Refined water security assessment for sustainable water management: A case study of 15 key cities in the Yangtze River Delta, China.

Water security represents ecological security and a policy priority for sustainable development; however, un-gridded assessment results cannot be used to support urban environmental management decisions. This study proposes a systematic framework to obtain a gridded regional water security assessment, which reflects the regional natural resource, based on the index system derived from the Pressure-State-Response (PSR) model and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. The results were applied to sustainable water management. Using 15 key cities in the Yangtze River Delta (YRD) region as a case study to apply the methodology, we found that the comprehensive water security was relatively high and high-value areas were widely distributed, accounting for about two-thirds of the study area. Low-value areas were mainly distributed in central and eastern regions, such as Shanghai, Suzhou, and Nanjing. There was evidence of a water resource shortage during the twelve-month period studied, particularly in August. The proportions of comprehensive water security in each administrative unit and the differences between simulated and target water quality could be used in the spatial planning and the exploration of payments for ecosystem services (PES) mechanism in county-level or smaller administrative units. Despite the premise requirement and the grid resolution problems of the InVEST model, it can be concluded that our assessment method proves capable of matching spatial and temporal differences in water supply and demand at a fine scale, and results can be used to supply useful information for urban management decision making.

The Interconnecting Process and Sensing Performance of Stretchable Hybrid Electronic Yarn for Body Temperature Monitoring.

Flexible and stretchable electronic yarn containing electronic components (i.e., hybrid electronic yarn) are essential for manufacturing smart textile garments or fabrics. Due to their low stretchability and easy interconnection fracture, previously reported hybrid electronic sensing yarns have poor mechanical durability and washability. In order to address this issue, a stretchable hybrid electronic yarn for body temperature monitoring was designed and prepared using a spandex filament as the core yarn and a thin enameled copper wire connected with a thermal resistor as the wrapping fiber. The temperature sensing performance of different hybrid electronic yarn samples was evaluated using the following three types of interconnection methods: conductive adhesive bonding, melt soldering, and hot pressure bonding. The optimal interconnection method with good sensing performance was determined. Furthermore, in order to improve the mechanical durability of the hybrid electronic yarn made using the optimal interconnection method, the interconnection area was encapsulated with polymers, and the effect of polymer materials and structures on the temperature-sensing properties was evaluated. The results show that traditional wrapping combined with hot pressing interconnection followed by tube encapsulating technology is beneficial for achieving high stretchability and good temperature-sensing performance of hybrid electronic yarn.

Long-term exposure to PM2.5 chemical constituents and diabesity: evidence from a multi-center cohort study in China.

