1. Eliciting national and subnational sets of disability weights in mainland China:Findings from the Chinese disability weight measurement study
- Author
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Liu, Xiaoxue, Wang, Fang, Yu, Chuanhua, Zhou, Maigeng, Yu, Yong, Qi, Jinlei, Yin, Peng, Yu, Shicheng, Zhou, Yuchang, Lin, Lin, Liu, Yunning, Wang, Qiqi, Zhong, Wenling, Huang, Shaofen, Li, Yanxia, Liu, Li, Liu, Yuan, Ma, Fang, Zhang, Yine, Tian, Yuan, Yu, Qiuli, Zeng, Jing, Pan, Jingju, Zhou, Mengge, Kang, Weiwei, Zhou, Jin Yi, Yu, Hao, Liu, Yuehua, Li, Shaofang, Yu, Huiting, Wang, Chunfang, Xia, Tian, Xi, Jinen, Ren, Xiaolan, Xing, Xiuya, Cheng, Qianyao, Fei, Fangrong, Wang, Dezheng, Zhang, Shuang, He, Yuling, Wen, Haoyu, Liu, Yan, Shi, Fang, Wang, Yafeng, Sun, Panglin, Bai, Jianjun, Wang, Xuyan, Shen, Hui, Ma, Yudiyang, Yang, Donghui, Mubarik, Sumaira, Cao, Jinhong, Meng, Runtang, Zhang, Yunquan, Guo, Yan, Yan, Yaqiong, Zhang, Wei, Ke, Sisi, Zhang, Runhua, Wang, Dingyi, Zhang, Tingting, Nomura, Shuhei, Hay, Simon I., Salomon, Joshua A., Haagsma, Juanita A., Murray, Christopher J.L., Vos, Theo, Liu, Xiaoxue, Wang, Fang, Yu, Chuanhua, Zhou, Maigeng, Yu, Yong, Qi, Jinlei, Yin, Peng, Yu, Shicheng, Zhou, Yuchang, Lin, Lin, Liu, Yunning, Wang, Qiqi, Zhong, Wenling, Huang, Shaofen, Li, Yanxia, Liu, Li, Liu, Yuan, Ma, Fang, Zhang, Yine, Tian, Yuan, Yu, Qiuli, Zeng, Jing, Pan, Jingju, Zhou, Mengge, Kang, Weiwei, Zhou, Jin Yi, Yu, Hao, Liu, Yuehua, Li, Shaofang, Yu, Huiting, Wang, Chunfang, Xia, Tian, Xi, Jinen, Ren, Xiaolan, Xing, Xiuya, Cheng, Qianyao, Fei, Fangrong, Wang, Dezheng, Zhang, Shuang, He, Yuling, Wen, Haoyu, Liu, Yan, Shi, Fang, Wang, Yafeng, Sun, Panglin, Bai, Jianjun, Wang, Xuyan, Shen, Hui, Ma, Yudiyang, Yang, Donghui, Mubarik, Sumaira, Cao, Jinhong, Meng, Runtang, Zhang, Yunquan, Guo, Yan, Yan, Yaqiong, Zhang, Wei, Ke, Sisi, Zhang, Runhua, Wang, Dingyi, Zhang, Tingting, Nomura, Shuhei, Hay, Simon I., Salomon, Joshua A., Haagsma, Juanita A., Murray, Christopher J.L., and Vos, Theo
- Abstract
Background: The disability weight (DW) quantifies the severity of health states from disease sequela and is a pivotal parameter for disease burden calculation. We conducted a national and subnational DW measurement in China. Methods: In 2020–2021, we conducted a web-based survey to assess DWs for 206 health states in 31 Chinese provinces targeting health workers via professional networks. We fielded questions of paired comparison (PC) and population health equivalence (PHE). The PC data were analysed by probit regression analysis, and the regression results were anchored by results from the PHE responses on the DW scale between 0 (no loss of health) and 1 (health loss equivalent to death). Findings: We used PC responses from 468,541 respondents to estimate DWs of health states. Eight of 11 domains of health had significantly negative coefficients in the regression of the difference between Chinese and Global Burden of Disease (GBD) DWs, suggesting lower DW values for health states with mention of these domains in their lay description. We noted considerable heterogeneity within domains, however. After applying these Chinese DWs to the 2019 GBD estimates for China, total years lived with disability (YLDs) increased by 14·9% to 177 million despite lower estimates for musculoskeletal disorders, cardiovascular diseases, mental disorders, diabetes and chronic kidney disease. The lower estimates of YLDs for these conditions were more than offset by higher estimates of common, low-severity conditions. Interpretation: The differences between the GBD and Chinese DWs suggest that there might be some contextual factors influencing the valuation of health states. While the reduced estimates for mental disorders, alcohol use disorder, and dementia could hint at a culturally different valuation of these conditions in China, the much greater shifts in YLDs from low-severity conditions more likely reflects methodological difficulty to distinguish between health states that vary
- Published
- 2022