Relationship between Sn elemental background values and regional longevity levels—Data from Yunnan, China

The relationship between geographical environments and human health has been a long-standing focus of scientific inquiry. Magnesium (Mg) and silicon (Si), as essential elements for the human body, play vital roles in individual health and may influence longevity. However, the extent to which the statistical characteristics of population longevity are associated with geochemical background values at a regional scale remains an important question. This study examines Yunnan, China, a region with diverse and complex geographical conditions, and used global autocorrelation analysis, cluster and outlier analysis, and hotspot analysis to comprehensively analyze the Spatial Distribution Characteristics of magnesium oxide (MgO) and silicon dioxide (SiO₂) background values. It further investigates the individual and synergistic relationships of these geochemical factors with population longevity at the county scale in Yunnan using the Spearman rank correlation. The results demonstrate that the MgO background value (ω(MgO)) exhibits a significant positive correlation with the Ultra-octogenarian Index and has a positive synergistic effect on regional longevity levels. In contrast, the SiO₂ background value (ω(SiO₂)) shows a significant negative correlation with both the longevity index and the Ultra-octogenarian Index, while the ratio of Si to Mg (ω(Si/Mg)) is also significantly negatively correlated with the Ultra-octogenarian Index. These findings suggest that MgO-enriched natural environments may positively contribute to regional population longevity, while excessively high SiO₂ background values may have a detrimental effect. This study offers a novel perspective on the relationship between regional longevity levels and natural geographical environments, which may inform the selection and sustainable development of longevity-oriented tourism destinations.

Relationship between lifespan indicators and elemental background values: A case study in Guangdong Province, China

A novel natural environment background model for Monte Carlo simulation and its application in the simulation of anticoincidence measurement

The identification of poverty at the county level is the precondition for poverty alleviation by formulating accurate strategies that are targeted for a certain area. Yunnan Province has the largest number of poverty counties in China. The vast number of people living under the poverty-line, and the deep degree of poverty across a wide distribution range, pose major challenges. Based on the rural poverty incidence data, this paper describes the rural poverty patterns in Yunnan Province in 2010 and 2015, and then it explores the main factors which influence the incidence and changes in rural poverty at the county level in Yunnan Province using a stepwise regression analysis method. This study found that the rural poverty in counties of Yunnan Province was deeply affected by natural conditions and the geographical environment. In 2010 and 2015, the rural poverty situation in the middle region of Yunnan Province was relatively light, while it was more serious in the northwest, northeast and south regions. The pattern of county poverty is in good agreement with the topography and landforms of Yunnan Province and the poverty-stricken areas. There are strong correlations between the incidence of rural poverty in Yunnan Province with both the annual per capita net income of rural residents and the degree of agricultural mechanization. These factors are related to the living standards and agricultural production necessary for the peasantry to sustain their livelihood. The change in the incidence of rural poverty at the county level in Yunnan Province from 2010 to 2015 is significantly correlated with changes in the value-added of the primary industries and the degree of agricultural mechanization. These correlations indicate that the development of primary industry plays a key role in the process of lifting rural residents in Yunnan Province out of poverty so they can achieve prosperity. Therefore, improving the annual per capita net income of rural residents and the degree of agricultural mechanization for rural areas in Yunnan Province are still the main points for focused efforts. In the current phase of poverty alleviation, Yunnan Province should emphasize increasing rural residents' income and agricultural production and management in order to formulate effective policies and measures for poverty alleviation.