Background: Long-term exposure to PM2.5 is known to increase the risks for diabetes and obesity, but its effects on their coexistence, termed diabesity, remain uncertain. This study aimed to investigate the associations of long-term exposure to PM2.5 and its chemical constituents with the risks for diabesity, diabetes, and obesity. Methods: This cross-sectional study used the baseline data of a multi-center cohort, consisting of three provincially representative cohorts comprising a total of 134,403 participants from the eastern (Fujian Province), central (Hubei Province), and western (Yunnan Province) regions of China. Obesity and diabetes, and diabesity were identified by a body mass index (BMI) ≥28 kg/m2 and fasting plasma glucose (FPG) ≥126 mg/dL. The average concentrations of PM2.5 and five chemical constituents (NO3 -, SO4 2-, NH4 +, organic matter, and black carbon) over participants' residence during the past three years were estimated using machine learning models. Logistic regression models with double robust estimators, Bayesian kernel machine regression, and weighted quantile sum regression were employed to estimate independent and joint effects of PM2.5 chemical constituents on the risks for diabesity, diabetes, and obesity, as well as the differences from the effects on obesity. Stratified analyses were performed to examine effect modification of sociodemographic and lifestyle factors. Findings: There were 129,244 participants with a mean age of 54.1 ± 13.8 years included in the study. Each interquartile range increase in PM2.5 concentration (8.53 µg/m3) was associated with an increased risk for diabesity (OR = 1.23 [1.17, 1.30]), diabetes only (OR = 1.16 [1.13, 1.19]), and obesity only (OR = 1.03 [1.00, 1.05]). Long-term exposure to each PM2.5 chemical constituent was associated with an increased risk for diabesity, where organic matter exposure, with maximum weight (48%), was associated with a higher risk for diabesity (OR = 1.21 [1.16, 1.27]). Among those with obesity, black carbon contributed most (68%) to the joint effect of PM2.5 chemical constituents on diabesity (OR = 1.16 [1.11, 1.22]). Physical activity reduced adverse effects of PM2.5 on diabesity. Also, additive rather than multiplicative effects of obesity on the PM2.5-diabetes association were observed. Interpretation: Long-term exposure to PM2.5 and its chemical constituents was associated with an increased risk for diabesity, stronger than associations for diabetes and obesity alone. The main constituents associated with diabesity and obesity were black carbon and organic matter. Funding: National Natural Science Foundation of China (42271433, 723B2017), National Key R&D Program of China (2023YFC3604702), Fundamental Research Funds for the Central Universities (2042023kfyq04, 2042024kf1024), the Science and Technology Major Project of Tibetan Autonomous Region of China (XZ202201ZD0001G), Science and technology project of Tibet Autonomous Region（XZ202303ZY0007G), Key R&D Project of Sichuan Province (2023YFS0251), Renmin Hospital of Wuhan University (JCRCYG-2022-003), Jiangxi Provincial 03 Special Foundation and 5G Program (20224ABC03A05), Wuhan University Specific Fund for Major School-level Internationalization Initiatives (WHU-GJZDZX-PT07).

Environmental determinants of childhood obesity: a meta-analysis.

BACKGROUND: The increasing prevalence of childhood obesity has contributed to the growing global burden of chronic diseases over the life course, which has been largely attributed to obesogenic environments. This giant-scale review was done to translate existing obesogenic environmental studies into evidence-based governance for fighting childhood obesity and promoting life-course health. METHODS: Following a standard strategy of literature search and inclusion, all obesogenic environmental studies, published since the inception of the electronic databases, were reviewed to identify the evidence on associations with childhood obesity of 16 obesogenic environmental factors, including 10 built environmental factors or indices (ie, land-use mix, street connectivity, residential density, speed limit, urban sprawl, and access to green space, public transport, bike lanes, sidewalks, and neighbourhood aesthetics) and six food environmental factors (ie, access to convenience stores, supermarkets, grocery stores, full-service restaurants, fast-food restaurants, and fruit and vegetable markets). A meta-analysis was conducted to quantify the influence of each factor with sufficient studies on childhood obesity. FINDINGS: A total of 24 155 search results were found and filtered, with 457 studies included in the analysis. All built environmental factors, except speed limit and urban sprawl, were negatively associated with childhood obesity by encouraging physical activity while discouraging sedentary behaviours; the access to all food venues, except convenience stores and fast-food restaurants, was negatively associated with childhood obesity by encouraging their healthy eating behaviours. There were some globally consistent associations, such as between greater access to fast-food restaurants in the neighbourhood and more fast-food consumption, between better access to bike lanes and more physical activity, between better access to sidewalks and reduced sedentary behaviours, and between greater access to green space and more physical activity and less TV or computer screen time. INTERPRETATION: Findings have formed the unprecedentedly inclusive evidence for policy making and the establishment of the future research agenda regarding the obesogenic environment. FUNDING: National Natural Science Foundation of China, Chengdu Technological Innovation R&D Project, Sichuan Provincial Key R&D Program, and Wuhan University Specific Fund for Major School-level Internationalization Initiatives.

Development and validation of an age-sex-ethnicity-specific metabolic syndrome score in the Chinese adults.

