Spatial variations and macroeconomic determinants of life expectancy and mortality rate in China: a county-level study based on spatial analysis models
The life expectancy and mortality rate always exhibit remarkable spatial variations. Their spatial distribution patterns and economic determinants in China were explored.
Four indexes including lifespan expectancy at birth (LEB), infant mortality rate (IMR), under-5 mortality rate (U5MR) and crude mortality rate (CMR) at county level in China were calculated. The spatial distribution patterns of these indexes were illustrated. Meanwhile, spatial regressive model was applied to explore the relations between major macroeconomic determinants and these indexes.
Spatial dependence of these four indexes in China was identified, and the positive spatial autocorrelation indicated a clustering feature rather than stochastic distribution. Additionally, local Moran’s I statistics revealed opposite local spatial clusters of LEB and IMR, U5MR in China, that LEB showed that high value clusters in the southwest and low value clusters in the eastern part and northern Xinjiang, and IMR/U5MR exhibited that low value clusters in the east and high value clusters in the west. The spatial regression revealed that income per capita influenced positively on LEB and CMR, and GDP per capita was associated positively with IMR and U5MR.
Geographical factors should be highly considered, and the L–L LEB or H–H IMR/U5MR clustered areas need to be integrated as a whole to formulate public health and economic development plans.
KeywordsLife expectancy at birth Infant and childhood mortality rate Spatial distribution patterns Macroeconomic determinants China
Supports for this research were provided by the Open foundation of Key Laboratory of Coal Resources Exploration and Comprehensive Utilization, Ministry of Land and Resources, P. R. China (Grant No. KF2018-7) and the National Natural Sciences Foundation of China (Grant No. 41502329). The authors express their gratitude for data support from “National Earth System Science Data Sharing Infrastructure, National Science & Technology Infrastructure of China (http://www.geodata.cn)” and data calculation assistance from Dr. Y.J. Du and Dr. Y.L. Liu.
Compliance with ethical standards
Conflict of interest
The authors confirm that this research involved no conflict of interest.
This article is based on a secondary analysis of administrative data and does not contain any studies with human participants performed by any of the authors.
- Anderson RN (1999) A method for constructing complete annual US life tables. Vital Health Stat 2:1–28Google Scholar
- Cutler DM, Huang W, Lleras-Muney A (2016) Economic conditions and mortality: evidence from 200 years of data. National Bureau of Economic ResearchGoogle Scholar
- Dabla-Norris ME, Kochhar MK, Suphaphiphat MN et al (2015) Causes and consequences of income inequality: a global perspective. International Monetary FundGoogle Scholar
- Li RB, Tan JA, Wang WY, Yang H (2000) The yearly change and regional difference of population life-span in China. Hum Geogr 15:1–6Google Scholar
- Shryock HS, Siegel JS, Stockwell EG (1976) The methods and materials of demography. Academic Press, New YorkGoogle Scholar
- Smith JP (1999) Healthy bodies and thick wallets: the dual relation between health and economic status. J Econ Perspect J Am Econ Assoc 13:144–166Google Scholar
- UNDP (2010) International Human Development IndicatorsGoogle Scholar
- United Nations (2011) World population prospects the 2010 revision, demographic profiles, vol IIGoogle Scholar
- Wang X (2006) Income inequality in China and its influencing factors. WIDER working paper series 126. World Institute for Development Economic Research (UNU-WIDER)Google Scholar
- Wang H, Liddell CA, Coates MM, Mooney MD, Levitz CE et al (2014b) Global, regional, and national levels of neonatal, infant, and under-5 mortality during 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. The Lancet 384:957–979. https://doi.org/10.1016/S0140-6736(14)60497-9 CrossRefGoogle Scholar
- Wang H, Naghavi M, Allen C, Barber RM, Bhutta ZA et al (2016) Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015. The Lancet 388:1459–1544. https://doi.org/10.1016/S0140-6736(16)31012-1 CrossRefGoogle Scholar
- WHO (2013) World Health Statistics 2011. WHO, GenevaGoogle Scholar
- Xu Y, Zhang W, Yang R et al (2014) Infant mortality and life expectancy in China. Med Sci Monit Int Med J Exp Clin Res 20:379Google Scholar
- You D, Hug L, Ejdemyr S et al (2015) Global, regional, and national levels and trends in under-5 mortality between 1990 and 2015, with scenario-based projections to 2030: a systematic analysis by the UN Inter-agency Group for Child Mortality Estimation. The Lancet 386:2275–2286CrossRefGoogle Scholar