Research on the spatial patterns and evolution trends of the coupling coordination between digital finance and sustainable economic development in the Yellow River Basin, China.

In the current global context, digital finance (DF) and sustainable economic development (SED) are important topics. The synergies between DF and SED have already been proven. However, the measurement and quantitative analysis of the coupling coordination degree (CCD) of DF and SED have not received sufficient attention to date. Based on data from 55 cities in the Yellow River Basin (YRB) from 2011 to 2021, this study constructs an evaluation index system of DF and SED and measures their level, respectively. The proposed CCD model is then used to measure the CCD between the two systems. In addition, kernel density estimation, Markov chain, σ-convergence, ß-convergence, and the quadratic assignment procedure (QAP) method are used to study the spatial pattern, distribution dynamic evolution trend, convergence, and influencing factors of the regional differences in the CCD. The results show that: (1) From 2011 to 2021, the CCD level showed a stable upward trend and regional heterogeneity, and the time stage characteristics were more obvious. (2) The center position and change interval of the overall distribution curve of the kernel density estimation gradually shifted to the right. The Markov transfer probability matrix shows that the CCD is more stable among different levels, indicating a phenomenon of "club convergence". (3) A convergence analysis shows that there are significant σ-convergence, absolute ß-convergence, and conditional ß-convergence. (4) The QAP regression shows that factors such as the regional differences in GDP per capita have a significant impact on the regional differences in the CCD. This study offers a comprehensive structure that can be used to examine the synergistic effects between DF and SED; the research findings can also provide perspectives for other areas.

Exploring "Equigenesis" in the Associations Between Green Space and Kidney Health Among Middle-Aged and Older Adults Using Street View Data.

Background and Objectives: This study systematically explores the association between community green space and preventing kidney failure among middle-aged and older adults in China, using street view data. Research Design and Methods: The 33 Chinese Community Health Study was used to conduct the analysis. We used street view data to assess street view green space (SVG) exposure and clearly distinguished the difference between grass (SVG-grass) and trees (SVG-tree). The normalized difference vegetation index (NDVI) was also used. Kidney failure was defined as a serum creatinine concentration of above 177 mol/L. We used multilevel logistic regression models (controlled for a series of covariates) to examine the associations between SVG and the odds of middle-aged and older adults having kidney failure. We also tested whether middle-aged and older adults from socioeconomically disadvantaged groups are likely to derive greater benefits from the effects of green space ("equigenesis"). Results: The results showed that both SVG (OR = 0.353; 95% CI = 0.171-0.731) and SVG-trees (OR = 0.327; 95% CI = 0.146-0.736) were negatively associated with the likelihood of middle-aged and older adults experiencing kidney failure, but there was no significant evidence of any links between either SVG-grass (OR = 0.567; 95% CI = 0.300-1.076) or the NDVI (OR = 0.398; 95% CI = 0.237-1.058) and kidney failure. Furthermore, the moderation analysis indicated that income and educational attainment have a moderating effect on the association between green space and the improvement of kidney health, which suggests that green space has greater positive effects on the kidney health of disadvantaged groups. Discussion and Implications: To reduce inequalities in relation to kidney disease through urban planning, policymakers are advised to provide more visual green space-especially trees-within the community and to focus in particular on socioeconomically disadvantaged population groups.

Assessment of agricultural pesticide inert ingredient transport following modeling approach: Case study of two formulation agents in Sacramento River watershed.

This research provides the first assessment of the environmental fate and transport of agricultural pesticide formulation agents following a dynamic modeling approach. Two formulation agents of toxicological concern, Naphthalene and Solvent Naphtha (Petroleum), Heavy Aromatic, were simulated from their usage in commercially-applied pesticides. The Soil and Water Assessment Tool (SWAT) was applied to simulate these formulation agents during 2011-2014 in the agriculturally intensive Sacramento River watershed. The sensitivity and uncertainty of some key parameters were analyzed. The predicted transport masses of these formulation agents in surface water were strongly associated with rainfall. While predicted transport masses were quite small at the watershed scale (<0.01% of applied masses), they were 26-31 times higher in certain locales at the subbasin level. Since many formulation agents are widely used in pesticides throughout this and other agriculturally impacted watersheds, their potential risks in the environment need more thorough investigation by modeling and monitoring, especially for areas with heavy usage.

Sarcopenia and catastrophic health expenditure by socio-economic groups in China: an analysis of household-based panel data.

