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

Abstract

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. Int. J. Environ. Res. Public Health 2020, 17, 906 2 of 15 2010 [3]. Therefore, it is an urgent task to explore the spatial characteristics and influencing factors of LE in order to deal with the regional inequality of LE in China.There have been many studies concerning the various influencing factors of LE. These factors can mainly be divided into two categories: biological and social and environmental factors [4]. Biological factors involve the individual's genetic factors, living habits, etc. Differences in LE between men and women are mainly due to differences in gene expression intensity. In addition, a study also found that people who smoked, drank and exercised less were vulnerable to cancer, cardiovascular and cerebrovascular diseases, which caused a reduction of LE [5]. However, social and environmental factors were the most frequently considered and important influencing factors in LE research [6]. Many studies found that economy and demographic composition were key influencing factors of LE [7-10]. Studies have found that health care and services had a positive effect on disease prevention and treatment, so the LE level was often higher in areas with good medical conditions [11]. People with a higher educat...

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

“…In addition to being the most important index in the evaluation of levels of health and aging, life expectancy is also a comprehensive index used to evaluate levels of economic development, education, and medical and health services [1]. The United Nations Sustainable Development Goals (2015-2030) clearly put forward various measures and methods, such as reducing the global maternal mortality, ending preventable deaths of newborns and children, reducing the death rate of various communicable and non-communicable diseases, and deaths and injuries from road traffic accidents, to ensure healthy living and promote wellbeing [2].…”

“…The United Nations Sustainable Development Goals (2015-2030) clearly put forward various measures and methods, such as reducing the global maternal mortality, ending preventable deaths of newborns and children, reducing the death rate of various communicable and non-communicable diseases, and deaths and injuries from road traffic accidents, to ensure healthy living and promote wellbeing [2]. Therefore, how to scientifically measure life expectancy in a country or region, study its influencing factors, and formulate effective government measures to increase life expectancy and improve health and wellbeing have always been hot topics for governments and scholars [1][2][3][4][5]. Many studies have shown that natural environment; the level of economic development, education, and medical and health service; living environment; living habits; behavioral patterns; and marital status play an important role in life expectancy.…”

“…Increasing life expectancy and improving people's health and wellbeing are also important policy objectives of the Chinese government. Since the Reform and Opening Up, life expectancy in China has greatly increased [1,13,14]. The 13th Five-Year Plan in China proposes to increase life expectancy by 1 year from 2015 to 2020 [15].…”

“…In addition, the Healthy China Action (2019-2030) explicitly takes life expectancy as the main indicator in the action plan [5]. Some empirical studies point out that China covers a large territory, with local economic development varying greatly, and there are differences in the factors influencing life expectancy in different places and at different stages of development [1,13,14]. Therefore, it is up to local governments to accurately assess life expectancy and its influencing factors, as well as to formulate effective policies to achieve the goal of increasing life expectancy.…”

“…Therefore, it is up to local governments to accurately assess life expectancy and its influencing factors, as well as to formulate effective policies to achieve the goal of increasing life expectancy. However, at present, China only publishes life expectancy in the national and provincial census years [16], and studies on the influencing factors of life expectancy only reach the provincial level, lacking research on urban and local scales, which makes it difficult to meet the needs of formulating effective policies to improve life expectancy [1,13,14].…”