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Disability weight measurement for the severity of different diseases in Wuhan, China

Authors :
Xiaoxue Liu
Yan Guo
Fang Wang
Yong Yu
Yaqiong Yan
Haoyu Wen
Fang Shi
Yafeng Wang
Xuyan Wang
Hui Shen
Shiyang Li
Yanyun Gong
Sisi Ke
Wei Zhang
Qiman Jin
Gang Zhang
Yu Wu
Maigeng Zhou
Chuanhua Yu
Source :
Population Health Metrics, Vol 21, Iss 1, Pp 1-14 (2023)
Publication Year :
2023
Publisher :
BMC, 2023.

Abstract

Abstract Background Measurement 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. Methods We 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). Results A 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

Details

Language :
English
ISSN :
14787954
Volume :
21
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Population Health Metrics
Publication Type :
Academic Journal
Accession number :
edsdoj.08b2a64429440bc9ddb91cd1165884f
Document Type :
article
Full Text :
https://doi.org/10.1186/s12963-023-00304-y