Unknown

Dataset Information

0

Rural population's preferences matter: a value set for the EQ-5D-3L health states for China's rural population.


ABSTRACT:

Purpose

To develop an EQ-5D-3L social value set based on Chinese rural population's preferences using the time trade-off (TTO) method, and to compare the differences in preferences on health states between China urban and rural population.

Methods

Between Sep 2013 and Nov 2013, a total of 1201 participants were recruited from rural areas of five Chinese cities (Beijing, Chengdu, Guiyang, Nanjing, and Shenyang) using a quota sampling method. Each respondent valued 13 health states using the TTO, and a total of 97 EQ-5D-3L health states were directly valued for estimating the value set. Various models with different specifications were explored at both aggregate and individual levels. The final model was determined by a set of predefined selection criteria.

Findings

An ordinary least square model at the aggregate level included 10 dummy variables for specifying the level 2 and 3 for each dimension and an N3 term presenting any dimension on level 3 was selected as the final model. The final model provides a value set ranges from - 0.218 to 0.859. The predicted utility values were highly correlated with but consistently lower than that of the published Chinese EQ-5D-3L value set (for urban population).

Conclusion

The availability of the China rural value set provides a set of social preferences weights for researchers and policy decision-makers for use in China rural area.

SUBMITTER: Liu GG 

PROVIDER: S-EPMC8800217 | biostudies-literature |

REPOSITORIES: biostudies-literature

Similar Datasets

| S-EPMC9628592 | biostudies-literature
| S-EPMC11343814 | biostudies-literature
| S-EPMC9485017 | biostudies-literature
| S-EPMC8306594 | biostudies-literature
| S-EPMC9124748 | biostudies-literature
| S-EPMC8009800 | biostudies-literature
| S-EPMC5656740 | biostudies-literature
| S-EPMC8068700 | biostudies-literature
| S-EPMC7295839 | biostudies-literature
| S-EPMC10060331 | biostudies-literature