Estimating wheat grain yield by assimilating phenology and LAI with the WheatGrow model based on theoretical uncertainty of remotely sensed observation

Quantifying the effectiveness of ecological restoration projects on long-term vegetation dynamics in the karst regions of Southwest China

Despite a number of longevity indicators having been used in previous longevity studies, few studies have critically evaluated whether these indicators are suitable to assess the regional longevity level. In addition, an increasing number of studies have attempted to determine the influence of socioeconomic and natural factors on regional longevity, but only certain factors were considered. This study aims to bridge this gap by determining the relationship between the 7 longevity indicators and selecting 24 natural and socioeconomic indicators in 109 selected counties and urban districts in Guangxi, China. This study has applied spatial analysis and geographically weighted regression as the main research methods. The seven longevity indicators here refer to centenarian ratio, longevity index, longevity level, aging tendency, 80+ ratio, 90+ ratio, and 95+ ratio. Natural indicators in this study mainly refer to atmospheric pressure, temperature, difference in temperature, humidity, rainfall, radiation, water vapor, and altitude. Socioeconomic indicators can be categorized into those related to economic status, education, local infrastructure, and health care facilities. The results show that natural factors such as the difference in temperature and altitude, along with socioeconomic factors such as GDP, might be the most significant contributors to the longevity of people aged 60–90 years in Guangxi. The longevity index and longevity level are useful supplementary indexes to the centenarian ratio for assessing the regional longevity.

Through the efforts of the 13th Five Year Plan, the health level of the Chinese people has continuously improved. Guided by policies such as the 14th Five Year Plan and Healthy China 2030, China's major health industry has flourished. While paying increasing attention to health issues, China also emphasizes the improvement of its living environment and adheres to the path of sustainable development. Yunnan Province has made outstanding achievements in the construction of the big health industry due to its geographical environment and other advantages, and the green transformation and upgrading of the big health industry in Yunnan Province has also played a leading role. In this context, this article studies the background and methods of the green transformation of the big health industry in Yunnan Province, China. By studying the necessity of the big health industry in Yunnan Province, it summarizes the current situation of the big health industry in Yunnan Province, analyzes the obstacles to its green transformation, and summarizes the successful ideas for the green transformation of the big health industry in Yunnan Province, providing reference for the transformation and upgrading of other enterprises.

Ecological science focuses on the structure and function of the natural environment. However, the study of ecological environments primarily focuses on single-element research and lacks a comprehensive perspective. To examine ecological environmental trends on different scales, the present paper selected Yunnan Province as the study area. Chemical oxygen demand, rocky desertification, forest coverage, natural disaster data and spatial analysis methods were used to obtain the ecological environmental characteristics of each county and construct a comprehensive evaluation method of the ecological environment. The present paper revealed that the environmental capacity in Yunnan Province was at a moderate level, the ecological environment fragility was remarkable, the significance of the ecological environment was very high, natural disasters occurred frequently, and spatial differentiation between ecological environments was obvious. The province may be divided into three functional areas: the comprehensive-balanced area, the efficiency-dominated area and the environment-dominated area. Central Yunnan was a key development zone and the main area for the manufacturing and service industries, which were built as a modern industrial system in Yunnan Province. The ecological environment in northwestern Yunnan and southern Yunnan is of high significance, and this region was an ecological environment protection area that was important area for the construction of the modern agricultural system in Yunnan Province. To achieve sustainable development of the ecological environment, the spatial characteristics of the ecological environment must be determined at the county scale.

We aim to analyze the temporal and spatial distribution characteristics of new cases of leprosy in Yunnan province during 2011 to 2016, and provide the basis for the prevention and control of regional leprosy. Based on the statistical data of new cases of leprosy in Yunnan province, which was provided by the center for disease control and prevention of Yunnan province, the temporal and spatial distribution characteristics of new cases were analyzed by the methods of exploratory data analysis and GIS spatial analysis. On the spatial scale of autonomous prefecture or prefectural-Level city, new cases are mainly concentrated in Wenshan, Honghe, Kunming and Pu-er. On the county scale, the distribution of new cases shows the characteristics of the small number of cases but widely distributed and the counties with a large number of cases are spatially adjacent. And on the time scale, the number of new cases showed a downward trend. During 2011 to 2016, the temporal and spatial distribution characteristics of new cases of leprosy in Yunnan province are typical, and targeted measures should be taken in the follow-up prevention and control.