BACKGROUND: Sarcopenia was thought to be associated with adverse outcomes and will cause lots of health expenditure. But the relationship between sarcopenia and catastrophic health expenditure (CHE) had been little explored. Here, we examined the distribution of sarcopenia in relation to medical and payment burdens. METHODS: We used data from three waves of China Health and Retirement Longitudinal Study including 14 130 participants from 9077 households aged over 50 years old. Sarcopenia was operationalized according to the Asian Working Group for Sarcopenia 2019. Medical expenditure was obtained by self-reported data, and CHE was identified by WHO definitions. We used the negative binomial regression model and logistic mixed-effects models to examine the associations between sarcopenia and medical and CHE. RESULTS: A total of 14 130 participants [52.2% female, aged 60.8 (SD 9.3)] from 9077 households were included in this study. The prevalence of sarcopenia was 19.8%, 11.9% for moderate sarcopenia, and 7.9% for severe sarcopenia, respectively. We identified 1416 household CHE events in all three waves. Severe sarcopenia was associated with an increase in the number of inpatient visits [incidence rate ratio 1.31, 95% confidence interval (CI): 1.03-1.66, P = 0.03] and the risk of CHE (odds ratio: 1.04, 95% CI: 1.01-1.07, P < 0.01). We saw similar effects in health service use of sarcopenia in different socio-economic groups. Moderate sarcopenia increased the risk of CHE in the lowest socio-economic group (odds ratio 1.03, 95% CI: 1.01-1.06, P = 0.03) and had no statistical significance in other groups. The association between severe sarcopenia and CHE did not attenuate after the adjustment of disease factors. CONCLUSIONS: Severe sarcopenia may increase the risk of CHE. Timely and effective intervention on moderate sarcopenia from severe sarcopenia will contribute to reduce the health burden.

Mapping the geodemographics of racial, economic, health, and COVID-19 deaths inequalities in the conterminous US.

A large number of studies have examined individual-level factors that increase COVID-19 fatalities. However, no research has focused on the geodemographic classification of the most susceptible communities to COVID-19. In this cross-sectional ecological study, we used local fuzzy geographically-weighted clustering to create the socioeconomic profile of the US counties in relation to COVID-19 death rates. We demonstrate that living in a county which has households with lower income, people with a lack of health insurance, a high African-American percentage, and lower education level, lead to 27.12% higher COVID-19 death rates than the national median, and 72.56% higher compared to the least vulnerable counties. Compared to counties with a high COVID-19 death rate, counties with a low COVID-19 death rate have 44.90% higher annual median household income and nearly double house worth (89.51% more). Results show that the effects of the COVID-19 pandemic are not universal and that the minoritised and impoverished populations suffer more. Our analysis can effectively pinpoint the most vulnerable counties and importantly allows for understanding the socioeconomic context in which tailored interventions can be applied to mitigate COVID-19 deaths.

Assessment of pyrethroid contamination and potential mitigation strategies in California Central Coast surface waters.

Increased use of pyrethroids in the Central Coast of California since 2011 has resulted in a dramatic increase in the number and proportion of surface water samples with detectable concentrations at levels of concern to the public and state regulators. The goals of this study were to investigate the relationships between pyrethroid usage and environmental contamination, quantify and assess the potential risks, and recommend mitigation strategies. This study compiled the available pyrethroid use and surface water sampling data for the region, and then applied GIS methods to dynamic simulation modeling and usage-restriction buffer analyses. The results showed that in Monterey County alone, the agricultural usages of bifenthrin and permethrin each increased by ~50%, and the positive detection frequencies of both also increased around 2011-2013. County-wide, bifenthrin positive detections in surface water samples increased precipitously from 8.2% (7/85) for 2008-2012 up to 36.4% (106/291) for 2013-2017, and detections above its crustacean LC50 concentration went from 7.1% (6/85) to 35.7% (104/291). Despite its higher usage by mass, comparable figures for permethrin were more modest for the same time-periods, with positive detections going from 10.6% (9/85) to 14.4% (64/444), and detections above its crustacean LC50 going from 3.5% (3/85) to 7.2% (32/444). The seasonal lag between high bifenthrin usage in spring/summer and high detections in fall/winter samples showed the best correlations with 128- to 182-day lag times. This timing suggests that fallow season rain is likely the main driver of pyrethroid off-site movement into surface waters. SWAT modeling indicated that significant reductions in surface water permethrin concentrations only occurred with buffer distances of 1.6-3.2 km, but not with narrower buffers. However, if those wider buffers were implemented, permethrin could no longer be used on the majority of land where it is currently applied. Specifically, a 1.6-km buffer reduced the instream concentration by 8% but impacted 50% of the cropland, and a 3.2-km buffer reduced the concentration by 50% while impacting 76% of cropland. This study suggested that more promising alternative management practices could include an overall reduction in pyrethroid usage back to 2011 levels or other active mitigation strategies, like planting cover crops during the fallow winter wet season, or installing either vegetated buffer strips and/or sediment check dams on small tributaries to minimize sediment runoff.

A SWAT-based optimization tool for obtaining cost-effective strategies for agricultural conservation practice implementation at watershed scales.

