Quantitatively evaluate the environmental impact factors of the life expectancy in Tibet, China

Exploring the Association between Oxygen Concentration and Life Expectancy in China: A Quantitative Analysis

The aim of this study was to investigate and quantify the association between oxygen concentration and life expectancy. The data from 34 provinces and 39 municipalities were included in all analyses. Bayesian regression modeling with spatial-specific random effects was used to quantify the impact of oxygen concentration (measured as partial pressure of oxygen) on life expectancy, adjusting for other potential confounding factors. We used hierarchical cluster analysis to group the provinces according to disease burden and analyzed the oxygen levels and the characteristics of causes of death between the clusters. The Bayesian regression analysis showed that the life expectancy at the provincial level increased by 0.15 (95% CI: 0.10-0.19) years, while at the municipal level, it increased by 0.17 (95% CI: 0.12-0.22) years, with each additional unit (mmHg) of oxygen concentration, after controlling for potential confounding factors. Three clusters were identified in the hierarchical cluster analysis, which were characterized by different oxygen concentrations, and the years of life lost from causes potentially related to hypoxia were statistically significantly different between the clusters. A positive correlation was found between oxygen concentration and life expectancy in China. The differences in causes of death and oxygen levels in the provincial clusters suggested that oxygen concentration may be an important factor in life expectancy when mediated by diseases that are potentially related to hypoxia.

Study on ecological adaptability construction characteristics of residential buildings in Kangba area, Tibet, China

Located in the southwest of the Qinghai-Tibet Plateau, Tibet is characterized by high cold, high radiation, and large differences in temperature between day and night. Tibetan residential buildings are famous for adapting to the harsh ecological environment and maintaining durability. Based on the residential buildings in Tibet, this paper extracts the technical process and color decoration culture in the construction process in order to adapt to the harsh natural environment. This paper first analyzed the four ecological construction modes of Tibetan residential buildings, analyzed the interior layout characteristics and cultural customs connotation, and introduced the architectural decoration characteristics and decorative color painting. The results show that the ramming type of adobe mainly includes the selection of building foundation, wall laying, floor and roof construction and so on, and its insulation effect is better. The rubble masonry type mainly adopts irregular gneiss, supplemented by clay, which has strong compressive capacity. Logs dry type using log masonry, heat preservation. and shock resistance is better. Concrete-infilled wall frame is composed of horizontal and vertical load-bearing system, which has stronger seismic performance. Tibetan residential buildings generally have two or three floors. The first floor is the enclosure and sundry room, the second floor is the rest place, and the third floor is the Sutra hall and sun terrace. The overall outdoor color of Kangba Tibetan buildings is mainly red and black, while the indoor color is mainly blue and red, with wood carvings and furniture. The layout of Tibetan villages can be divided into centripetal layout and scattered layout. Tibetan residential buildings provide a new sustainable development direction for the current global urbanization process at the expense of the ecological environment. It can alleviate the crisis of global resource shortage, climate warming, and biodiversity degradation.

Impacts from Economic Development and Environmental Factors on Life Expectancy: A Comparative Study Based on Data from Both Developed and Developing Countries from 2004 to 2016

Both economic development level and environmental factors have significant impacts on life expectancy at birth (LE). This paper takes LE as the research object and selects nine economic and environmental indicators with various impacts on LE. Based on a dataset of economic and environmental indicators of 20 countries from 2004 to 2016, our research uses the Pearson Correlation Coefficient to evaluate the correlation coefficients between the indicators, and we use multiple regression models to measure the impact of each indicator on LE. Based on the results from models and calculations, this study conducts a comparative analysis of the influencing mechanisms of different indicators on LE in both developed and developing countries, with conclusions as follow: (1) GDP per capita and the percentage of forest area to land area have a positive impact on LE in developed countries; however, they have a negative impact on LE in developing countries. Total public expenditure on education as a percentage of GDP and fertilizer consumption have a negative impact on LE in developed countries; however, they have a positive impact on LE in developing countries. Gini coefficient and average annual exposure to PM2.5 have no significant effect on LE in developed countries; however, they have a negative impact on LE in developing countries. Current healthcare expenditures per capita have a negative impact on LE in developed countries, and there is no significant impact on LE in developing countries. (2) The urbanization rate has a significant positive impact on LE in both developed countries and developing countries. Carbon dioxide emissions have a negative impact on LE in both developed and developing countries. (3) In developed countries, GDP per capita has the greatest positive impact on LE, while fertilizer consumption has the greatest negative impact on LE. In developing countries, the urbanization rate has the greatest positive impact on LE, while the Gini coefficient has the greatest negative impact on LE. To improve and prolong LE, it is suggested that countries should prioritize increasing GDP per capita and urbanization level. At the same time, countries should also work on reducing the Gini coefficient and formulating appropriate healthcare and education policies. On the other hand, countries should balance between economic development and environmental protection, putting the emphasis more on environmental protection, reducing environmental pollution, and improving the environment's ability of self-purification.

