31 research outputs found

    The Happy Life Club™ study protocol: A cluster randomised controlled trial of a type 2 diabetes health coach intervention

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    The Happy Life Club™ is an intervention that utilises health coaches trained in behavioural change and motivational interviewing techniques to assist with the management of type 2 diabetes mellitus (T2DM) in primary care settings in China. Health coaches will support participants to improve modifiable risk factors and adhere to effective self-management treatments associated with T2DM

    Influencing Indicators and Quantitative Assessment of Water Resources Security in Karst Region Based on PSER Model—The Case of Guizhou

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    An important basis to achieve a sustainable balance between water availability and demand is effectively identifying the factors affecting water resource security and evaluating the effectiveness of existing water resource management measures. To reasonably evaluate water resource security in Guizhou Province, this study combined the water resource security features, selected the indicator system based on the Press–Status–Effect–Response (PSER) framework, and used Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and grey correlation analysis for the province from 2001 to 2015. This allowed us to identify the main driving factors affecting water resource security. The results showed that: (1) Water resource security in Guizhou Province showed an overall trend of improvement from 2001 to 2015 and reached a maximum index of 0.57 in 2015. This amelioration in water security was mainly due to the continuous improvement of the response and effect subgroup as a result of improvements in its existing subgroup factors (policies), such as water consumption per unit of gross domestic product (GDP), the proportion of water conservancy investment, and the proportion of the tertiary industry. Increased water stress due to rapid economic development, such as water supply for the reservoir, and the instability of the status subgroup, were the main factors negatively affecting water resource security. (2) Reduction of water consumption per USD of industrial value added, the control force of water and soil erosion being strengthened, and investment in water resources being increased, are the key factors for achieving water resource security in Guizhou during this period of rapid social and economic development. This indicates that the existing water resource management measures have been improving water resource security. The management measures need to be further improved in the future to protect water resource

    Multi-Scale Spatiotemporal Variations and Drivers of PM2.5 in Beijing-Tianjin-Hebei from 2015 to 2020

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    Understanding the spatiotemporal heterogeneity and complex drivers of PM2.5 concentration variations has important scientific value for sustainable urban development. Taking Beijing-Tianjin-Hebei (BTH) as the research area, and using spatial analysis techniques and wavelet methods to explore the spatiotemporal heterogeneity of variations in PM2.5 concentrations, the research shows that in the past six years (2015–2020), the PM2.5 concentrations in the BTH area have a downward trend, and the mean is 59.41 μg/m3; however, the distribution pattern of PM2.5 pollution has changed very little, and the concentration in the south and southwest is still generally high. The continuous wavelet transform revealed that the PM2.5 concentrations in the study area have a short period of about a week to a half a month and a long period dominated by annual cycle. The effect of a single meteorological factor on PM2.5 concentrations is weak, but this effect has obvious spatial differentiation characteristics from coastal to inland and has a double-sided effect due to different geographical locations. The wavelet transform coherence revealed that dewpoint temperature at 2 m (TED), meridional wind at 10 m (WV) and air temperature at 2 m (TEM) are important single meteorological factors that affect the variation of PM2.5 concentrations. The multiple wavelet coherence reveals that in scenarios where two meteorological factors are combined, the combination of TED-mean wind speed (WS) is the best combination to explain the variation in PM2.5 concentrations (AWC = 0.77, PASC = 41%). In the combination of three meteorological factors, TEM-WV-WS explained the variations of PM2.5 concentrations in the BTH region to the greatest degree (AWC = 0.89, PASC = 45%). Finally, the research shows that the variations of PM2.5 concentrations in the BTH region can be better explained by a combination of 2–3 meteorological factors, among which temperature and wind are the key meteorological factors. This research will provide a new window for the multi-scale variation characteristics and multi-factor control relationship of PM2.5 concentrations in the BTH region and provide a new insight for the prevention and control of air pollution

    Multi-Scale Spatiotemporal Variations and Drivers of PM<sub>2.5</sub> in Beijing-Tianjin-Hebei from 2015 to 2020

