General information of health resource distribution in rural Guangxi
1. Comparative analysis of per capita health resource distribution in different regions
In 2019, the average number of institutions per 1,000 rural population in rural Guangxi was 0.03, which was lower than that of China, Eastern China, Mid-China and Western China regions. The number of beds per 1,000 rural population is 1.41, lower than that of China and western China regions. The number of health worker per 1,000 rural population is 1.59, lower than the average number of China, Eastern China and Western China regions. The number of doctors per 1,000 rural population was 0.4, lower than that of China, Eastern China, Mid-China and Western China regions. The number of nurses per 1,000 rural population was 0.046, lower than that of China, Eastern China, Mid-China and Western China regions. In Guangxi, the average number of institutions per 1,000 rural population in Yulin was the highest, while the average number of institutions per 1,000 rural population in Nanning was the lowest (Table 1).
2. Comparative analysis of per square kilometer health resource distribution in different regions
In 2019, the average number of institutions, beds, health workers, doctors and nurses per Km2 in Guangxi were 0.005, 0.29, 0.33, 0.08 and 0.1, respectively, which were lower than the Mid-China region. In Guangxi, the average number of rural health resources per Km2 in Baise, Hechi, Laibin and Chongzuo were lower than the average number of Guangxi (Table 1).
Table 1
Rural health resource allocation in Guangxi in 2019
|
Region
|
Institution
|
Bed
|
Health Workers
|
Doctor
|
Nurse
|
103 pooulation
|
103 M2
|
103 pooulation
|
103 M2
|
103 pooulation
|
103 M2
|
103 pooulation
|
103 M2
|
103 pooulation
|
103 M2
|
China
|
0.07
|
0.004
|
1.48
|
0.14
|
1.56
|
0.15
|
0.91
|
0.05
|
0.71
|
0.04
|
Eastern China
|
0.05
|
0.005
|
1.34
|
0.22
|
1.68
|
0.28
|
1.02
|
0.1
|
0.72
|
0.07
|
Mid-China
|
0.06
|
0.011
|
1.43
|
0.48
|
1.34
|
0.45
|
0.91
|
0.16
|
0.67
|
0.12
|
Western China
|
0.09
|
0.002
|
1.68
|
0.01
|
1.71
|
0.07
|
0.84
|
0.02
|
0.76
|
0.02
|
Guangxi
|
0.02
|
0.005
|
1.77
|
0.29
|
1.99
|
0.33
|
0.29
|
0.08
|
0.32
|
0.1
|
Eastern Gui
|
0.04
|
0.007
|
2.98
|
0.48
|
3.38
|
0.54
|
0.89
|
0.14
|
0.99
|
0.16
|
Southern Gui
|
0.05
|
0.005
|
3.15
|
0.36
|
3.32
|
0.38
|
0.82
|
0.09
|
1.01
|
0.12
|
Westhern Gui
|
0.07
|
0.005
|
1.89
|
0.12
|
2.99
|
0.19
|
0.68
|
0.04
|
0.79
|
0.05
|
Nothern Gui
|
0.06
|
0.005
|
1.82
|
0.17
|
2.7
|
0.25
|
0.83
|
0.08
|
0.77
|
0.07
|
Mid-Gui
|
0.06
|
0.005
|
3.43
|
0.28
|
3.57
|
0.29
|
0.87
|
0.07
|
1
|
0.08
|
Nanning
|
0
|
0.005
|
0.4
|
0.43
|
0.41
|
0.45
|
0.11
|
0.12
|
0.13
|
0.15
|
Liuzhou
|
0.07
|
0.005
|
3.03
|
0.23
|
3.54
|
0.27
|
0.92
|
0.07
|
0.98
|
0.07
|
Guilin
|
0.06
|
0.005
|
1.82
|
0.17
|
2.7
|
0.25
|
0.83
|
0.08
|
0.77
|
0.07
|
Wuzhou
|
0.04
|
0.005
|
2.48
|
0.29
|
3.45
|
0.4
|
0.92
|
0.11
|
1.04
|
0.12
|
Beihai
|
0.03
|
0.006
|
3.31
|
0.58
|
3.29
|
0.57
|
0.9
|
0.16
|
1.05
|
0.18
|
Fangchenggang
|
0.07
|
0.005
|
2.85
|
0.18
|
3.48
|
0.22
|
0.88
|
0.06
|
0.98
|
0.06
|
Qinzhou
|
0.03
|
0.005
|
3.18
|
0.58
|
3.01
|
0.54
|
0.68
|
0.12
|
0.89
|
0.16
|
