OBJECTIVEWe aimed to investigate the associations of macronutrient quality indices with the incident metabolically unhealthy normal weight (MUNW) and metabolically unhealthy overweight/obesity (MUO) ...phenotypes.METHODSThis prospective study included 512 metabolically healthy normal weight and 787 metabolically healthy overweight/obese adults from the third study examination of the Tehran Lipid and Glucose Study. The participants were followed through the sixth study examination. Diet was measured with a food frequency questionnaire. The macronutrient quality index (MQI), carbohydrate quality index (CQI), fat quality index (FQI), and healthy plate quality index (HPPQI) were calculated. Hazard ratio (HR) and 95 % confidence interval (95 % CI) were estimated for incident unhealthy phenotypes using Cox regression.RESULTSAfter controlling all possible confounding factors, a one-point higher HPPQI was linked to a 28 % lower risk of MUNW (HR = 0.72; 95 % CI = 0.59, 0.87). Compared to the lowest quartile, the incident MUNW was also lower in the two last quartiles of the HPPQI. A one-unit increase in MQI was associated with a 5 % lower incident MUO (HR = 0.95; 95 % CI = 0.92, 0.99). The incident MUO was also higher for the highest compared to the lowest MQI quartile. In quartiles 2-4 of the HPPQI, incident MUO was lower with respective HRs (95 % CI) of 0.71 (0.54, 0.93), 0.60 (0.45, 0.80), and 0.66 (0.50, 0.86) in the fully-adjusted model.CONCLUSIONSA higher overall macronutrient quality was independently associated with a lower incident MUO. A higher dietary protein quality was related to a lower risk for MUNW and MUO.
The present study investigated and compared the diagnostic accuracy of Dysphonia Severity Index (DSI) and Acoustic Voice Quality Index (AVQI) in Indian adults in the age range of 18-40years across ...different levels of dysphonia severity. Normophonic individuals (n=163) and individuals with dysphonia (n=134) were selected using purposive sampling in the age range of 18-40years. For DSI, Computerized Speech Lab 4500 and for AVQI, Praat 6.1.03 was used for recording. The results of receiver operating characteristics (ROC) analysis for DSI have revealed that DSI can discriminate the normophonic versus mild, mild versus moderate, and moderate versus severe dysphonic with cut-off values of 1.36, -1.83, and -4.07, respectively. The sensitivity and specificity reported for mild versus moderate and moderate versus severe are slightly lower for obtained threshold points. For AVQI v.02.03, ROC analysis revealed that high sensitivity and specificity cut-off points for normophonic versus mild, mild versus moderate, and moderate versus severe dysphonic are 2.50, 3.86, and 6.21, respectively. AVQI is a more effective technique than DSI for distinguishing between dysphonia severities levels, particularly when it comes to mild versus moderate and moderate versus severe, according to comparisons of AROC curves made using the DeLang method.The present study investigated and compared the diagnostic accuracy of Dysphonia Severity Index (DSI) and Acoustic Voice Quality Index (AVQI) in Indian adults in the age range of 18-40years across different levels of dysphonia severity. Normophonic individuals (n=163) and individuals with dysphonia (n=134) were selected using purposive sampling in the age range of 18-40years. For DSI, Computerized Speech Lab 4500 and for AVQI, Praat 6.1.03 was used for recording. The results of receiver operating characteristics (ROC) analysis for DSI have revealed that DSI can discriminate the normophonic versus mild, mild versus moderate, and moderate versus severe dysphonic with cut-off values of 1.36, -1.83, and -4.07, respectively. The sensitivity and specificity reported for mild versus moderate and moderate versus severe are slightly lower for obtained threshold points. For AVQI v.02.03, ROC analysis revealed that high sensitivity and specificity cut-off points for normophonic versus mild, mild versus moderate, and moderate versus severe dysphonic are 2.50, 3.86, and 6.21, respectively. AVQI is a more effective technique than DSI for distinguishing between dysphonia severities levels, particularly when it comes to mild versus moderate and moderate versus severe, according to comparisons of AROC curves made using the DeLang method.
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IoT-enabled sensor devices and machine learning methods have played an essential role in monitoring and forecasting mine hazards. In this paper, a prediction model has been proposed ...for improving the safety and productivity of underground coal mines using a hybrid CNN-LSTM model and IoT-enabled sensors. The hybrid CNN-LSTM model can extract spatial and temporal features from mine data and efficiently predict different mine hazards. The proposed model also improves the flexibility, scalability, and coverage area of a mine monitoring system to an underground mine's remote locations to minimize the loss of miners' lives. The proposed model efficiently predicts miner's health quality index (MHQI) for working faces and gases in goaf areas of mines. The experimental results demonstrated that the predicted mean square error of the proposed model is less than 0.0009 and 0.0025 for MHQI; 0.0011 and 0.0033 for CH4 in comparison with CNN and LSTM models, respectively. The less means square error indicates the better prediction accuracy of the trained. Similarly, the correlation coefficient (R2) value of the proposed model is found greater than 0.005 and 0.001 for MHQI; 0.007 and 0.001 for CH4 compared to CNN and LSTM models, respectively. Thus, the proposed CNN-LSTM model performed better than the two existing models.
