武汉市不同疾病严重程度的残疾体重测量

IF 3.2 2区医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Population Health Metrics Pub Date : 2023-05-04 DOI:10.1186/s12963-023-00304-y

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

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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). 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引用次数: 0

摘要

背景:用残疾调整生命年(DALYs)测量中国疾病负担需要残疾体重(DW)来量化疾病和损伤的所有非致命后果的健康损失。全球疾病负担(GBD) 2013年DW研究表明，由于DW数据缺乏地理差异以及目前的测量方法，该研究受到限制。我们的目标是估计武汉人群中主要疾病的一组健康状态的DW。方法:我们通过计算机辅助面对面访谈的家庭调查和网络调查对206个健康状态进行了DW测量研究。在GBD 2013 DW研究的基础上，采用配对比较(PC)和人口健康等效(PHE)方法，对每个被调查者随机分配不同的PC/PHE问题。在统计分析中，对PC数据进行概率回归分析。probit回归结果将以公共卫生数据的结果为基础，这些数据是通过DW尺度上的区间回归分析得出的，单位在0(没有健康损失)和1(相当于死亡的损失)之间。结果:共有2610人和3140人分别被纳入家庭调查和网络调查。汇总数据的结果显示健康状态为“轻度贫血”(DW = 0.005, 95% UI为0.000-0.027)或“过敏性鼻炎(花粉热)”。DW最低(0.005,95% UI 0.000 ~ 0.029)，最高的是“海洛因及其他阿片类药物依赖，严重”(0.699,95% UI 0.579 ~ 0.827)。高相关系数(Pearson’s r = 0.876;结论:该DWs可用于计算武汉市人群的当地疾病负担，为卫生决策提供依据。GBD调查与武汉市调查的DW差异表明，可能存在一些背景或文化因素影响疾病严重程度的评估。

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

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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来源期刊

Population Health Metrics PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-

CiteScore

6.50

自引率

0.00%

发文量

审稿时长

29 weeks

期刊介绍： Population Health Metrics aims to advance the science of population health assessment, and welcomes papers relating to concepts, methods, ethics, applications, and summary measures of population health. The journal provides a unique platform for population health researchers to share their findings with the global community. We seek research that addresses the communication of population health measures and policy implications to stakeholders; this includes papers related to burden estimation and risk assessment, and research addressing population health across the full range of development. Population Health Metrics covers a broad range of topics encompassing health state measurement and valuation, summary measures of population health, descriptive epidemiology at the population level, burden of disease and injury analysis, disease and risk factor modeling for populations, and comparative assessment of risks to health at the population level. The journal is also interested in how to use and communicate indicators of population health to reduce disease burden, and the approaches for translating from indicators of population health to health-advancing actions. As a cross-cutting topic of importance, we are particularly interested in inequalities in population health and their measurement.