Arsenic Induced Gallbladder Cancer Risk in Eastern Part of Indo-Gangetic Plains

BackgroundIn recent times Gallbladder cancer (GBC) incidences increased many folds in India. Majority of GBC cases are being reported from arsenic hotspots identified in Bihar. MethodsIn this prospective study volunteers were selected who underwent surgery in our cancer institute. There were 11 control benign gallbladder cases and 28 confirmed gallbladder cancer cases. Their biological samples such as blood, gallbladder tissue, gallbladder stone, bile and hair samples were collected for arsenic estimation. Moreover, n=512 gallbladder cancer patients blood samples were evaluated for the presence of arsenic to understand exposure level in the population. ResultsA significantly high arsenic concentration (p<0.05) was detected in the blood samples, gallbladder tissue, gallstones, bile and hair samples in comparison to the control group. Moreover, n=512 blood samples of GBC patients had significantly very high arsenic concentration. ConclusionsThe study shows very high arsenic concentration observed in the blood, gallbladder tissue, gallbladder stone, bile and hair samples in GBC cases in comparison to the benign control cases indicates the correlation between chronic arsenic exposure and gallbladder cancer incidences in eastern Indo-Gangetic plains region. The study also makes an attempt to establish the likely correlation/association between arsenic exposure and gallbladder cancer disease.

Screening for Noise-Induced Hearing Loss among Palm Oil Mill Workers in Peninsular Malaysia: A Comparison across Noise Exposure Levels

Background: Palm oil mill workers in Malaysia are exposed to hazardous levels of noise in the workplace, and thus are at risk of developing noise-induced hearing loss (NIHL). In 2019, Malaysia introduced a new noise regulation, which reduced the level of permissible noise exposure. Objectives: This study aims to determine the prevalence of NIHL among palm oil mill workers based on screening data and assess the effects of different noise exposure levels on NIHL. Methods: A cross-sectional study was conducted by analyzing data from noise risk assessment reports of selected mills and screening audiometric data from workers. NIHL was defined as bilateral high-frequency hearing loss. Results: The overall NIHL prevalence was 50.8%. Noise exposure level and age were significant predictors of NIHL among the workers. The risk of developing NIHL was high even for workers who were not categorized in the high-risk group. Conclusions: In view of the findings, a precautionary approach is needed when evaluating the risk of NIHL in the study population. Vulnerable groups of workers must be protected from occupational noise hazards through the implementation of effective hearing conservation programs in the workplace.

Estimating Sound Exposure Levels Due to a Broadband Source over Large Areas of Shallow Sea

3D sound propagation modeling in the context of acoustic noise monitoring problems is considered. A technique of effective source spectrum reconstruction from a reference single-hydrophone measurement is discussed, and the procedure of simulation of sound exposure level (SEL) distribution over a large sea area is described. The proposed technique is also used for the modeling of pulse signal waveforms at other receiver locations, and results of a direct comparison with the pulses observed in the experimental data is presented.

Measurements and Spatial Distribution Simulation of Impact Pile Driving Underwater Noise Generated During the Construction of Offshore Wind Power Plant Off the Southwest Coast of Korea

Offshore wind power plants are under construction worldwide, and concerns about the adverse effects of underwater noise generated during their construction on the marine environment are increasing. As part of an environmental impact assessment, underwater noise generated by impact pile driving was measured during the construction of an offshore wind farm off the southwest coast of Korea. The sound exposure levels of impact pile driving noise were estimated as a function of distance and compared with those predicted by a damped cylindrical spreading model and broadband parabolic equation simulation. Source level at 1 m was estimated to be in a range of 183–184 dB re 1μPa2s in the sound exposure level based on the model predictions and it tended to decrease by 21log⁡r as the distance increased. Finally, the spatial distribution of impact pile driving noise was predicted. This result, if combined with noise-induced damage thresholds for marine life, may be used to assess the effects of wind farm construction on marine ecosystems.

Effect of intensity and duration of anthropic noises on European mink locomotor activity and faecal cortisol metabolite levels

Human activities involving noise emission can affect wild animals. European mink was exposed to road noise and human voice playbacks to analyse how sound intensity level and duration of both noises altered the time that individuals were active and if their faecal cortisol metabolite (FCM) levels varied. A Hierarchical Analysis Cluster was performed to established two mink groups with respect to both noise source type: short duration/low intensity (SL) and long duration/high intensity (LH). We performed General Linear Mixed Models to evaluate the variation in locomotor activity duration (s) and FCM (ng/g) levels, respectively. The results showed both road noise and human voices decreased locomotor activity duration in SL more sharply compared to LH, and human voices were the triggers that induced the most pronounced response to both exposure conditions. FCM levels increased in SL compared to LH during road noise while the opposite happened during human voices. Differences based on sex and age of individuals were observed. In conclusion, noise characteristics given by the sound type determined the variations in locomotor activity duration while noise exposure level determined the variations in FCM levels. Attention should be paid to noisy activities (e.g. recreational activities for visitors in protected natural areas) and loud groups of people to conserve wildlife, especially noise sensitive species.