•People are less willing to engage in PEB (e.g., purchasing pro-environmental products, recycling, sustainable travel, donation to environmental organizations) when air pollution is severe.•Search ...indexes for PEB are significantly negatively related to the air quality.•The negative effect of air pollution on people’s pro-environmental behavior is mediated by the negative mood state triggered by the air pollution.
Air pollution has been a major environmental problem impacting billions of people worldwide. Despite a large stream of literature discussing the psychological, economic, and environmental effects of air pollution, limited research has explored how people’s pro-environmental behavior (PEB) is affected by air pollution. The present research indicates that people are less willing to engage in PEB when air pollution is severe. Our results show that public attention to PEB is significantly negatively related to air quality (Pilot Study). Additionally, when exposed to air pollution, people are less likely to purchase pro-environmental products (Studies 1 and 2), engage in recycling (Study 3), participate in sustainable travel (Study 4) and donate to environmental organizations (Studies 4 and 5). This is because the negative mood triggered by air pollution inhibits their willingness to engage in PEB (Studies 1 and 3). The theoretical and practical implications of the present research are also discussed.
The world’s longest trans-basin water diversion project, the Middle-Route (MR) of the South-to-North Water Diversion Project of China (SNWDPC), has officially been in operation for over 5 years since ...December 2014. Its water quality status has always attracted special attention because it is related to the health and safety of more than 58 million people and the integrity of an ecosystem covering more than 155,000 km2. This study presented and analysed the spatio-temporal variations and trends of 16 water quality parameters, including pH, water temperature (WT), dissolved oxygen (DO), permanganate index (PI), five-day biochemical oxygen demand (BOD5), fecal coliform (F. coli), total phosphorus (TP), total nitrogen (TN), ammonia nitrogen (NH3−N), sulphate (SO42−), fluoride (F−), mercury (Hg), arsenic (As), selenium (Se), copper (Cu), and zinc (Zn), which were determined monthly from samples collected at 27 water quality monitoring stations in the MR of the SNWDPC from March 2016 to February 2019. The water quality index (WQI) was used to evaluate the seasonal and spatial water quality changes during the monitoring period, and a new WQImin model consisting of five crucial parameters, i.e., TP, F. coli, Hg, WT, and DO, was built by using stepwise multiple linear regression analysis. The results demonstrated that the water quality status of the MR of the SNWDPC has been steadily maintained at an “excellent” level during the monitoring period, with an overall average WQI value of 90.39 and twelve seasonal mean WQI values ranging from 87.67 to 91.82. The proposed WQImin model that uses the selected five key parameters and the weights of those parameters has exhibited excellent performance in the water quality assessment of the project, with the coefficient of determination (R2), Root Mean Square Error (RMSE), and Percentage Error (PE) values of 0.901, 2.21, 1.93%, respectively, showing that the proposed WQImin model is a useful and efficient tool to evaluate and manage the water quality. For the management department, the risk sources near certain stations with abnormally high values should be carefully inspected and strictly managed to maintain excellent water quality. The potential risks of algae proliferation in this project should be of concern in future research.
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•A comprehensive analyses and assessments of water quality were conducted.•The project water quality status has been steadily maintained at “excellent” level.•TP, F. coli, Hg, WT, and DO are the most important parameters of the project.•The potential risks of algae proliferation in the main canal should be of concern.
Rivers are one of the main water resources for agricultural, drinking, environmental and industrial use. Water quality indices can and have been used to identify threats to water quality along a ...stream and contribute to better water resources management. There are many water quality indices for the assessment and use of surface water for drinking purposes. However, there is no well-established index for the assessment and direct use of river water for irrigation purposes. The aim of this study was to adopt the framework of the National Sanitation Foundation Water Quality Index (NSFWQI) and, with adjustments, apply it in a way which will conform to irrigation water quality requirements. To accomplish this, the NSFWQI parameters for drinking water use were amended to include water quality parameters suitable for irrigation. For each selected parameter, an individual weighting chart was generated according to the FAO 29 guideline. The NSFWQI formula was then used to calculate a final index value, and for each parameter an acceptable range in this value was determined. The new index was then applied to the Ghezel Ozan River in Iran as a case study. A forty five year record of water quality data (1966 to 2010) was collected from four hydrometery stations along the river. Water quality parameters including Na+, Cl−, pH, HCO−3, EC, SAR and TDS were employed for water quality analysis using the adjusted NSFWQI formula. The results of this case study showed variation in water quality from the upstream to downstream ends of the river. Consistent monitoring of the river water quality and the establishment of a long term management plan were recommended for the protection of this valuable water resource.