Previous studies have reported that centenarians escape the major agerelated diseases. No studies on prevalence and severity of osteoarthritis (OA) in longevity population have previously been reported. Because OA is associated with morbidity and mortality, we hypothesized that radiographic hand OA would generally be less prevalent and would develop at a later age in longevity populations vs non-longevity populations. Aim was to evaluate the prevalence and mode of development of radiographic hand OA in three longevity populations (Abkhazians, Azerbaijanis and Georgians) and in one non-longevity population (Russians). Crosssectional observational study. Longevity index was calculated as a ratio of the number of individuals aged >90 years vs the number of people aged >60, expressed per mil (‰). A population with longevity index >40‰was considered as a longevity population. Radiographic hand OA was evaluated using the left hand radiograms in 14 joints according to Kellgren and Lawrence's (K-L) grading system. Each individual was characterized by the total number of affected (K-L≥2) joints (NAJ). Prevalence of hand OA was defined as the presence of at least one affected joint. Statistical analyses included prevalence estimation, linear, logistic and polynomial regressions, and ANOVA. A significant difference (p<0.003) in age standardized prevalence of hand OA was found between each pair of studied samples, except between Russians and Georgians and between Azerbaijanis and Abkhazians (p>0.05). The lowest age-standardized prevalence was found in Abkhazians, followed by Azerbaijanis and Georgians. The highest prevalence was found in Russians. ANOVA showed significant differences (p<0.01) between the age-adjusted means of NAJs. The lowest age-adjusted NAJ was found in the Abkhazian population, followed by Azerbaijanis and Georgians. The highest NAJ was found in Russians. We observed that the pattern of radiographic hand OA in longevity populations differs from the pattern in non-longevity populations. On average, first joints with OA appear at an older age, and progression of hand OA, measured by NAJ, is slower.

Karst rocky desertification is a major ecologic and geologic problem in Southwest China that has restricted the sustainable development of society and the economy. Many methods have been used to evaluate rocky desertification based on satellite remote sensing, but the results of these methods are affected by the heterogeneous surroundings of the karst region and the low resolution of sensors. In this study, a new method that combines satellite images and unmanned aerial vehicle (UAV) images was used to quantitatively extract information and evaluate rocky desertification. First, we extracted the bare rock ratio from the local high‐resolution UAV images, and then the regression models were established between the bare rock ratio of UAV images and the band reflectivity and eight rock indices of satellite images to invert the bare rock ratio at the county scale. The results showed that the overall accuracy and F1 of the classification of UAV images was 97% and 90%, respectively. The linear regression model between the reflectivity of the pixels in band 2 of the LANDSAT image and the bare rock ratio extracted from the UAV images was the best (R2 = 0.86). In addition, our method in which rocky desertification was assessed by the inversion model based on UAV images and LANDSAT images was superior to the traditional approach based on vegetation coverage. These results suggested that we can extract information on rocky desertification based on high‐resolution UAV images and assess rocky desertification by the inversion model from the local to regional scale.