Risk assessment of workers exposed to respirable crystalline silica in silica crushing units in Azandarian Industrial Zone, Hamadan, Iran

Introduction: Azandarian industrial zone with about 40 active silica crushing units is one of the largest industrial area in Hamadan province, Iran. Materials and methods: In this study, the personal exposure of workers in the activated silica crushing units was measured. Assessing the risk of mortality due to exposure to Respirable Crystalline Silica (RCS) in the workplace was then estimated through measuring the personnel exposure in accordance with the National Institute for Occupational Safety and Health (NIOSH) 7601 method. Moreover, the mortality rate of lung cancer and risk of mortality due to exposure to RCS were estimated. Results: Based on the results, the average exposure of employees to RCS in the crushing units was in the range of 1.70 -0.14 mg/m3. As observed, the lowest and highest exposure was obtained for the admission unit and sandstone, respectively. In general, it can be inferred that in all studied occupation positions, the exposure level was higher than the recommended standard (0.25 mg/m3). As can be seen, the carcinogenic risk level for the exposed workers was in the range 2-26/1000. The results of risk assessment showed that the highest risk level was related to the stamping machine operator unit and the lowest was related to the administrative unit. Conclusion: Therefore, the workers working in high-risk units such as stamping machine operator and stone separation operator are more likely to suffer from adverse health complications such as silicosis, lung cancer and other respiratory complications.

Prevalence and risk factors of depression symptoms among rural and urban populations affected by Ebola virus disease in the Democratic Republic of the Congo: a representative cross-sectional study

ObjectivesHigh mortality rates, anxiety and distress associated with Ebola virus disease (EVD) are risk factors for mood disorders in affected communities. This study aims to document the prevalence and risk factors associated with depressive symptoms among a representative sample of individuals affected by EVD.DesignCross-sectional study.SettingThe current study was conducted 7 months (March 11, 2019 to April 23, 2019) after the end of the ninth outbreak of EVD in the province of Equateur in the Democratic Republic of the Congo (DRC).ParticipantsA large population-based sample of 1614 adults (50% women, Mage=34.05; SD=12.55) in health zones affected by the ninth outbreak in DRC.Primary and secondary outcome measuresParticipants completed questionnaires assessing EVD exposure level, stigmatisation related to EVD and depressive symptoms. The ORs associated with sociodemographic data, EVD exposure level and stigmatisation were analysed through logistic regressions.ResultsOverall, 62.03% (95% CI 59.66% to 64.40%) of individuals living in areas affected by EVD were categorised as having severe depressive symptoms. The multivariable logistic regression analyses showed that adults in the two higher score categories of exposure to EVD were at two times higher risk of developing severe depressive symptoms (respectively, OR 1.94 (95% CI 1.22 to 3.09); OR 2.34 (95% CI 1.26 to 4.34)). Individuals in the two higher categories of stigmatisation were two to four times more at risk (respectively, OR 2.42 (95% CI 1.53 to 3.83); OR 4.73 (95% CI 2.34 to 9.56)). Living in rural areas (OR 0.19 (95% CI 0.09 to 0.38)) and being unemployed (OR 0.68 (95% CI 0.50 to 0.93)) increased the likelihood of having severe depressive symptoms.ConclusionsResults indicate that depressive symptoms in EVD affected populations is a major public health problem that must be addressed through culturally adapted mental health programs.

A Multiscale Land Use Regression Approach for Estimating Intraurban Spatial Variability of PM2.5 Concentration by Integrating Multisource Datasets

Poor air quality has been a major urban environmental issue in large high-density cities all over the world, and particularly in Asia, where the multiscale complex of pollution dispersal creates a high-level spatial variability of exposure level. Investigating such multiscale complexity and fine-scale spatial variability is challenging. In this study, we aim to tackle the challenge by focusing on PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 µm,) which is one of the most concerning air pollutants. We use the widely adopted land use regression (LUR) modeling technique as the fundamental method to integrate air quality data, satellite data, meteorological data, and spatial data from multiple sources. Unlike most LUR and Aerosol Optical Depth (AOD)-PM2.5 studies, the modeling process was conducted independently at city and neighborhood scales. Correspondingly, predictor variables at the two scales were treated separately. At the city scale, the model developed in the present study obtains better prediction performance in the AOD-PM2.5 relationship when compared with previous studies (R2¯ from 0.72 to 0.80). At the neighborhood scale, point-based building morphological indices and road network centrality metrics were found to be fit-for-purpose indicators of PM2.5 spatial estimation. The resultant PM2.5 map was produced by combining the models from the two scales, which offers a geospatial estimation of small-scale intraurban variability.