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
Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, No. 115 Donghu Road, Wuchang District, Wuhan 430071, Hubei Province, China.
Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou 221004, China.
Lancet Reg Health West Pac. 2022 Jul 26;26:100520. doi: 10.1016/j.lanwpc.2022.100520. eCollection 2022 Sep.
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.
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).
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.
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 a little in absolute DW value but a lot in relative terms.
This work was supported by the National Natural Science Foundation of China [grant number 82173626], the National Key Research and Development Program of China [grant numbers 2018YFC1315302], Wuhan Medical Research Program of Joint Fund of Hubei Health Committee [grant number WJ2019H304], and Ningxia Natural Science Foundation Project [grant number 2020AAC03436].
残疾权重(DW)量化了疾病后遗症导致的健康状态严重程度,是疾病负担计算的关键参数。我们在中国开展了一项全国性及省级以下层面的残疾权重测量。
在2020 - 2021年,我们通过专业网络针对卫生工作者开展了一项基于网络的调查,以评估中国31个省份206种健康状态的残疾权重。我们提出了成对比较(PC)和人群健康等效性(PHE)问题。PC数据通过概率回归分析进行分析,回归结果以PHE在残疾权重量表(范围从0(无健康损失)到1(健康损失等同于死亡))上的回答结果为基准。
我们使用了468,541名受访者的PC回答来估计健康状态的残疾权重。在健康的11个领域中,有8个领域在中国与全球疾病负担(GBD)残疾权重差异的回归中具有显著的负系数,这表明在通俗描述中提及这些领域的健康状态的残疾权重值较低。然而,我们注意到各领域内存在相当大的异质性。将这些中国残疾权重应用于2019年中国的GBD估计值后,尽管肌肉骨骼疾病、心血管疾病、精神障碍、糖尿病和慢性肾脏病的估计值有所降低,但残疾生活年数(YLDs)总计增加了14.9%,达到1.77亿。这些疾病YLDs的较低估计值被常见的低严重程度疾病的较高估计值所抵消。
GBD残疾权重与中国残疾权重之间的差异表明,可能存在一些背景因素影响健康状态的估值。虽然精神障碍、酒精使用障碍和痴呆症估计值的降低可能暗示中国对这些疾病的文化估值有所不同,但YLDs从低严重程度疾病的更大变化更可能反映了在区分绝对残疾权重值变化不大但相对差异很大的健康状态方面的方法学困难。
本研究得到了中国国家自然科学基金[项目编号82173626]、中国国家重点研发计划[项目编号2018YFC1315302]、湖北省卫生健康委联合基金武汉医学研究项目[项目编号WJ2019H304]以及宁夏自然科学基金项目[项目编号2020AAC03436]的支持。