Table 3 The Bayesian posterior median and 95% CI of temporal 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 | Temporal matching OR between PAR and NLCPTR (95% CI) | Temporal matching OR between PAR and NRNTR (95% CI) | Temporal matching OR between PAR and NBHTR (95% CI) |
|---|---|---|---|
Beijing | 0.89 (0.84, 0.94) | 0.60 (0.56, 0.65) | 0.71 (0.67, 0.76) |
Tianjin | 0.94 (0.88, 0.99) | 0.71 (0.64, 0.78) | 0.82 (0.77, 0.87) |
Hebei | 0.96 (0.89, 1.02) | 0.92 (0.81, 1.05) | 0.91 (0.85, 0.97) |
Shanxi | 0.88 (0.82, 0.94) | 0.93 (0.83, 1.04) | 0.87 (0.81, 0.94) |
Inner Mongolia | 0.83 (0.78, 0.89) | 0.96 (0.86, 1.07) | 0.94 (0.88, 1.01) |
Liaoning | 0.88 (0.83, 0.93) | 0.82 (0.74, 0.91) | 0.91 (0.86, 0.96) |
Jilin | 0.83 (0.78, 0.88) | 0.83 (0.74, 0.92) | 0.83 (0.77, 0.88) |
Heilongjiang | 0.82 (0.77, 0.88) | 0.82 (0.73, 0.93) | 0.87 (0.82, 0.93) |
Shanghai | 0.88 (0.82, 0.93) | 0.60 (0.55, 0.64) | 0.78 (0.74, 0.83) |
Jiangsu | 1.06 (1.01, 1.12) | 1.01 (0.91, 1.12) | 1.05 (1.00, 1.11) |
Zhejiang | 1.06 (1.00, 1.13) | 0.95 (0.87, 1.04) | 1.02 (0.95, 1.08) |
Anhui | 1.05 (0.98, 1.12) | 1.08 (0.96, 1.22) | 1.06 (0.99, 1.12) |
Fujian | 1.14 (1.06, 1.22) | 1.10 (1.00, 1.23) | 1.09 (1.02, 1.17) |
Jiangxi | 0.97 (0.90, 1.05) | 1.01 (0.90, 1.16) | 1.07 (0.99, 1.15) |
Shandong | 1.00 (0.94, 1.06) | 0.99 (0.90, 1.10) | 0.93 (0.88, 0.99) |
Henan | 1.03 (0.96, 1.11) | 1.12 (0.99, 1.26) | 1.03 (0.96, 1.10) |
Hubei | 1.03 (0.97, 1.09) | 1.13 (1.02, 1.25) | 1.10 (1.03, 1.17) |
Hunan | 1.11 (1.04, 1.19) | 1.13 (1.01, 1.27) | 1.18 (1.11, 1.25) |
Guangdong | 1.08 (1.00, 1.17) | 0.92 (0.82, 1.02) | 1.03 (0.95, 1.11) |
Guangxi | 1.12 (1.04, 1.20) | 1.21 (1.09, 1.36) | 1.11 (1.03, 1.19) |
Hainan | 1.15 (1.06, 1.26) | 1.10 (0.98, 1.23) | 1.12 (1.03, 1.21) |
Chongqing | 1.06 (0.99, 1.12) | 1.26 (1.12, 1.41) | 1.17 (1.11, 1.24) |
Sichuan | 1.02 (0.97, 1.08) | 1.22 (1.09, 1.37) | 1.17 (1.10, 1.23) |
Guizhou | 1.18 (1.10, 1.27) | 1.47 (1.29, 1.69) | 1.32 (1.24, 1.41) |
Yunnan | 1.08 (1.01, 1.18) | 1.33 (1.17, 1.54) | 1.12 (1.04, 1.20) |
Tibet | 1.18 (1.07, 1.30) | 1.21 (0.99, 1.47) | 1.20 (1.10, 1.32) |
Shaanxi | 1.00 (0.94, 1.07) | 1.14 (1.04, 1.27) | 1.03 (0.97, 1.10) |
Gansu | 1.00 (0.93, 1.08) | 1.07 (0.94, 1.20) | 1.00 (0.93, 1.07) |
Qinghai | 1.02 (0.94, 1.11) | 1.03 (0.91, 1.17) | 1.08 (1.00, 1.17) |
Ningxia | 0.96 (0.88, 1.04) | 1.01 (0.90, 1.15) | 0.91 (0.84, 0.99) |
Xinjiang | 0.96 (0.88, 1.04) | 0.94 (0.84, 1.05) | 0.89 (0.82, 0.96) |