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•A simple direct index for assessing surface water quality for irrigation demand was developed.•The selected parameters were provided with a weighting based on the survey outcomes.•The resulting index was similar to the original NSFWQI index.•FAO 29 guideline for irrigation water quality and an iterative survey employed.•This study showed variation in water quality from the upstream to downstream ends of the river.
Groundwater is a vital source of freshwater in both urban and rural regions of the world. However, its injudicious abstraction and rapidly increasing contamination are posing a severe threat for ...sustainable water supply worldwide. Geographical Information System (GIS)-based groundwater quality evaluation using Groundwater Quality Index (GQI) has been proved to be a cost-effective tool for assessing groundwater quality and its variability at a larger scale. However, the conventional GQI approach is unable to deal with uncertainties involved in the assessment of environmental problems. To overcome this limitation, a novel hybrid framework integrating Fuzzy Logic with the GIS-based GQI is proposed in this study for assessing groundwater quality and its spatial variability. The proposed hybrid framework is demonstrated through a case study in a hard-rock terrain of Southern India using ten prominent groundwater-quality parameters measured during pre-monsoon and post-monsoon seasons. Two conventional GIS-based GQI models GQI-10 (using all the ten groundwater-quality parameters) and GQI-7 (using seven ‘concerned/critical’ groundwater-quality parameters) as well as hybrid Fuzzy-GIS-based GQI (FGQI) models (using seven critical parameters) were developed for the two seasons and the results were compared. The Trapezoidal membership functions classified the model input parameters into ‘desirable’, ‘acceptable’ and ‘unacceptable’ classes based on the experts’ knowledge and water quality standards for drinking purposes. The concentrations of Ca2+, Mg2+, and SO42− in groundwater were found within the WHO desirable limits for drinking water throughout the year, while the concentrations of seven parameters (TDS, NO3−-N, Na+, Cl−, K+, F− and Hardness) exceed their permissible limits during pre-monsoon and post-monsoon seasons. A comparative evaluation of GQI models revealed that the FGQI model predicts groundwater quality better than the conventional GQI-10 and GQI-7 models. GQI modeling results suggest that the groundwater of most of eastern and southern parts (∼60% in pre-monsoon season; ∼90% in post-monsoon season) of the study area is unsuitable for drinking. Further, the groundwater quality deteriorates during post-monsoon seasons compared to pre-monsoon seasons, which indicates an increased influx of contaminants from different industries, mining areas, waste disposal sites and agricultural fields during monsoon seasons. This finding calls for the strict enforcement of regulations for proper handling of effluents from various contamination sources in the study area. It is concluded that the fuzzy logic-based decision-making approach (FGQI) is more reliable and pragmatic for groundwater-quality assessment and analysis at a larger scale. It can serve as a useful tool for the water planners and decision makers in efficiently monitoring and managing groundwater quality at watershed or basin scales.
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•Novel hybrid framework integrating Fuzzy Logic with GIS-based GQI is developed.•FGQI is more reliable and useful for water-quality evaluation at larger scales.•Groundwater polluted zones are in eastern and southern parts of the study area.•Groundwater quality in post-monsoon seasons is worse than in pre-monsoon seasons.•Comprehensive strategies for sustainable groundwater management are urgently needed.
Air pollution events occur frequently in northwest China, which results in serious detrimental effects on human health. Therefore, it is essential to understand the air pollution characteristics and ...assess the risks to humans. In this study, we analyzed the pollution characteristics of criteria pollutants in six key cities in northwest China from 2015 to 2018. We used the air quality index (AQI), aggregate AQI (AAQI), and health-risk based AQI (HAQI) to assess the health risks and determine the proportion of people exposed to air pollution. Additionally, on this basis, the AirQ2.2.3 model was used to quantify the health effects of the pollutants. The results showed that PM10 pollution occurred mainly in spring and winter and was caused by frequent dust storms. PM2.5 pollution was caused mainly by anthropogenic activities (especially coal-fired heating in winter). Because of a series of government policies and pollutant reduction measures, PM2.5, SO2, NO2, and CO concentrations showed a downward trend during the study period (except for a small increase in the case of NO2 in some years.). However, O3 showed high concentrations due to the high intensity of solar radiation in summer and inadequate emission reduction measures. The air quality levels based on their classification were generally higher than the Chinese ambient air quality standard classified by the AQI index. We also found that the higher the AQI index was, the more serious the air pollution classified based on the AAQI and HAQI indices was. The HAQI index could better reflect the impact of pollutants on human health. Based on the HAQI index, 20% of the population in the study area was exposed to polluted air. The total mortality values attributable to PM10, PM2.5, SO2, O3, NO2, and CO, quantified by the AirQ2.2.3 model, were 3.00%, 1.02%, 1.00%, 4.22%, 1.57%, and 0.95% (Confidence Interval:95%), respectively; the attributable proportions of mortality for respiratory system and cardiovascular diseases were consistent with the change rule of total mortality, because the number of deaths attributable to the latter was greater than that for the former. According to the exposure reaction curves of pollutants, PM10 and PM2.5 still showed a large change at high concentrations. However, the tendencies of SO2, NO2, CO, and O3 were more obvious under low concentration exposure, which indicated that the expected mortality rate due to lower air pollution concentrations was much higher than the mortality due to high air pollution concentrations.