Life Expectancy in Chinese Cities: Spatially Varied Role of Socioeconomic Development, Population Structure, and Natural Conditions

Improving life expectancy, as well as people's health and wellbeing, is an important goal both for the Chinese government and the United Nations. Therefore, to analyze the main factors influencing life expectancy in prefecture-level cities in China, this study uses classical ordinary least-squares regression and geographical weighted regression on the data of the latest census. Moreover, regional differences induced by each influencing factor are also depicted in this study. The results demonstrate that there is significant heterogeneity and spatial positive correlation among the distribution of life expectancy in prefecture-level cities, with a generally higher life expectancy in the provincial capitals and eastern China, and lower in western China. The geographically weighted regression analysis shows that the economic development level, medical conditions, demographic structure, natural environment, and city attributes all affect the distribution of life expectancy, but that their effects have significant spatial heterogeneity. Life expectancy of the less developed areas in Western China is affected dominantly by economic development level, whereas medical services and education are of great importance in determining the life expectancy in Northern and Southern China, respectively. Thus, it is crucial to solve health problems based on local conditions, especially focusing on the improvement of health and health care in underdeveloped areas. Meanwhile, for the eastern developed areas, special attention should be paid to environmental protection in the economic process, while striving to achieve high-quality development.

Diagnostic reference values for sarcopenia in Tibetans in China

Sarcopenia is an age-associated disease characterized by loss of muscle mass and function, but the diagnostic cutoff values remain controversial. To investigate the diagnostic cutoff values and incidence of sarcopenia in a plateau population, the limb skeletal muscle mass, gait speed and grip strength of 2318 Tibetan adults were measured according to the criteria of the Asian Working Group for Sarcopenia. We found that the diagnostic reference values for sarcopenia in the high-altitude population were significantly lower than those in the plain population, and the incidences of sarcopenia in the high-altitude population over 60 years old were 17.2% in men and 36.0% in women, which were significantly higher than those in the plain population. Our study proposes reference values for the diagnosis of sarcopenia in Tibet. We suggest that the cutoff value for sarcopenia in the plateau population should be established based on altitude. Hypoxia may be an important risk factor for sarcopenia.

Spatial Characteristics of Life Expectancy and Geographical Detection of Its Influencing Factors in China

Life expectancy (LE) is a comprehensive and important index for measuring population health. Research on LE and its influencing factors is helpful for health improvement. Previous studies have neither considered the spatial stratified heterogeneity of LE nor explored the interactions between its influencing factors. Our study was based on the latest available LE and social and environmental factors data of 31 provinces in 2010 in China. Descriptive and spatial autocorrelation analyses were performed to explore the spatial characteristics of LE. Furthermore, the Geographical Detector (GeoDetector) technique was used to reveal the impact of social and environmental factors and their interactions on LE as well as their optimal range for the maximum LE level. The results show that there existed obvious spatial stratified heterogeneity of LE, and LE mainly presented two clustering types (high-high and low-low) with positive autocorrelation. The results of GeoDetector showed that the number of college students per 100,000 persons (NOCS) could mainly explained the spatial stratified heterogeneity of LE (Power of Determinant (PD) = 0.89, p < 0.001). With the discretization of social and environmental factors, we found that LE reached the highest level with birth rate, total dependency ratio, number of residents per household and water resource per capita at their minimum range; conversely, LE reached the highest level with consumption level, GDP per capita, number of college students per 100,000 persons, medical care expenditure and urbanization rate at their maximum range. In addition, the interaction of any two factors on LE was stronger than the effect of a single factor. Our study suggests that there existed obvious spatial stratified heterogeneity of LE in China, which could mainly be explained by NOCS.