Table 2 The Bayesian posterior median and 95% CI of spatial matching OR between the PAR and three types of NMRTR in the 31 provincial regions in mainland China
From: Spatiotemporal matching between medical resources and population ageing in China from 2008 to 2017
Provincial regions | Spatial matching OR between PAR and NLCPTR (95% CI) | Spatial matching OR between PAR and NRNTR (95% CI) | Spatial matching OR between PAR and NBHTR (95% CI) |
|---|---|---|---|
Beijing | 0.50 (0.48, 0.52) | 0.41 (0.39, 0.42) | 0.72 (0.69, 0.74) |
Tianjin | 0.91 (0.87, 0.94) | 0.93 (0.87, 0.98) | 1.10 (1.06, 1.14) |
Hebei | 1.08 (1.04, 1.13) | 1.31 (1.21, 1.42) | 1.12 (1.08, 1.17) |
Shanxi | 0.72 (0.69, 0.75) | 0.85 (0.79, 0.91) | 0.84 (0.80, 0.88) |
Inner Mongolia | 0.73 (0.70, 0.76) | 0.91 (0.85, 0.97) | 0.88 (0.84, 0.92) |
Liaoning | 1.00 (0.97, 1.04) | 1.03 (0.97, 1.09) | 0.92 (0.89, 0.95) |
Jilin | 0.85 (0.82, 0.88) | 1.03 (0.96, 1.10) | 0.89 (0.86, 0.92) |
Heilongjiang | 0.97 (0.93, 1.01) | 1.07 (1.00, 1.15) | 0.86 (0.83, 0.90) |
Shanghai | 0.86 (0.83, 0.89) | 0.64 (0.61, 0.67) | 0.96 (0.93, 1.00) |
Jiangsu | 1.25 (1.20, 1.29) | 1.20 (1.13, 1.27) | 1.28 (1.24, 1.32) |
Zhejiang | 0.87 (0.84, 0.90) | 0.86 (0.82, 0.91) | 1.02 (0.99, 1.06) |
Anhui | 1.59 (1.52, 1.65) | 1.50 (1.38, 1.62) | 1.42 (1.37, 1.48) |
Fujian | 1.04 (0.99, 1.09) | 0.95 (0.89, 1.02) | 1.13 (1.08, 1.18) |
Jiangxi | 1.21 (1.16, 1.27) | 1.13 (1.04, 1.23) | 1.28 (1.23, 1.34) |
Shandong | 1.07 (1.03, 1.12) | 1.08 (1.01, 1.15) | 1.16 (1.11, 1.20) |
Henan | 1.24 (1.18, 1.30) | 1.17 (1.08, 1.26) | 1.05 (1.00, 1.10) |
Hubei | 1.14 (1.10, 1.18) | 1.06 (1.00, 1.14) | 1.16 (1.12, 1.20) |
Hunan | 1.38 (1.33, 1.43) | 1.34 (1.24, 1.44) | 1.25 (1.20, 1.29) |
Guangdong | 0.86 (0.82, 0.91) | 0.70 (0.65, 0.75) | 0.96 (0.91, 1.02) |
Guangxi | 1.26 (1.21, 1.32) | 1.11 (1.03, 1.19) | 1.39 (1.33, 1.45) |
Hainan | 0.98 (0.93, 1.03) | 0.75 (0.70, 0.80) | 1.06 (1.01, 1.11) |
Chongqing | 1.67 (1.61, 1.74) | 1.63 (1.51, 1.76) | 1.45 (1.40, 1.50) |
Sichuan | 1.40 (1.35, 1.45) | 1.55 (1.45, 1.68) | 1.36 (1.32, 1.41) |
Guizhou | 1.37 (1.31, 1.44) | 1.33 (1.23, 1.46) | 1.07 (1.03, 1.12) |
Yunnan | 1.15 (1.09, 1.21) | 1.14 (1.04, 1.24) | 0.92 (0.88, 0.96) |
Tibet | 0.83 (0.78, 0.88) | 1.38 (1.21, 1.60) | 0.84 (0.79, 0.90) |
Shaanxi | 1.10 (1.05, 1.14) | 0.96 (0.90, 1.02) | 0.96 (0.92, 0.99) |
Gansu | 1.16 (1.11, 1.22) | 1.28 (1.19, 1.40) | 1.04 (0.99, 1.08) |
Qinghai | 0.70 (0.66, 0.74) | 0.76 (0.71, 0.82) | 0.64 (0.61, 0.67) |
Ningxia | 0.65 (0.62, 0.68) | 0.71 (0.66, 0.76) | 0.62 (0.60, 0.66) |
Xinjiang | 0.65 (0.61, 0.68) | 0.60 (0.56, 0.64) | 0.52 (0.49, 0.54) |