Spatial variations and macroeconomic determinants of life expectancy and mortality rate in China: a county-level study based on spatial analysis models

Air Quality, Pollution Perception, and Residents' Health: Evidence from China

Environmental and resident health issues associated with air pollution are an area of growing concern for both policy officials and the general public. In recent years, China has been accelerating the construction of a Beautiful China and a Healthy China, with the aim of protecting and improving the environment and ensuring public health. In this study, we aimed to explore the impact of air quality and air pollution perception on residents' health. This study used the 2017 Chinese General Social Survey data to measure self-rated health, mental health, and air pollution perception. Using matched socioeconomic indicators and air pollution data, we analyzed the relationship between subjective perception of air pollution, objective air pollution data, and residents' health. The results showed the following: (1) Air pollution perception has a significant negative impact on self-rated health and mental health. Thus, it needs more consideration to reduce environmental health risks. (2) Objective air pollution has a significant negative impact on mental health. At the same time, its effect on self-rated health was insignificant. These results provide empirical evidence supporting the Chinese government's decision to invest more in combating air pollution and ensuring the health of Chinese residents.

Spatiotemporal trends in neonatal, infant, and child mortality (1990-2019) based on Bayesian spatiotemporal modeling

Background

Neonatal mortality rate (NMR), infant mortality rate (IMR), and child mortality rate (CMR) show a huge difference across countries, which has been posing challenges for public health policies and medical resource allocation.

Methods

Bayesian spatiotemporal model is applied to assess the detailed spatiotemporal evolution of NMR, IMR, and CMR from a global perspective. Panel data from 185 countries from 1990 to 2019 are collected.

Results

The continuously decreasing trend of NMR, IMR, and CMR indicated a great improvement in neonatal, infant, and child mortality worldwide. Further, huge differences in the NMR, IMR, and CMR still exist across countries. In addition, the gap of NMR, IMR, and CMR across the countries presented a widening trend from the perspective of dispersion degree and kernel densities. The spatiotemporal heterogeneities demonstrated that the decline degree among these three indicators could be observed as CMR > IMR > NMR. Countries such as Brazil, Sweden, Libya, Myanmar, Thailand, Uzbekistan, Greece, and Zimbabwe showed the highest values of b_1i , indicating a weaker downward trend compared to the overall downward trend in the world.

Conclusions

This study revealed the spatiotemporal patterns and trends in the levels and improvement of NMR, IMR, and CMR across countries. Further, NMR, IMR, and CMR show a continuously decreasing trend, but the differences in improvement degree present a widening trend across countries. This study provides further implications for policy in newborns, infants, and children's health to reduce health inequality worldwide.

Spatial variations and social determinants of life expectancy in China, 2005-2020: A population-based spatial panel modelling study

BACKGROUND

Social determinants of health (SDOH) produce a broad range of life expectancy (LE) disparities. In China, limited literatures were found to report association between SDOH and LE at ecological level during a consecutive period of time from the spatial perspectives. This study aimed to determine the existence, quantify the magnitude, and interpret the association between SDOH and LE in China.

METHODS

Provincial-level LE were estimated from mortality records during 2005-2020 from National Mortality Surveillance System in China. A spatial panel Durbin model was used to investigate LE associated SDOH proxies. Spatial spillover effects were introduced to interpret direct and indirect effects caused by SDOH during long-term and short-term period on LE disparities.

FINDINGS

Nationwide, LE increased from 73.1 (95% confidence interval (CI): 71.3, 74.4) years to 77.7 (95%CI: 76.5, 78.7) years from 2005 to 2020. Unequally spatial distribution of LE with High-High clustering in coastal areas and Low-Low clustering in western regions were observed. Locally, it was estimated that SDOH proxies statistically significant related to an increase of LE, including GDP (coefficient: 0.02, 95%CI: 0.00, 0.03), Gini index (coefficient: 2.35, 95%CI: 1.82, 2.88), number of beds in health care institutions (coefficient: 0.02, 95%CI: 0.00, 0.05) and natural growth rate of resident population (coefficient: 0.02, 95%CI: 0.01, 0.02). Direct and indirect effects decomposition during long-term and short-term of LE associated SDOH proxies demonstrated that GDP, urbanization rate, unemployment rate, education attainment, Gini index, number of beds in health care institutions, sex ratio, gross dependence ratio and natural growth rate of resident population not only affected local LE, but also exerted spatial spillover effects towards geographical neighbors.

