Dataset Information

Eliciting national and subnational sets of disability weights in mainland China: Findings from the Chinese disability weight measurement study.

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 a little in absolute DW value but a lot in relative terms.

Funding

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].

SUBMITTER: Liu X

PROVIDER: S-EPMC9335373 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Publications

Eliciting national and subnational sets of disability weights in mainland China: Findings from the Chinese disability weight measurement study.

Liu Xiaoxue X Wang Fang F Yu Chuanhua C Zhou Maigeng M Yu Yong Y Qi Jinlei J Yin Peng P Yu Shicheng S Zhou Yuchang Y Lin Lin L Liu Yunning Y Wang Qiqi Q Zhong Wenling W Huang Shaofen S Li Yanxia Y Liu Li L Liu Yuan Y Ma Fang F Zhang Yine Y Tian Yuan Y Yu Qiuli Q Zeng Jing J Pan Jingju J Zhou Mengge M Kang Weiwei W Zhou Jin-Yi JY Yu Hao H Liu Yuehua Y Li Shaofang S Yu Huiting H Wang Chunfang C Xia Tian T Xi Jinen J Ren Xiaolan X Xing Xiuya X Cheng Qianyao Q Fei Fangrong F Wang Dezheng D Zhang Shuang S He Yuling Y Wen Haoyu H Liu Yan Y Shi Fang F Wang Yafeng Y Sun Panglin P Bai Jianjun J Wang Xuyan X Shen Hui H Ma Yudiyang Y Yang Donghui D Mubarik Sumaira S Cao Jinhong J Meng Runtang R Zhang Yunquan Y Guo Yan Y Yan Yaqiong Y Zhang Wei W Ke Sisi S Zhang Runhua R Wang Dingyi D Zhang Tingting T Nomura Shuhei S Hay Simon I SI Salomon Joshua A JA Haagsma Juanita A JA Murray Christopher J L CJL Vos Theo T

The Lancet regional health. Western Pacific 20220726

<h4>Background</h4>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.<h4>Methods</h4>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 ...[more]

PMID: 35910433

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Project description:IntroductionMeasurement of the burden of disease using disability-adjusted life years requires disability weights to quantify health losses for non-fatal consequences of disease and injury. We aimed to obtain a set of disability weights for environmental and non-environmental noise-related health states (NOISE) using a nationally representative sample survey among the general population of four European countries; and to compare the resulting NOISE disability weights with those estimated in the Global Burden of Disease 2010 (GBD 2010) and European (EURO) disability weights measurement studies.MethodsWe administered a web-based survey among a cohort of individuals from Hungary, Italy, Sweden and the Netherlands. It included paired comparison questions on 82 different health states. Each respondent performed 13 paired comparison tasks. We analysed paired comparison responses with probit regression analysis, and regression results were anchored on the disability weight scale between 0 (equivalent to full health) and 1 (equivalent to death).ResultsIn total, 4056 respondents participated in the study. Comparison of the regression results from paired comparison responses for each country-specific dataset with those run on the pooled dataset showed high linear correlations (0.96-0.98, p<0.001). The resulting disability weights ranged from 0.005 for mild impairment of distance vision and mild anaemia to 0.761 for intensive care unit admission. The disability weight for moderate and severe annoyance was 0.006 and 0.011, respectively. Comparison of disability weights showed a higher correlation between EURO and NOISE disability weights (pseudo R-squared=0.955, Pearson correlation=0.954) compared with GBD 2010 and NOISE disability weights (pseudo R-squared=0.893, Pearson correlation=0.946).ConclusionsThe NOISE disability weights are consistent and highly correlated across the four European countries. The NOISE disability weights set can be used to estimate the burden of disease attributable to noise-related outcomes across Europe.

Project description:BackgroundA universal set of disability weights(DWs) is mainly based on the survey of North America, Australia and Europe, whereas the participants in Asia was limited. The debate hasn't yet settled whether a universal DW is desirable or useful.The focus of the debate is its representativenes-s.After all, the DWs come from people's subjective evaluation of pain, and they may vary according to cultural background.The differences of the DWs could have implications for the magnitude or ranking of disease burdens.The DWs of Anhui Province has not been completely presented.This paper aims to obtain the DWs suitable for the general population of Anhui Province of China, and attempts to explore the differences between different DWs by comparing the DWs with the similar-cultural background and the DWs with cross-cultural background.MethodsA web-based survey was conducted to estimate the DWs for 206 health states of Anhui province in 2020. Paired comparison (PC) data were analyzed and anchored by probit regression and fitting loess model. We compared the DWs in Anhui with other provinces in China and those in Global burden of disease (GBD) and Japan.ResultsCompared with Anhui province, the proportion of health states which showed 2 times or more differences ranged from 1.94% (Henan) to 11.17% (Sichuan) in China and domestic provinces. It was 19.88% in Japan and 21.51% in GBD 2013 respectively. In Asian countries or regions, most of the health states with top 15 DWs belonged to the category of mental, behavioral, and substance use disorders. But in GBD, most were infectious diseases and cancer. The differences of DWs in neighboring provinces were smaller than other geographically distant provinces or countries.ConclusionPC responses were largely consistent across very distinct settings,but the exceptions do need to be faced squarely.The differences of DWs among similar-cultural regions were smaller than cross-cultural regions. There is an urgent need for relevant gold standards.

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Project description:BackgroundMeasurement of the Chinese burden of disease with disability-adjusted life-years (DALYs) requires disability weight (DW) that quantify health losses for all non-fatal consequences of disease and injury. The Global Burden of Disease (GBD) 2013 DW study indicates that it is limited by lack of geographic variation in DW data and by the current measurement methodology. We aim to estimate DW for a set of health states from major diseases in the Wuhan population.MethodsWe conducted the DW measurement study for 206 health states through a household survey with computer-assisted face-to-face interviews and a web-based survey. Based on GBD 2013 DW study, paired comparison (PC) and Population health equivalence (PHE) method was used and different PC/PHE questions were randomly assigned to each respondent. In statistical analysis, the PC data was analyzed by probit regression. The probit regression results will be anchored by results from the PHE data analyzed by interval regression on the DW scale units between 0 (no loss of health) and 1 (loss equivalent to death).ResultsA total of 2610 and 3140 individuals were included in the household and web-based survey, respectively. The results from the total pooled data showed health state "mild anemia" (DW = 0.005, 95% UI 0.000-0.027) or "allergic rhinitis (hay fever)" (0.005, 95% UI 0.000-0.029) had the lowest DW and "heroin and other opioid dependence, severe" had the highest DW (0.699, 95% UI 0.579-0.827). A high correlation coefficient (Pearson's r = 0.876; P < 0.001) for DWs of same health states was observed between Wuhan's survey and GBD 2013 DW survey. Health states referred to mental symptom, fatigue, and the residual category of other physical symptoms were statistically significantly associated with a lower Wuhan's DWs than the GBD's DWs. Health states with disfigurement and substance use symptom had a higher DW in Wuhan population than the GBD 2013 study.ConclusionsThis set of DWs could be used to calculate local diseases burden for health policy-decision in Wuhan population. The DW differences between the GBD's survey and Wuhan's survey suggest that there might be some contextual or culture factors influencing assessment on the severity of diseases.

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Dataset Information

Eliciting national and subnational sets of disability weights in mainland China: Findings from the Chinese disability weight measurement study.

Background

Methods

Findings

Interpretation

Funding

Publications

Eliciting national and subnational sets of disability weights in mainland China: Findings from the Chinese disability weight measurement study.

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