Guigang
|
0.03
|
0.007
|
2.52
|
0.52
|
3.22
|
0.66
|
0.92
|
0.19
|
0.84
|
0.17
|
Yulin
|
0.04
|
0.009
|
3.67
|
0.84
|
3.38
|
0.77
|
0.86
|
0.2
|
1.02
|
0.23
|
Baise
|
0.08
|
0.005
|
1.36
|
0.09
|
3.05
|
0.19
|
0.67
|
0.04
|
0.76
|
0.05
|
Hezhou
|
0.06
|
0.005
|
2.71
|
0.25
|
3.62
|
0.34
|
0.88
|
0.08
|
1.14
|
0.11
|
Hechi
|
0.07
|
0.004
|
2.46
|
0.16
|
2.94
|
0.19
|
0.68
|
0.04
|
0.83
|
0.05
|
Laibin
|
0.06
|
0.006
|
3.88
|
0.35
|
3.61
|
0.33
|
0.81
|
0.07
|
1.02
|
0.09
|
Chongzuo
|
0.07
|
0.005
|
2.18
|
0.16
|
2.83
|
0.21
|
0.63
|
0.05
|
0.77
|
0.06
|
3. Time trends of health resources allocation in rural Guangxi from 2016 to 2019
From 2016 to 2019, the average number of institutions, nurses per 1,000 rural population and the ratio of doctors to nurses in Guangxi were lower than that of China, Eastern China, Mid-China and Western China regions. The number of beds, health workers and doctors per 1,000 rural population in rural Guangxi were higher than that of China, Eastern China, Mid-China and Western China regions. Compared to the China, Eastern China, Mid-China and Western China regions, the average annual growth rate (AAGR) of beds and doctors per 1,000 rural population was the highest, while the ratio of doctors to nurses was the lowest (Table 2).
Table 2
Health resources allocation in rural Guangxi from 2016 to 2019
|
Health resources
|
Region
|
2016
|
2017
|
2018
|
2019
|
AAGR(%)
|
Institutions per 1,000 rural population
|
Guangxi
|
0.02
|
0.02
|
0.02
|
0.02
|
0
|
China
|
0.07
|
0.07
|
0.07
|
0.07
|
0
|
Eastern China
|
0.05
|
0.05
|
0.05
|
0.05
|
0
|
Mid-China
|
0.06
|
0.06
|
0.06
|
0.06
|
0
|
Western China
|
0.09
|
0.09
|
0.09
|
0.09
|
0
|
|
|
|
|
|
|
|
Beds per 1,000 rural population
|
Guangxi
|
1.49
|
1.56
|
1.65
|
1.77
|
5.91
|
China
|
1.26
|
1.35
|
1.43
|
1.48
|
5.51
|
Eastern China
|
1.14
|
1.21
|
1.26
|
1.34
|
5.54
|
Mid-China
|
1.24
|
1.32
|
1.37
|
1.43
|
4.87
|
Western China
|
1.42
|
1.52
|
1.57
|
1.68
|
5.76
|
|
|
|
|
|
|
|
Health workers per 1,000 rural population
|
Guangxi
|
1.74
|
1.81
|
1.91
|
1.99
|
4.58
|
China
|
1.36
|
1.42
|
1.49
|
1.56
|
4.68
|
Eastern China
|
1.45
|
1.51
|
1.56
|
1.68
|
5.03
|
Mid-China
|
1.24
|
1.27
|
1.27
|
1.34
|
2.62
|
Western China
|
1.41
|
1.5
|
1.56
|
1.71
|
6.64
|
|
|
|
|
|
|
|
Doctors per 1,000 rural population
|
Guangxi
|
0.85
|
0.89
|
0.92
|
0.96
|
4.14
|
China
|
0.82
|
0.84
|
0.87
|
0.54
|
-13.00
|
Eastern China
|
0.92
|
0.94
|
0.97
|
0.63
|
-11.86
|
Mid-China
|
0.86
|
0.88
|
0.88
|
0.53
|
-14.90
|
|
Western China
|
0.7
|
0.74
|
0.77
|
0.47
|
-12.43
|
|
|
|
|
|
|
|
Nurses per 1,000 rural population
|
Guangxi
|
0.24
|
0.25
|
0.26
|
0.29
|
6.51
|
China
|
0.58
|
0.62
|
0.62
|
0.71
|
6.97
|
Eastern China
|
0.61
|
0.64
|
0.69
|
0.72
|
5.68
|
Mid-China
|
0.55
|
0.57
|
0.59
|
0.67
|
6.80
|
Western China
|
0.59
|
0.66
|
0.7
|
0.76
|
8.81
|
|
|
|
|
|
|
|
Ratio of doctors to nurses
|
Guangxi
|
0.91
|
0.88
|
0.85
|
0.82
|
-3.41
|
China
|
0.7
|
0.73
|
0.97
|
0.78
|
3.67
|
Eastern China
|
0.66
|
0.69
|
0.95
|
0.71
|
2.46
|
Mid-China
|
0.64
|
0.65
|
0.95
|
0.74
|
4.96
|
Western China
|
0.84
|
0.9
|
1.02
|
0.91
|
2.70
|
4. Structure of health workers in rural Guangxi