To address the harmful algal blooms problem in Lake Erie, one solution is to determine the most cost-effective strategies for implementing agricultural best management practices (BMPs) in the Maumee River watershed. An optimization tool, which combines multi-objective optimization algorithms, SWAT (Soil and Water Assessment Tool), and a computational efficient framework, was created to optimally identify agricultural BMPs at watershed scales. The optimization tool was demonstrated in the Matson Ditch watershed, an agricultural watershed in the Maumee River basin considering critical areas (25% of the watershed with the greatest pollutant loadings per area) and the entire watershed. The initial implementation of BMPs with low expenditures greatly reduced pollutant loadings; beyond certain levels of pollutant reductions, additional expenditures resulted in less significant reductions in pollutant loadings. Compared to optimization for the entire watershed, optimization in critical areas can greatly reduce computational time and obtain similar optimization results for initial reductions in pollutant loadings, which were 10% for Dissolved Reactive Phosphorus (DRP) and 38% for Total Phosphorus (TP); however, for greater reductions in pollutant loadings, critical area optimization was less cost-effective. With the target of simultaneously reducing March-July DRP/TP losses by 40%, the optimized scenario that reduced DRP losses by 40% was found to reduce 51.1% of TP; however, the optimized scenario that reduced TP losses by 40% can only decrease 11.3% of DRP. The optimization tool can help stakeholders identify optimal types, quantities, and spatial locations of BMPs that can maximize reductions in pollutant loadings with the lowest BMP costs.

Exploring the association between urbanisation and self-rated health of older adults in China: evidence from a national population sample survey.

OBJECTIVES: This study investigated the association between urbanisation and self-rated health of older adults in China, particularly how different dimensions, rate and level of urbanisation are related to older people's health. Additionally, it examined the moderating effect of education on the association between each of the four dimensions of urbanisation and older people's health. DESIGN: The study uses a cross-sectional survey design. PARTICIPANTS: This study analysed 236 030 individuals (aged 60-79 years) nested within 267 prefecture-level cities from 2005 China's 1% population sample survey. OUTCOME MEASURES: Self-rated health was the outcome variable. Four groups of predictors assessed prefectures' level and rate of urbanisation: land-use conversion, economic growth, population concentration and health services. Multilevel logistic regression was used to examine the association between self-rated health and the level and rate of urbanisation, after adjusting for individual-level covariates. Multiplicative interactions explored variations by education. RESULTS: The odd of reporting fair or poor health was negatively associated with the level and rate of population concentration (OR 0.93,95%CI 0.87 to 0.99 and 0.74,95%CI 0.59 to 0.93, respectively) and positively associated with the level of health services (OR 1.12, 95% CI 1.06 to 1.19). Land-use conversion, economic growth and health service improvements (the forms of rate of urbanisation) were not significantly associated with self-rated health. Education had a moderating effect on the association between urbanisation and self-rated health. CONCLUSIONS: Older people living in more densely populated areas and areas undergoing rapid population concentration were less likely to report fair or poor health. This result supports healthy migration and 'salmon bias' hypotheses. No urban health penalty was observed for the older adults in China; therefore, the following pathways linking urbanisation to health are unclear: lifestyle changes, environmental pollution and cultivated land reduction.

Environmental fate and impact assessment of thiobencarb application in California rice fields using RICEWQ.

Thiobencarb is a commonly used herbicide in Northern California rice fields. Released paddy water containing thiobencarb may pose ecological risks to non-targeted organisms. In this research, the Rice Water Quality Model (RICEWQ) is equilibrium tested and then calibrated using monitoring data at field level. Then it is employed to assess the environmental fate and impacts of thiobencarb in the Colusa Basin, and the effects of different management practices on water use and thiobencarb exposures. The model predicted thiobencarb concentrations from rice fields for multiple years throughout the Basin, using input from California Pesticide Use Reporting (PUR) database, and assessed both the temporal/spatial distribution of thiobencarb exposure and potential acute toxicity on non-target organisms. Our study indicated that RICEWQ can accurately reflect the initial partitioning of thiobencarb in both paddy water and soil phases and capture the dynamics of thiobencarb at field level after calibration. Mandatory water holding is critical for reducing thiobencarb exposure in released paddy water. A thirty-day holding time reduces thiobencarb concentrations by 64% relative to a 6-day holding practice. The geo-spatial pattern of exposure in the study domain indicates the differing extents of pollutant levels and their distribution over space. "Risk zones" for different species were identified based on the geospatial patterns of thiobencarb exposure and the species-specific susceptibilities of various non-target species to thiobencarb.

Development of an immunochromatographic strip test for rapid detection of lily symptomless virus.

A rapid immunochromatographic strip (ICS) test for specific detection of lily symptomless virus (LSV) was developed. The test is based on a double-antibody sandwich format and employs two distinct anti-LSV polyclonal antibodies (IgG1 and IgG2). The first antibody, IgG1 was used as the detection antibody conjugated to colloidal gold and the second antibody, IgG2 was used to as the capture antibody at the test line. The performance of the ICS test was evaluated and the results obtained were compared with a quadruplex RT-PCR assay. When serial dilutions of purified LSV were tested, the LSV detection limit of the ICS test was 6.0 × 10(-8)mg/mL, which was the same as the quadruplex RT-PCR assay. Relative to quadruplex RT-PCR, the specificity and sensitivity of the ICS were 98.6% and 100%, respectively for field leaf samples. There was significant agreement between the results of the ICS and quadruplex RT-PCR tests (κ = 0.983). Compared with conventional lily virus detection methods, our ICS test has many advantages: simple, fast, low cost, high sensitivity and specificity, and has applications in the laboratory and in the field to detect and control LSV.