.003, and 0.011 to 0.046, respectively. Health risk assessment results indicatedthat the hazard index and hazard quotient were above the recommended limit of > 1 in most of the samples for infants and children. Non-carcinogenic risk and carcinogenic risks were more likely to affect infants and children rather than adults through ingestion of contaminated water.

Perception and Role of Indirect and Post-Discharge Surveillance in Predicting Surgical Site Infection in Surgical Patients: An Institutional Experience

Abstract Background: Surgical site infection (SSI) surveillance is a process of observing and reporting of infections following surgery. SSI surveillance studies are few in our country. Objectives: Present study was conducted to know the perception and role of SSI surveillance. Incidence of surgical site infection, identification of risk factors and bacterial spectrum of surgical wounds during surveillance were also studied. Methods: Patients who underwent a surgical procedure between July 2022 and June 2023 at our hospital were included. A prospective incidence surveillance for SSI was done to look for any signs of infection and record them in the surveillance form. Wound swabs or pus aspirates were sent for microbiological culture. Results: A total of 2312 patients underwent surgery during the study period, of whom 61 patients were diagnosed with SSI. The incidence of SSI was 2.6%. SSI was encountered more in female patients (57.3%). Age distribution had a significant association with SSI (P = 0.025). Most operative wounds were clean-contaminated (45.9%). Most SSIs were superficial (91.8%), followed by deep (8.2%). Most patients who developed SSI had a National Nosocomial Infection Surveillance (NNIS) patient risk index of 2 (45.9%). Bacterial growth was observed in 45.9% of cases. Multidrug resistance (MDR) among these isolates was 42.6%. Conclusion: This study helped to determine predictors of SSI like duration of surgery, type of wound, duration of hospital stays, and NNIS risk index. MDR isolates are now contributing to SSI. The perception of healthcare workers about SSI surveillance was that it was feasible to use and practice. Surveillance helped clinicians to strengthen the existing infection prevention and control practices for the future.

Sources Analysis and Health Risk Assessment of Heavy Metals in Street Dust from Urban Core of Zhengzhou, China

Fifty-one street dust samples were systematically collected from the urban core of Zhengzhou, China, and analyzed for potentially toxic metals. The concentrations of vanadium (V), manganese (Mn), copper (Cu), zinc (Zn), arsenic (As), lead (Pb), and nickel (Ni) in the samples surpassed the background values of the local soil, indicating a notable potential for contamination. Spatially, the traffic area was the most polluted with a total heavy metal concentration of Cu, Zn, As, Pb, and Ni, while the pollution levels were lower in the culture and education area and commercial area with total concentrations of V and Mn. Seasonal variations were discerned in the concentrations of heavy metals, with V, Cu, Zn, and As exhibiting heightened levels during the fall and winter, while Mn, Ni, and Pb reached peaks in the spring season. Zn exhibited the highest mean geo-accumulation index (Igeo) value at 2.247, followed by Cu at 2.019, Pb at 0.961, As at 0.590, Ni at 0.126, Mn at −0.178, and V at −0.359. The potential ecological risk index (RI) in the traffic-intensive area markedly exceeded other functional areas. Health risk assessments showed that children were more vulnerable to heavy metal exposure than adults, particularly through the ingestion pathway. Correlation analysis, principal component analysis (PCA), and cluster analysis (CA) were applied in conjunction with the spatial–temporal concentration patterns across various functional areas to ascertain the plausible sources of heavy metal pollutants. The results indicated that heavy metals in the urban street dust of Zhengzhou were multifaceted, stemming from natural processes and diverse anthropogenic activities such as coal burning, industrial emissions, traffic, and construction operations.

Comparison of Photon Dose Distribution in Breast Cancer Using 3DCRT and Half Beam Techniques

