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Table 3 Effects of the time variable on health utility values in the multiple linear regression analyses

From: The trend in quality of life of Chinese population: analysis based on population health surveys from 2008 to 2020

Time variable

Health utility values (N = 67,254)

β

95% CI

p value *

R2

Excepted utility method a

 Year (vs. 2008)

  2013

−0.009

(−0.012, − 0.007)

< 0.001

0.170

  2020

−0.010

(− 0.012, − 0.009)

< 0.001

Original

 Year (vs. 2008)

  2013

−0.014

(−0.016, − 0.012)

< 0.001

0.193

  2020

−0.028

(− 0.031, − 0.026)

< 0.001

Monte Carlo simulation method a

 Year (vs. 2008)

  2013

−0.009

(−0.012, − 0.006)

< 0.001

0.159

  2020

−0.010

(− 0.012, − 0.008)

< 0.001

Most-likely probability method a

 Year (vs. 2008)

     2013

−0.008

(−0.010, − 0.007)

< 0.001

0.165

     2020

−0.040

(− 0.042, − 0.037)

< 0.001

DSU method b

 Year (vs. 2008)

  2013

−0.016

(−0.019, − 0.013)

< 0.001

0.150

  2020

−0.058

(− 0.062, − 0.055)

< 0.001

  1. * The p-value in bold formatting represents significant in multivariable linear regression model at 0.05 level
  2. a The EQ-5D-3L responses were mapped to EQ-5D-5L responses by the UK response mapping algorithm [28] and then converted to utility values for the mapped responses using the excepted-utility method [29]
  3. b The responses of respondents in 2020 elicited from the EQ-5D-5L were indirectly mapped to the EQ-5D-3L by the DSU method [31]
  4. Abbreviation: 95% CI 95% confidence interval; DSU, Decision Support Unit