INTERPRETATION

Spatial variations of LE existed at provincial-level in China. SDOH regarding socioeconomic development and equity, healthcare resources, as well as population characteristics not only affected LE disparities at local scale but also among nearby provinces. Externalities of policy of those SDOH proxies should be took into consideration to promote health equity nationally. Comprehensive approaches on the basis of population strategy should be consolidated to optimize supportive socioeconomic environment and narrow the regional gap to reduce health disparities and increase LE.

FUNDING

National Key Research & Development Program of China (Grant No.2018YFC1315301); Ministry of Education of China Humanities and Social Science General Program (Grant No.18YJC790138).

Spatial heterogeneity of human lifespan in relation to living environment and socio-economic polarization: a case study in the Beijing-Tianjin-Hebei region, China

The spatial heterogeneity and influence factors of public lifespan have been reported worldwide at the national level or typical longevous areas. However, few sub-national studies considering the living environment and socio-economic level together have been explored in the imbalanced developed region with a huge population base and deteriorated air quality. In this paper, spatial heterogeneity of lifespan integrating environment and socio-economic influence factors was investigated in the Beijing-Tianjin-Hebei (BTH) region of China using geographically weighted regression (GWR). Five indicators were constructed to determine the lifespan based on the three national censuses (1990-2010) in the BTH region. The results showed that the areas with higher CH (centenarians per 100,000 inhabitants) and centenarity index (CI) exhibited changing distribution in the BTH region, whereas those with lower CH and CI and extreme value of the ultra-octogenarian index (UOI) and LI (> 90/ > 65) maintained a relatively stable feature through time. But as lifespan indicators increase overall, the differences between the counties/districts widen. Furthermore, remarkable spatial heterogeneity was detected for the associations between the significant environmental and socio-economic variables and lifespan indicators. Although the natural geographic condition (altitude) still exhibited a negative influence on the longevity of the population, the socio-economic factors (GDP_pc and income level) showed a more dominant influence on the extension of the elderly and longevity population. Correspondingly, the widened unbalance of population lifespan (UOI, LI, CH) was considered closely related to the socio-economic polarization, and the adverse effects of air pollution on life expectancy at birth (LEB) have also emerged. To further improve the overall lifespan level and narrow the lifespan gap in the BTH region, future work on cleaner air and more balanced development is still needed.

Spatiotemporal trends in life expectancy and impacts of economic growth and air pollution in 134 countries: A Bayesian modeling study

Life expectancy (LE) varies across countries in space and time, and economic growth and air pollution are two important influence factors to LE. This study mainly aims to investigate spatiotemporal trends in LE in 134 countries from 1960 to 2016 by using Bayesian spatiotemporal modeling. Further, the relations between per capita gross domestic product (GDP_pc) and population-weighted fine particulate matter (pwPM_2.5) and LE are investigated from a global perspective from 1998 to 2016 by using the Bayesian regression model. The results illustrated the heterogeneity of spatiotemporal trends in LE globally. Specifically, Africa and South-East Asia show much lower LE levels, and the Americas, European, and Western Pacific exhibit a relatively higher LE level compared to the overall level. The countries with low overall levels of LE show a relatively stronger upward trend than the overall upward trend and vice versa. In addition, this study demonstrates that the spatial differences in effects of influence factors on LE in the six WHO regions in the 134 countries. Africa shows the highest positive regression coefficient of GDP_pc and lowest negative regression coefficient of pwPM_2.5 on LE than other regions in the world. Furthermore, it shows the complexity of the interaction between economic growth and air pollution on LE across six WHO regions. Our findings suggest the public policies to reduce the health damage caused by air pollution, especially in Africa, Eastern Mediterranean, and Europe where the pwPM_2.5 negatively affect the LE benefits from economic growth.