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    Understanding the spatiotemporal heterogeneity and complex drivers of PM2.5 concentration variations has important scientific value for sustainable urban development. Taking Beijing-Tianjin-Hebei (BTH) as the research area, and using spatial analysis techniques and wavelet methods to explore the spatiotemporal heterogeneity of variations in PM2.5 concentrations, the research shows that in the past six years (2015–2020), the PM2.5 concentrations in the BTH area have a downward trend, and the mean is 59.41 μg/m3; however, the distribution pattern of PM2.5 pollution has changed very little, and the concentration in the south and southwest is still generally high. The continuous wavelet transform revealed that the PM2.5 concentrations in the study area have a short period of about a week to a half a month and a long period dominated by annual cycle. The effect of a single meteorological factor on PM2.5 concentrations is weak, but this effect has obvious spatial differentiation characteristics from coastal to inland and has a double-sided effect due to different geographical locations. The wavelet transform coherence revealed that dewpoint temperature at 2 m (TED), meridional wind at 10 m (WV) and air temperature at 2 m (TEM) are important single meteorological factors that affect the variation of PM2.5 concentrations. The multiple wavelet coherence reveals that in scenarios where two meteorological factors are combined, the combination of TED-mean wind speed (WS) is the best combination to explain the variation in PM2.5 concentrations (AWC = 0.77, PASC = 41%). In the combination of three meteorological factors, TEM-WV-WS explained the variations of PM2.5 concentrations in the BTH region to the greatest degree (AWC = 0.89, PASC = 45%). Finally, the research shows that the variations of PM2.5 concentrations in the BTH region can be better explained by a combination of 2–3 meteorological factors, among which temperature and wind are the key meteorological factors. This research will provide a new window for the multi-scale variation characteristics and multi-factor control relationship of PM2.5 concentrations in the BTH region and provide a new insight for the prevention and control of air pollution

    Comparison of Random Forest Model and Frequency Ratio Model for Landslide Susceptibility Mapping (LSM) in Yunyang County (Chongqing, China)

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    To compare the random forest (RF) model and the frequency ratio (FR) model for landslide susceptibility mapping (LSM), this research selected Yunyang Country as the study area for its frequent natural disasters; especially landslides. A landslide inventory was built by historical records; satellite images; and extensive field surveys. Subsequently; a geospatial database was established based on 987 historical landslides in the study area. Then; all the landslides were randomly divided into two datasets: 70% of them were used as the training dataset and 30% as the test dataset. Furthermore; under five primary conditioning factors (i.e., topography factors; geological factors; environmental factors; human engineering activities; and triggering factors), 22 secondary conditioning factors were selected to form an evaluation factor library for analyzing the landslide susceptibility. On this basis; the RF model training and the FR model mathematical analysis were performed; and the established models were used for the landslide susceptibility simulation in the entire area of Yunyang County. Next; based on the analysis results; the susceptibility maps were divided into five classes: very low; low; medium; high; and very high. In addition; the importance of conditioning factors was ranked and the influence of landslides was explored by using the RF model. The area under the curve (AUC) value of receiver operating characteristic (ROC) curve; precision; accuracy; and recall ratio were used to analyze the predictive ability of the above two LSM models. The results indicated a difference in the performances between the two models. The RF model (AUC = 0.988) performed better than the FR model (AUC = 0.716). Moreover; compared with the FR model; the RF model showed a higher coincidence degree between the areas in the high and the very low susceptibility classes; on the one hand; and the geographical spatial distribution of historical landslides; on the other hand. Therefore; it was concluded that the RF model was more suitable for landslide susceptibility evaluation in Yunyang County; because of its significant model performance; reliability; and stability. The outcome also provided a theoretical basis for application of machine learning techniques (e.g., RF) in landslide prevention; mitigation; and urban planning; so as to deliver an adequate response to the increasing demand for effective and low-cost tools in landslide susceptibility assessments

    Evaluating Water Resource Security in Karst Areas Using DPSIRM Modeling, Gray Correlation, and Matter–Element Analysis

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    To evaluate the long-term security of water resources in Guizhou, this paper presents an evaluation index that incorporates the driving force–pressure–state–impact–response–management (DPSIRM) framework, the gray correlation method, and matter–element analysis. For the period of 2005–2012, our results show that water resources were within the “generally safe” limits for all years except 2006 and 2011, which were characterized by drought conditions. In karst regions, drought has a relatively large impact on water security and is compounded in Guizhou by rapid economic development, nonpoint-source agricultural pollution, and inadequate sewage treatment. Nonetheless, recent efforts to return farmland to forest and grassland and to control desertification have led to increased forest cover and higher levels of soil and water conservation, while systems have been implemented to foster the effective management of water resources in karst areas. In this study, we used both gray matter–element analysis and a DPSIRM framework to assess the state of water resources in Guizhou, the results of which were compared and verified by the gray set pair method, and to provide a reference for evaluating other karst areas

    The Relationship between Water Resources Use Efficiency and Scientific and Technological Innovation Level: Case Study of Yangtze River Basin in China