•Air pollution characteristics and health risks were analyzed in Northwest China.•The AQI underestimated the health risks of air pollution.•The HAQI showed that 20% of the study area was exposed to polluted air.•PM10 and O3 contributed more to total mortality than other pollutants.
Secondary vegetation succession can alter soil functions and quality. However, data on changes to soil quality at different stages of vegetation succession in karst areas of southwest China is ...limited. This study aimed to evaluate the effects of different vegetation succession on soil quality and further to identify the factors that influencing soil quality. Secondary forest, shrub, grass, and cropland (as a reference) were selected and sampled in the subtropical karst of southwest China. Soil quality index (SQI) was developed by two methods of Total Data Set (TDS) and Minimum Data Set (MDS). Based on principal component analysis (PCA), soil organic carbon, silt, available phosphorous, available potassium, soil thickness, and soil water content were identified as the most representative indicators for the MDS. Both methods showed that the highest SQI values were observed in secondary forest, followed by shrub and grass, and the cropland values were the lowest. This showed vegetation succession significantly influenced on soil physiochemical properties and thus on soil quality. MDS could adequately represent TDS to quantify the effects of vegetation succession on soil quality since similar SQI results were derived from the two methods (R2 = 0.68, P < 0.01). The influencing factors explained about 75% of the total variation in SQI using a generalized linear model. Vegetation types accounted for the largest proportion of the SQI variability followed by restoration time, indicating these factors significantly affect soil quality during vegetation succession. In general, vegetation succession significantly influenced soil properties, and also has long-term and positive effects on soil quality during vegetation restoration. This study helps to understand the changes in soil quality during vegetation succession and provides guidance for the sustainable management of revegetation in subtropical karst regions in China.
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•Soil organic carbon, available phosphorous, available potassium, soil thickness and soil water content were selected as MDS.•Vegetation succession significantly influenced soil properties and soil quality.•Vegetation type and restoration time were significant factors influencing SQI.
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•Water quality variations over the last decade were assessed in Baiyangdian Lake.•WQI method and multivariate statistical techniques were used for the assessment.•The lake was divided ...into two regions based on spatial heterogeneity of water quality.•Influences of human activity on water quality were greater than those of natural factors.•Water quality in the two regions was determined by different types of human activities.
Baiyangdian Lake, the largest shallow lake in the North China Plain, is essential for maintaining ecosystem functioning in this highly populated region. To explore the influences of human activities on the lake’s water quality, an improved Water Quality Index (WQI) method and multivariate statistical techniques were adopted to assess the temporal and spatial variations of the lake’s water quality and explore the dominant factors of these variations. Datasets for 11 water quality parameters from six monitoring stations were used to evaluate the period spanning from 2006 to 2016. Assessment of the annual WQI showed that the water quality of the lake has generally improved over the past decade. Cluster analysis divided 12 months into the dry and wet periods and the six monitoring stations into those located in the western and eastern parts of the lake. Discriminant analysis demonstrated that with only two parameters (water temperature and fluoride) and six parameters (dissolved oxygen, ammonia nitrogen, total nitrogen, total phosphorus, anionic surfactant, and fecal coliform), 96.0% and 93.8% of the water quality data can be classified into the correct spatial and temporal clusters, respectively. For the principal component analysis and factor analysis, the varifactors detected for the two temporal clusters were similar, and varifactors related to pollution explained more variance in the water quality variation than the ones representing natural factors. For the two spatial clusters, the varifactors were different, indicating they are influenced by different types of anthropogenic activities. Correlation analysis between lake water level and water quality indicated that environmental water allocation to the lake generally improve water quality. These findings provide a more thorough understanding of driving mechanism of water quality and may be helpful for making environmental management decisions in Baiyangdian Lake and other large, shallow lakes in highly populated dryland regions.
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