A Systematic Review of Sociodemographic, Macroeconomic, and Health Resources Factors on Life Expectancy

This review was aimed at systematically synthesizing and appraising the existing literature of sociodemographic, macroeconomic, and health resources factors on life expectancy. A systematic literature search of English databases, that is, PubMed/MEDLINE were scrutinized for exploring sociodemographic, macroeconomic, and health resources factors on life expectancy. The literature search was conducted in January 2020, covering a total of 46 articles from 2004 to 2019 met the review criteria, which were fully discussed subsequently. Among sociodemographic factors, infant mortality rate, literacy rate, education level, socioeconomic status, population growth, and gender inequality have a significant impact on life expectancy. Gross domestic product, Gini, income level, unemployment rate, and inflation rate are the main macroeconomic factors that significantly correlated with life expectancy. Among various health care resources, health care facilities, the number of the health care profession, public health expenditure, death rates, smoking rate, pollution, and vaccinations had a significant correlation with life expectancy. The systematic review showed general conformity of different studies, with a significant association between life expectancy and factors comprising several sociodemographic, macroeconomic, and various health care variables. This review found that only one study examined factors affecting life expectancy in Arabic countries. More studies on this region to fill this research gap were highly recommended.

Is centenarian rate independent from economy?

BACKGROUND

Economy development and income are compactly associated with mortality of infant, children, young people, and mid age all over the world, and high income brings higher life expectancy, aging rate and 80+ rate as a result. On the contrary, the relationship between income and centenarian rate is obscure, in China, low income regions have lower life expectancy, lower 80+ rate but higher 90+ rate and 100+ rate before 2000, but 90+ rate and centenarian rate in low income regions fall behind high income regions after 2010.

OBJECTIVE

The aim of this study is to explore the relationship between regional economic performance and centenarian rate in long period.

METHOD

Gravity center of five longevity indicators, demographic methodology between age-specific mortality rate and centenarian rate were conducted of 31 provinces in China from 1982 to 2018. We also explored the association between centenarian rate and per capita income using binary logistic regression.

RESULTS

higher income brings better medical care and mortality rate is sharply decreased, among all age stages, the age 70-84 has the highest number of death, and will get most number of extra lives when the mortality rate decreases, and then 80+ rate will be increased immediately. Meanwhile, the extra 70-84 years people increased denominator of 90+ rate and centenarian rate, then 90+ rate and centenarian rate in higher income region will be fall behind. 10-20 years later, benefited from additional 70-84 years population, the number of 90+ will be largely increased. 20-30 years later, the number of 100+ will be largely increased too.

CONCLUSION

Income is positively related with lower mortality rate of oldest-old and higher 90+ rate and centenarian rate, although the effect will be lagged for 10-20 years and 20-30 years, respectively.

Spatial heterogeneity of the associations of economic and health care factors with infant mortality in China using geographically weighted regression and spatial clustering

Economic factors and health care resources are important influential factors of infant mortality. We aimed to examine prefecture-level spatial heterogeneity and clustering of the associations of economic and health care factors with infant mortality rates (IMR) in China. IMR data in 348 prefectures were calculated and adjusted, and economic and health care data were collected in each prefecture in China, 2010. Stepwise regression was used to select important variables, and geographically weighted regression (GWR) was applied to examine the spatial variations of the relationships between economic and health care factors and IMR. The k-means clustering was developed to elucidate the spatial clustering patterns of the GWR coefficients. The results showed that three important variables were selected in the multivariable regression model, including per capita income of rural residents, Engel's coefficient of rural residents, and proportion of government health expenditure. The GWR with these three variables revealed spatial heterogeneity of the associations between IMR and economic and health care factors; western China generally had higher GWR R-squares and stronger associations between IMR and all the three variables than the middle-eastern part of China. Based on the GWR coefficients, three distinct spatial clusters were identified. This study contributes new findings on the spatial heterogeneity of the associations between economic and health care factors and infant mortality rate in China, which calls for region-specific policies to reduce infant mortality in China.

Spatial patterns and social-economic influential factors of population aging: A global assessment from 1990 to 2010

The world's population is aging rapidly. In this paper, three population aging indicators were collected to represent the elderly population, the oldest-old population, and centenarians. The spatial patterns of three population aging indicators and the influencing social-economic factors and their spatial spillover effects in the world from 1990 to 2010 were investigated. The empirical strategy was based on application of spatial autocorrelation methods and spatial error modeling. The results revealed the significant positive spatial autocorrelation as well as the obvious spatial disparities and clusters of the aging indicators in the world. Furthermore, spatial spillover effects of population aging indicators were detected with positive influence of several social-economic factors (e.g., per capita GNI, urbanization rate, and life expectancy) not only of population aging in a country itself, but in its neighboring counties. In sum, these findings indicated that population aging are a spatio-temporal process, and the spatial spillover effects from neighbors also vary among these indicators, which should be considered into the differentiated policies in response to the challenge of an aging society.