Radiotherapy planning can be done with 3D Conformal Radiotherapy (3DCRT) and Half Beam. The success of radiotherapy planning is considered by comparing the isodose curve, Dose Volume Histogram (DVH), Organs At Risk (OAR), Homogeneity Index (HI), and Conformity Index (CI) obtained by the 3DCRT and Half Beam techniques. This study used data from 5 patients at the Radiotherapy Installation at A.W. Hospital. Sjahranie Samarinda with radiation planning of 5000 cGy (25×2 Gy) for breast cancer. The two radiation plans used gantry angles of 310˚ and 120˚. The calculated dose distribution value can be seen through the 90%, 95% PTV dose, and OAR absorbed dose. PTV doses of 90% and 95% in the 3DCRT technique covered the target well. The radiation dose values of the 3DCRT technique at PTV 90% were around 4860 cGy – 4930 cGy and PTV 95% were around 4750 cGy – 4840 cGy. Meanwhile, the Half Beam technique could not cover the target well. It was because the radiation dose values received by the Half Beam technique at 90% PTV were around 780 cGy – 4860 cGy and 95% PTV were around 2210 cGy – 5020 cGy. The OAR absorbed doses values for the 3DCRT and Half Beam techniques were still within the safe limits of tolerance according to QUANTEC. Meanwhile, the HI and CI values in the 3DCRT technique were closer to the rules of ICRU Report 83 of 2010 compared to the Half Beam technique. Therefore, from the values that have been obtained, the success rate of the radiotherapy planning process after measurements is shown in the 3DCRT technique. It has the value of more efficient dose calculations and can be used as a reference in optimizing dose distribution to patients.

Occupational Exposure to Silica Dust and Silicosis Risk in Chinese Noncoal Mines: Qualitative and Quantitative Risk Assessment.

Despite increasing awareness, silica dust-induced silicosis still contributes to the huge disease burden in China. Worryingly, recent silica dust exposure levels and silicosis risk in Chinese noncoal mines remain unclear. We aimed to determine recent silica dust exposure levels and assess the risk of silicosis in Chinese noncoal mines. Between May and December 2020, we conducted a retrospective cohort study on 3 noncoal mines and 1 public hospital to establish, using multivariable Cox regression analyses, prediction formulas of the silicosis cumulative hazard ratio (H) and incidence (I) and a cross-sectional study on 155 noncoal mines in 10 Chinese provinces to determine the prevalence of silica dust exposure (PDE), free silica content, and total dust and respirable dust concentrations. The qualitative risk of silicosis was assessed using the International Mining and Metals Commission's risk-rating table and the occupational hazard risk index; the quantitative risk was assessed using prediction formulas. Kaplan-Meier survival analysis revealed significant differences in the silicosis probability between silica dust-exposed male and female miners (log-rank test χ21=7.52, P=.01). A total of 126 noncoal mines, with 29,835 miners and 4623 dust samples, were included; 13,037 (43.7%) miners were exposed to silica dust, of which 12,952 (99.3%) were male. The median PDE, free silica content, total dust concentration, and respirable dust concentration were 61.6%, 27.6%, 1.30 mg/m3, and 0.58 mg/m3, respectively, indicating that miners in nonmetal, nonferrous metal, small, and open-pit mines suffer high-level exposure to silica dust. Comprehensive qualitative risk assessment showed noncoal miners had a medium risk of silicosis, and the risks caused by total silica dust and respirable silica dust exposure were high and medium, respectively. When predicting H and I over the next 10, 20, and 30 years, we assumed that the miner gender was male. Under exposure to current total silica dust concentrations, median I10, I20, and I30 would be 6.8%, 25.1%, and 49.9%, respectively. Under exposure to current respirable silica dust concentrations, median I10, I20, and I30 would be 6.8%, 27.7%, and 57.4%, respectively. These findings showed that miners in nonmetal, nonferrous metal, small, and open-pit mines have a higher I and higher qualitative silicosis risk. Chinese noncoal miners, especially those in nonmetal, nonferrous metal, small, and open-pit mines, still suffer high-level exposure to silica dust and a medium-level risk of silicosis. Data of both total silica dust and respirable silica dust are vital for occupational health risk assessment in order to devise effective control measures to reduce noncoal mine silica dust levels, improve miners' working environment, and reduce the risk of silicosis.

Sex differences in the association between chest computed tomography-defined sarcopenia and cardiovascular risk factors among inpatients.