Metabolic syndrome (MetS) is characterized by metabolic dysfunctions and could predict future risk for cardiovascular diseases (CVDs). However, the traditionally defined dichotomous MetS neither reflected MetS severity nor considered demographic variations. Here we develop a continuous, age-sex-ethnicity-specific MetS score based on continuous measures of the five metabolic dysfunctions (waist circumference [WC], triglycerides [TG], high-density lipoprotein cholesterol [HDL-C], mean arterial pressure [MAP], and fasting blood glucose [FBG]). We find that the weights of metabolic dysfunctions in the score vary across age-sex-ethnicity-specific subgroups, with higher weights for TG, HDL-C, and WC. Each unit increase in the score is associated with increased risks for hyperlipidemia, diabetes, and hypertension, and elevated levels of HbA1c, cholesterol, body mass index, and serum uric acid. The score shows high sensitivity and accuracy for detecting CVD-related risk factors and is validated in different geographical regions. Our study would advance early identification of CVD risks and, more broadly, preventive medicine and sustainable development goals.

Global spreading of Omicron variant of COVID-19.

Although two years have passed since the coronavirus disease 2019 (COVID-19) outbreak, various variants are still rampant across the globe. The Omicron variant, in particular, is rapidly gained dominance through its ability to spread. In this study, we elucidated the spatial distribution pattern of Omicron from a global perspective. We used the cumulative number of notified COVID-19 cases per country spanning four weeks up to February 10, 2022, and the proportion of the Omicron variant genomic sequences from the Global Initiative on Sharing Avian Influenza Data (GISAID). The global spatial distribution of Omicron was investigated by analyzing Global & Local Moran's I and Getis- Ord General G. The spatial weight matrix was defined by combining K-Nearest neighbour and flight connectivity between countries. The results showed that the epidemic is relatively severe in Europe, countries with a high number of Omicron cases and incidence tended to be clustered spatially. In contrast, there are relatively fewer Omicron cases in Asia and Africa, with few hotspots identified. Furthermore, some noted spatial outliers, such as a lowvalue area surrounded by high-value areas, deserve special attention. This study has improved our awareness of the global distribution of Omicron. The findings can provide helpful information for deploying targeted epidemic preparedness for the subsequent COVID-19 variant and future epidemics.

Identification of two-dimensional copper signatures in human blood for bladder cancer with machine learning.

Currently, almost all available cancer biomarkers are based on concentrations of compounds, often suffering from low sensitivity, poor specificity, and false positive or negative results. The stable isotopic composition of elements provides a different dimension from the concentration and has been widely used as a tracer in geochemistry. In health research, stable isotopic analysis has also shown potential as a new diagnostic/prognostic tool, which is still in the nascent stage. Here we discovered that bladder cancer (BCa) could induce a significant variation in the ratio of natural copper isotopes (65Cu/63Cu) in the blood of patients relative to benign and healthy controls. Such inherent copper isotopic signatures permitted new insights into molecular mechanisms of copper imbalance underlying the carcinogenic process. More importantly, to enhance the diagnostic capability, a machine learning model was developed to classify BCa and non-BCa subjects based on two-dimensional copper signatures (copper isotopic composition and concentration in plasma and red blood cells) with a high sensitivity, high true negative rate, and low false positive rate. Our results demonstrated the promise of blood copper signatures combined with machine learning as a versatile tool for cancer research and potential clinical application.

New Approaches to Anticipate the Risk of Reverse Zoonosis.

The coronavirus disease 2019 (COVID-19) pandemic can cause reverse zoonoses (i.e., human-animal transmission of COVID-19). It is vital to utilize up-to-date methods to improve the control, management, and prevention of reverse zoonoses. Awareness of reverse zoonoses should be raised at both individual and regional/national levels for better protection of both humans and animals.

The direct and interactive impacts of hydrological factors on bacillary dysentery across different geographical regions in central China.