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    The Yangtze River Basin's water resource utilization efficiency (WUE) and scientific and technological innovation level (STI) are closely connected, and the comprehension of these relationships will help to improve WUE and promote local economic growth and conservation of water. This study uses 19 provinces and regions along the Yangtze River's mainstream from 2009 to 2019 as its research objects and uses a Vector Auto Regression (VAR) model to quantitatively evaluate the spatiotemporal evolution of the coupling coordination degree (CCD) between the two subsystems of WUE and STI. The findings show that: (1) Both the WUE and STI in the Yangtze River Basin showed an upward trend during the study period, but the STI effectively lagged behind the WUE; (2) The CCD of the two subsystems generally showed an upward trend, and the CCD of each province was improved to varying degrees, but the majority of regions did not develop a high-quality coordination stage; (3) The CCD of the two systems displayed apparent positive spatial autocorrelation in the spatial correlation pattern, and there were only two types: high-high (H-H) urbanization areas and low-low (L-L) urbanization areas; (4) The STI showed no obvious response to the impact of the WUE, while the WUE responded greatly to the STI, and both of them were highly dependent on themselves. Optimizing their interaction mechanisms should be the primary focus of high-quality development in the basin of the Yangtze River in the future. These results give the government an empirical basis to enhance the WUE and promote regional sustainable development

    Identification and Evolution of the Noncoordination Coupling Relationship between Tourism Poverty Alleviation and Ecological Environments in Poor Mountainous Areas

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    Tourism poverty alleviation and ecological environments are closely associated with each other’s dissipation structure, which contains various coordinated and noncoordinated coupling states. Based on the perspective of reverse thinking and problem diagnosis, this paper constructs a bridge from uncoordinated pathology to coordinated development. From the perspective of incongruity, the framework model and evaluation index system of tourism poverty alleviation and ecological environments incongruity coupling coordination driving mechanism are constructed. Also, the variation coefficient method is used to calculate the weight of each evaluation index and the coupling relationship and evolution of tourism poverty alleviation and ecological environments in Liupanshui city are analyzed by the noncoordination coupling function. The results suggest the following: (1) During the study period, the poverty alleviation level of tourism in Liupanshui city presents a continuous growth curve. Meanwhile, ecological environment development level depicts rapid growth initially and then slows down and improves further. In this way, it shows different stage characteristics from the tourism poverty alleviation level. (2) The discordant coupling between tourism poverty alleviation and ecological environments in Liupanshui city shows a decreasing curve. So, the noncoordinated development relationship between tourism poverty alleviation and ecological environments is significant

    How New Urbanization Affects Tourism Eco-Efficiency in China: An Analysis Considering the Undesired Outputs

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    In the context of the global Sustainable Development Goals, the study of tourism eco-efficiency (TE) becomes particularly important for the balance between environmental protection and economic development in tourist destinations. This paper improves the measurement method of tourism carbon emissions, uses the Super-SBM model of undesired output to measure China&rsquo;s TE, and then explores the impact of new urbanization (NU) on TE. The results show that TE in China is in dynamic equilibrium in general, the agglomeration characteristics of efficiency changed from high in the east and low in the west to low in the south and high in the north, and developmental differences first increased and then decreased. NU development has a significant one-way positive impact on TE at the national level and in the eastern region. As far as impact, economic urbanization plays a great role, and ecological factors become more and more important. NU has a rapid and long-term impact on TE, and its contribution rate to developed economic regions can reach 35%. This study will provide an important reference for sustainable development of tourism under the trend of urbanization

    What was the spatiotemporal evolution characteristics of high-quality development in China? A case study of the Yangtze River economic belt based on the ICGOS-SBM model

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    High-Quality Development (HQD) can well meet human’s growing needs for a better life, and it is an important manifestation of efficient, fair and sustainable development. It is a crucial turning point for China from high-speed development to HQD. A better understanding the HQD from perspective of efficiency is very important for the development of China. Using prefecture-level city panel data of China from 2005 to 2019, this study built a model coupled with innovation, coordination, greenness, openness, sharing, and slacks-based measure (ICGOS-SBM) based on the Super-SBM model of slack variables. By introducing efficiency thinking, this study measured the HQD level of the Yangtze River Economic Belt (YREB, one of driving forces spearheading China’s HQD in a new era) from the perspective of development “quality”, and explored its spatial and temporal distribution characteristics. The results showed that (a) the temporal HQD levels of the YREB presented an “N”, pattern of rising first, then falling, and then rising; (b) the HQD levels exhibited noticeable regional heterogeneity a the different urban scale, and the development trend of the upper of YREB drove that of the middle and then that of the downstream; (c) the HQD levels of the YREB presented different degrees of spatial agglomeration, with an increasing trend over time, and the high-high agglomeration areas were mainly concentrated in the upper of the YREB with better natural endowments; and (d) the spatial HQD trajectory of the YREB mainly moved back and forth in the southwest-northeast direction, which may be due to its unstable development, showing a relatively obvious back-and-forth movement between Changde and Jingzhou. It aims to provide an innovative perspective for the measurement of HQD levels by introducing efficiency thinking
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