In 2019, the proportion of Junior college degree was acecounted for the largest (44.72%), followed by the Technical secondary school degree (43.77%), while the Senior High school and below degree was accounted for the least (0.57%). The proportion of No titles/ unknown was accounted for the largest (40.87%), while the proportion of Senior professional title was accounted for the least (0.04%) (Table 3).
Table 3
The proportion of education background and professional titles (%)
|
Structure/ Personnel
|
Doctor
|
Nurse
|
Health technical personnel
|
Health worker
|
Degree
|
Postgraduate
|
0.18
|
0.01
|
0.06
|
0.06
|
Undergraduate
|
20.32
|
5.01
|
10.79
|
10.79
|
Junior college
|
54.33
|
42.16
|
44.72
|
44.72
|
Technical Secondary school
|
24.82
|
52.57
|
43.86
|
43.77
|
Senior High school and Below
|
0.34
|
0.18
|
0.57
|
0.57
|
Professional titles
|
Senior
|
0.09
|
0.03
|
0.04
|
0.04
|
Middle
|
3.44
|
1.17
|
1.45
|
1.45
|
Junior
|
16.1
|
13.15
|
9.91
|
9.91
|
Technical expert
|
30.35
|
19.89
|
17.82
|
17.82
|
Assistant
|
24.82
|
33.18
|
29.92
|
29.92
|
No titles/unknown
|
25.2
|
32.58
|
40.87
|
40.87
|
Fairness assessment
1. Changes of Lorenz curve and Gini coefficient from 2016 to 2019
From 2016 to 2019, G against GDP size was higher than that of population and geographic size. Compared with 2016, except for institutions, G by geographic size in 2019 was greater than 0.3. G by population was 0.068 - 0.217: where 0.187 - 0.217 for institutions, 0.118 - 0.160 for beds, 0.068 - 0.088 for health workers, which means that the distribution of the health resources was relatively equity. In addition, the G by geographic area was 0.080 - 0.367: where 0.080–0.081 for institutions, 0.289–0.357 for beds, 0.266–0.367 for health workers, indicating that the distribution of the health resources was the lower equity level. Moreover, G by GDP was 0.135 - 0.354: where 0.336 - 0.340 for institutions, 0.249 - 0.354 for beds, 0.135 - 0.276 for health workers, indicating that the distribution of the health resources exhibits lower equity level (Table 4).
By the population size, the Lorenz curves of the health workers was closest to the absolute equity curve, while the institutions was the farthest (Figure 1-2). This finding affirmed that the equity of health workers was the best while the institutions was the worst against population dimension. By the geographic size, the Lorenz curve of the institutions was the closest to the absolute equity curve, while the beds was the farthest (Figure 3-4). This finding verified that the equity of institutions was the best and that of the health workers was the worst in terms of the geographical dimension. By the GDP size, the Lorenz curve of the health workers was the closest to the absolute equity curve, while the institutions was the farthest (Figure 5-6). This finding verified that the equity of health workers was the best and that of the institutions was the worst in terms of the GDP dimension. Furthermore, the trends of G of health workers fluctuated the most, dropping from 0.276 in 2016 to 0.135 in 2019. G of institutions in geographic and population size fluctuated slightly, and all of them were less than 0.2 (Figure 7-9).
