Abstract
With the rapid increase of the aging population in China, research on the aging phenomenon has become critical. Studying population aging from a spatial perspective is of vital practical significance. Based on China’s census data from 1990 to 2010, this study establishes the indicator system of aging level and chooses the entropy method, standard deviational ellipse, and spatial autocorrelation as main methods. Taking Liaoning province of China as an example, the study measures the aging level of its 100 districts and counties, analyzing the overall spatial movement degree, and elucidates the temporal-spatial evolution of aging development. It further discusses the spatial correlational characteristics between each county unit. The results reveal that, first, the spatial distribution of aging in Liaoning shows an unceasingly intensifying northeast-southwest pattern. County areas along the Shenyang-Dalian line show a stronger effect of aging of the whole province. Second, the average score of aging in all county areas is on the increase; the degree of aging shows an increasing trend, but the speed of aging tends to slow down. Population aging in Liaoning shows an obvious spatial heterogeneity, which is mainly manifested by regional differences, urban-rural differences, and minority differences. Third, Moran’s I index of aging level first increases and then decreases; the values are all positive. The overall spatial pattern has a positive correlation; the spatial agglomeration effect is first enhanced and then weakened. The hot spots are distributed in the surrounding counties of Shenyang and Dalian, showing a distribution pattern of two cores; the cold spots gradually form a binary structure represented by Chaoyang-Huludao and Yingkou-Panjin. The study showed the positive spatial correlation of the aging level between the county units, thereby paving the way for future research on the balanced distribution. Population aging studies will contribute to optimize the population structure and promote a virtuous circle of economy. The study showed the positive spatial correlation of the aging level between the county units, thereby paving the way for future research on the balanced distribution. Population aging studies will contribute to optimize the population structure and promote a virtuous circle of economy.
Highlights
In today’s world of a rapidly aging population, aging issues are given close attention and importance. e “silent revolution” caused by declining birthrate and increasing lifespans has taken place all over the world [1]
Since 1990, census has been taken every 10 years periodically, and the recent one is the sixth census. e statistical caliber of this study is the resident population. e data of the 4th, 5th, and 6th census comes from Tabulation on the 1990 Population Census of Liaoning Province, Tabulation of the 2000 Population Census of the People’s Republic of China by County, and Tabulation of the 2010 Population Census of the People’s Republic of China by County; other social and economic data come from Liaoning Statistical Yearbook and China Statistical Yearbook in 1990, 2000, and 2010
Using the entropy method to determine the index weights can overcome the randomness and assumption that the subjective weighting method cannot avoid, and effectively solve the problem of overlapping information between multiple index variables. erefore, the study attempts to use this method to determine the index weight and measure the population aging level. e raw data are processed into the same dimension by min-max normalization, the entropy is defined according to the matrix, and the weight is confirmed. e processing equation is as follows: First, define the entropy according to the matrix X′ (Xi′j)m×n(0 ≤ Xi′j ≤ 1): m
Summary
In today’s world of a rapidly aging population, aging issues are given close attention and importance. e “silent revolution” caused by declining birthrate and increasing lifespans has taken place all over the world [1]. The aging problem in developing countries usually appears at the lower economic level, and people are more likely unprepared for its rapid and large-scale development Having both the largest population and the largest aging population, China is one of the fastest growing countries in terms of aging. To analyze the differences and the characteristics of evolution of the aging region, many scholars have conducted comparative studies from the provincial scale and from the perspective of urban agglomerations [22,23,24]. Based on the period of China’s population census, this study determines 1990 to 2010 as the time scale to discuss the aging problem in Liaoning province after the implementation of family planning at the county level, hoping to enrich aging studies at the small scale from a spatial perspective. Based on the period of China’s population census, this study determines 1990 to 2010 as the time scale to discuss the aging problem in Liaoning province after the implementation of family planning at the county level, hoping to enrich aging studies at the small scale from a spatial perspective. e study does not choose the regular single indicator, which is the percentage of population over the age of 65, to measure the aging level, but selects five reasonable indicators to establish an indicator system, showing a certain degree of innovation in the selection of indicators. e study measures the aging level with certain novelty value and makes empirical contribution to the implications of the uneven distribution of aging for developing regions
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