Previous studies found non-linear mutual interactions among hydrometeorological factors on diarrheal disease. However, the complex interactions of the hydrometeorological, topographical and human activity factors need to be further explored. This study aimed to reveal how hydrological and other factors jointly influence bacillary dysentery in different geographical regions. Using Anhui Province in China, consisted of Huaibei plain, Jianghuai hilly and Wannan mountainous regions, we integrated multi-source data (6 meteorological, 3 hydrological, 2 topographic, and 9 socioeconomic variables) to explore the direct and interactive relationship between hydrological factors (quick flow, baseflow and local recharge) and other factors by combining the ecosystem model InVEST with spatial statistical analysis. The results showed hydrological factors had significant impact powers (q = 0.444 (Huaibei plain) for local recharge, 0.412 (Jianghuai hilly region) and 0.891 (Wannan mountainous region) for quick flow, respectively) on bacillary dysentery in different regions, but lost powers at provincial level. Land use and soil properties have created significant interactions with hydrological factors across Anhui province. Particularly, percentage of farmland in Anhui province can influence quick flow across Jianghuai, Wannan regions and the whole province, and it also has significant interactions with the baseflow and local recharge across the plain as well as the whole province. Percentage of urban areas had interactions with baseflow and local recharge in Jianghuai and Wannan regions. Additionally, baseflow and local recharge could be interacted with meteorological factors (e.g. temperature and wind speed), while these interactions varied in different regions. In conclusion, it was evident that hydrological factors had significant impacts on bacillary dysentery, and also interacted significantly with meteorological and socioeconomic factors. This study applying ecosystem model and spatial analysis help reveal the complex and nonlinear transmission of bacillary dysentery in different geographical regions, supporting the development of precise public health interventions with consideration of hydrological factors.

Green space access in the neighbourhood and childhood obesity.

Access to green space may influence individual physical activity (PA) and subsequently weight status, as increased exposure to green space could improve health by increasing opportunities and the actual levels of PA. However, whether such associations hold empirically remains inconclusive. This study reviewed articles that analysed the association between access to green space and weight-related behaviours/outcomes among children, published before 1 January 2019. The sample sizes ranged from 108 to 44 278. Four cohorts and 17 cross-sectional studies conducted in nine countries were identified. Overall, evidence showed a positive association between access to green space and PA and a negative association between access to green space and television-watching time, body mass index (BMI) and weight status among children. Distance to the nearest green space, measured by geographic information system (GIS) in 10 studies, was often used to represent access to the nearest green space. It still remains difficult to draw a clear conclusion on the association between access to green space and BMI. Longitudinal studies can directly estimate the strength of the association between exposure and disease, which is needed to determine the causal association between access to green space and weight status.

Access to bike lanes and childhood obesity: A systematic review and meta-analysis.

The lack of bike lane access has been a proven risk factor for childhood obesity due to its role in discouraging healthy lifestyles. However, there has not been a systematic review of this important association in the existing literature. This study aims to fill this gap. A literature search was conducted in the Cochrane Library, PubMed, Embase, and Web of Science for studies published from 1 January 2019 onwards that examined the association between bike lane access and weight-related behaviours and outcomes among children aged <18 years. A total of 21 studies were included in this systematic review. Among them, most of the studies showed that bike lane access was significantly associated with children and adolescents' physical activity (PA), whereas only two studies showed a negative association. Meta-analysis also supported these findings and showed that bike lane access was significantly associated with children and adolescents' PA (odds ratio [OR] = 1.57, 95% confidence interval [CI]: 1.37-1.81). Additionally, we reviewed how bike lane characteristics and microenvironment variables such as children and adolescents' choice of bicycle travel mode, the degree of separation of cycle path, cycle path unevenness, and street maintenance were associated with adolescents' preferences and intention to cycle. This systematic review and meta-analysis strongly suggests that bike lane access is associated with children and adolescents' PA. Nonetheless, it was difficult to draw a conclusion on the association between bike lane access and weight-related outcomes.

Natural environment and childhood obesity: A systematic review.