Table 4
Gini coefficient of health resources in rural Guangxi from 2016 to 2019
|
Dimension /Year
|
2016
|
2017
|
2018
|
2019
|
Population size
|
Institution
|
0.215
|
0.187
|
0.216
|
0.217
|
Bed
|
0.118
|
0.125
|
0.16
|
0.147
|
Health Workers
|
0.088
|
0.086
|
0.068
|
0.085
|
Geographic size
|
Institution
|
0.081
|
0.08
|
0.08
|
0.08
|
Bed
|
0.289
|
0.289
|
0.363
|
0.357
|
Health Workers
|
0.266
|
0.205
|
0.257
|
0.367
|
GDP size
|
Institution
|
0.336
|
0.338
|
0.338
|
0.34
|
Bed
|
0.283
|
0.354
|
0.249
|
0.289
|
Health Workers
|
0.276
|
0.223
|
0.166
|
0.135
|
2. Theil index and contribution rate from 2016 to 2019
By population size, Ttotal was lower than 0.1. By geographic size, except for beds, Ttotal showed a decreasing trend from 2016 to 2019. By GDP size, except for health worker, Ttotal showed a trend of increasing year by year. By population and geographic size, except for institutions, the contribution rate of Thiel index of health resources in rural Guangxi was Tbetween < Twithin. In GDP size, except for beds, the contribution rate of Theil index of all health resources was Twithin > Tbetween. The trends Theil index from 2016 to 2019 were similar as that of the Gini index. Overall, there was no significant change in the inter-group and intra-group differences in the contribution rate of Theil index (Table 5 and Figure 10-12).
Table 5
Theil index and contribution rate (%) of health resources in rural Guangxi from 2016 to 2019
|
Dimension /Year
|
Institutions
|
Beds
|
Health Workers
|
Ttotal
|
Tbetween
|
Twithin
|
Ttotal
|
Tbetween
|
Twithin
|
Ttotal
|
Tbetween
|
Twithin
|
Population size
|
|
|
|
|
|
|
|
|
|
2016
|
0.08
|
54.95
|
45.05
|
0.029
|
24.94
|
75.06
|
0.019
|
19.27
|
80.73
|
2017
|
0.08
|
54.77
|
45.23
|
0.031
|
26.78
|
73.22
|
0.019
|
20.34
|
79.66
|
2018
|
0.08
|
54.81
|
45.27
|
0.03
|
30.35
|
69.65
|
0.018
|
23.37
|
76.63
|
2019
|
0.081
|
53.51
|
46.49
|
0.041
|
26.54
|
73.46
|
0.018
|
25.97
|
74.03
|
Geographic size
|
|
|
|
|
|
|
|
|
|
2016
|
0.013
|
47.11
|
52.89
|
0.134
|
60.03
|
39.97
|
0.111
|
69.97
|
30.03
|
2017
|
0.013
|
47.36
|
52.64
|
0.135
|
63.75
|
36.25
|
0.106
|
69.56
|
30.44
|
2018
|
0.014
|
47.8
|
52.2
|
0.136
|
60.18
|
39.82
|
0.104
|
69.21
|
30.79
|
2019
|
0.013
|
53.29
|
46.71
|
0.211
|
64.48
|
35.52
|
0.107
|
68.87
|
31.13
|
GDP size
|
|
|
|
|
|
|
|
|
|
2016
|
0.186
|
61.62
|
38.38
|
0.132
|
48.15
|
51.85
|
0.129
|
55.71
|
44.29
|
2017
|
0.188
|
61.55
|
38.45
|
0.139
|
49.14
|
50.86
|
0.13
|
56.18
|
43.82
|
2018
|
0.188
|
61.75
|
38.25
|
0.133
|
47.67
|
52.33
|
0.129
|
57.69
|
42.31
|
2019
|
0.19
|
61.64
|
38.36
|
0.136
|
38.16
|
61.84
|
0.128
|
58.89
|
41.11
|