WOFOST (world food study) model had been successfully used in daily business of agro meteorological monitoring and yield forecasting in European Union, and also been widely used in crop growth process simulation and yield estimation all over the world. In this study, with the help of the rice growth observed data, the meteorological data at the same time and the rice planting regional planning data in Heilongjiang Province, the crop parameters for WOFOST model were improved. Based on the localization and regionalization of the model, the rice yield in county and region scale in Heilongjiang Province was simulated. In province scale, the WOFOST simulated yield was good, and the relative error between estimated yield and statistical yield from 2006 to 2013 were respectively 2.71%, 8.47%, 6.41%, –15.96%, 3.95%, 0.02%, –7.06%, 0.88%, four of which beyond ±5%. But in county scale, the correlation between WOFOST simulated and statistical yield was poor, and not passing the test of significance. In order to improve the precision, the trend yield calculated by the statistical yield and the WOFOST simulated yield were both used to build a comprehensive rice yield simulation model by the multiple linear regression method year by year from 2006 to 2013. Then the rice yield both in county and province scale in Heilongjiang Province was calculated by using the comprehensive model. In county scale, the comprehensive simulated yield and the statistical yield in county scale passed significant test of 0.01, and the correlation coefficients were respectively 0.715, 0.728, 0.829, 0.810, 0.888, 0.919, 0.868, 0.798, the R2 were respectively 0.511, 0.529, 0.686, 0.656, 0.789, 0.844, 0.753, 0.636. In province scale, the relative error between the estimated yield and statistical yield during 2006–2013 were respectively –1.72%, 2.12%, 3.02%, –2.45%, 1.27%, –0.89%, –0.38%, 1.96%. The comprehensive model had a good effect on improving the defects of fluctuation in individual year with a relative higher accuracy than that of only using WOFOST model, and could satisfy the application of rice yield estimation in large region.

Aging, as a global demographic issue, is characterized by its rapid growth, which drives an increase in people's healthcare awareness. The emergence of wellness bases caters to this market demand. Therefore, the identification of potential areas suitable for wellness activities and the construction of wellness bases, referred to as Wellness Target Areas (WTAs), becomes a crucial first step. Currently, commonly used identification methods are mostly based on traditional statistical approaches, which are often complex, cumbersome, and subject to potential risks of subjective assumptions, affecting the reliability of WTAs identification results. Longevity level serves as a comprehensive indicator reflecting the natural and socio-economic environment of a region, making it the most indicative of the regional wellness environment status. This study proposes using longevity level as the benchmark for WTAs identification to simplify the identification process and reduce the impact of subjective bias on the results. The study focuses on 129 county-level units in Yunnan Province. Firstly, the Geodetector (GD) is utilized to explore the complex interaction between the longevity level and the geographical environment to determine regional wellness factors. Secondly, using ArcGIS and geographical weighted regression (GWR), the study investigates the role of different wellness factors, ultimately classifying and grading the WTAs. The longevity level in Yunnan Province exhibits a pattern of multi-point clustering, forming three major longevity regions. Factors that significantly influence longevity level include annual average precipitation, sunshine duration, PM2.5 content, per capita disposable income, density of tourist attractions, and distance from residential areas to hospitals. Based on the degree of longevity and the contribution rate of influencing factors, Yunnan Province's WTAs are classified into three levels and two types (natural and comprehensive). Our study aims to establish a connection between longevity level and the selection of wellness bases, exploring regional wellness factors through the relationship between longevity phenomena and geographical environment, identifying potential construction areas for wellness bases (i.e., WTAs), providing new insights for the precise selection of wellness bases, effectively enhancing the scientificity of site selection, promoting population health, and contributing to the global aging process with better health.

The process of eliminating absolute poverty is inevitable for China’s social and economic transformation. However, there are currently few studies on the relationship between land use transformation (LUT) and rural income under different stages of poverty governance. This study, therefore, uses spatial autocorrelation analysis and a multiscale geographic weighted regression (MGWR) model to explore the mechanisms of LUT on rural income and its spatiotemporal heterogeneity in Yunnan Province during the comprehensive poverty alleviation (CPA) period and the targeted poverty alleviation (TPA) period at the county scale. The results demonstrate that: (1) the numbers of both low-income and high-income counties continued to decrease, while the number of middle-high-income counties increased, and rural income demonstrated a positive spatial correlation. (2) Most of the variables in the dominant recessive increased in the CPA and decreased in the TPA period. As for recessive morphology, the ecological function variables decreased first and then increased. (3) The driving force of dominant morphology is strong and sustained, and the driving force of recessive morphology is gradually enhanced. The results are vital for consolidating the results of poverty eradication and bridging rural revitalization. They may also provide useful references for sustainable land use and effective poverty alleviation in other developing countries.