The associations between built and food environments and childhood obesity have been studied extensively. However, the association between the natural environment and childhood obesity has received too little scholarly attention. This study reviewed the literature published before 1 January 2019, which described associations between a full range of natural environmental factors (e.g., rainfall, temperature, sunlight, natural disasters, flood and drought) and weight-related behaviours and childhood obesity. Five cross-sectional studies and one longitudinal study were identified. Measures of natural environmental factors varied across six included studies, falling into five broad categories: weather conditions, altitude, natural disaster risk, air quality and day length. It was found that temperature was a significant weather indicator in most included studies and was associated with a reduction of daily physical activity. Children living in high-altitude areas were more likely to be shorter and heavier than their counterparts in low-altitude areas. Findings of this study will contribute to helping multiple stakeholders, including policy makers and urban planners, and formulate health policies and interventions to mitigate the detrimental impact of the natural environment on childhood obesity. More longitudinal studies should be designed to confirm these effects and explore the potential health effects of more natural environmental factors.

Neighbourhood speed limit and childhood obesity.

As an important factor for neighbourhood walkability, the speed limit in the neighbourhood may influence children's physical activity (PA) outdoors, especially active transport, and further their weight status. This review aimed to systematically evaluate the association between neighbourhood speed limit and obesity-related behaviours and outcomes among children and adolescents. PubMed, Embase and Web of Science were systematically searched for relevant studies published from the inception of the database to 1 January 2019. Sixteen studies were included, with 13 cross-sectional studies and three longitudinal studies. Speed limit was measured as the percentage/number of high-speed roads, perception of safe driving speed, perception of speeding and use of traffic-calming tools in the neighbourhood. Eleven studies measured the use of active transport as the outcome of interest, and seven studies measured PA directly. Eleven studies revealed an association between a lower speed limit and increased PA, whereas one study showed a negative association, and three studies reported non-significant associations. Only one study associated speed limit with weight status, which reported a non-significant association. This review generally supported a negative association between speed limit and PA among children and adolescents. More studies are needed to examine their causality, as well as the association between speed limit and weight status, in order to increase the impact of this research area on public health policy making.

A spatial database of CO2 emissions, urban form fragmentation and city-scale effect related impact factors for the low carbon urban system in Jinjiang city, China.

This paper presented the spatial database collected in 2013 for mitigating the urban carbon emissions of Jinjiang city, China. The database included the high-resolution CO2 emissions gridded maps, urban form fragmentation evaluation maps, and city-scale effect related impact factors distribution maps at 30 m and 500 m. We collected the multi-sources data including statistical, vector, and raster data from open-access websites and local governments. We used a general hybrid approach based on global downscaled and bottom-up elements to produce the CO2 emissions gridded maps. The urban fragmentation was measured by the landscape fragmentation metrics under the feature scale and the accurate identification of the urban functional districts. The percentage of the urban area and the points of interest (POI) density representing the city-scale effect related impact factors were calculated in each grid by the land use and POI data. Our database could be used for the validation of urban CO2 emissions estimation at the city scale. The landscape metrics and city-scale effect related impact factors maps can also be used for evaluating the socio-economic status in order to solve the other urban spatial planning problems.

Analysis of Heavy Metal Sources in the Soil of Riverbanks Across an Urbanization Gradient.

Regional soil quality issues arising from rapid urbanization have received extensive attention. The riverbank that runs through a city is representative of urbanization gradient transformation. Thirty soil samples in the Yangtze River Delta urban agglomeration were collected and analyzed for the concentrations of seven analytes. Correlation, principle component analysis, cluster analysis and GeoDetector models suggested that the four groups (Cr-Ni-Cu, Cu-Zn-As-Sb, Cd and Pb) shared the same sources in the core urban region; five groups (Cr-Ni-Cu-Zn, As, Cd, Sb and Pb) in the suburbs and three groups (Cr-Ni, Cu-Zn-Cd-Sb-Pb and As) in the exurbs. GeoDetector methods not only validated the results of the three other methods, but also provided more possible impact factors. Besides the direct influences, the interaction effects among factors were quantified. Interactive combination with strong nonlinear increment changed from between-two-weak factors in the central region to between-strong-and-weak factors in the suburbs. In the exurbs, the stronger interaction effects were observed between strong and weak factors. Therefore, the GeoDetector model, which provided more detailed information of artificial sources could be used as a tool for identifying the potential factors of toxic elements and offering scientific basis for the development of subsequent pollution reduction strategies.