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.

This paper used the sectional data of Chinese counties to analyze the spatial distribution characteristics of sustainable development of e-commerce for agricultural products in China at the county-level. The standard deviation ellipses and Moran’s index were used to research this subject. Then, by constructing spatial measurement models, the spatial spillover effects and influencing factors of the development of county-level agricultural products e-commerce were analyzed from economic development, economic structure, economic vitality, and agricultural development. The results show that: (1) the top 100 counties of agricultural products e-commerce mainly concentrate in southeastern China, spreading along the northeast and southwest; (2) the county-level agricultural products e-commerce shows significant negative spatial spillover effects; (3) the level of economic development and public services have a positive impact on the development of county-level agricultural products e-commerce, while the level of industrial development shows a negative correlation; (4) the level of agricultural development and industrial development have a significant negative external effect on the development of agricultural products e-commerce. This study is of great significance to promote the sustainable development of agricultural products e-commerce, the process of rural urbanization and the optimization of county industrial patterns.