Obstacle Factors and Spatial Measurement of the Well-Being of the Elderly in China
Abstract
:1. Introduction
2. Research Methodology and Data Sources
2.1. Constructing the Indicator System
2.2. Measurement Model
3. Measurement and Analysis of the Well-being Level of the Elderly in Various Provinces of China
3.1. Measurement Result
3.2. Analysis of Influencing Factors
4. Conclusions and Recommendations
4.1. Conclusions
4.2. Recommendations
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Target Level | Guideline Level | Indicator Abbreviation | Indicators | Nature of Indicator | Weighting |
---|---|---|---|---|---|
Well- Being of the elderly | Health well-being | H1 | Total health expenditure per capita (CNY) | Positive | 0.0322 |
H2 | Density of public health institutions (per 10,000 square kilometers) | Positive | 0.0565 | ||
H3 | Number of beds per 1000 population in health care facilities (in beds) | Positive | 0.0611 | ||
H4 | Number of health technicians per 1000 population (unit) | Positive | 0.0351 | ||
Income well-being | G1 | Gross regional product per capita (CNY) | Positive | 0.0699 | |
G2 | Per capita disposable income of urban and rural residents (CNY) | Positive | 0.0634 | ||
G3 | Local revenue within the general budget (CNY billion) | Positive | 0.0543 | ||
G4 | Average employee wage (CNY) | Positive | 0.0598 | ||
G5 | Per capita consumption expenditure (CNY/person) | Positive | 0.0532 | ||
G6 | Engel coefficient (%) | Negative | 0.0367 | ||
Social well-being | S1 | Elderly dependency ratio (%) | Positive | 0.053 | |
S2 | Number of nursing homes (unit) | Positive | 0.0799 | ||
S3 | Number of residential care beds per 1000 elderly people (unit) | Positive | 0.039 | ||
S4 | Public library collections (million volumes) | Positive | 0.0707 | ||
S5 | Urban road area per capita (m2) | Positive | 0.0374 | ||
S6 | Number of buses per 10,000 people (vehicles per 10,000 people) | Positive | 0.0428 | ||
Educational well-being | E1 | Education expenses (CNY million) | Positive | 0.0481 | |
E2 | Average years of schooling (years) | Positive | 0.0215 | ||
E3 | Illiteracy rate (%) | Negative | 0.0191 | ||
E4 | Number of higher education schools for adults (unit) | Positive | 0.0662 |
Classification Number | Classification Criteria | Classification Results | Grade | Province |
---|---|---|---|---|
1 | 0 ≤ R < (M − Std) | 0 ≤ R < 0.4203 | Lower | Gansu, Yunnan, Ningxia, Qinghai, Hainan, Tibet |
2 | (M − Std) ≤ R < M | 0.4203 ≤ R < 0.4664 | Moderate | Fujian, Hebei, Chongqing, Heilongjiang, Shaanxi, Jiangxi, Jilin, Inner Mongolia, Xinjiang, Shanxi, Guizhou, Guangxi |
3 | M ≤ R < (M + Std) | 0.4664 ≤ R < 0.5125 | Higher | Liaoning, Sichuan, Hubei, Hunan, Tianjin, Anhui, Henan |
4 | (M + Std) ≤ R ≤ 1 | 0.5125 ≤ R ≤ 1 | Highest | Beijing, Shanghai, Jiangsu, Zhejiang, Shandong, Guangdong |
Provincial Area | First Barrier Degree | Second Barrier Degree | Third Barrier Degree | Fourth Barrier Degree | ||||