While sarcopenia has been found to be associated with increased risks of cardiovascular diseases (CVDs), evidence exploring sex-related differences remains insufficient. This study aimed to investigate the differences in how often sarcopenia occurs in each sex, as determined by skeletal muscle area (SMA) in chest CT images, and its association with CVD common risk factors. This cross-sectional study involved 1,340 inpatients from the Department of Geriatrics of Renji Hospital, affiliated to Shanghai Jiaotong University School of Medicine. Data on age, sex, body mass index (BMI), smoking status, disease history, and clinical parameters were collected. Sarcopenia was defined using chest CT images with a cut-off value of T12-SMA/height2 <25.75 cm2/m2 in male patients and <20.16 cm2/m2 in female patients. Cardiovascular risk was assessed using the Framingham risk score (FRS). The association between T12-SMA/height2-defined sarcopenia and CVD risk factors by sex was evaluated using a multivariate logistic regression analysis. The overall prevalence of T12-SMA/height2-defined sarcopenia (<25.75 cm2/m2 for male patients, <20.16 cm2/m2 for female patients) was 54.03%, with 48.09% in male patients and 63.19% in female patients. The proportion of male patients with high CVD risk was greater than that of female patients. The multivariate analysis revealed that T12-SMA/height2-defined sarcopenia was independently associated with age (in male patients only), systolic blood pressure (SBP), cholesterol, and high-density lipoprotein cholesterol (HDL-C) among the six FRS cardiovascular risk indices. Our results suggest that T12-SMA/height2-defined sarcopenia was more prevalent in male patients than in female patients. Sarcopenia was associated with higher levels of SBP and HDL-C and lower levels of cholesterol. Increasing age had a more significant effect on CVD risk in male patients.

A Coastal Asset Risk Index (CARI) based on multi-criteria spatial analysis: New Zealand pilot study

A Coastal Asset Risk Index (CARI) based on multi-criteria spatial analysis: New Zealand pilot study

Evaluating the Impact of Nutritional Risk on Stress-Induced Hyperglycemia and Trauma Patient Outcomes.

Stress-induced hyperglycemia (SIH) and malnutrition are common in trauma patients and are linked to worse outcomes. This study examined the influence of nutritional status, determined by the Geriatric Nutritional Risk Index (GNRI), on the incidence of SIH in trauma patients. A retrospective analysis was conducted on adult trauma patients admitted to a Level I trauma center from 1 January 2009 to December 31, 2021. Patients were categorized into four groups: SIH, diabetic hyperglycemia (DH), diabetic normoglycemia (DN), and non-diabetic normoglycemia (NDN). Nutritional status was assessed using GNRI: high risk (GNRI < 82), moderate risk (82 ≤ GNRI < 92), low risk (92 ≤ GNRI ≤ 98), and no risk (GNRI > 98). Incidence of SIH and outcomes were analyzed across GNRI groups. SIH was associated with higher mortality across all GNRI groups compared to NDN, with the highest rate (45.7%) in the high-risk group. Mortality decreased as GNRI increased in all glucose groups. NDN patients had the lowest mortality rates across GNRI groups. There was no correlation between GNRI and SIH incidence (p = 0.259). SIH significantly influenced mortality across all nutritional status groups, with the highest impact in malnourished patients. Although malnutrition did not affect SIH incidence, both SIH and poor nutritional status independently contributed to worse trauma outcomes. Targeted management of hyperglycemia and nutritional deficiencies is crucial for improving survival.

Assessing risk indicators of intimate partner femicide considering victim's coping strategies to violence: A dynamic multilevel linear mixed model based on genetic algorithms

Intimate partner femicide (IPF) is a grave social and health concern affecting women worldwide, with approximately 30,000 deaths annually at the hands of their current or former intimate partners. Previous studies have focused on identifying risk factors for IPF and developing risk assessment tools to identify high-risk cases. However, an important aspect that has been overlooked in these studies is victims' coping strategies in response to intimate partner violence. Understanding victims' coping strategies can provide valuable insights into how they deal with the abuse and can inform the development of effective interventions and prevention strategies. This study aims to address this gap by developing a multilevel linear mixed model (LMM) to analyze the impact of engagement and disengagement coping on the likelihood of IPF and identify common and specific IPF risk indicators for these coping strategies. A total of 491 Spanish cases of violence against women by current or former intimate partners were analyzed from penal sentences issued by Spanish provincial and supreme courts from 2019 to 2022. The LMM model obtained from the study has competitive performance in identifying IPF and non-IPF cases, including risk indicators of prior history of injuries, history of sexual aggression, frequency and escalation of violence, physical violence, place of crime, lonely place of crime, and community presence. Victims with engagement coping and disengagement coping share some risk indicators, while others belong to just one category. Overall, the results suggest that victims with disengagement coping are more predisposed to suffer IPF than victims with engagement coping. This evidenced-based knowledge emphasizes the significance of considering coping strategies in predicting and preventing IPF, with further implications discussed at the end of this paper.