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Disability weight measurement for the severity of different diseases in Wuhan, China.
Liu, Xiaoxue; Guo, Yan; Wang, Fang; Yu, Yong; Yan, Yaqiong; Wen, Haoyu; Shi, Fang; Wang, Yafeng; Wang, Xuyan; Shen, Hui; Li, Shiyang; Gong, Yanyun; Ke, Sisi; Zhang, Wei; Jin, Qiman; Zhang, Gang; Wu, Yu; Zhou, Maigeng; Yu, Chuanhua.
Afiliação
  • Liu X; Department of Epidemiology and Biostatistics, School of Pubic Health, Wuhan University, 115 Donghu Road, Wuchang District, Wuhan, 430071, Hubei, China.
  • Guo Y; Global Health Research Division, Public Health Research Center and Department of Public Health and Preventive Medicine, Wuxi School of Medicine, Jiangnan University, Wuxi, 214122, Jiangsu, China.
  • Wang F; Wuhan Centers for Disease Control and Prevention, Wuhan, 430024, Hubei, China.
  • Yu Y; Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, China.
  • Yan Y; School of Public Health and Management, Hubei University of Medicine, Shiyan, 442000, Hubei, China.
  • Wen H; Wuhan Centers for Disease Control and Prevention, Wuhan, 430024, Hubei, China.
  • Shi F; Department of Epidemiology and Biostatistics, School of Pubic Health, Wuhan University, 115 Donghu Road, Wuchang District, Wuhan, 430071, Hubei, China.
  • Wang Y; Department of Epidemiology and Biostatistics, School of Pubic Health, Wuhan University, 115 Donghu Road, Wuchang District, Wuhan, 430071, Hubei, China.
  • Wang X; Global Health Research Division, Public Health Research Center and Department of Public Health and Preventive Medicine, Wuxi School of Medicine, Jiangnan University, Wuxi, 214122, Jiangsu, China.
  • Shen H; Department of Epidemiology and Biostatistics, School of Pubic Health, Wuhan University, 115 Donghu Road, Wuchang District, Wuhan, 430071, Hubei, China.
  • Li S; Department of Epidemiology and Biostatistics, School of Pubic Health, Wuhan University, 115 Donghu Road, Wuchang District, Wuhan, 430071, Hubei, China.
  • Gong Y; Department of Epidemiology and Biostatistics, School of Pubic Health, Wuhan University, 115 Donghu Road, Wuchang District, Wuhan, 430071, Hubei, China.
  • Ke S; Department of Epidemiology and Biostatistics, School of Pubic Health, Wuhan University, 115 Donghu Road, Wuchang District, Wuhan, 430071, Hubei, China.
  • Zhang W; Wuhan Centers for Disease Control and Prevention, Wuhan, 430024, Hubei, China.
  • Jin Q; Wuhan Centers for Disease Control and Prevention, Wuhan, 430024, Hubei, China.
  • Zhang G; Wuhan Centers for Disease Control and Prevention, Wuhan, 430024, Hubei, China.
  • Wu Y; Wuhan Centers for Disease Control and Prevention, Wuhan, 430024, Hubei, China.
  • Zhou M; Global Health Research Division, Public Health Research Center and Department of Public Health and Preventive Medicine, Wuxi School of Medicine, Jiangnan University, Wuxi, 214122, Jiangsu, China.
  • Yu C; National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Nanwei Road 27, Xicheng District, Beijing, 100050, China.
Popul Health Metr ; 21(1): 5, 2023 05 04.
Article em En | MEDLINE | ID: mdl-37143047
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 < 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.

CONCLUSIONS:

This 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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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Pessoas com Deficiência Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Pessoas com Deficiência Idioma: En Ano de publicação: 2023 Tipo de documento: Article