---|---|---|---|---|---|---|---|---|
Factors | Obstacles | Factors | Obstacles | Factors | Obstacles | Factors | Obstacles | |
Beijing | G4 | 14.355% | G3 | 13.246% | H4 | 12.756% | G5 | 10.868% |
Tianjin | G1 | 8.500% | G5 | 7.054% | G4 | 6.664% | H2 | 6.608% |
Shanghai | G2 | 13.782% | G4 | 13.206% | G5 | 12.214% | H2 | 11.668% |
Chongqing | H3 | 5.440% | E3 | 3.458% | H2 | 3.426% | G1 | 3.290% |
Hebei | H2 | 6.263% | S6 | 4.463% | S2 | 4.337% | E1 | 4.326% |
Shanxi | G6 | 4.554% | S1 | 4.033% | E2 | 3.730% | H2 | 3.700% |
Liaoning | E4 | 6.859% | S2 | 6.049% | H3 | 5.660% | S4 | 4.253% |
Jilin | E4 | 5.054% | G6 | 4.274% | S2 | 4.272% | H3 | 3.607% |
Heilongjiang | E4 | 7.220% | H3 | 4.504% | S2 | 4.311% | S6 | 4.081% |
Jiangsu | S4 | 9.791% | G3 | 9.255% | S2 | 8.000% | G1 | 7.973% |
Zhejiang | S4 | 9.022% | G2 | 8.391% | S3 | 7.805% | G3 | 7.016% |
Anhui | S2 | 7.446% | S5 | 4.883% | S3 | 4.508% | E1 | 3.633% |
Fujian | G1 | 5.693% | S6 | 4.890% | S1 | 4.531% | G2 | 4.513% |
Jiangxi | S2 | 8.298% | S1 | 4.047% | S5 | 3.932% | E3 | 3.425% |
Shandong | H2 | 7.182% | S2 | 7.079% | G3 | 6.892% | E1 | 6.863% |
Henan | E1 | 6.103% | H2 | 5.934% | S2 | 4.661% | G6 | 4.120% |
Hubei | E4 | 5.054% | H3 | 4.544% | S3 | 4.172% | S4 | 3.968% |
Hunan | H3 | 5.221% | S6 | 5.026% | E4 | 4.332% | E1 | 4.081% |
Guangdong | G3 | 13.083% | E1 | 11.510% | S4 | 10.033% | G5 | 5.577% |
Hainan | S1 | 5.250% | E2 | 3.730% | E3 | 3.443% | S5 | 3.251% |
Sichuan | E4 | 5.776% | H3 | 5.600% | E1 | 5.383% | G3 | 4.055% |
Guizhou | H3 | 4.882% | S3 | 3.769% | G6 | 3.625% | E1 | 3.232% |
Yunnan | S1 | 4.356% | E1 | 3.487% | G6 | 3.460% | S6 | 3.396% |
Shaanxi | H4 | 6.214% | E4 | 5.054% | H3 | 4.384% | G6 | 3.958% |
Gansu | S3 | 3.773% | H3 | 3.587% | S5 | 3.544% | S1 | 3.121% |
Qinghai | S1 | 5.656% | S6 | 4.431% | H3 | 4.225% | H4 | 4.091% |
Inner Mongolia | S3 | 7.904% | S5 | 4.830% | S1 | 4.554% | H4 | 4.168% |
Guangxi | S5 | 3.945% | S1 | 3.674% | E3 | 3.530% | E1 | 3.043% |
Tibet | G4 | 9.347% | S1 | 6.753% | H1 | 3.393% | S5 | 2.028% |
Ningxia | S5 | 4.881% | H4 | 4.709% | S1 | 4.619% | G6 | 4.400% |
Xinjiang | S1 | 5.762% | H3 | 5.620% | S6 | 4.346% | S5 | 4.189% |
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Dong, L.; Jia, Z.; Zhang, L.; Wang, S. Obstacle Factors and Spatial Measurement of the Well-Being of the Elderly in China. Sustainability 2022, 14, 1950. https://doi.org/10.3390/su14041950
Dong L, Jia Z, Zhang L, Wang S. Obstacle Factors and Spatial Measurement of the Well-Being of the Elderly in China. Sustainability. 2022; 14(4):1950. https://doi.org/10.3390/su14041950
Chicago/Turabian StyleDong, Lijing, Zhanhua Jia, Lingyu Zhang, and Shaohua Wang. 2022. "Obstacle Factors and Spatial Measurement of the Well-Being of the Elderly in China" Sustainability 14, no. 4: 1950. https://doi.org/10.3390/su14041950